Predicting pathological response and overall survival in locally advanced gastric cancer patients undergoing neoadjuvant chemotherapy: the role of PET/computed tomography

Background Gastric cancer is the second leading cause of cancer-related deaths, with a 5-year survival rate of about 20-25%. The ability to predict pathological response (PR) to neoadjuvant chemotherapy (NACT); hence, overall survival (OS) probability of patients can allow the clinician to individualize treatment strategies. We investigated the role of F-18 fluorodeoxyglucose PET-computed tomography (F-18 FDG PET/CT) in predicting histopathologic response and prognosis in locally advanced gastric cancer (LAGC) patients undergoing NACT. Methods F-18FDG PET/CT images taken before and after NACT, adenocarcinoma histopathology and operation pyesis reports of 43 LAGC patients were analyzed. Maximum (SUVmax) and mean (SUVmean) standardized uptake values, metabolic tumor volume (MTV), and total lesion glycolysis (TLG) of lesions were measured before and after NACT. Changes in percentage were calculated for Delta SUVmax%, Delta SUVmean%, Delta MTV%, Delta TLG%, and cutoff values were determined by receiver operating characteristic curve analysis. NACT response in pathology pyesis was determined according to the College of American Pathologists classification. PR and OS were analyzed with Kaplan-Meier and Cox proportional hazards regression models based on cutoffs found with PET measurements. Results Cutoffs were Delta SUVmax = 33.31%, Delta SUVmean = 42.96%, Delta MTV = 30.38%, and Delta TLG = 28.14%, and all patients showed significance in PR and OS based on these cutoffs (all P < 0.01). PET/CT findings before and after NACT (Delta MTV > 30.38%, Delta TLG > 28.14%) predicted PR with 100% sensitivity and specificity. Multivariate analysis showed Delta SUVmean as an independent risk factor predicting OS (hazard ratio 0.348, 95% confidence interval 2.91-22.3, P = 0.03). Conclusions Metabolic parameters obtained with F-18 FDG PET/CT scanning before and after NACT in LAGC patients can accurately predict PR and OS.