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Radiological Society of North America (RSNA) 3D printing Special Interest Group (SIG): guidelines for medical 3D printing and appropriateness for clinical scenarios

RSNA Special Interest Group for 3D Printing, Leonid Chepelev, Nicole Wake and 16 more

3D Printing in Medicine · 2018

doi:10.1186/s41205-018-0030-y

Abstract

Medical three-dimensional (3D) printing has expanded dramatically over the past three decades with growth in both facility adoption and the variety of medical applications. Consideration for each step required to create accurate 3D printed models from medical imaging data impacts patient care and management. In this paper, a writing group representing the Radiological Society of North America Special Interest Group on 3D Printing (SIG) provides recommendations that have been vetted and voted on by the SIG active membership. This body of work includes appropriate clinical use of anatomic models 3D printed for diagnostic use in the care of patients with specific medical conditions. The recommendations provide guidance for approaches and tools in medical 3D printing, from image acquisition, segmentation of the desired anatomy intended for 3D printing, creation of a 3D-printable model, and post-processing of 3D printed anatomic models for patient care.

Shown for reading. Its publisher allows quoting it, not republishing it.

Full text

From PubMed Central, U.S. National Library of Medicine, as current on Oct 22, 2026. Paragraph numbers are ours, so an answer can point at one.

Background

In 2016, the Radiological Society of North America (RSNA) approved a proposal to create the Special Interest Group on 3D Printing (SIG). This document fulfills two of the original SIG goals: to provide recommendations towards consistent and safe production of 3D printed models derived from medical images, and to describe a set of clinical scenarios for 3D printing is appropriate for the intended use of caring for patients with those medical conditions. This project also fills a previously unmet need for practice parameters/guidelines regarding the clinical service of anatomic modeling (3D Printing) described for proposed new billing codes, including those for the American Medical Association. These practice parameters and recommendations are not intended as comprehensive standards but do reflect several salient aspects of clinical anatomic modeling and appropriateness. The guidelines subcommittee of the SIG will maintain and devote the time and effort necessary to continually develop and update these recommendations. This subcommittee is comprised of volunteer members of the SIG who form the writing group of this document.

In its current state, medical 3D printing has been performed for a variety of patients, but without evidence-based appropriateness guidelines. For many body parts, this document includes a comprehensive assessment of appropriateness from the medical literature, supplemented by expert opinion (SIG members) when there is a paucity of peer-review data. After the clinical decision to use 3D printing for patient care, there are many subsequent steps, as reviewed in prior literature. These include image acquisition, image segmentation (demarcation of the desired 3D anatomy), creating 3D-printable file types for each segmented part, printing, and post processing of 3D medical models. This document differs from existing works, including case reports, small and larger studies, and 3D printing review articles in the literature. This is not a review article; instead of reviewing the literature or providing data regarding the clinical utility of medical 3D printing, the RSNA SIG has assembled a group of experts to begin to provide consensus recommendations on the practice of medical modeling and 3D printing, particularly for practice within healthcare facilities. 3D printing of anatomical models within a hospital has recently become recognized as point-of-care manufacturing. These recommendations create a foundational outline to provide practice recommendations for those steps required for medical 3D printing, including image acquisition, segmentation, printing, post-processing, and model verification.

Consensus methodology recommendations

The recommendations regarding medical image acquisition, image data preparation and manipulation, generation of 3D printed models, quality control, communication with referring physicians, preoperative planning using 3D printed models, and considerations regarding materials were discussed and summarized by members of the RSNA Special Interest Group for 3D Printing during several meetings, including on August 31 (Silver Spring, MD) and December 1, 2017 (Chicago, IL) after review of the relevant medical 3D printing literature and the local clinical practice of representative members of the Special Interest Group. Relevant recommendations were further exposed to internal online discussion and summarized by a focused taskforce. The final recommendations were reviewed and vetted by all RSNA 3D printing SIG members.

Appropriateness consensus guideline generation

The Special Interest Group has initiated the quality and safety scholarship to identify those clinical situations for which 3D Printing is considered an appropriate, and not appropriate, representation of the data contained in a medical imaging examination. These documents highlight appropriateness of medical 3D printing for clinical utilization, research, scientific, and informational purposes. This work is loosely modeled after the American College of Radiology Appropriateness Criteria® in that the guidelines committee uses an evidence-based approach at scoring. Consensus among members is used when there is a paucity of evidence.

Each category was led by a separate writing group, composed of a small group of experts in that domain of medical imaging and 3D printing. The SIG Executive committee, led by the Guidelines Chairperson, formed the review panel. Ratings were generated via by a vote of Special Interest Group members at in-person meetings. The results of the ratings follow the following 1–9 format (with 9 being the most appropriate):1–3, red, rarely appropriate: There is a lack of a clear benefit or experience that shows an advantage over usual practice.4–6, yellow, maybe appropriate: There may be times when there is an advantage, but the data is lacking, or the benefits have not been fully defined.7–9, green, usually appropriate: Data and experience shows an advantage to 3D printing as a method to represent and/or extend the value of data contained in the medical imaging examination.

1–3, red, rarely appropriate: There is a lack of a clear benefit or experience that shows an advantage over usual practice.

4–6, yellow, maybe appropriate: There may be times when there is an advantage, but the data is lacking, or the benefits have not been fully defined.

7–9, green, usually appropriate: Data and experience shows an advantage to 3D printing as a method to represent and/or extend the value of data contained in the medical imaging examination.

The supporting evidence was obtained through structured PubMed searches, as detailed in the Appendix. In rare circumstances, supporting literature was recommended directly by the members of the committee and was explicitly identified outside of the structured PubMed search results.

A subset of applications of 3D printing, including in congenital heart, vascular, craniomaxillofacial, musculoskeletal, genitounirary, and breast pathologies was selected for detailed review. All final components of this section were vetted and approved by vote of Special Interest Group members at several face-to-face meetings including on August 31 (Silver Spring, MD) and December 1, 2017 (Chicago, IL) as well as via internal posting on the SIG member intranet.

Medical image acquisition

The most common medical imaging modalities for 3D printing are computed tomography (CT) and magnetic resonance imaging (MRI); however, any 3D imaging dataset including sonography (e.g., echocardiography) may be utilized as input data for segmentation. The international standard format for these imaging files is Digital Imaging and Communications in Medicine (DICOM). At this time, DICOM images are not routinely sent directly to a 3D printer for printing, so medical images are segmented and converted to a file type that is recognized by 3D printers. Common file types include Standard Tessellation Language (STL), OBJ, VRML/WRL, AMF, 3MF, and X3D. Once this functionality is implemented by 3D printing vendors, picture archiving and communication system (PACS) vendors, and at the point of care facility, it will allow 3D files in the form of STLs, for example, to be stored in a patient’s medical record.

Spatial resolution and slice thickness

Medical imaging data should have sufficient spatial resolution to accurately represent the anatomy to be modeled. The spatial resolution of an imaging method refers to the smallest resolvable distance between two different objects or two different features of the same object. Low spatial resolution techniques will be unable to differentiate two adjacent structures that are close together and have similar tissue properties. When the intent to produce a 3D model is known prior to a medical imaging procedure, the image acquisition should be tailored so that the anatomy in the intended 3D model can be adequately visualized. The optimal spatial resolution will depend on the anatomy being imaged.

Slice thickness, which influences the spatial resolution and image noise (discussed in the next section), can also be optimized depending on the intended use. In general, this means that the smallest anatomy of interest should be captured on multiple sequential DICOM images of a particular series. For example, if the anatomy of interest measures 3 mm, it would be desirable for this anatomy to be captured on at least 3 sequential image slices; therefore, the slice thickness should be no greater than 1 mm, and preferably smaller. If images are acquired with a large slice thickness, stair-step boundaries may be seen in the 3D model.

For CT, in combination with scan distance, consideration may be given regarding collimation (the thickness of the X-ray beam) and overlap. Typically, the scan distance and collimation are the same; however, if the slice distance is smaller than the collimation, there will be an overlap which may lead to improved results. Cone Beam CT has technical differences with conventional CT, and often results in a lower patient radiation exposure and subsequently less image contrast that typical clinical CT images. Image artifacts and consistency of SNR throughout the scan can also limit studies. For MRI, voxels may be isotropic or rectangular solids and the resolution may be different in the three dimensions. The size of the voxel depends on the matrix size, the field of view (FOV), and the slice thickness.

In some clinical scenarios, there are patients for which suboptimal imaging data is available, but a separate acquisition is contraindicated. If superior spatial resolution is preferred and CT data is required, that benefit should be weighed against the risk of delivering more radiation to the patient.

Signal to Noise Ratio (SNR) and Contrast to Noise Ratio (CNR)

The SNR is a metric of image quality. A higher SNR, all else being equal, implies more trustworthy data for 3D printing. The CNR is the relationship of the signal intensity differences (the contrast) between two regions, scaled to noise. High contrast between various organs in the body is an important feature of medical imaging and is necessary to delineate structures for 3D printing. The SNR and CNR of images used for 3D printing should be comparable to, or superior to, those for “3D visualization”, defined as the comprehensive ensemble of manipulation of a volumetric data set for viewing on a 2D surface such as a computer monitor.

If the SNR and/or CNR are inconsistent, or suboptimal, the risks of inaccurate segmentation must be weighed against those of rescanning the patient. Regarding high noise data, a judgment call must be made to determine whether the segmentation operator is capable of delineating the data (e.g. in the case of a cone beam CT image series).

In CT, the X-ray tube voltage may also be adjusted to maximize the signal. A lower kV can be used to increase the enhancement of iodine contrast when building vascular models. In addition, the raw data reconstruction parameters selected may affect the appearance of specific anatomical structures. For example, the reconstruction kernel (image filter) impacts both the spatial resolution and image noise, which must be balanced, based on the application. Typically, kernel options range from “sharp” to “smooth.” Sharpening filters increase edge sharpness at a cost of increasing noise while smoothing filters reduce noise content in images by also decrease edge sharpness. For models with fine structures, such as the temporal bone, a sharp kernel is preferred; and for larger, low contrast models, a smooth kernel is more appropriate. CT is considered the imaging modality of choice for bone imaging and is often used to produce 3D anatomical models of hard tissue structures such as bone. In MRI, the SNR may be improved by performing a volume acquisition (at the expense of time), decreasing noise by reducing the bandwidth, altering the echo time or repeat time, increasing the FOV, decreasing the matrix size, or increasing the slice thickness.

Image artifact

The sub-volume of the imaging dataset that will be 3D printed is defined in this document as the printing Region of Interest (ROI). All medical images contain artifact, and image processing steps should be taken to minimize artifact. The ROI should be small enough to enable confident segmentation for 3D printing. There are cases for which medical interpretation is possible (see Image interpretation Section), but 3D printing can be limited by the presence of artifact, motion, or other spatial or noise limitations in DICOM images. When this is the case, we recommend that the model be annotated with documentation of those parts of the ROI where segmentation quality may be limited.

Image interpretation

Medical images acquired for a clinical indication should be interpreted with the interpretation being incorporated into the patient medical record. The interpretation should include the ROI being considered for printing. Often, interpretation of the ROI incorporates 3D visualization to enable or enhance diagnosis. Examples of 3D visualization include multi-planar reformatting, maximum intensity projections, and volume rendering. Such interpretations are currently billable in the United States under CPT codes 76376 and 76377.

Image segmentation

Image segmentation is necessary to create 3D printable files from medical images. The segmentation process, which subdivides medical images into anatomical regions, typically begins by importing a set of DICOM images into dedicated image post-processing software. Anatomical regions are selected using a combination of automated and semi-automated tools. Once the desired ROI for 3D printing has been selected, data is interpolated and a surface-based 3D model which describes the 3D geometry of that volume is calculated. To date, the most common, widely used, and accepted file format for medical 3D printed objects is the STL file.

STL files are composed of triangular faces, and the number of these faces can affect anatomical accuracy of a model. Each lab should determine the appropriate number of faces/triangles for their medical models to adequately represent anatomy. Operators should be aware of any reduction, smoothing, or further file manipulation or optimization within the segmentation software when creating and exporting the STL file.

The contours of the STL file should be routinely checked against the source medical imaging data; typical segmentation software packages allow the final STL to be re-imported and its contours displayed over the original DICOM images. This option can be used to verify the surface accuracy of an anatomical model STL file. Additional file formats noted above should also meet the same criteria.

Segmentation and Computer Aided Design (CAD) software

Medical image processing software is required to generate a file format amenable to 3D printing. The RSNA 3D printing SIG concurs with the FDA that software that has been favorably evaluated by the FDA be used to translate medical images into formats amenable to 3D printing for all aspects of patient care, defined by the SIG as all interactions with healthcare professionals, or patients and their families, related to medical care. The SIG recommends that software used for segmentation is FDA cleared to produce 3D Printed models suitable for diagnostic use, specifically using the FDA definition of diagnostic use and noting that FDA cleared software for 3D printed models will also include machines and materials validated for this intended use. At the time of manuscript submission, the FDA has approved one complete system, consisting of software through the printing process, for medical model production.

File storage and descriptors

Files stored within a repository should contain or be linked to a set of corresponding descriptors, including those pertaining to image acquisition and further imaging processing. Descriptors should be supported by standardized terminology from a consensus vocabulary; the SIG acknowledges that this vocabulary represents a current, unmet need. If the descriptors are not within digital files, this information should be otherwise archived.

Reference to file manipulation and alteration

Data from medical images undergo alterations in the design of the physical model. These changes have been categorized into Minor and Major alterations, with the latter generally representing changes that could impact clinical care. When modifications include major changes, the operator should verify that both the digital file and 3D printed model is labeled/identified appropriately.

3D printing

There are many different 3D printing technologies, each differing in the way that the final 3D printed model is created. When 3D printed models are generated from medical images, the resolution of the 3D printer should be equal to, or superior to that of the clinical images used to segment the model. Similar to the DICOM acquisition stage, it is preferable that printed layers be a multiplier of the smallest geometry of interest. For example, if the smallest anatomical object of interest on the 3D model is 1 mm, this object should be printed on at least 3 layers of the model. Due to the nature of medical models, and the need for sub-millimeter accuracy, a layer thickness of no more than one-third of a millimeter is recommended, and preferably less than or equal to one-eighth of a millimeter. In addition to the layer thickness of the 3D printing hardware, the in-plane (x-y) resolution should be known, with a target of less than one-quarter of a millimeter. The values above are global recommendations may not be applicable in all cases. If a model requires a higher or lower accuracy, these parameters should be modified accordingly.

The medical model should include a patient identifier or an internal unique identification number that can be tracked back to the patient and date of the image acquisition. Labels can be incorporated (3D printed) into the model itself. Labels should be externally attached to the model if size or location does not allow for printed labeling. Printed models are assumed to be of anatomic size (1:1) unless a scaling factor is otherwise noted. Additional identifiers such as model sidedness (left, right) should be noted, as appropriate. Institutional guidelines should be used to verify models are free of protected health information, or models are handled appropriately in accordance to Health Insurance Portability and Accountability Act (HIPAA) guidelines.

Post-processing printed models

Post-processing steps should not alter the intended morphology and desired accuracy of the part, but instead should only enhance the utility (including clarity and transparency) and/or durability of the model. It should be noted that finishing may slightly alter the dimensional accuracy of a part, but this variation should be minimal (or within the desired global accuracy of the part) and the benefits (for example: strength and clarity) should outweigh the dimensional change. All support materials and residual manufacturing materials and/or substances should be removed as completely as possible. If all supporting material is not capable of being removed, this should be noted and presented to the requesting provider. Should the model be damaged either during or after post-processing and cleaning, repairs should be performed in a manner that reconstitutes the quality to which the original model adhered. If these repairs are not possible, the model should be reprinted. Any damage should be noted to the provider and the option to reprint should be presented. Cleaning solution concentration and saturation levels should be monitored and maintained in accordance to manufacture recommendations.

Model inspection

The model should be inspected by the 3D printing laboratory before clinical use. For cases where the model may be limited by a known image artifact, the model will be noted with any areas of concern. Qualitative and/or quantitative measures to confirm that the 3D printed model matches the desired input data will be taken, including but not limited to expert subjective assessment and objective fitting to the original volume submitted for printing. This can be done on a per part basis, per build basis, or in accordance with an additional internal protocol of the 3D lab. Some examples of qualitative assessments could include comparing the model to a digital representation or printed picture of the model and inspecting the model for printing imperfections or inaccuracies. Some examples of quantitative inspections could include measurements of a test specimen, measurements of the model, or scanning and comparing the model back to the original DICOM data sets.

The U.S. Food and Drug Administration (FDA)

The U.S. Food and Drug Administration (FDA) ensures the safety and efficacy of personalized devices in the United States of America. 3D Printing falls under the auspices of The Center for Devices and Radiological Health (CDRH). There have been four FDA benchmarks related to 3D printing and medical devices from 2014 to 2018.

First, in October 2014, the FDA held a public workshop entitled “Additive Manufacturing of Medical Devices: An Interactive Discussion on the Technical Considerations of 3D Printing”. Second, the FDA published “Additively Manufactured Medical Products – The FDA Perspective”. Third, in December 2017, the FDA published “Technical Considerations for Additive Manufactured Devices”. This perspective included insights regarding 3D printing data manipulation and hardware for modeling patient-specific anatomy. Fourth, the FDA commented on the publication “Maintaining Safety and Efficacy for 3D Printing in Medicine”. This paper uses a similar, logical 3-step format of these consensus recommendations, and then develops different suggestions for regulatory models that depend on how much, if at all, the anatomical data is modified before 3D printing. On August 31st, 2017, the RSNA SIG and the FDA engaged in a joint meeting to discuss 3D printed anatomic models. The intended output of this meeting is a co-published white paper that will form the next benchmark.

Quality control program

Due to environmental factors and material properties, model morphology is expected to change over time. As part of a complete quality control program, 3D printers should undergo regular accuracy testing, including test prints, preventative maintenance, and recalibration. Laboratories may develop a process using a phantom to ensure regular quality standards for their printers. If the reference standard is known or assumed, mathematical operations can be applied equally to those volumes in the ROI to determine the overall accuracy of the model, including not only potential manual errors from segmentation, but also generation of the final data set including digital post-processing steps such as smoothing.

Delivery and discussion with referring physicians

3D printed models represent an advanced form of communication of the data in medical images, and may include the summation of data from multiple sources. Extensive multidisciplinary teaching opportunities for 3D printing have been realized. Physicians should have an opportunity to discuss the salient features and intended use of all models. Any concerns about the model or segmentation process, if not discussed previously, should be noted to the provider at the time of delivery. Where possible, annotations detailing critical points of model anatomy should be stored both within the digital record of the model, and physically placed on the 3D printed model. One example is annotation of a subtle fracture that may not otherwise be represented in either or both, the segmented, or the 3D printed model.

Pre-operative planning

“Pre-operative planning” with 3D printing refers to virtual surgical planning (also called digital templating, digital surgical planning, virtual planning, computerized planning, computer-assisted surgical simulation). This detailed planning of the intervention occurs in the digital space. There are times when the simulation itself is the end product, and the interventionist acquires valuable information regarding patient anatomy and medical devices to be used to increase confidence and knowledge before surgery. For these cases the digital plan is transferred to patient care by way of 3D printed templates, guides, or models. This type of planning usually involves major changes to the digital model while utilizing original patient contours. This necessitates the systematic application of the 3D printing recommendations outlined above to the models used for virtual surgical planning as a minimum requirement.

Material biocompatibility, cleaning, and sterilization

For anatomical models and surgical guides/templates/jigs potentially entering a surgical field, material biocompatibility, cleaning, and sterilization are vitally important. The details are beyond the scope of this document. However, biocompatibility of materials depends on several factors including base material, the 3D printing process (and any variations), any post-processing techniques, and hospital cleaning and sterilization methods and requirements. Manufacturers should provide cleaning recommendations and specifications for materials which have been formally tested for biocompatibility and sterility, and these specifications should be followed by the facility. Additional internal sterilization policies may exist depending on the hospital.

Appropriateness of 3D printing (anatomic modeling) for selected clinical scenarios

This section provides evidence-based guidelines, supplemented by expert opinion when there is a paucity of peer-review data, to define and support the use of 3D printing for patients with a variety of conditions, including congenital heart, vascular, craniomaxillofacial, musculoskeletal, genitounirary, and breast pathologies (Table 1).

Discussion

Reviews that include the types of 3D printers commonly used in medicine have been published. Regarding image post-processing and software, several tutorials are available for step-by-step training. The following discussion includes the specific descriptions from the SIG writing group for each clinical group of clinical scenarios considered for appropriateness.

Congenital heart disease

Congenital heart diseases (CHD) are the most common significant birth defects. Substantial literature supports the benefit of 3D printing for patients with congenital heart disease. Regarding improved outcomes, precise preoperative understanding of the complex anatomy from a printed model may obviate or shorten lengthy exploration, and therefore operation and cardiopulmonary bypass time can be reduced.

These recommendations utilize and conform to the CHD nomenclature defined by the European Association for Cardio-Thoracic Surgery / Society of Thoracic Surgery (EACTS-STS) version of the International Pediatric and Congenital Cardiac Code (IPCCC), except as where noted otherwise. The clinical scenarios defined by the IPCCC include the following: Septal Defects, Pulmonary Venous Anomalies, Cor Triatriatum, Pulmonary Venous Stenosis, Right Heart Lesions, Left Heart Lesions, Single Ventricle, Transposition of the Great Arteries, DORV, DOLV.

Structured searches were performed using the US National Library of Medicine (PubMed), which enabled the querying and retrieval of appropriate clinical documents supporting the appropriateness of 3D printing-enabled technologies for each specific diagnosis. The search results were reviewed by experts and some references were removed and some were relocated to different categories. As noted above, references outside of the structured searches were added but noted and approved by the writing group. As a general rule, the benefits of 3D printing to define and rehearse an intervention increase with the overall degree of complexity of disease.

Craniomaxillofacial pathologies

The International Classification of Diseases, Tenth Revision (ICD-10) descriptions and categorization were used to categorize the clinical scenarios for rating craniomaxillofacial conditions. Four major groups were used as the starting point; 1) Craniomaxillofacial Trauma, 2) Congenital Malformations, 3) Acquired/Developmental Deformities and 4) Neoplasms. Further sub-groups were formed underneath the major groupings. Additional clarification for “simple” versus “complex” diagnoses within a particular group was given based on inherent differences in appropriateness ratings between subgroups of patients in these groups. Further language describing each diagnostic grouping helps describe the difference between a simple and a complex case in each subcategory.

Structured searches were performed using the US National Library of Medicine (PubMed), which enabled the querying and retrieval of appropriate clinical documents supporting the appropriateness of 3D printing-enabled technologies for a specific condition. The search results were reviewed by experts and some references were removed because they were not relevant. A small number of references were added because they were found to be relevant, but not appearing using the stated search string. As noted above, these were vetted by the writing group before inclusion. Clinical scenarios that were only dental or only brain have not been included. The authors recognize that these include many important clinical scenarios of for 3D printing, and the goal is to include them in upcoming documents.

Craniomaxillofacial (CMF) conditions for the purposes of this document encompass several different surgical specialties all working in the head and neck area with both pediatric and adult patients. These include oral and maxillofacial surgery, craniofacial surgery, plastic surgery, microvascular surgery, pediatric neurosurgery and otolaryngology. Use of 3D printing-enabled technologies to aid clinical care in the craniomaxillofacial area has been seen from the very advent of 3D printing in the late 1980s. Even before the commercialization of stereolithography there were surgeons, engineers and researchers figuring out more manual ways of converting medical imaging datasets into 3D models. The fit seems clear, CMF surgery has both a functional component, and for most cases an aesthetic component, where the form carries importance along with the functional restoration. In the CMF arena, the use of anatomical models of anatomy is primarily derived from CT and MRI datasets, and also from an increasing volume of cone beam CT datasets. Patient-specific anatomical models are the baseline, but for many of these applications the value of these technologies has been found in either, a) patient-matched implants (for instance temporomandibular joint reconstruction), or b) virtual surgery combined with templates and guides (for instance orthognathic surgery). The scenarios to follow were thought of in this way, with some of them relying heavily on anatomical models alone and some of them relying with increasing importance on the role that digital planning combined with patient-matched implants or templating is playing.

Genitourinary pathologies

The genitourinary conditions have been organized anatomically, recognizing that common genitourinary interventions are largely based on anatomic considerations. The complication rate after major genitourinary surgeries is reflected in the complexity of the lesion. For example, more complex kidney tumors are associated with longer operative times, warm ischemia times, and greater blood loss. High kidney tumor complexity can also be correlated to the risk of major postoperative complications requiring a secondary intervention.

There is a growing body of literature that supports the benefits to patients from 3D printed models. Specifically, 3D printed models may improve comprehension of anatomy and facilitate pre-surgical planning for complex surgical cases, ultimately reducing operation times and improving patient outcomes.

This document describes and provides rating for the clinical scenarios related to 3D printing of genitourinary pathology. Structured searches were performed using the US National Library of Medicine (PubMed), which enabled the querying and retrieval of appropriated clinical documents supporting the appropriateness of 3D printing for a specific diagnosis. As a general rule, the benefits of 3D printing to define and rehearse a genitourinary intervention increases with the overall degree of complexity of the pathology that is represented by the physical model based on a medical imaging study performed in a radiology department.

Musculoskeletal pathologies

The role of 3D printed models in addressing musculoskeletal pathologies can vary depending on a specific clinical scenario, ranging from aiding in informed consent to use in preoperative planning. Custom fixation plates, surgical osteotomy guides and implants can also be generated from 3D data, allowing for virtual surgery and design of a custom implant that is modeled after the contralateral healthy side. In addition, mock surgeries can be performed on the physical 3D models, allowing for more intuitive problem solving and measurements preoperatively. Such planning alters surgical management for some patients, either by delaying intervention, or by suggesting an alternative approach. Pre-surgical planning can also decrease operating room time and the number of devices and tools that need to be tried and subsequently wasted and/or re-sterilized. In this sense, 3D printing has proven useful for demonstrating musculoskeletal pathology and for planning interventions.

Based on the accumulating evidence, the use of 3D printed models can positively impact numerous metrics associated with musculoskeletal interventions, including patient and physician satisfaction, operative time, blood loss, and the various direct and indirect costs associated with patient-centered decision making regarding management of complex disease. At present, the musculoskeletal pathologies with potential and established 3D printing-enabled management have been broadly categorized into fractures, chronic osseous abnormalities, degenerative disorders, neoplastic pathologies, scoliosis, and miscellaneous specific applications including ligamentous injury and heterotopic ossification.

Vascular pathologies

3D printing has been shown to be useful for understanding the vascular anatomy, evaluation of hemodynamics, treatment planning (surgical and endovascular) as well as preclinical testing of devices. It has also been used for medical education and procedural training on vascular models. There are several clinical scenarios for which 3D printing has been used in the care of patients with vascular disease. Because of the nature of vascular pathology, dissection, aneurysm, and stenosis are often treated with medical management and “watchful waiting”; most patients follow this algorithm, and there is little to no role for 3D printing. However, some patients have a clinical presentation and non-invasive tests that warrant intervention, while others progress from watchful waiting to planned intervention. For many of these patients, 3D printing is appropriate. Of note, coronary 3D printing, and cardiac printing in general falls outside the scope of this document. These clinical scenarios will be discussed in future documents.

Most aortic dissections are treated medically, and for these patients there is no indication for 3D printing. However, 3D printing may be appropriate for planning intervention in complex dissections, and in particular dissections that also have enlargement. Models have been used for planning and simulation of stent deployment. Simulation on models can help in identifying the best projections for angiography, best catheter and wire combinations to navigate the anatomy, in for determining appropriate balloon and stent size as well as position.

Endovascular repair of complex aortic aneurysm involving the origin of branches, extreme angulations, complex neck anatomy, and short landing zones can be quite challenging. Use of 3D printed models can aid understanding of complex anatomy, device selection, and design of prosthesis best suited for patient’s anatomy. These models have shown to be useful in planning procedures and increase operator confidence. 3D printed models have also been used to precisely place fenestrations on stent grafts to treat complex aneurysms. In addition, graft replicas can be tested on patient specific 3D model for suitability before being deployed in patients.

Aortic surgeries, especially in the region of aortic arch and upper abdominal aorta can be quite challenging due to origin of branches, angulation and complex aneurysm neck anatomy. 3D printed models have shown to improve surgeons’ understanding of anatomy and help preoperative planning. Further, 3D printed models can potentially also be used to plan and simulate surgical and endovascular interventions on visceral aneurysms. These models can also be used for designing and testing endovascular devices like catheters, coils, balloons, and stents.

Breast pathologies

Breast cancer is the most common solid malignancy in women in the United States. The overall lifetime risk of developing breast cancer for women in the United States is 12.4%. Advancements in diagnostic tests and treatments have led to decreasing death rates of 1.8% per year from 2005 to 2014. Understanding the extent of disease at the time of diagnosis allows appropriate staging and determination of prognosis and survival, in addition to selection of suitable surgical options. Benefits from 3D printed models and its role as an aid to clinical care has been increasingly described in the literature. 3D printed models have the ability of depicting the extent of disease and relationships of sensitive anatomy, thereby possibly reducing operating time, enhancing utilization of new oncoplastic techniques, and improving patient outcomes.

Benign breast diseases are common and include a wide range of entities. The most common of these entities, fibrocystic change, is clinically observed in up to 50% of women and found histologically in 90% of women. Fibroadenomas are the next most common benign breast disease occurring in 15–23% of women. Surgical management of these entities may be needed in cases where cosmesis is altered or when symptom relief is needed. Surgical management may impact developing breast tissue in young women leading to alterations in its proper development. Therefore, careful understanding of the anatomy may minimize the deleterious effects of surgery in benign breast disease.

Conclusions

3D printing will play an increasingly important role in enabling precision medicine. This document addresses the clinical scenarios where pathology complexity necessitates a transformation of clinical imaging data into a physical model. Adoption of common clinical standards regarding appropriate use, information and material management, and quality control are needed to ensure the greatest possible clinical benefit from3D printing.

This work provides the first comprehensive literature-based guideline document regarding the implementation of 3D printing in clinical practice and details the appropriate scenarios for numerous clinical applications of 3D printing. It is anticipated that this consensus guideline document, created by the members of the RSNA 3D printing special group, will provide the initial reference for method and clinical application standardization. The document and will be substantially expanded and refined, based on expanding clinical applications.

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    Qiu X, Lü B, Xu N, Yan CW, Ouyang WB, Liu Y, Zhang FW, Yue ZQ, Pang KJ, Pan XB. Feasibility of device closure for multiple atrial septal defects using 3D printing and ultrasound-guided intervention technique. Zhonghua Yi Xue Za Zhi. 2017;97(16):1214-1217.

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    Wang Z, Liu Y, Xu Y, Gao C, Chen Y, Luo H. Three-dimensional printing-guided percutaneous transcatheter closure of secundum atrial septal defect with rim deficiency: first-in-human series. Cardiol J. 2016;23(6):599-603.

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    Wang Z, Luo H, Gao C, Xu Y. Three-dimensional printing model for the postoperative follow-up of atrial septal defect. Int J Cardiol. 2016;222:891-892.

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    Yang F, Zheng H, Lyu J, Yang X, Yang Y, Pang Y, Liang F, Zhang G, Xu Z, Jiang S, Lyu B, Meng F, Hao B. A case of transcatheter closure of inferior vena cava type atrial septal defect with patent ductus arteriosus occlusion device guided by 3D printing technology. Zhonghua Xin Xue Guan Bing Za Zhi. 2015;43(7):631-633.

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    Bhatla P, Mosca RS, Tretter JT. Altering management decisions with gained anatomical insight from a 3D printed model of a complex ventricular septal defect. Cardiol Young. 2017;27(2):377-380.

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    Bhatla P, Tretter JT, Ludomirsky A, Argilla M, Latson LA, Chakravarti S, Barker PC, Yoo S-J, McElhinney DB, Wake N, Mosca RS. Utility and scope of rapid prototyping in patients with complex muscular ventricular septal defects or double-outlet right ventricle: does it Alter Management decisions? Pediatr Cardiol. 2017;38(1):103-114.

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    Farooqi KM, Uppu SC, Nguyen K, Srivastava S, Ko HH, Choueiter N, Wollstein A, Parness IA, Narula J, Sanz J, Nielsen JC. Application of virtual three-dimensional models for simultaneous visualization of Intracardiac anatomic relationships in double outlet right ventricle. Pediatr Cardiol. 2015;37(1):90-98.

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    Garekar S, Bharati A, Chokhandre M, Mali S, Trivedi B, Changela VP, Solanki N, Gaikwad S, Agarwal V. Clinical application and multidisciplinary assessment of three dimensional printing in double outlet right ventricle with remote ventricular septal defect. World J Pediatr Congenit Heart Surg. 2016;7(3):344-350.

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    Ngan EM, Rebeyka IM, Ross DB, Hirji M, Wolfaardt JF, Seelaus R, Grosvenor A, Noga ML. The rapid prototyping of anatomic models in pulmonary atresia. J Thorac Cardiovasc Surg. 2006;132(2):264-269.

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    Olivieri LJ, Krieger A, Loke Y-H, Nath DS, Kim PCW, Sable CA. Three-dimensional printing of intracardiac defects from three-dimensional echocardiographic images: feasibility and relative accuracy. J Am Soc Echocardiogr. 2015;28(4):392-397.

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    Sodian R, Weber S, Markert M, Rassoulian D, Kaczmarek I, Lueth TC, Reichart B, Daebritz S. Stereolithographic models for surgical planning in congenital heart surgery. Ann Thorac Surg. 2007;83(5):1854-1857.

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    Valverde I, Gomez G, Gonzalez A, Suarez-Mejias C, Adsuar A, Coserria JF, Uribe S, Gomez-Cia T, Hosseinpour AR. Three-dimensional patient-specific cardiac model for surgical planning in Nikaidoh procedure. Cardiol Young. 2015;25(4):698-704.

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    Schievano S, Migliavacca F, Coats L, Khambadkone S, Carminati M, Wilson N, Deanfield JE, Bonhoeffer P, Taylor AM. Percutaneous pulmonary valve implantation based on rapid prototyping of right ventricular outflow tract and pulmonary trunk from MR data. Radiology. 2007;242(2):490-497.

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    Ryan JR, Moe TG, Richardson R, Frakes DH, Nigro JJ, Pophal S. A novel approach to neonatal Management of Tetralogy of Fallot, with pulmonary atresia, and multiple Aortopulmonary collaterals. JACC Cardiovasc Imaging. 2015;8(1):103-104.

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    Bhatla P, Tretter JT, Chikkabyrappa S, Chakravarti S, Mosca RS. Surgical planning for a complex double-outlet right ventricle using 3D printing. Echocardiography. 2017;34(5):802-804.

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    Farooqi KM, Gonzalez-Lengua C, Shenoy R, Sanz J, Nguyen K. Use of a three dimensional printed cardiac model to assess suitability for biventricular repair. World J Pediatr Congenit Heart Surg. 2016;7(3):414-416.

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    Farooqi KM, Nielsen JC, Uppu SC, Srivastava S, Parness IA, Sanz J, Nguyen K. Use of 3-dimensional printing to demonstrate complex intracardiac relationships in double-outlet right ventricle for surgical planning. Circ Cardiovasc Imaging. 2015;8(5):e003043.

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    Dydynski PB, Kiper C, Kozik D, Keller BB, Austin E, Holland B. Three-dimensional reconstruction of Intracardiac anatomy using CTA and surgical planning for double outlet right ventricle: early experience at a tertiary care congenital heart center. World J Pediatr Congenit Heart Surg. 2016;7(4):467-474.

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    Kappanayil M, Koneti NR, Kannan RR, Kottayil BP, Kumar K. Three-dimensional-printed cardiac prototypes aid surgical decision-making and preoperative planning in selected cases of complex congenital heart diseases: early experience and proof of concept in a resource-limited environment. Ann Pediatr Cardiol. 2017;10(2):117-125.

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    Biglino G, Giardini A, Hsia T-Y, Figliola R, Taylor AM, Schievano S, MOCHA Collaborative Group. Modeling single ventricle physiology: review of engineering tools to study first stage palliation of hypoplastic left heart syndrome. Front Pediatr. 2013;1:31.

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    Smith ML, McGuinness J, O’Reilly MK, Nolke L, Murray JG, Jones JFX. The role of 3D printing in preoperative planning for heart transplantation in complex congenital heart disease. Ir J Med Sci. 2017;186(3):753-756.

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    Gosnell J, Pietila T, Samuel BP, Kurup HKN, Haw MP, Vettukattil JJ. Integration of computed tomography and three-dimensional echocardiography for hybrid three-dimensional printing in congenital heart disease. J Digit Imaging. 2016;29(6):665-669.

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    Olivieri L, Krieger A, Chen MY, Kim P, Kanter JP. 3D heart model guides complex stent angioplasty of pulmonary venous baffle obstruction in a mustard repair of D-TGA. Int J Cardiol. 2014;172(2):e297-e298.

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    Aung SC, Tan BK, Foo CL, Lee ST. Selective laser sintering: application of a rapid prototyping method in craniomaxillofacial reconstructive surgery. Ann Acad Med Singap. 1999;28(5):739-743.

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    Cheung LK, Wong MC, Wong LL. Refinement of facial reconstructive surgery by stereo-model planning. Ann R Australas Coll Dent Surg. 2002;16:129-132.

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    Schantz JT, Hutmacher DW, Lam CX, Brinkmann M, Wong KM, Lim TC, Chou N, Guldberg RE, Teoh SH. Repair of calvarial defects with customised tissue-engineered bone grafts II. Evaluation of cellular efficiency and efficacy in vivo. Tissue Eng. 2003;9 Suppl 1:S127-S139.

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    Wagner JD, Baack B, Brown GA, Kelly J. Rapid 3-dimensional prototyping for surgical repair of maxillofacial fractures: a technical note. J Oral Maxillofac Surg. 2004;62(7):898-901.

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    Levine JP, Patel A, Saadeh PB, Hirsch DL. Computer-aided design and manufacturing in craniomaxillofacial surgery: the new state of the art. J Craniofac Surg. 2012;23(1):288-293.

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    Cui J, Chen L, Guan X, Ye L, Wang H, Liu L. Surgical planning, three-dimensional model surgery and preshaped implants in treatment of bilateral craniomaxillofacial post-traumatic deformities. J Oral Maxillofac Surg. 2014;72(6):1138.e1-1138.14.

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    Kaur H, Nanda A, Koli D, Verma M, Singh H, Bishnoi I, Pathak P, Gupta A. An alternate vista in rehabilitation of cranial defects: combining digital and manual techniques to fabricate a hybrid Cranioplast. J Craniofac Surg. 2015;26(4):1313-1315.

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    Xie Y, Rustom LE, McDermott AM, Boerckel JD, Johnson AJ, Alleyne AG, Hoelzle DJ. Net shape fabrication of calcium phosphate scaffolds with multiple material domains. Biofabrication. 2016;8(1):015005.

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    Florentino VG, Mendonça DS, Bezerra AV, Silva Lde F, Pontes RF, Melo CV, Mello Mde J, de Aguiar AS. Reconstruction of frontal bone with custom-made prosthesis using rapid prototyping. J Craniofac Surg. 2016;27(4):e354-e356.

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    Shao H, Ke X, Liu A, Sun M, He Y, Yang X, Fu J, Liu Y, Zhang L, Yang G, Xu S, Gou Z. Bone regeneration in 3D printing bioactive ceramic scaffolds with improved tissue/material interface pore architecture in thin-wall bone defect. Biofabrication. 2017;9(2):025003.

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    Gao F, Wang Q, Liu C, Xiong B, Luo T. Individualized 3D printed model-assisted posterior screw fixation for the treatment of craniovertebral junction abnormality: a retrospective study. J Neurosurg Spine. 2017;27(1):29-34.

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    Edwards J, Rogers T. The accuracy and applicability of 3D modeling and printing blunt force cranial injuries. J Forensic Sci. 2018;3(3):683-691.

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    Murray DJ, Edwards G, Mainprize JG, Antonyshyn O. Optimizing craniofacial osteotomies: applications of haptic and rapid prototyping technology. J Oral Maxillofac Surg. 2008;66(8):1766-1772.

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    Kozakiewicz M, Elgalal M, Loba P, Komuński P, Arkuszewski P, Broniarczyk-Loba A, Stefańczyk L. Clinical application of 3D pre-bent titanium implants for orbital floor fractures. J Craniomaxillofac Surg. 2009;37(4):229-234.

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    Li WZ, Zhang MC, Li SP, Zhang LT, Huang Y. Application of computer-aided three-dimensional skull model with rapid prototyping technique in repair of zygomatico-orbito-maxillary complex fracture. Int J Med Robot. 2009;5(2):158-163.

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    Tang W, Guo L, Long J, Wang H, Lin Y, Liu L, Tian W. Individual design and rapid prototyping in reconstruction of orbital wall defects. J Oral Maxillofac Surg. 2010;68(3):562-570.

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    Herlin C, Koppe M, Béziat JL, Gleizal A. Rapid prototyping in craniofacial surgery: using a positioning guide after zygomatic osteotomy - a case report. J Craniomaxillofac Surg. 2011;39(5):376-379.

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    Feng F, Wang H, Guan X, Tian W, Jing W, Long J, Tang W, Liu L. Mirror imaging and preshaped titanium plates in the treatment of unilateral malar and zygomatic arch fractures. Oral Surg Oral Med Oral Pathol Oral Radiol Endod. 2011;112(2):188-194.

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    An JG, Zhang Y, He Y, Li JM. Application of 3-D skull models and guide plates in the treatment of unilateral orbitozygomatic deformity after fracture. Zhonghua Zheng Xing Wai Ke Za Zhi. 2011;27(2):81-85.

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    He LS, Shang HT, Bai SZ, Bo B. Digital surgical technology in reconstruction of orbital frame. Zhonghua Kou Qiang Yi Xue Za Zhi. 2011;46(8):452-457.

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    Li J, Li P, Lu H, Shen L, Tian W, Long J, Tang W. Digital design and individually fabricated titanium implants for the reconstruction of traumatic zygomatico-orbital defects. J Craniofac Surg. 2013;24(2):363-368.

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    Fang JJ, Liu JK, Wu TC, Lee JW, Kuo TH. Complex facial deformity reconstruction with a surgical guide incorporating a built-in occlusal stent as the positioning reference. J Craniofac Surg. 2013;24(3):e260-e265.

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    Liu XZ, Shu DL, Ran W, Guo B, Liao X. Digital surgical templates for managing high-energy zygomaticomaxillary complex injuries associated with orbital volume change: a quantitative assessment. J Oral Maxillofac Surg. 2013;71(10):1712-1723.

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    Ernoult C, Bouletreau P, Meyer C, Aubry S, Breton P, Bachelet JT. Reconstruction assisted by 3D printing in maxillofacial surgery. Rev Stomatol Chir Maxillofac Chir Orale. 2015;116(2):95-102.

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    Park SW, Choi JW, Koh KS, Oh TS. Mirror-imaged rapid prototype skull model and pre-molded synthetic scaffold to achieve optimal orbital cavity reconstruction. J Oral Maxillofac Surg. 2015;73(8):1540-1553.

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    D'Souza N, Mainprize J, Edwards G, Binhammer P, Antonyshyn O. Teaching facial fracture repair: a novel method of surgical skills training using three-dimensional biomodels. Plast Surg (Oakv). 2015;23(2):81-86.

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    Tabaković SZ, Konstantinović VS, Radosavljević R, Movrin D, Hadžistević M, Hatab N. Application of computer-aided designing and rapid prototyping Technologies in Reconstruction of blowout fractures of the orbital floor. J Craniofac Surg. 2015;26(5):1558-1563.

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    Sun L, Xiao J, Lan Y, Xiong Y, Zhang L, Zhou H, Zhang L. Reconstruction of the orbital fracture with enophthalmos using customized titanium mesh combined with Medpor. Hua Xi Kou Qiang Yi Xue Za Zhi. 2015;33(3):272-275.

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    Podolsky DJ, Mainprize JG, Edwards GP, Antonyshyn OM. Patient-specific orbital implants: development and implementation of Technology for More Accurate Orbital Reconstruction. J Craniofac Surg. 2016;27(1):131-133.

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    Huang L, Lin L, Wang Z, Shi B, Zhu X, Qiu Y, Huang Y, Yu X, Liao Y. Personalized reconstruction of traumatic orbital defects based on precise three-dimensional orientation and measurements of the globe. J Craniofac Surg. 2017;28(1):172-179.

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    Williams JV, Revington PJ. Novel use of an aerospace selective laser sintering machine for rapid prototyping of an orbital blowout fracture. Int J Oral Maxillofac Surg. 2010;39(2):182-184.

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    Kozakiewicz M, Elgalal M, Piotr L, Broniarczyk-Loba A, Stefanczyk L. Treatment with individual orbital wall implants in humans - 1-year ophthalmologic evaluation. J Craniomaxillofac Surg. 2011;39(1):30-36.

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    Li P, Tang W, Li J, Tian DW. Preliminary application of virtual simulation and reposition template for zygomatico-orbitomaxillary complex fracture. J Craniofac Surg. 2012;23(5):1436-1439.

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    Ciprandi MT, Primo BT, Gassen HT, Closs LQ, Hernandez PA, Silva AN. Calcium phosphate cement in orbital reconstructions. J Craniofac Surg. 2012;23(1):145-148.

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    Huang YH, Seelaus R, Zhao L, Patel PK, Cohen M. Virtual surgical planning and 3D printing in prosthetic orbital reconstruction with percutaneous implants: a technical case report. Int Med Case Rep J. 2016;9:341-345.

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    Herford AS, Miller M, Lauritano F, Cervino G, Signorino F, Maiorana C. The use of virtual surgical planning and navigation in the treatment of orbital trauma. Chin J Traumatol. 2017;20(1):9-13.

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    Tetsworth K, Block S, Glatt V. Putting 3D modelling and 3D printing into practice: virtual surgery and preoperative planning to reconstruct complex post-traumatic skeletal deformities and defects. SICOT J. 2017;3:16.

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    Veit JA, Thierauf J, Egner K, Wiggenhauser S, Friedrich D, Greve J, Schuler PJ, Hoffmann TK, Schramm A. Virtual planning of prosthetic treatment of the orbit. Laryngorhinootologie. 2017;96(6):374-379.

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    Li J, Hsu Y, Luo E, Khadka A, Hu J. Computer-aided design and manufacturing and rapid prototyped nanoscale hydroxyapatite/polyamide (n-HA/PA) construction for condylar defect caused by mandibular angle ostectomy. Aesthet Plast Surg. 2011;35(4):636-640.

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    Wang G, Li J, Khadka A, Hsu Y, Li W, Hu J. CAD/CAM and rapid prototyped titanium for reconstruction of ramus defect and condylar fracture caused by mandibular reduction. Oral Surg Oral Med Oral Pathol Oral Radiol. 2012;113(3):356-361.

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    Prisman E, Haerle SK, Irish JC, Daly M, Miles B, Chan H. Value of preoperative mandibular plating in reconstruction of the mandible. Head Neck. 2014;36(6):828-833.

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    Yamada H, Nakaoka K, Horiuchi T, Kumagai K, Ikawa T, Shigeta Y, Imamura E, Iino M, Ogawa T, Hamada Y. Mandibular reconstruction using custom-made titanium mesh tray and particulate cancellous bone and marrow harvested from bilateral posterior ilia. J Plast Surg Hand Surg. 2014;48(3):183-190.

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    Xu X, Deng RX, Deng SM, Yang JL, Chen J. Application of three dimensional model in treatment of superolateral dislocation of mandibular condyle. Zhejiang Da Xue Xue Bao Yi Xue Ban. 2014;43(5):572-576.

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    Dong Z, Li Q, Bai S, Zhang L. Application of 3-dimensional printing technology to Kirschner wire fixation of adolescent condyle fracture. J Oral Maxillofac Surg. 2015;73(10):1970-1976.

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    Fowell C, Edmondson S, Martin T, Praveen P. Rapid prototyping and patient-specific pre-contoured reconstruction plate for comminuted fractures of the mandible. Br J Oral Maxillofac Surg. 2015;53(10):1035-1037.

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    el-Gengehi M, Seif SA. Evaluation of the accuracy of computer-guided mandibular fracture reduction. J Craniofac Surg. 2015;26(5):1587-1591.

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    Qu Z, Wang Q, Feng X, Sheng L, Ma W, Qu W. Application of 3D printing technique in bilateral sagittal split osteotomy. Hua Xi Kou Qiang Yi Xue Za Zhi. 2015;33(5):504-508.

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    van de Velde WL, Schepers RH, van Minnen B. The 3D-printed dental splint: a valuable tool in the surgical treatment of malocclusion after polytrauma. Ned Tijdschr Tandheelkd. 2016;123(1):19-23.

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    Yamada H, Nakaoka K, Sonoyama T, Kumagai K, Ikawa T, Shigeta Y, Harada N, Kawamura N, Ogawa T, Hamada Y. Clinical usefulness of mandibular reconstruction using custom-made titanium mesh tray and autogenous particulate cancellous bone and marrow harvested from tibia and/or Ilia. J Craniofac Surg. 2016;27(3):586-592.

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    Druelle C, Touzet-Roumazeille S, Raoul G, Ferri J, Nicot R. How to produce pre-shaped rigid arch bars using low-cost 3D printing technology- a technical note. J Stomatol Oral Maxillofac Surg. 2017;118:213-216.

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    Paeng JY, Lee JH, Lee JH, Kim MJ. Condyle as the point of rotation for 3-D planning of distraction osteogenesis for hemifacial microsomia. J Craniomaxillofac Surg. 2007;35(2):91-102.

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    Robiony M, Salvo I, Costa F, Zerman N, Bazzocchi M, Toso F, Bandera C, Filippi S, Felice M, Politi M. Virtual reality surgical planning for maxillofacial distraction osteogenesis: the role of reverse engineering rapid prototyping and cooperative work. J Oral Maxillofac Surg. 2007;65(6):1198-1208.

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    McGurk M, Slabberti HD, Amis A, McDonald F. A preliminary report of a case using an intra-oral distraction device. Br Dent J. 1997;183(2):63-66.

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    Klammert U, Böhm H, Schweitzer T, Würzler K, Gbureck U, Reuther J, Kübler A. Multi-directional Le fort III midfacial distraction using an individual prefabricated device. J Craniomaxillofac Surg. 2009;37(4):210-215.

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    Zhou L, He L, Shang H, Liu G, Zhao J, Liu Y. Correction of hemifacial microsomia with the help of mirror imaging and a rapid prototyping technique: case report. Br J Oral Maxillofac Surg. 2009;47(6):486-488.

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    Olszewski R, Reychler H. Three-dimensional surgical guide for frontal-nasal-ethmoid-vomer disjunction in Le fort III osteotomy. J Craniofac Surg. 2011;22(5):1791-1792.

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    Gao QW, Song HF, Xu MH, Liu CM, Chai JK. Mandibular-driven simultaneous maxillo-mandibular distraction for hemifacial microsomia with rapid prototyping technology. Zhonghua Zheng Xing Wai Ke Za Zhi. 2013;29(6):431-434.

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    Seres L, Varga E, Kocsis A, Rasko Z, Bago B, Varga E, Piffko J. Correction of a severe facial asymmetry with computerized planning and with the use of a rapid prototyped surgical template: a case report/technique article. Head Face Med. 2014;10:27.

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    Engel M, Hoffmann J, Castrillon-Oberndorfer G, Freudlsperger C. The value of three-dimensional printing modelling for surgical correction of orbital hypertelorism. Oral Maxillofac Surg. 2015;19(1):91-95.

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    Kang SH, Kim MK, You TK, Lee JY. Modification of planned postoperative occlusion in orthognathic surgery, based on computer-aided design/computer-aided manufacturing-engineered preoperative surgical simulation. J Oral Maxillofac Surg. 2015;73(1):134-151.

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    Yin L, Tang X, Shi L, Yin H, Zhang Z. Mandibular distraction combined with orthognathic techniques for the correction of severe adult mandibular hypoplasia. J Craniofac Surg. 2014;25(6):1947-1952.

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    Mazzoni S, Bianchi A, Schiariti G, Badiali G, Marchetti C. Computer-aided design and computer-aided manufacturing cutting guides and customized titanium plates are useful in upper maxilla waferless repositioning. J Oral Maxillofac Surg. 2015;73(4):701-707.

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    Shi L, Liu W, Yin L, Feng S, Xu S, Zhang ZY. Surgical guide assistant mandibular distraction osteogenesis and sagittal split osteotomy in the treatment of hemifacial microsomia. J Craniofac Surg. 2015;26(2):498-500.

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    Xu H, Zhang C, Shim YH, Li H, Cao D. Combined use of rapid-prototyping model and surgical guide in correction of mandibular asymmetry malformation patients with normal occlusal relationship. J Craniofac Surg. 2015;26(2):418-421.

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    Soleman J, Thieringer F, Beinemann J, Kunz C, Guzman R. Computer-assisted virtual planning and surgical template fabrication for frontoorbital advancement. Neurosurg Focus. 2015;38(5):E5.

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    Li Y, Jiang Y, Ye B, Hu J, Chen Q, Zhu S. Treatment of Dentofacial deformities secondary to Osteochondroma of the mandibular condyle using virtual surgical planning and 3-dimensional printed surgical templates. J Oral Maxillofac Surg. 2016;74(2):349-368.

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    Ying B, Ye N, Jiang Y, Liu Y, Hu J, Zhu S. Correction of facial asymmetry associated with vertical maxillary excess and mandibular prognathism by combined orthognathic surgery and guiding templates and splints fabricated by rapid prototyping technique. Int J Oral Maxillofac Surg. 2015;44(11):1330-1336.

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    Chai G, Tan A, Yao CA, Magee WP, Junjun P, Zhu M, Bogari M, Hsu Y, Xu H, Zhang Y. Treating parry-Romberg syndrome using three-dimensional scanning and printing and the anterolateral thigh dermal Adipofascial flap. J Craniofac Surg. 2015;26(6):1826-1829.

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    Seres L, Kocsis A, Varga E, Raskó Z, Virág V, Bagó B, Varga E, Piffkó J. Surgery on virtual model and 3-dimensional printing of a surgical wafer for the correction of a severe mandibular asymmetry. Fogorv Sz. 2015;108(2):45-52.

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    Steinbacher DM. Three-dimensional analysis and surgical planning in Craniomaxillofacial surgery. J Oral Maxillofac Surg. 2015;73(12 Suppl):S40-S56.

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    Fiaschi P, Pavanello M, Imperato A, Dallolio V, Accogli A, Capra V, Consales A, Cama A, Piatelli G. Surgical results of cranioplasty with a polymethylmethacrylate customized cranial implant in pediatric patients: a single-center experience. J Neurosurg Pediatr. 2016;17(6):705-710.

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    Di Rocco F, Szathmari A, Mottolese C. Wire fixation of internal distractor for cranial vault remodeling. Childs Nerv Syst. 2016;32(6):1131-1133.

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    Ikawa T, Shigeta Y, Hirabayashi R, Hirai S, Hirai K, Harada N, Kawamura N, Ogawa T. Computer assisted mandibular reconstruction using a custom-made titan mesh tray and removable denture based on the top-down treatment technique. J Prosthodont Res. 2016;60(4):321-331.

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    Lee UL, Kwon JS, Woo SH, Choi YJ. Simultaneous Bimaxillary surgery and mandibular reconstruction with a 3-dimensional printed titanium implant fabricated by Electron beam melting: a preliminary mechanical testing of the printed mandible. J Oral Maxillofac Surg. 2016;74(7):1501.e1-1501.e15.

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    Emodi O, Shilo D, Israel Y, Rachmiel A. Three-dimensional planning and printing of guides and templates for reconstruction of the mandibular ramus and condyle using autogenous costochondral grafts. Br J Oral Maxillofac Surg. 2017;55(1):102-104.

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    Hatamleh M, Turner C, Bhamrah G, Mack G, Osher J. Improved virtual planning for Bimaxillary orthognathic surgery. J Craniofac Surg. 2016;27(6):e568-e573.

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    Eley KA, Watt-Smith SR, Golding SJ. ‘Black Bone’ MRI: a novel imaging technique for 3D printing. Dentomaxillofac Radiol. 2017;46(3):20160407.

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    LoPresti M, Daniels B, Buchanan EP, Monson L, Lam S. Virtual surgical planning and 3D printing in repeat calvarial vault reconstruction for craniosynostosis: technical note. J Neurosurg Pediatr. 2017;19(4):490-494.

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    Rubio-Palau J, Prieto-Gundin A, Cazalla AA, Serrano MB, Fructuoso GG, Ferrandis FP, Baró AR. Three-dimensional planning in craniomaxillofacial surgery. Ann Maxillofac Surg. 2016;6(2):281-286.

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    Wang L, Tian D, Sun X, Xiao Y, Chen L, Wu G. The precise repositioning instrument for Genioplasty and a three-dimensional printing technique for treatment of complex facial asymmetry. Aesthet Plast Surg. 2017;41(4):919-929.

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    Jiménez Ormabera B, Díez Valle R, Zaratiegui Fernández J, Llorente Ortega M, Unamuno Iñurritegui X, Tejada Solís S. 3D printing in neurosurgery: a specific model for patients with craniosynostosis. Neurocirugia (Astur). 2017;28(6):260-265.

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    Salles F, Anchieta M, Costa Bezerra P, Torres ML, Queiroz E, Faber J. Complete and isolated congenital aglossia: case report and treatment of sequelae using rapid prototyping models. Oral Surg Oral Med Oral Pathol Oral Radiol Endod. 2008;105(3):e41-e47.

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    Yu Q, Gong X, Wang GM, Yu ZY, Qian YF, Shen G. A novel technique for presurgical nasoalveolar molding using computer-aided reverse engineering and rapid prototyping. J Craniofac Surg. 2011;22(1):142-146.

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    Zgong X, Yu Q, Yu ZY, Wang GM, Qian YF. Presurgical alveolar molding using computer aided design in infants with unilateral complete cleft lip and palate. Shanghai Kou Qiang Yi Xue. 2012;21(2):180-184.

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    Gong X, Yu Q. Correction of maxillary deformity in infants with bilateral cleft lip and palate using computer-assisted design. Oral Surg Oral Med Oral Pathol Oral Radiol. 2012;114(5 Suppl):S74-S78.

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    Loeffelbein DJ, Rau A, Wolff KD. Impression technique for monitoring and virtual treatment planning in nasoalveolar moulding. Br J Oral Maxillofac Surg. 2013;51(8):898-901.

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    Wang J, Liu JF, Liu W, Wang JC, Wang SY, Gui L. Application of computer techniques in repair of oblique facial clefts with outer-table calvarial bone grafts. J Craniofac Surg. 2013;24(3):957-960.

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    Zheng Y, Zhang D, Qin T, Wu G. Correction of nasal deformity in infants with unilateral cleft lip and palate using multiple digital techniques. J Prosthet Dent. 2016;115(6):788-791.

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    Ritschl LM, Rau A, Güll FD, diBora B, Wolff KD, Schönberger M, Bauer FX, Wintermantel E, Loeffelbein DJ. Pitfalls and solutions in virtual design of nasoalveolar molding plates by using CAD/CAM technology--a preliminary clinical study. J Craniomaxillofac Surg. 2016;44(4):453-459.

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    Cho MJ, Kane AA, Hallac RR, Gangopadhyay N, Seaward JR. Liquid latex molding: a novel application of 3D printing to facilitate flap design. Cleft Palate Craniofac J. 2017;54(4):453-456.

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    Lioufas PA, Quayle MR, Leong JC, McMenamin PG. 3D printed models of cleft palate pathology for surgical education. Plast Reconstr Surg Glob Open. 2016;4(9):e1029.

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    Du F, Li B, Yin N, Cao Y, Wang Y. Volumetric analysis of alveolar bone defect using three-dimensional-printed models versus computer-aided engineering. J Craniofac Surg. 2017;28(2):383-386.

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    Wu Y, Wang G, Yang Y, Chen Y. Application of computer-aided design and customized implants in the reconstruction of pyriform aperture defects secondary to unilateral cleft lip and palate. J Craniofac Surg. 2017;28:1517-1520.

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    Nicot R., Couly G., Ferri J., Levaillant J.-M. Three-dimensional printed haptic model from a prenatal surface-rendered oropalatal sonographic view: a new tool in the surgical planning of cleft lip/palate. International Journal of Oral and Maxillofacial Surgery. 2018;47(1):44-47.

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    Klein M, Hein A, Lueth T, Bier J. Robot-assisted placement of craniofacial implants. Int J Oral Maxillofac Implants. 2003;18(5):712-718.

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    Hatamleh MM, Watson J. Construction of an implant-retained auricular prosthesis with the aid of contemporary digital technologies: a clinical report. J Prosthodont. 2013;22(2):132-136.

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    Watson J, Hatamleh MM. Complete integration of technology for improved reproduction of auricular prostheses. J Prosthet Dent. 2014;111(5):430-436.

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    Chen ZC, Albdour MN, Lizardo JA, Chen YA, Chen PK. Precision of three-dimensional stereo-photogrammetry (3dMDTM) in anthropometry of the auricle and its application in microtia reconstruction. J Plast Reconstr Aesthet Surg. 2015;68(5):622-631.

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    Berens AM, Newman S, Bhrany AD, Murakami C, Sie KC, Zopf DA. Computer-aided design and 3D printing to produce a costal cartilage model for simulation of auricular reconstruction. Otolaryngol Head Neck Surg. 2016;155(2):356-359.

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    Thomas DJ. Could 3D bioprinted tissues offer future hope for microtia treatment? Int J Surg. 2016;32:43-44.

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    Zhu P, Chen S. Clinical outcomes following ear reconstruction with adjuvant 3D template model. Acta Otolaryngol. 2016;136(12):1236-1241.

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    Jeon B, Lee C, Kim M, Choi TH, Kim S, Kim S. Fabrication of three-dimensional scan-to-print ear model for microtia reconstruction. J Surg Res. 2016;206(2):490-497.

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    Flores RL, Liss H, Raffaelli S, Humayun A, Khouri KS, Coelho PG, Witek L. The technique for 3D printing patient-specific models for auricular reconstruction. J Craniomaxillofac Surg. 2017;45(6):937-943.

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    Chen HY, Ng LS, Chang CS, Lu TC, Chen NH, Chen ZC. Pursuing Mirror image reconstruction in unilateral Microtia: customizing auricular framework by application of three-dimensional imaging and three-dimensional printing. Plast Reconstr Surg. 2017;139(6):1433-1443.

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    Federspil PA. The role of auricular prostheses (Epitheses) in ear reconstruction. Facial Plast Surg. 2015;31(6):626-632.

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    Mueller A, Krishnan KG, Uhl E, Mast G. The application of rapid prototyping techniques in cranial reconstruction and preoperative planning in neurosurgery. J Craniofac Surg. 2003;14(6):899-914.

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    Murray DJ, Edwards G, Mainprize JG, Antonyshyn O. Advanced technology in the management of fibrous dysplasia. J Plast Reconstr Aesthet Surg. 2008;61(8):906-916.

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    Ching WC, Goh RC, Lin CL, Lo LJ, Chen YR. Aesthetic restoration of fronto-orbital deformity with prefabricated implant utilizing modeling clay and rapid-prototyping technology. Aesthet Plast Surg. 2011;35(6):1176-1179.

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    Huang D, Chen M, He D, Yang C, Yuan J, Bai G, Wang Y, Wei W, Chen Z. Preservation of the inferior alveolar neurovascular bundle in the osteotomy of benign lesions of the mandible using a digital template. Br J Oral Maxillofac Surg. 2015;53(7):637-641.

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    Darwood A, Collier J, Joshi N, Grant WE, Sauret-Jackson V, Richards R, Dawood A, Kirkpatrick N. Re-thinking 3D printing: a novel approach to guided facial contouring. J Craniomaxillofac Surg. 2015;43(7):1256-1260.

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    Kang SJ, Oh MJ, Jeon SP. A novel and easy approach for contouring surgery in patients with craniofacial fibrous dysplasia. J Craniofac Surg. 2015;26(6):1977-1978.

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    Nahumi N, Shohet MR, Bederson JB, Elahi E. Frontorbital fibrous dysplasia resection and reconstruction with custom Polyetherlatone Alloplast. J Craniofac Surg. 2015;26(8):e720-e722.

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    Pan J, Ye B, Hu J, Li X, Zhang Y, Li J. Application of reverse engineering template for the correction of asymmetric deformity of maxillofacial fibrous dysplasia. J Craniofac Surg. 2016;27(2):e154-e157.

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    Wang R, Li G, Liu C, Jia C, Han Y. Three-dimensional printing of reduction template in the contouring of craniofacial fibrous dysplasia. J Craniofac Surg. 2016;27(7):1792-1794.

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    Eisenmenger LB, Wiggins RH, Fults DW, Huo EJ. Application of 3D printing in a case of osteogenesis imperfecta for patient education, anatomic understanding, preoperative planning, and intraoperative evaluation. World Neurosurg. 2017;107:1049.e1-1049.e7.

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    Bill JS, Reuther JF. Rapid prototyping in planning reconstructive surgery of the head and neck. Review and evaluation of indications in clinical use. Mund Kiefer Gesichtschir. 2004;8(3):135-153.

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    Poukens J, Haex J, Riediger D. The use of rapid prototyping in the preoperative planning of distraction osteogenesis of the cranio-maxillofacial skeleton. Comput Aided Surg. 2003;8(3):146-154.

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    Mavili ME, Canter HI, Saglam-Aydinatay B, Kamaci S, Kocadereli I. Use of three-dimensional medical modeling methods for precise planning of orthognathic surgery. J Craniofac Surg. 2007;18(4):740-747.

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    Metzger MC, Hohlweg-Majert B, Schwarz U, Teschner M, Hammer B, Schmelzeisen R. Manufacturing splints for orthognathic surgery using a three-dimensional printer. Oral Surg Oral Med Oral Pathol Oral Radiol Endod. 2008;105(2):e1-e7.

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    Robiony M, Salvo I, Costa F, Zerman N, Bandera C, Filippi S, Felice M, Politi M. Accuracy of virtual reality and stereolithographic models in maxillo-facial surgical planning. J Craniofac Surg. 2008;19(2):482-489.

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    Ibrahim D, Broilo TL, Heitz C, de Oliveira MG, de Oliveira HW, Nobre SM, Dos Santos Filho JH, Silva DN. Dimensional error of selective laser sintering, three-dimensional printing and PolyJet models in the reproduction of mandibular anatomy. J Craniomaxillofac Surg. 2009;37(3):167-173.

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    Edwards SP. Computer-assisted craniomaxillofacial surgery. Oral Maxillofac Surg Clin North Am. 2010;22(1):117-134.

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    Olszewski R, Tranduy K, Reychler H. Innovative procedure for computer-assisted genioplasty: three-dimensional cephalometry, rapid-prototyping model and surgical splint. Int J Oral Maxillofac Surg. 2010;39(7):721-724.

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    Freitas EP, Rahal SC, Teixeira CR, Silva JV, Noritomi PY, Villela CH, Yamashita S. Rapid prototyping and inclined plane technique in the treatment of maxillofacial malformations in a fox. Can Vet J. 2010;51(3):267-270.

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    Kim BC, Lee CE, Park W, Kim MK, Zhengguo P, Yu HS, Yi CK, Lee SH. Clinical experiences of digital model surgery and the rapid-prototyped wafer for maxillary orthognathic surgery. Oral Surg Oral Med Oral Pathol Oral Radiol Endod. 2011;111(3):278-285.

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    Bai S, Bo B, Bi Y, Wang B, Zhao J, Liu Y, Feng Z, Shang H, Zhao Y. CAD/CAM surface templates as an alternative to the intermediate wafer in orthognathic surgery. Oral Surg Oral Med Oral Pathol Oral Radiol Endod. 2010;110(5):e1-e7.

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    Li B, Zhang L, Sun H, Yuan J, Shen SG, Wang X. A novel method of computer aided orthognathic surgery using individual CAD/CAM templates: a combination of osteotomy and repositioning guides. Br J Oral Maxillofac Surg. 2013;51(8):e239-e244.

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    Sun H, Li B, Zhao Z, Zhang L, Shen SG, Wang X. Error analysis of a CAD/CAM method for unidirectional mandibular distraction osteogenesis in the treatment of hemifacial microsomia. Br J Oral Maxillofac Surg. 2013;51(8):892-897.

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    Smith EJ, Anstey JA, Venne G, Ellis RE. Using additive manufacturing in accuracy evaluation of reconstructions from computed tomography. Proc Inst Mech Eng H. 2013;227(5):551-559.

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    Adolphs N, Liu W, Keeve E, Hoffmeister B. Craniomaxillofacial surgery planning based on 3D models derived from cone-beam CT data. Comput Aided Surg. 2013;18(5–6):101-108.

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    Al-Ahmad HT, M Saleh MW, Hussein AM. Evaluation of an innovative computer-assisted sagittal split ramus osteotomy to reduce neurosensory alterations following orthognathic surgery: a pilot study. Int J Med Robot. 2013;9(2):134-141.

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    Salvato G, Chiavenna C, Meazzini MC. Guide surgery osteotomy system (GSOS) a new device for treatment in orthognathic surgery. J Craniomaxillofac Surg. 2014;42(3):234-238.

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    Abdel-Moniem Barakat A, Abou-ElFetouh A, Hakam MM, El-Hawary H, Abdel-Ghany KM. Clinical and radiographic evaluation of a computer-generated guiding device in bilateral sagittal split osteotomies. J Craniomaxillofac Surg. 2014;42(5):e195-e203.

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    Sun Y, Luebbers HT, Agbaje JO, Schepers S, Vrielinck L, Lambrichts I, Politis C. Accuracy of upper jaw positioning with intermediate splint fabrication after virtual planning in bimaxillary orthognathic surgery. J Craniofac Surg. 2013;24(6):1871-1876.

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    Cousley RR, Turner MJ. Digital model planning and computerized fabrication of orthognathic surgery wafers. J Orthod. 2014;41(1):38-45.

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    Adolphs N, Liu W, Keeve E, Hoffmeister B. RapidSplint: virtual splint generation for orthognathic surgery - results of a pilot series. Comput Aided Surg. 2014;19(1–3):20-28.

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    Zhu M, Chai G, Li Q. Application of three-dimensional printing technique in correction of mandibular prognathism. Zhongguo Xiu Fu Chong Jian Wai Ke Za Zhi. 2014;28(3):296-299.

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    Shqaidef A, Ayoub AF, Khambay BS. How accurate are rapid prototyped (RP) final orthognathic surgical wafers? A pilot study. Br J Oral Maxillofac Surg. 2014;52(7):609-614.

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    Kang SH, Kim MK, Kim BC, Lee SH. Orthognathic Y-splint: a CAD/CAM-engineered maxillary repositioning wafer assembly. Br J Oral Maxillofac Surg. 2014;52(7):667-669.

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    Ye N, Long H, Zhu S, Yang Y, Lai W, Hu J. The accuracy of computer image-guided template for mandibular angle Ostectomy. Aesthet Plast Surg. 2015;39(1):117-123.

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    Li Y, Jiang Y, Zhang N, Xu R, Hu J, Zhu S. Clinical feasibility and efficacy of using virtual surgical planning in bimaxillary orthognathic surgery without intermediate splint. J Craniofac Surg. 2015;26(2):501-505.

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    Cassetta M, Pandolfi S, Giansanti M. Minimally invasive corticotomy in orthodontics: a new technique using a CAD/CAM surgical template. Int J Oral Maxillofac Surg. 2015;44(7):830-833.

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    Lee UL, Kwon JS, Choi YJ. Keyhole system: a computer-assisted designed and computer-assisted manufactured Maxillomandibular complex Repositioner in orthognathic surgery. J Oral Maxillofac Surg. 2015;73(10):2024-2029.

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    Choi JW, Kim N. Clinical application of three-dimensional printing technology in craniofacial plastic surgery. Arch Plast Surg. 2015;42(3):267-277.

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    Fang C, Fang Z, Fan Y, Li J, Xiang F, Tao H. Application of 3D visualization, 3D printing and 3D laparoscopy in the diagnosis and surgical treatment of hepatic tumors. Nan Fang Yi Ke Da Xue Xue Bao. 2015;35(5):639-645.

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    Mendez BM, Chiodo MV, Patel PA. Customized in-Office' three-dimensional printing for virtual surgical planning in craniofacial surgery. J Craniofac Surg. 2015;26(5):1584-1586.

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    He W, Tian K, Xie X, Wang X, Li Y, Wang X, Li Z. Individualized surgical templates and titanium microplates for Le fort I osteotomy by computer-aided design and computer-aided manufacturing. J Craniofac Surg. 2015;26(6):1877-1881.

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    Lee JW, Lim SH, Kim MK, Kang SH. Precision of a CAD/CAM-engineered surgical template based on a facebow for orthognathic surgery: an experiment with a rapid prototyping maxillary model. Oral Surg Oral Med Oral Pathol Oral Radiol. 2015;120(6):684-692.

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    Suomalainen A, Stoor P, Mesimäki K, Kontio RK. Rapid prototyping modelling in oral and maxillofacial surgery: a two year retrospective study. J Clin Exp Dent. 2015;7(5):e605-e612.

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    Pfaff MJ, Steinbacher DM. Plastic surgery applications using three-dimensional planning and computer-assisted design and manufacturing. Plast Reconstr Surg. 2016;137(3):603e-616e.

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    Resnick CM, Inverso G, Wrzosek M, Padwa BL, Kaban LB, Peacock ZS. Is there a difference in cost between standard and virtual surgical planning for orthognathic surgery? J Oral Maxillofac Surg. 2016;74(9):1827-1833.

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    Li B, Wei HP, Jiang TF, Shen SY, Shen GF, Wang XD. Clinical application and accuracy of the genioplasty surgical templates system for osseous genioplasty. Zhonghua Kou Qiang Yi Xue Za Zhi. 2016;51(11):646-650.

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    Shaheen E, Sun Y, Jacobs R, Politis C. Three-dimensional printed final occlusal splint for orthognathic surgery: design and validation. Int J Oral Maxillofac Surg. 2017;46(1):67-71.

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    Chen X, Li X, Xu L, Sun Y, Politis C, Egger J. Development of a computer-aided design software for dental splint in orthognathic surgery. Sci Rep. 2016;6:38867.

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    Legocki AT, Duffy-Peter A, Scott AR. Benefits and limitations of entry-level 3-dimensional printing of maxillofacial skeletal models. JAMA Otolaryngol Head Neck Surg. 2017;143(4):389-394.

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    Stokbro K, Aagaard E, Torkov P, Bell RB, Thygesen T. Surgical accuracy of three-dimensional virtual planning: a pilot study of bimaxillary orthognathic procedures including maxillary segmentation. Int J Oral Maxillofac Surg. 2016;45(1):8-18.

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    Li B, Shen S, Jiang W, Li J, Jiang T, Xia JJ, Shen SG, Wang X. A new approach of splint-less orthognathic surgery using a personalized orthognathic surgical guide system: a preliminary study. Int J Oral Maxillofac Surg. 2017;46(10):1298-1305.

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    Xiao Y, Sun X, Wang L, Zhang Y, Chen K, Wu G. The application of 3D printing Technology for Simultaneous Orthognathic Surgery and Mandibular Contour Osteoplasty in the treatment of craniofacial deformities. Aesthet Plast Surg. 2017;41(6):1413-1424.

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    Egger J, Wallner J, Gall M, Chen X, Schwenzer-Zimmerer K, Reinbacher K, Schmalstieg D. Computer-aided position planning of miniplates to treat facial bone defects. PLoS One. 2017;12(8):e0182839.

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    Lim SH, Kim MK, Kang SH. Genioplasty using a simple CAD/CAM (computer-aided design and computer-aided manufacturing) surgical guide. Maxillofac Plast Reconstr Surg. 2015;37(1):44.

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    Hou JS, Chen M, Pan CB, Tao Q, Wang JG, Wang C, Zhang B, Huang HZ. Immediate reconstruction of bilateral mandible defects: management based on computer-aided design/computer-aided manufacturing rapid prototyping technology in combination with vascularized fibular osteomyocutaneous flap. J Oral Maxillofac Surg. 2011;69(6):1792-1797.

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    Lethaus B, Poort L, Böckmann R, Smeets R, Tolba R, Kessler P. Additive manufacturing for microvascular reconstruction of the mandible in 20 patients. J Craniomaxillofac Surg. 2012;40(1):43-46.

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    Rohner D, Guijarro-Martínez R, Bucher P, Hammer B. Importance of patient-specific intraoperative guides in complex maxillofacial reconstruction. J Craniomaxillofac Surg. 2013;41(5):382-390.

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    Man QW, Jia J, Liu K, Chen G, Liu B. Secondary reconstruction for mandibular osteoradionecrosis defect with fibula osteomyocutaneous flap flowthrough from radial forearm flap using stereolithographic 3-dimensional printing modeling technology. J Craniofac Surg. 2015;26(2):e190-e193.

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    Inzana JA, Trombetta RP, Schwarz EM, Kates SL, Awad HA. 3D printed bioceramics for dual antibiotic delivery to treat implant-associated bone infection. Eur Cell Mater. 2015;30:232-247.

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    Wu W, Ye C, Zheng Q, Wu G, Cheng Z. A therapeutic delivery system for chronic osteomyelitis via a multi-drug implant based on three-dimensional printing technology. J Biomater Appl. 2016;31(2):250-260.

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    Mercuri LG, Wolford LM, Sanders B, White RD, Hurder A, Henderson W. Custom CAD/CAM total temporomandibular joint reconstruction system: preliminary multicenter report. J Oral Maxillofac Surg. 1995;53(2):106-115.

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    Undt G, Wild K, Reuther G, Ewers R. MRI-based stereolithographic models of the temporomandibular joint: technical innovation. J Craniomaxillofac Surg. 2000;28(5):258-263.

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    Mercuri LG, Wolford LM, Sanders B, White RD, Giobbie-Hurder A. Long-term follow-up of the CAD/CAM patient fitted total temporomandibular joint reconstruction system. J Oral Maxillofac Surg. 2002;60(12):1440-1448.

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    Xia JJ, Gateno J, Teichgraeber JF. Three-dimensional computer-aided surgical simulation for maxillofacial surgery. Atlas Oral Maxillofac Surg Clin North Am. 2005;13(1):25-39.

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    Keith DA. Custom-made total temporomandibular joint prostheses. Atlas Oral Maxillofac Surg Clin North Am. 2005;13(1):83-89.

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    van der Wal KG. Dissertations 25 years after the date 7. Temporomandibular joint ankylosis. Ned Tijdschr Tandheelkd. 2005;112(10):380-384.

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    Christensen RW, Walker CR, Dollar JV. New hope for Treacher-Collins syndrome: a surgical case report. Surg Technol Int. 2005;14:319-327.

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    Worrall SF, Christensen RW. Alloplastic reconstruction of the temporomandibular joint in treatment of craniofacial developmental or congenital anomalies: a surgical case report. Surg Technol Int. 2006;15:291-301.

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    Mercuri LG, Edibam NR, Giobbie-Hurder A. Fourteen-year follow-up of a patient-fitted total temporomandibular joint reconstruction system. J Oral Maxillofac Surg. 2007;65(6):1140-1148.

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    Pearce CS, Cooper C, Speculand B. One stage management of ankylosis of the temporomandibular joint with a custom-made total joint replacement system. Br J Oral Maxillofac Surg. 2009;47(7):530-534.

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    Chaware SM, Bagaria V, Kuthe A. Application of the rapid prototyping technique to design a customized temporomandibular joint used to treat temporomandibular ankylosis. Indian J Plast Surg. 2009;42(1):85-93.

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    Bell RB. Computer planning and intraoperative navigation in cranio-maxillofacial surgery. Oral Maxillofac Surg Clin North Am. 2010;22(1):135-156.

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    Zizelmann C, Bucher P, Rohner D, Gellrich NC, Kokemueller H, Hammer B. Virtual restoration of anatomic jaw relationship to obtain a precise 3D model for total joint prosthesis construction for treatment of TMJ ankylosis with open bite. Int J Oral Maxillofac Surg. 2010;39(10):1012-1015.

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    Chandran R, Keeler GD, Christensen AM, Weimer KA, Caloss R. Application of virtual surgical planning for total joint reconstruction with a stock alloplast system. J Oral Maxillofac Surg. 2011;69(1):285-294.

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    Zhang S, Liu X, Xu Y, Yang C, Undt G, Chen M, Haddad MS, Yun B. Application of rapid prototyping for temporomandibular joint reconstruction. J Oral Maxillofac Surg. 2011;69(2):432-438.

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    Keller EE, Baltali E, Liang X, Zhao K, Huebner M, An KN. Temporomandibular custom hemijoint replacement prosthesis: prospective clinical and kinematic study. J Oral Maxillofac Surg. 2012;70(2):276-288.

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    Patel A, Otterburn D, Saadeh P, Levine J, Hirsch DL. 3D volume assessment techniques and computer-aided design and manufacturing for preoperative fabrication of implants in head and neck reconstruction. Facial Plast Surg Clin North Am. 2011;19(4):683-709.

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    Gelesko S, Markiewicz MR, Weimer K, Bell RB. Computer-aided orthognathic surgery. Atlas Oral Maxillofac Surg Clin North Am. 2012;20(1):107-118.

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    Deshmukh TR, Kuthe AM, Chaware SM, Bagaria V, Ingole DS. A novel rapid prototyping and finite element method-based development of the patient-specific temporomandibular joint implant. Comput Methods Biomech Biomed Engin. 2012;15(4):363-370.

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    Marinescu C. CAD/CAM restorative principles. Dent Today. 2012;31(4):130.

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    Gonçalves JR, Gomes LC, Vianna AP, Rodrigues DB, Gonçalves DA, Wolford LM. Airway space changes after maxillomandibular counterclockwise rotation and mandibular advancement with TMJ concepts total joint prostheses: three-dimensional assessment. Int J Oral Maxillofac Surg. 2013;42(8):1014-1022.

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    Villegas C, Janakiraman N, Nanda R, Uribe F. Management of unilateral condylar hyperplasia with a high condylectomy, skeletal anchorage, and a CAD/CAM alloplast. J Clin Orthod. 2013;47(6):365-374.

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    Schneider R, Burton R. Coordinated reconstruction with bilateral condylar replacement and dental implant rehabilitation: a clinical report. J Prosthet Dent. 2014;111(2):101-106.

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    Haq J, Patel N, Weimer K, Matthews NS. Single stage treatment of ankylosis of the temporomandibular joint using patient-specific total joint replacement and virtual surgical planning. Br J Oral Maxillofac Surg. 2014;52(4):350-355.

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    Rodrigues DB, Wolford LM, Malaquias P, Campos PS. Concomitant treatment of mandibular ameloblastoma and bilateral temporomandibular joint osteoarthritis with bone graft and total joint prostheses. J Oral Maxillofac Surg. 2015;73(1):63-74.

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    Green JM, Lawson ST, Liacouras PC, Wise EM, Gentile MA, Grant GT. Custom anatomical 3D spacer for temporomandibular joint resection and reconstruction. Craniomaxillofac Trauma Reconstr. 2016;9(1):82-87.

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    Ryu J, Cho J, Kim HM. Bilateral temporomandibular joint replacement using computer-assisted surgical simulation and three-dimensional printing. J Craniofac Surg. 2016;27(5):e450-e452.

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    Pho Duc JM, Hüning SV, Grossi ML. Parallel randomized controlled clinical trial in patients with temporomandibular disorders treated with a CAD/CAM versus a conventional stabilization splint. Int J Prosthodont. 2016;29(4):340-350.

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    Sawh-Martinez R, Parsaei Y, Wu R, Lin A, Metzler P, DeSesa C, Steinbacher DM. Improved temporomandibular joint position after 3-dimensional planned mandibular reconstruction. J Oral Maxillofac Surg. 2017;75(1):197-206.

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    Tarsitano A, Battaglia S, Ramieri V, Cascone P, Ciocca L, Scotti R, Marchetti C. Short-term outcomes of mandibular reconstruction in oncological patients using a CAD/CAM prosthesis including a condyle supporting a fibular free flap. J Craniomaxillofac Surg. 2017;45(2):330-337.

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    Ritschl LM, Mücke T, Fichter A, Güll FD, Schmid C, Duc JMP, Kesting MR, Wolff KD, Loeffelbein DJ. Functional outcome of CAD/CAM-assisted versus conventional microvascular, fibular free flap reconstruction of the mandible: a retrospective study of 30 cases. J Reconstr Microsurg. 2017;33(4):281-291.

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    Ackland DC, Robinson D, Redhead M, Lee PV, Moskaljuk A, Dimitroulis G. A personalized 3D-printed prosthetic joint replacement for the human temporomandibular joint: from implant design to implantation. J Mech Behav Biomed Mater. 2017;69:404-411.

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    Farzad P. Reconstruction of nongrowing hemifacial microsomia patient with custom-made unilateral temporomandibular joint total joint prosthesis and orthognathic surgery. J Oral Biol Craniofac Res. 2017;7(1):62-66.

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    Hu Y, Zhang L, He D, Yang C, Chen M, Zhang S, Li H, Ellis Iii E. Simultaneous treatment of temporomandibular joint ankylosis with severe mandibular deficiency by standard TMJ prosthesis. Sci Rep. 2017;7:45271.

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    Kozakiewicz M, Wach T, Szymor P, Zieliński R. Two different techniques of manufacturing TMJ replacements - a technical report. J Craniomaxillofac Surg. 2017;5(9):1432-1437.

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    Ciocca L, Marchetti C, Mazzoni S, Baldissara P, Gatto MR, Cipriani R, Scotti R, Tarsitano A. Accuracy of fibular sectioning and insertion into a rapid-prototyped bone plate, for mandibular reconstruction using CAD-CAM technology. J Craniomaxillofac Surg. 2015;43(1):28-33.

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    Chen MJ, Yang C, Huang D, He DM, Wang YW, Zhang WH. Modified technique for preservation of inferior alveolar nerve during mandibulectomy. Head Neck. 2017;39(12):2562-2566.

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    Eckardt A, Swennen GR. Virtual planning of composite mandibular reconstruction with free fibula bone graft. J Craniofac Surg. 2005;16(6):1137-1140.

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    Westendorff C, Kaminsky J, Ernemann U, Reinert S, Hoffmann J. Image-guided sphenoid wing meningioma resection and simultaneous computer-assisted cranio-orbital reconstruction: technical case report. Neurosurgery. 2007;60(2 Suppl 1):ONSE173-ONSE174.

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    Hu YJ, Hardianto A, Li SY, Zhang ZY, Zhang CP. Reconstruction of a palatomaxillary defect with vascularized iliac bone combined with a superficial inferior epigastric artery flap and zygomatic implants as anchorage. Int J Oral Maxillofac Surg. 2007;36(9):854-857.

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    Xu X, Ping FY, Chen J, Yan FG, Mao HQ, Shi YH, Zhao ZY. Application of CAD/CAM techniques in mandible large-scale defect and reconstruction with vascularized fibular bone graft. Zhejiang Da Xue Xue Bao Yi Xue Ban. 2007;36(5):498-502.

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    Singare S, Liu Y, Li D, Lu B, Wang J, He S. Individually prefabricated prosthesis for maxilla Reconstuction. J Prosthodont. 2008;17(2):135-140.

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    Xu X, Ping FY, Chen J, Yan JL, Yan FG. Application of computer aided design/computer aided manufactured techniques in mandible defect reconstruction. Zhonghua Kou Qiang Yi Xue Za Zhi. 2007;42(8):492-495.

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    Wu CT, Lee ST, Chen JF, Lin KL, Yen SH. Computer-aided design for three-dimensional titanium mesh used for repairing skull base bone defect in pediatric neurofibromatosis type 1. A novel approach combining biomodeling and neuronavigation. Pediatr Neurosurg. 2008;44(2):133-139.

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    Cohen A, Laviv A, Berman P, Nashef R, Abu-Tair J. Mandibular reconstruction using stereolithographic 3-dimensional printing modeling technology. Oral Surg Oral Med Oral Pathol Oral Radiol Endod. 2009;108(5):661-666.

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    Juergens P, Krol Z, Zeilhofer HF, Beinemann J, Schicho K, Ewers R, Klug C. Computer simulation and rapid prototyping for the reconstruction of the mandible. J Oral Maxillofac Surg. 2009;67(10):2167-2170.

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    Tong D, Huang MW, Zhang JG, Feng HL, Li YS. Clinical application of computer-aided design and rapid prototyping technique for radioactive seeds contained maxillary device. Beijing Da Xue Xue Bao. 2010;42(1):63-66.

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    Matsuo A, Chiba H, Takahashi H, Toyoda J, Abukawa H. Clinical application of a custom-made bioresorbable raw particulate hydroxyapatite/poly-L-lactide mesh tray for mandibular reconstruction. Odontology. 2010;98(1):85-88.

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    Cheng HT, Wu CI, Tseng CS, Chen HC, Lee WS, Chen PK, Chang SC. The occlusion-adjusted prefabricated 3D mirror image templates by computer simulation: the image-guided navigation system application in difficult cases of head and neck reconstruction. Ann Plast Surg. 2009;63(5):517-521.

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    Zhou LB, Shang HT, He LS, Bo B, Liu GC, Liu YP, Zhao JL. Accurate reconstruction of discontinuous mandible using a reverse engineering/computer-aided design/rapid prototyping technique: a preliminary clinical study. J Oral Maxillofac Surg. 2010;68(9):2115-2121.

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    Roser SM, Ramachandra S, Blair H, Grist W, Carlson GW, Christensen AM, Weimer KA, Steed MB. The accuracy of virtual surgical planning in free fibula mandibular reconstruction: comparison of planned and final results. J Oral Maxillofac Surg. 2010;68(11):2824-2832.

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    Hou JS, Chen M, Pan CB, Wang M, Wang JG, Zhang B, Tao Q, Wang C, Huang HZ. Application of CAD/CAM-assisted technique with surgical treatment in reconstruction of the mandible. J Craniomaxillofac Surg. 2012;40(8):e432-e437.

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    Ciocca L, Mazzoni S, Fantini M, Marchetti C, Scotti R. The design and rapid prototyping of surgical guides and bone plates to support iliac free flaps for mandible reconstruction. Plast Reconstr Surg. 2012;129(5):859e-861e.

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    Ciocca L, Mazzoni S, Fantini M, Persiani F, Marchetti C, Scotti R. CAD/CAM guided secondary mandibular reconstruction of a discontinuity defect after ablative cancer surgery. J Craniomaxillofac Surg. 2012;40(8):e511-e515.

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    Zheng GS, Su YX, Liao GQ, Chen ZF, Wang L, Jiao PF, Liu HC, Zhong YQ, Zhang TH, Liang YJ. Mandible reconstruction assisted by preoperative virtual surgical simulation. Oral Surg Oral Med Oral Pathol Oral Radiol. 2012;113(5):604-611.

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    Yu HB, Zhang SL, Wang XD, Lin YP, Wang CT, Shen GF. Application of computer-assisted navigation in oral and maxillofacial surgery: retrospective analysis of 104 consecutive cases. Shanghai Kou Qiang Yi Xue. 2012;21(4):416-421.

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    Wang WH, Zhu J, Deng JY, Xia B, Xu B. Three-dimensional virtual technology in reconstruction of mandibular defect including condyle using double-barrel vascularized fibula flap. J Craniomaxillofac Surg. 2013;41(5):417-422.

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    Yu H, Shen SG, Wang X, Zhang L, Zhang S. The indication and application of computer-assisted navigation in oral and maxillofacial surgery-Shanghai's experience based on 104 cases. J Craniomaxillofac Surg. 2013;41(8):770-774.

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    Thomas CV, McMillan KG, Jeynes P, Martin T, Parmar S. Use of a titanium cutting guide to assist with raising and inset of a DCIA free flap. Br J Oral Maxillofac Surg. 2013;51(8):958-961.

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    Bullock P, Dunaway D, McGurk L, Richards R. Integration of image guidance and rapid prototyping technology in craniofacial surgery. Int J Oral Maxillofac Surg. 2013;42(8):970-973.

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    Coppen C, Weijs W, Bergé SJ, Maal TJ. Oromandibular reconstruction using 3D planned triple template method. J Oral Maxillofac Surg. 2013;71(8):e243-e247.

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    Yan G, Wang X, Tan X, Wang X, Yang M, Lu L. Study on accuracy of virtual surgical planning in free fibula mandibular reconstruction by using SurgiCase software. Zhongguo Xiu Fu Chong Jian Wai Ke Za Zhi. 2013;27(8):1006-1009.

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    Matros E, Albornoz CR, Rensberger M, Weimer K, Garfein ES. Computer-assisted design and computer-assisted modeling technique optimization and advantages over traditional methods of osseous flap reconstruction. J Reconstr Microsurg. 2014;30(5):289-296.

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    Ciocca L, Scotti R. Oculo-facial rehabilitation after facial cancer removal: updated CAD/CAM procedures: a pilot study. Prosthetics Orthot Int. 2014;38(6):505-509.

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    Bai G, He D, Yang C, Lu C, Huang D, Chen M, Yuan J. Effect of digital template in the assistant of a giant condylar osteochondroma resection. J Craniofac Surg. 2014;25(3):e301-e304.

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    Succo G, Berrone M, Battiston B, Tos P, Goia F, Appendino P, Crosetti E. Step-by-step surgical technique for mandibular reconstruction with fibular free flap: application of digital technology in virtual surgical planning. Eur Arch Otorhinolaryngol. 2015;272(6):1491-1501.

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    Yu D, Liu J, Zhu H, Li Z, Huang X, Wei D, Lin Y, He J, Zhao W. Application of three-dimensional printing technique in repair and reconstruction of maxillofacial bone defect. Zhongguo Xiu Fu Chong Jian Wai Ke Za Zhi. 2014;28(3):292-295.

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    Shu DL, Liu XZ, Guo B, Ran W, Liao X, Zhang YY. Accuracy of using computer-aided rapid prototyping templates for mandible reconstruction with an iliac crest graft. World J Surg Oncol. 2014;12:190.

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    Shengwei H, Zhiyong W, Qingang H, Wei H. Combined use of an anterolateral thigh flap and rapid prototype modeling to reconstruct maxillary oncologic resections and midface defects. J Craniofac Surg. 2014;25(4):1147-1149.

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    Kim MS, Lee JY, Shin SW. Fabricating an obturator using rapid prototyping to design the framework: a case report. Int J Prosthodont. 2014;27(5):439-441.

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    Jiao T, Zhu C, Dong X, Gu X. Rehabilitation of maxillectomy defects with obturator prostheses fabricated using computer-aided design and rapid prototyping: a pilot study. Int J Prosthodont. 2014;27(5):480-486.

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    Berrone M, Crosetti E, Succo G. Repositioning template for mandibular reconstruction with fibular free flaps: an alternative technique to pre-plating and virtual surgical planning. Acta Otorhinolaryngol Ital. 2014;34(4):278-282.

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    Azuma M, Yanagawa T, Ishibashi-Kanno N, Uchida F, Ito T, Yamagata K, Hasegawa S, Sasaki K, Adachi K, Tabuchi K, Sekido M, Bukawa H. Mandibular reconstruction using plates prebent to fit rapid prototyping 3-dimensional printing models ameliorates contour deformity. Head Face Med. 2014;10:45.

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    Cornelius CP, Smolka W, Giessler GA, Wilde F, Probst FA. Patient-specific reconstruction plates are the missing link in computer-assisted mandibular reconstruction: a showcase for technical description. J Craniomaxillofac Surg. 2015;43(5):624-629.

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    Reiser V, Alterman M, Shuster A, Kleinman S, Shlomi B, Yanko-Arzi R, Zaretski A, Amir A, Fliss DM. V-stand--a versatile surgical platform for oromandibular reconstruction using a 3-dimensional virtual modeling system. J Oral Maxillofac Surg. 2015;73(6):1211-1226.

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    Kääriäinen M, Kuuskeri M, Gremoutis G, Kuokkanen H, Miettinen A, Laranne J. Utilization of three-dimensional computer-aided preoperative virtual planning and manufacturing in maxillary and mandibular reconstruction with a microvascular fibula flap. J Reconstr Microsurg. 2016;32(2):137-141.

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    Chen XB, Liu ZG, Yuan JB, Tian HW. Application of three-dimensional virtual technology in mandibular defects reconstruction with free fibular flap. Shanghai Kou Qiang Yi Xue. 2015;24(4):460-464.

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    Liu J, Zhang B, Yan D, Yu X, Lin M, Li Z, Yin Y, Xu Z. Digital and three-demention print technique in reconstruction for complex defect after resection of jaw neoplasms. Zhonghua Er Bi Yan Hou Tou Jing Wai Ke Za Zhi. 2015;50(6):473-476.

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    Nkenke E, Agaimy A, Vairaktaris E, Lell M, von Wilmowsky C, Eitner S. Case history report: immediate rehabilitation with a prefabricated fibula flap following removal of a locally aggressive maxillary tumor. Int J Prosthodont. 2016;29(1):53-58.

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    Yu Y, Zhang WB, Wang Y, Liu XJ, Guo CB, Peng X. A revised approach for mandibular reconstruction with the vascularized iliac crest flap using virtual surgical planning and surgical navigation. J Oral Maxillofac Surg. 2016;74(6):1285.e1-1285.e11.

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    Anchieta MV, Salles FA, Cassaro BD, Quaresma MM, Santos BF. Skull reconstruction after resection of bone tumors in a single surgical time by the association of the techniques of rapid prototyping and surgical navigation. Int J Comput Assist Radiol Surg. 2016;11(10):1919-1925.

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    Chang EI, Hanasono MM. State-of-the-art reconstruction of midface and facial deformities. J Surg Oncol. 2016;113(8):962-970.

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    Shui W, Zhou M, Chen S, Pan Z, Deng Q, Yao Y, Pan H, He T, Wang X. The production of digital and printed resources from multiple modalities using visualization and three-dimensional printing techniques. Int J Comput Assist Radiol Surg. 2017;12(1):13-23.

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    Brandmeir NJ, McInerney J, Zacharia BE. The use of custom 3D printed stereotactic frames for laser interstitial thermal ablation: technical note. Neurosurg Focus. 2016;41(4):E3.

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    Wiedermann JP, Joshi AS, Jamshidi A, Conchenour C, Preciado D. Utilization of a submental island flap and 3D printed model for skull base reconstruction: infantile giant cranio-cervicofacial teratoma. Int J Pediatr Otorhinolaryngol. 2017;92:143-145.

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    Leiggener C, Messo E, Thor A, Zeilhofer HF, Hirsch JM. A selective laser sintering guide for transferring a virtual plan to real time surgery in composite mandibular reconstruction with free fibula osseous flaps. Int J Oral Maxillofac Surg. 2009;38(2):187-192.

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    Liu XJ, Gui L, Mao C, Peng X, Yu GY. Applying computer techniques in maxillofacial reconstruction using a fibula flap: a messenger and an evaluation method. J Craniofac Surg. 2009;20(2):372-377.

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    Modabber A, Gerressen M, Stiller MB, Noroozi N, Füglein A, Hölzle F, Riediger D, Ghassemi A. Computer-assisted mandibular reconstruction with vascularized iliac crest bone graft. Aesthet Plast Surg. 2012;36(3):653-659.

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    Ayoub N, Ghassemi A, Rana M, Gerressen M, Riediger D, Hölzle F, Modabber A. Evaluation of computer-assisted mandibular reconstruction with vascularized iliac crest bone graft compared to conventional surgery: a randomized prospective clinical trial. Trials. 2014;15:114.

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    Rude K., Thygesen T. H., Sorensen J. A. Reconstruction of the maxilla using a fibula graft and virtual planning techniques. Case Reports. 2014;2014(may14 1):bcr2014203601-bcr2014203601.

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    Sieira Gil R, Roig AM, Obispo CA, Morla A, Pagès CM, Perez JL. Surgical planning and microvascular reconstruction of the mandible with a fibular flap using computer-aided design, rapid prototype modelling, and precontoured titanium reconstruction plates: a prospective study. Br J Oral Maxillofac Surg. 2015;53(1):49-53.

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    Suchyta M, Mardini S. Innovations and future directions in head and neck microsurgical reconstruction. Clin Plast Surg. 2017;44(2):325-344.

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    Stoetzer M, Rana M, von See C, Eckardt AM, Gellrich NC. Reconstruction of defects of maxillary sinus wall after removal of a huge odontogenic lesion using prebended 3D titanium-mesh and CAD/CAM technique. Head Face Med. 2011;7:21.

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    Tasopoulos T, Kouveliotis G, Polyzois G, Karathanasi V. Fabrication of a 3D printing definitive obturator prosthesis: a clinical report. Acta Stomatol Croat. 2017;51(1):53-58.

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    Antonelli JA. Innovations in surgical stone disease. Curr Opin Urol. 2016;26(3):240-247.

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    Atalay HA, Canat HL, Ülker V, Alkan İ, Özkuvanci Ü, Altunrende F. Impact of personalized three-dimensional -3D- printed pelvicalyceal system models on patient information in percutaneous nephrolithotripsy surgery: a pilot study. Int Braz J Urol. 2017;43:470-475.

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    Atalay HA, Ülker V, Alkan İ, Canat HL, Özkuvancı Ü, Altunrende F. Impact of three-dimensional printed Pelvicaliceal system models on residents’ understanding of Pelvicaliceal system anatomy before percutaneous Nephrolithotripsy surgery: a pilot study. J Endourol. 2016;30:1132-1137.

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    Bruyère F, Leroux C, Brunereau L, Lermusiaux P. Rapid prototyping model for percutaneous nephrolithotomy training. J Endourol. 2008;22:91-96.

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    Mishra S, Jagtap J, Sabnis RB, Desai MR. Training in percutaneous nephrolithotomy. Curr Opin Urol. 2013;23:147-151.

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    Powers MK, Lee BR, Silberstein J. Three-dimensional printing of surgical anatomy. Curr Opin Urol. 2016;26:283-288.

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    Sweet RM. The CREST simulation development process: training the next generation. J Endourol. 2017;31:S69-S75.

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    Westerman ME, Matsumoto JM, Morris JM, Leibovich BC. Three-dimensional printing for renal Cancer and surgical planning. Eur Urol Focus. 2016;2:574-576.

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    Wake N, Rude T, Kang SK, Stifelman MD, Borin JF, Sodickson DK, Huang WC, Chandarana H. 3D printed renal cancer models derived from MRI data: application in pre-surgical planning. Abdom Radiol (NY). 2017;42:1501-1509.

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    Golab A, Smektala T, Kaczmarek K, Stamirowski R, Hrab M, Slojewski M. Laparoscopic partial nephrectomy supported by training involving personalized silicone replica poured in three-dimensional printed casting Mold. J Laparoendosc Adv Surg Tech A. 2017;27:420-422.

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    Von Rundstedt F-C, Scovell JM, Agrawal S, Zaneveld J, Link RE. Utility of patient-specific silicone renal models for planning and rehearsal of complex tumour resections prior to robot-assisted laparoscopic partial nephrectomy. BJU Int. 2017;119:598-604.

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    Smektala T, Goląb A, Królikowski M, Slojewski M. Low cost silicone renal replicas for surgical training - technical note. Arch Esp Urol. 2016;69:434-436.

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    Golab A, Slojewski M, Brykczynski M, Lukowiak M, Boehlke M, Matias D, Smektala T. Three-dimensional printing as an interdisciplinary communication tool: preparing for removal of a Giant renal tumor and atrium neoplastic mass. Heart Surg Forum. 2016;19:E185-E186.

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    Jung JP, Bhuiyan DB, Ogle BM. Solid organ fabrication: comparison of decellularization to 3D bioprinting. Biomater Res. 2016;20:27.

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    Komai Y, Sugimoto M, Gotohda N, Matsubara N, Kobayashi T, Sakai Y, Shiga Y, Saito N. Patient-specific 3-dimensional printed kidney designed for “4D” surgical navigation: a novel aid to facilitate minimally invasive off-clamp partial nephrectomy in complex tumor cases. Urology. 2016;91:226-233.

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    Bernhard J-C, Isotani S, Matsugasumi T, Duddalwar V, Hung AJ, Suer E, Baco E, Satkunasivam R, Djaladat H, Metcalfe C, Hu B, Wong K, Park D, Nguyen M, Hwang D, Bazargani ST, de Castro Abreu AL, Aron M, Ukimura O, Gill IS. Personalized 3D printed model of kidney and tumor anatomy: a useful tool for patient education. World J Urol. 2016;34:337-345.

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    Knoedler M, Feibus AH, Lange A, Maddox MM, Ledet E, Thomas R, Silberstein JL. Individualized physical 3-dimensional kidney tumor models constructed from 3-dimensional printers result in improved trainee anatomic understanding. Urology. 2015;85:1257-1261.

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    Zhang Y, Ge H, Li N, Yu C, Guo H, Jin S, Liu J, Na Y. Evaluation of three-dimensional printing for laparoscopic partial nephrectomy of renal tumors: a preliminary report. World J Urol. 2016;34:533-537.

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    Stone L. Kidney cancer: a model for the masses--3D printing of kidney tumours. Nat Rev Urol. 2014;11:428.

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    Silberstein JL, Maddox MM, Dorsey P, Feibus A, Thomas R, Lee BR. Physical models of renal malignancies using standard cross-sectional imaging and 3-dimensional printers: a pilot study. Urology. 2014;84:268-272.

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    Challoner A, Erolin C. Creating pathology models from MRI data: a comparison of virtual 3D modelling and rapid prototyping techniques. J Vis Commun Med. 2013;36:11-19.

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    Cernat E, Docquier P-L, Paul L, Banse X, Codorean I-B. Patient specific instruments for complex tumor resection-reconstruction surgery within the pelvis: a series of 4 cases. Chirurgia (Bucur). 2016;111:439-444.

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    Srougi V, Rocha BA, Tanno FY, Almeida MQ, Baroni RH, Mendonça BB, Srougi M, Fragoso MC, Chambô JL. The use of three-dimensional printers for partial adrenalectomy: estimating the resection limits. Urology. 2016;90:217-220.

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    Wendler JJ, Klink F, Seifert S, Fischbach F, Jandrig B, Porsch M, Pech M, Baumunk D, Ricke J, Schostak M, Liehr U-B. Irreversible electroporation of prostate Cancer: patient-specific pretreatment simulation by electric field measurement in a 3D bioprinted textured prostate Cancer model to achieve optimal electroporation parameters for image-guided focal ablation. Cardiovasc Intervent Radiol. 2016;39:1668-1671.

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    Shin T, Ukimura O, Gill IS. Three-dimensional printed model of prostate anatomy and targeted biopsy-proven index tumor to facilitate nerve-sparing prostatectomy. Eur Urol. 2016;69:377-379.

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    Kadimisetty K, Mosa IM, Malla S, Satterwhite-Warden JE, Kuhns TM, Faria RC, Lee NH, Rusling JF. 3D-printed supercapacitor-powered electrochemiluminescent protein immunoarray. Biosens Bioelectron. 2016;77:188-193.

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    Fitzgerald KA, Guo J, Tierney EG, Curtin CM, Malhotra M, Darcy R, O’Brien FJ, O’Driscoll CM. The use of collagen-based scaffolds to simulate prostate cancer bone metastases with potential for evaluating delivery of nanoparticulate gene therapeutics. Biomaterials. 2015;66:53-66.

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    Zou W, Fisher T, Zhang M, Kim L, Chen T, Narra V, Swann B, Singh R, Siderit R, Yin L, Teo B-KK, McKenna M, McDonough J, Ning YJ. Potential of 3D printing technologies for fabrication of electron bolus and proton compensators. J Appl Clin Med Phys. 2015;16:4959.

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    Li P, Jiang S, Yu Y, Yang J, Yang Z. Biomaterial characteristics and application of silicone rubber and PVA hydrogels mimicked in organ groups for prostate brachytherapy. J Mech Behav Biomed Mater. 2015;49:220-234.

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    Priester A, Natarajan S, Le JD, Garritano J, Radosavcev B, Grundfest W, Margolis DJ, Marks LS, Huang J. A system for evaluating magnetic resonance imaging of prostate cancer using patient-specific 3D printed molds. Am J Clin Exp Urol. 2014;2:127-135.

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    Harrison KM, Ebert MA, Kron T, Howlett SJ, Cornes D, Hamilton CS, Denham JW. Design, manufacture, and evaluation of an anthropomorphic pelvic phantom purpose-built for radiotherapy dosimetric intercomparison. Med Phys. 2011;38:5330-5337.

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    Henry OY, Fragoso A, Beni V, Laboria N, Sánchez JLA, Latta D, Von Germar F, Drese K, Katakis I, O’Sullivan CK. Design and testing of a packaged microfluidic cell for the multiplexed electrochemical detection of cancer markers. Electrophoresis. 2009;30:3398-3405.

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    Sayed Aluwee SAZB, Zhou X, Kato H, Makino H, Muramatsu C, Hara T, Matsuo M, Fujita H. Evaluation of pre-surgical models for uterine surgery by use of three-dimensional printing and mold casting. Radiol Phys Technol. 2017;10:279-285.

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    Ji Z, Jiang YL, Guo FX, Peng R, Sun HT, Fan JH, Wang JJ. Dosimetry verification of radioactive seed implantation with 3D printing template and CT guidance for paravertebral/retroperitoneal malignant tumor. Zhonghua Yi Xue Za Zhi. 2017;97:996-1000.

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    Kadoya N, Miyasaka Y, Nakajima Y, Kuroda Y, Ito K, Chiba M, Sato K, Dobashi S, Yamamoto T, Takahashi N, Kubozono M, Takeda K, Jingu K. Evaluation of deformable image registration between external beam radiotherapy and HDR brachytherapy for cervical cancer with a 3D-printed deformable pelvis phantom. Med Phys. 2017;44:1445-1455.

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    Baek M-H, Kim D-Y, Kim N, Rhim CC, Kim J-H, Nam J-H. Incorporating a 3-dimensional printer into the management of early-stage cervical cancer. J Surg Oncol. 2016;114:150-152.

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    Lindegaard JC, Madsen ML, Traberg A, Meisner B, Nielsen SK, Tanderup K, Spejlborg H, Fokdal LU, Nørrevang O. Individualised 3D printed vaginal template for MRI guided brachytherapy in locally advanced cervical cancer. Radiother Oncol. 2016;118:173-175.

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    Bartellas M, Ryan S, Doucet G, Murphy D, Turner J. Three-dimensional printing of a hemorrhagic cervical Cancer model for postgraduate gynecological training. Cureus. 2017;9:e950.

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    Zhao Y, Yao R, Ouyang L, Ding H, Zhang T, Zhang K, Cheng S, Sun W. Three-dimensional printing of Hela cells for cervical tumor model in vitro. Biofabrication. 2014;6:035001.

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    Ajao MO, Clark NV, Kelil T, Cohen SL, Einarsson JI. Case report: three-dimensional printed model for deep infiltrating endometriosis. J Minim Invasive Gynecol. 2017;24:1239-1242.

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    Sethi R, Cunha A, Mellis K, Siauw T, Diederich C, Pouliot J, Hsu I-C. Clinical applications of custom-made vaginal cylinders constructed using three-dimensional printing technology. J Contemp Brachytherapy. 2016;8:208-214.

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    Park C-J, Kim H-W, Jeong S, Seo S, Park Y, Moon HS, Lee J-H. Anti-reflux ureteral stent with polymeric flap valve using three-dimensional printing: an in vitro study. J Endourol. 2015;29:933-938.

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    Bagaria V, Deshpande S, Rasalkar DD, Kuthe A, Paunipagar BK. Use of rapid prototyping and three-dimensional reconstruction modeling in the management of complex fractures. Eur J Radiol. 2011;80:814-820.

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    Bizzotto N, Tami I, Tami A, Spiegel A, Romani D, Corain M, Adani R, Magnan B. 3D printed models of distal radius fractures. Injury. 2016;47:976-978.

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    Bizzotto N, Sandri A, Regis D, Romani D, Tami I, Magnan B. Three-dimensional printing of bone fractures: a new tangible realistic way for preoperative planning and education. Surg Innov. 2015;22:548-551.

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    Brown GA, Firoozbakhsh K, DeCoster TA, Reyna JR, Moneim M. Rapid prototyping: the future of trauma surgery? J Bone Joint Surg Am. 2003;85-A Suppl 4:49-55.

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    Chana-Rodríguez F, Mañanes RP, Rojo-Manaute J, Gil P, Martínez-Gómiz JM, Vaquero-Martín J. 3D surgical printing and pre contoured plates for acetabular fractures. Injury. 2016;47:2507-2511.

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    Chen C, Cai L, Zhang C, Wang J, Guo X, Zhou Y. Treatment of die-punch fractures with 3D printing technology. J Investig Surg. 2017;19:1-8.

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    Chen H, Wang G, Li R, Sun Y, Wang F, Zhao H, Zhang P, Zhang X. A novel navigation template for fixation of acetabular posterior column fractures with antegrade lag screws: design and application. Int Orthop. 2016;40:827-834.

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    Chen X, Chen X, Zhang G, Lin H, Yu Z, Wu C, Li X, Lin Y, Huang W. Accurate fixation of plates and screws for the treatment of acetabular fractures using 3D-printed guiding templates: an experimental study. Injury. 2017;48:1147-1154.

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    Choy WJ, Mobbs RJ, Wilcox B, Phan S, Phan K, Sutterlin CE. Reconstruction of thoracic spine using a personalized 3D-printed vertebral body in adolescent with T9 primary bone tumor. World Neurosurg. 2017;105:1032.e13-1032.e17.

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    Chung KJ, Huang B, Choi CH, Park YW, Kim HN. Utility of 3D printing for complex distal Tibial fractures and malleolar avulsion fractures: technical tip. Foot Ankle Int. 2015;36:1504-1510.

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    Chung KJ, Hong DY, Kim YT, Yang I, Park YW, Kim HN. Preshaping plates for minimally invasive fixation of calcaneal fractures using a real-size 3D-printed model as a preoperative and intraoperative tool. Foot Ankle Int. 2014;35:1231-1236.

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    De Muinck Keizer RJO, Lechner KM, Mulders M a M, Schep NWL, Eygendaal D, Goslings JC. Three-dimensional virtual planning of corrective osteotomies of distal radius malunions: a systematic review and meta-analysis. Strategies Trauma Limb Reconstr. 2017;12:77-89.

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    Li B, Chen B, Zhang Y, Wang X, Wang F, Xia H, Yin Q. Comparative use of the computer-aided angiography and rapid prototyping technology versus conventional imaging in the management of the tile C pelvic fractures. Int Orthop. 2016;40:161-166.

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    Li Z, Li Z, Xu R, Li M, Li J, Liu Y, Sui D, Zhang W, Chen Z. Three-dimensional printing models improve understanding of spinal fracture--a randomized controlled study in China. Sci Rep. 2015;5:11570.

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    Omar Mohamed, Zeller Alexander-Nicolai, Gellrich Nils-Claudius, Rana Majeed, Krettek Christian, Liodakis Emannouil. Application of a customized 3D printed reduction aid after external fixation of the femur and tibia: Technical note. The International Journal of Medical Robotics and Computer Assisted Surgery. 2017;13(4):e1803.

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    Oxley B, Behr S. Stabilisation of a cranial cervical vertebral fracture using a 3D-printed patient-specific drill guide. J Small Anim Pract. 2016;57:277.

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    Sanghavi PS, Jankharia BG. Holding versus seeing pathology. Three-dimensional printing of the bony pelvis for preoperative planning of a complex pelvis fracture: a case report. Indian J Radiol Imaging. 2016;26:397-401.

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    Schweizer A, Fürnstahl P, Nagy L. Three-dimensional correction of distal radius intra-articular malunions using patient-specific drill guides. J Hand Surg Am. 2013;38:2339-2347.

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    Shuang F, Hu W, Shao Y, Li H, Zou H. Treatment of intercondylar humeral fractures with 3D-printed Osteosynthesis plates. Medicine (Baltimore). 2016;95:e2461.

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    Tricot M, Duy KT, Docquier P-L. 3D-corrective osteotomy using surgical guides for posttraumatic distal humeral deformity. Acta Orthop Belg. 2012;78:538-542.

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    Upex P, Jouffroy P, Riouallon G. Application of 3D printing for treating fractures of both columns of the acetabulum: benefit of pre-contouring plates on the mirrored healthy pelvis. Orthop Traumatol Surg Res. 2017;103:331-334.

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    Wu X-B, Wang J-Q, Zhao C-P, Sun X, Shi Y, Zhang Z-A, Li Y-N, Wang M-Y. Printed three-dimensional anatomic templates for virtual preoperative planning before reconstruction of old pelvic injuries: initial results. Chin Med J. 2015;128:477-482.

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    Yang L, Shang X-W, Fan J-N, He Z-X, Wang J-J, Liu M, Zhuang Y, Ye C. Application of 3D printing in the surgical planning of Trimalleolar fracture and doctor-patient communication. Biomed Res Int. 2016;2016:2482086.

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    Yang P, Du D, Zhou Z, Lu N, Fu Q, Ma J, Zhao L, Chen A. 3D printing-assisted osteotomy treatment for the malunion of lateral tibial plateau fracture. Injury. 2016;47:2816-2821.

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    Yin H-W, Xu J, Xu W-D. 3-dimensional printing-assisted percutaneous fixation for acute scaphoid fracture: 1-shot procedure. J Hand Surg Am. 2017;42:301.e1-301.e5.

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    You W, Liu LJ, Chen HX, Xiong JY, Wang DM, Huang JH, Ding JL, Wang DP. Application of 3D printing technology on the treatment of complex proximal humeral fractures (Neer3-part and 4-part) in old people. Orthop Traumatol Surg Res. 2016;102:897-903.

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    Zeng C, Xing W, Wu Z, Huang H, Huang W. A combination of three-dimensional printing and computer-assisted virtual surgical procedure for preoperative planning of acetabular fracture reduction. Injury. 2016;47:2223-2227.

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    Zeng C, Xiao J, Wu Z, Huang W. Evaluation of three-dimensional printing for internal fixation of unstable pelvic fracture from minimal invasive Para-rectus abdominis approach: a preliminary report. Int J Clin Exp Med. 2015;8:13039-13044.

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    Zhang Y, Lu S, Xu Y, Shi J, Li Y, Feng Z. Application of navigation template to fixation of sacral fracture using three-dimensional reconstruction and reverse engineering technique. Chin J Traumatol. 2009;12:214-217.

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    Park CH, Rios HF, Taut AD, Padial-Molina M, Flanagan CL, Pilipchuk SP, Hollister SJ, Giannobile WV. Image-based, fiber guiding scaffolds: a platform for regenerating tissue interfaces. Tissue Eng Part C Methods. 2014;20:533-542.

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    Sha Y, Wang H, Ding J, Tang H, Li C, Luo H, Liu J, Xu Y. A novel patient-specific navigational template for anatomical reconstruction of the lateral ankle ligaments. Int Orthop. 2016;40:59-64.

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    Pressel T, Max S, Pfeifer R, Ostermeier S, Windhagen H, Hurschler C. A rapid prototyping model for biomechanical evaluation of pelvic osteotomies. Biomed Tech (Berl). 2008;53:65-69.

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    Tong K, Zhang Y, Zhang S, Yu B. Application of computer-aided osteotomy template design in treatment of developmental dysplasia of the hip with steel osteotomy. Nan Fang Yi Ke Da Xue Xue Bao. 2013;33:906-909.

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    Xu J, Li D, Ma R, Barden B, Ding Y. Application of rapid prototyping pelvic model for patients with DDH to facilitate arthroplasty planning: a pilot study. J Arthroplast. 2015;30:1963-1970.

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    Zhang YZ, Chen B, Lu S, Yang Y, Zhao JM, Liu R, Li YB, Pei GX. Preliminary application of computer-assisted patient-specific acetabular navigational template for total hip arthroplasty in adult single development dysplasia of the hip. Int J Med Robot. 2011;7:469-474.

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    Zheng P, Yao Q, Xu P, Wang L. Application of computer-aided design and 3D-printed navigation template in locking compression pediatric hip PlateΤΜ placement for pediatric hip disease. Int J Comput Assist Radiol Surg. 2017;12:865-871.

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    Chen X, Xu L, Wang W, Li X, Sun Y, Politis C. Computer-aided design and manufacturing of surgical templates and their clinical applications: a review. Expert Rev Med Devices. 2016;13:853-864.

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    Kim D, Lim JY, Shim KW, Han JW, Yi S, Yoon DH, Kim KN, Ha Y, Ji GY, Shin DA. Sacral reconstruction with a 3D-printed implant after Hemisacrectomy in a patient with sacral osteosarcoma: 1-year follow-up result. Yonsei Med J. 2017;58:453-457.

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    Liang H, Ji T, Zhang Y, Wang Y, Guo W. Reconstruction with 3D-printed pelvic endoprostheses after resection of a pelvic tumour. Bone Joint J. 2017;99-B:267-275.

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    Luo W, Huang L, Liu H, Qu W, Zhao X, Wang C, Li C, Yu T, Han Q, Wang J, Qin Y. Customized knee prosthesis in treatment of Giant cell tumors of the proximal tibia: application of 3-dimensional printing Technology in Surgical Design. Med Sci Monit. 2017;23:1691-1700.

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    Ma L, Zhou Y, Zhu Y, Lin Z, Chen L, Zhang Y, Xia H, Mao C. 3D printed personalized titanium plates improve clinical outcome in microwave ablation of bone tumors around the knee. Sci Rep. 2017;7:7626.

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    Ma L, Zhou Y, Zhu Y, Lin Z, Wang Y, Zhang Y, Xia H, Mao C. 3D-printed guiding templates for improved osteosarcoma resection. Sci Rep. 2016;6:23335.

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    Mobbs RJ, Coughlan M, Thompson R, Sutterlin CE, Phan K. The utility of 3D printing for surgical planning and patient-specific implant design for complex spinal pathologies: case report. J Neurosurg Spine. 2017;26:513-518.

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    Peters P, Langlotz F, Nolte L-P. Computer assisted screw insertion into real 3D rapid prototyping pelvis models. Clin Biomech (Bristol, Avon). 2002;17:376-382.

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    Ren X, Yang L, Duan X-J. Three-dimensional printing in the surgical treatment of osteoid osteoma of the calcaneus: a case report. J Int Med Res. 2017;45:372-380.

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    Tam MD, Laycock SD, Bell D, Chojnowski A. 3-D printout of a DICOM file to aid surgical planning in a 6 year old patient with a large scapular osteochondroma complicating congenital diaphyseal aclasia. J Radiol Case Rep. 2012;6:31-37.

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    Wang X, Shi J, Zhang S, Zhang Z, Li X, Li Z. Pediatric lumbar pedicle screw placement using navigation templates: a cadaveric study. Indian J Orthop. 2017;51:468-473.

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    Wang Y-T, Yang X-J, Yan B, Zeng T-H, Qiu Y-Y, Chen S-J. Clinical application of three-dimensional printing in the personalized treatment of complex spinal disorders. Chin J Traumatol. 2016;19:31-34.

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    Wei R, Guo W, Ji T, Zhang Y, Liang H. One-step reconstruction with a 3D-printed, custom-made prosthesis after total en bloc sacrectomy: a technical note. Eur Spine J. 2017;26:1902-1909.

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    Xiao J-R, Huang W-D, Yang X-H, Yan W-J, Song D-W, Wei H-F, Liu T-L, Wu Z-P, Yang C. En bloc resection of primary malignant bone tumor in the cervical spine based on 3-dimensional printing technology. Orthop Surg. 2016;8:171-178.

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    Xu N, Wei F, Liu X, Jiang L, Cai H, Li Z, Yu M, Wu F, Liu Z. Reconstruction of the upper cervical spine using a personalized 3D-printed vertebral body in an adolescent with Ewing sarcoma. Spine. 2016;41:E50-E54.

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    Zhang Y, Wen L, Zhang J, Yan G, Zhou Y, Huang B. Three-dimensional printing and computer navigation assisted hemipelvectomy for en bloc resection of osteochondroma: a case report. Medicine (Baltimore). 2017;96:e6414.

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    Anderl W, Pauzenberger L, Schwameis E. The MyKnee® patient-specific system. Rationale, technique and results. Orthopade. 2016;45:294-301.

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    Beckmann J, Steinert A, Zilkens C, Zeh A, Schnurr C, Schmitt-Sody M, Gebauer M. Partial replacement of the knee joint with patient-specific instruments and implants (ConforMIS iUni, iDuo). Orthopade. 2016;45:322-330.

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    Gauci MO, Boileau P, Baba M, Chaoui J, Walch G. Patient-specific glenoid guides provide accuracy and reproducibility in total shoulder arthroplasty. Bone Joint J. 2016;98-B:1080-1085.

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    Hafez MA, Chelule KL, Seedhom BB, Sherman KP. Computer-assisted total knee arthroplasty using patient-specific templating. Clin Orthop Relat Res. 2006;444:184-192.

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    Leotta DF, Starnes BW. Custom fenestration templates for endovascular repair of juxtarenal aortic aneurysms. J Vasc Surg. 2015;61:1637-1641.

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    Lermusiaux P, Leroux C, Tasse JC, Castellani L, Martinez R. Aortic aneurysm: construction of a life-size model by rapid prototyping. Ann Vasc Surg. 2001;15:131-135.

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    Sun X, Zhang H, Zhu K, Wang C. Patient-specific three-dimensional printing for Kommerell’s diverticulum. Int J Cardiol. 2018;255:184-187.

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    Tam MD, Latham T, Brown JRI, Jakeways M. Use of a 3D printed hollow aortic model to assist EVAR planning in a case with complex neck anatomy: potential of 3D printing to improve patient outcome. J Endovasc Ther. 2014;21:760-762.

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    Tam MDBS, Laycock SD, Brown JRI, Jakeways M. 3D printing of an aortic aneurysm to facilitate decision making and device selection for endovascular aneurysm repair in complex neck anatomy. J Endovasc Ther. 2013;20:863-867.

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    Torres IO, De Luccia N. A simulator for training in endovascular aneurysm repair: the use of three dimensional printers. Eur J Vasc Endovasc Surg. 2017;54:247-253.

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    Treasure T, Takkenberg JJM, Golesworthy T, Rega F, Petrou M, Rosendahl U, Mohiaddin R, Rubens M, Thornton W, Lees B, Pepper J. Personalised external aortic root support (PEARS) in Marfan syndrome: analysis of 1-9 year outcomes by intention-to-treat in a cohort of the first 30 consecutive patients to receive a novel tissue and valve-conserving procedure, compared with the published results of aortic root replacement. Heart. 2014;100:969-975.

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    Valverde I, Gomez G, Coserria JF, Suarez-Mejias C, Uribe S, Sotelo J, Velasco MN, Santos De Soto J, Hosseinpour A-R, Gomez-Cia T. 3D printed models for planning endovascular stenting in transverse aortic arch hypoplasia. Catheter Cardiovasc Interv. 2015;85:1006-1012.

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    Wilasrusmee C, Suvikrom J, Suthakorn J, Lertsithichai P, Sitthiseriprapip K, Proprom N, Kittur DS. Three-dimensional aortic aneurysm model and endovascular repair: an educational tool for surgical trainees. Int J Angiol. 2008;17:129-133.

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    Winder RJ, Sun Z, Kelly B, Ellis PK, Hirst D. Abdominal aortic aneurysm and stent graft phantom manufactured by medical rapid prototyping. J Med Eng Technol. 2002;26:75-78.

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    You JH, Kang S-G, Kim BM. A novel measurement technique for the design of fenestrated stent grafts: comparison with three-dimensional aorta models. Exp Clin Cardiol. 2013;18:48-52.

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    Yuan D, Luo H, Yang H, Huang B, Zhu J, Zhao J. Precise treatment of aortic aneurysm by three-dimensional printing and simulation before endovascular intervention. Sci Rep. 2017;7:795.

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    Han X, Wu X, Kelly M, Chen X. Fabrication and optimal Design of Biodegradable Polymeric Stents for aneurysms treatments. J Funct Biomater. 2017;8(1):E8.

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    Ishibashi T, Takao H, Suzuki T, Yuki I, Kaku S, Kan I, Nishimura K, Suzuki T, Watanabe M, Karagiozov K, Murayama Y. Tailor-made shaping of microcatheters using three-dimensional printed vessel models for endovascular coil embolization. Comput Biol Med. 2016;77:59-63.

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    Lin JC, Myers E. Three-dimensional printing for preoperative planning of renal artery aneurysm surgery. J Vasc Surg. 2016;64:810.

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    Salloum C, Lim C, Fuentes L, Osseis M, Luciani A, Azoulay D. Fusion of information from 3D printing and surgical robot: an innovative minimally technique illustrated by the resection of a large celiac trunk aneurysm. World J Surg. 2016;40:245-247.

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    Shibata E, Takao H, Amemiya S, Ohtomo K. 3D-printed visceral aneurysm models based on CT data for simulations of endovascular embolization: evaluation of size and shape accuracy. AJR Am J Roentgenol. 2017;209:243-247.

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    Takao H, Amemiya S, Shibata E, Ohtomo K. 3D printing of preoperative simulation models of a splenic artery aneurysm. Precision and Accuracy Acad Radiol. 2017;24:650-653.

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    Lashkarinia S. Samaneh, Piskin Senol, Bozkaya Tijen A., Salihoglu Ece, Yerebakan Can, Pekkan Kerem. Computational Pre-surgical Planning of Arterial Patch Reconstruction: Parametric Limits and In Vitro Validation. Annals of Biomedical Engineering. 2018;46(9):1292-1308.

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    Shirakawa T, Yoshitatsu M, Koyama Y, Mizoguchi H, Toda K, Sawa Y. 3D-printed aortic stenosis model with fragile and crushable calcifications for off-the-job training and surgical simulation. Multimed Man Cardiothorac Surg. 2018. 10.1510/mmcts.2018.018.

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    Yang Y, Liu X, Xia Y, Liu X, Wu W, Xiong H, Zhang H, Xu L, Wong KKL, Ouyang H, Huang W. Impact of spatial characteristics in the left stenotic coronary artery on the hemodynamics and visualization of 3D replica models. Sci Rep. 2017;7:15452.

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    Jones TW, Seckeler MD. Use of 3D models of vascular rings and slings to improve resident education. Congenit Heart Dis. 2017;12(5):578-582.

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    Cao P, Duhamel Y, Olympe G, Ramond B, Langevin F. A new production method of elastic silicone carotid phantom based on MRI acquisition using rapid prototyping technique. Conf Proc IEEE Eng Med Biol Soc. 2013;2013:5331-5334.

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    Govsa F, Yagdi T, Ozer MA, Eraslan C, Alagoz AK. Building 3D anatomical model of coiling of the internal carotid artery derived from CT angiographic data. Eur Arch Otorhinolaryngol. 2017;274:1097-1102.

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    Lai SSM, Yiu BYS, Poon AKK, Yu ACH. Design of anthropomorphic flow phantoms based on rapid prototyping of compliant vessel geometries. Ultrasound Med Biol. 2013;39:1654-1664.

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    Xie J, Li M-H, Tan H-Q, Zhu Y-Q, Li Y-D, Fan C-H, Hu D-J, Qiao R-H. Establishment of an experimental intracranial internal carotid artery model and the application in covered-stent navigability testing. AJNR Am J Neuroradiol. 2009;30:1041-1045.

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    Yedavalli RV, Loth F, Yardimci A, Pritchard WF, Oshinski JN, Sadler L, Charbel F, Alperin N. Construction of a physical model of the human carotid artery based upon in vivo magnetic resonance images. J Biomech Eng. 2001;123:372-376.

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    Abla AA, Lawton MT. Three-dimensional hollow intracranial aneurysm models and their potential role for teaching, simulation, and training. World Neurosurg. 2015;83:35-36.

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    Andereggen L, Gralla J, Andres RH, Weber S, Schroth G, Beck J, Widmer HR, Reinert M, Raabe A, Peterhans M. Stereolithographic models in the interdisciplinary planning of treatment for complex intracranial aneurysms. Acta Neurochir. 2016;158:1711-1720.

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    Anderson JR, Klucznik R, Diaz O, Zhang YJ, Britz GW, Grossman RG, Karmonik C. Quantification of velocity reduction after flow diverter placement in intracranial aneurysm: an ex vivo study with 3D printed replicas. Conf Proc IEEE Eng Med Biol Soc. 2015;2015:7300-7303.

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    Anderson JR, Thompson WL, Alkattan AK, Diaz O, Klucznik R, Zhang YJ, Britz GW, Grossman RG, Karmonik C. Three-dimensional printing of anatomically accurate, patient specific intracranial aneurysm models. J Neurointerv Surg. 2016;8:517-520.

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    Benet A, Plata-Bello J, Abla AA, Acevedo-Bolton G, Saloner D, Lawton MT. Implantation of 3D-printed patient-specific aneurysm models into cadaveric specimens: a new training paradigm to allow for improvements in cerebrovascular surgery and research. Biomed Res Int. 2015;2015:939387.

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    Conti A, Pontoriero A, Iati G, Marino D, La Torre D, Vinci S, Germano A, Pergolizzi S, Tomasello F. 3D-printing of arteriovenous malformations for Radiosurgical treatment: pushing anatomy understanding to real boundaries. Cureus. 2016;8:e594.

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    Dong M, Chen G, Li J, Qin K, Ding X, Peng C, Zhou D, Lin X. Three-dimensional brain arteriovenous malformation models for clinical use and resident training. Medicine (Baltimore). 2018;97:e9516.

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    Dong M, Chen G, Qin K, Ding X, Zhou D, Peng C, Zeng S, Deng X. Development of three-dimensional brain arteriovenous malformation model for patient communication and young neurosurgeon education. Br J Neurosurg. 2018:1–4. 10.1080/02688697.2018.1424320.

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    Frolich AMJ, Spallek J, Brehmer L, Buhk J-H, Krause D, Fiehler J, Kemmling A. 3D printing of intracranial aneurysms using fused deposition modeling offers highly accurate replications. AJNR Am J Neuroradiol. 2016;37:120-124.

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    Imbesi SG, Knox K, Kerber CW. Reproducibility analysis of a new objective method for measuring arteriovenous malformation nidus size at angiography. AJNR Am J Neuroradiol. 2002;23:412-415.

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    Kaneko N, Mashiko T, Namba K, Tateshima S, Watanabe E, Kawai K. A patient-specific intracranial aneurysm model with endothelial lining: a novel in vitro approach to bridge the gap between biology and flow dynamics. J Neurointerv Surg. 2018;10:306-309.

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    Karmonik C, Anderson JR, Elias S, Klucznik R, Diaz O, Zhang YJ, Grossman RG, Britz GW. Four-dimensional phase contrast magnetic resonance imaging protocol optimization using patient-specific 3-dimensional printed replicas for in vivo imaging before and after flow diverter placement. World Neurosurg. 2017;105:775-782.

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    Khan IS, Kelly PD, Singer RJ. Prototyping of cerebral vasculature physical models. Surg Neurol Int. 2014;5:11.

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    Konno T, Mashiko T, Oguma H, Kaneko N, Otani K, Watanabe E. Rapid 3-dimensional models of cerebral aneurysm for emergency surgical clipping. No Shinkei Geka. 2016;44:651-660.

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    Lan Q, Chen A, Zhang T, Li G, Zhu Q, Fan X, Ma C, Xu T. Development of three-dimensional printed Craniocerebral models for simulated neurosurgery. World Neurosurg. 2016;91:434-442.

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    Liu Y, Gao Q, Du S, Chen Z, Fu J, Chen B, Liu Z, He Y. Fabrication of cerebral aneurysm simulator with a desktop 3D printer. Sci Rep. 2017;7:44301.

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    Mashiko T, Kaneko N, Konno T, Otani K, Nagayama R, Watanabe E. Training in cerebral aneurysm clipping using self-made 3-dimensional models. J Surg Educ. 2017;74:681-689.

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    Mashiko T, Otani K, Kawano R, Konno T, Kaneko N, Ito Y, Watanabe E. Development of three-dimensional hollow elastic model for cerebral aneurysm clipping simulation enabling rapid and low cost prototyping. World Neurosurg. 2015;83:351-361.

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    Namba K, Higaki A, Kaneko N, Mashiko T, Nemoto S, Watanabe E. Microcatheter shaping for intracranial aneurysm coiling using the 3-dimensional printing rapid prototyping technology: preliminary result in the first 10 consecutive cases. World Neurosurg. 2015;84(1):178-186.

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    Russ M, O’Hara R, Setlur Nagesh SV, Mokin M, Jimenez C, Siddiqui A, Bednarek D, Rudin S, Ionita C. Treatment planning for image-guided neuro-vascular interventions using patient-specific 3D printed phantoms. Proc SPIE Int Soc Opt Eng. 2015. 10.1117/12.2081997.

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    Ryan JR, Almefty KK, Nakaji P, Frakes DH. Cerebral aneurysm clipping surgery simulation using patient-specific 3D printing and silicone casting. World Neurosurg. 2016;88:175-181.

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    Shah A, Jankharia B, Goel A. Three-dimensional model printing for surgery on arteriovenous malformations. Neurol India. 2017;65:1350-1354.

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    Thawani JP, Pisapia JM, Singh N, Petrov D, Schuster JM, Hurst RW, Zager EL, Pukenas BA. Three-dimensional printed modeling of an arteriovenous malformation including blood flow. World Neurosurg. 2016;90:675-683.e2.

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