SUVmax/THKmax as a biomarker for distinguishing advanced gastric carcinoma from primary gastric lymphoma.

BACKGROUND: Gastric carcinoma and primary gastric lymphoma (PGL) are the two most common malignancies in stomach. The purpose of this study was to screen and validate a biomarker of (18)F-fluorodeoxyglucose positron emission tomography/computed tomography ((18)F-FDG PET/CT) for distinguishing advanced gastric carcinoma (AGC) from PGL for clinical applications. METHODOLOGY/PRINCIPAL FINDINGS: We reviewed PET/CT scans collected from January 2008 to April 2012 of 69 AGC and 38 PGL (14 low-grade mucosa-associated lymphoid tissue [MALT], 24 non-MALT aggressive non-Hodgkin lymphoma [ANHL]) with a focus on FDG intensity (maximum standardized uptake value [SUVmax]) of primary lesions and its CT-detected abnormalities, including maximal gastrointestinal wall thickness (THKmax) and mucosal ulcerations. Gastric FDG uptake was found in 69 (100%) patients with AGC and 36 (95%, 12 MALT vs. 24 ANHL)with PGL. The presence of CT-detected abnormalities of AGC and PGL were 97% (67/69) and 89% (12 MALT vs. 22 ANHL), respectively. After controlling for THKmax, SUVmax was higher with ANHL than AGC (17.10 ± 8.08 vs. 9.65 ± 5.24, p<0.05) and MALT (6.20 ± 3.60, p<0.05). THKmax did not differ among MALT, ANHL and AGC. Mucosal ulceration was more common with AGC (n = 9) than PGL (n = 2),but the difference was not statistically significant (p>0.05). Cross-validation analysis showed that for distinguishing ANHL from AGC, the classifier with SUVmax as a feature achieved a correct classification rate of 81% with thresholds 13.40 ± 1.12 and the classifier with SUVmax/THKmax as a feature achieved a correct classification rate of 83% with thresholds 7.51 ± 0.63. CONCLUSIONS/SIGNIFICANCE: SUVmax/THKmax may be as a promising biomarker of FDG-PET/CT for distinguishing ANHL from AGC. Structural CT abnormalities alone may not be reliable but can help with PET assessment of gastric malignancies. (18)F-FDG PET/CT have potential for distinguishing AGC from PGL at the individual level.

Abstract licence: CC BY

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