Prognostic Value of Metabolic Information in Advanced Gastric Cancer Using Preoperative ¹⁸F-FDG PET/CT / 대한핵의학회잡지

ABSTRACT

PURPOSE: This study evaluated the usefulness of semiquantitative and volumetric PET parameters for predicting prognosis in patients with advanced gastric cancer (AGC).METHODS: We enrolled 213 patients who underwent ¹⁸F-fluoro-2-deoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) prior to curative surgery for AGC. Maximum standardized uptake value (SUVmax) and tumor-to-liver uptake ratio (TLR) were measured in all patients. Metabolic tumor volume (MTV) and total lesion glycolysis were measured in volume-measurable patients. For further quantification of FDG uptake, we developed PET prognostic scores by combining SUVmax and MTV (1 low SUVmax/low MTV; 2 high SUVmax/low MTV; 3 high SUVmax/high MTV). Comparison of PET parameters between recurrence and non-recurrence groups was performed. Univariate and multivariate analyses for recurrence-free survival (RFS) and overall survival (OS) were subsequently performed.RESULTS: The recurrence rate was 32.4% (69/213 patients). Mean SUVmax and mean MTV of the recurrence group were significantly higher than those of the non-recurrence group (p = 0.026 and p = 0.025). TLR showed marginal significance (p = 0.051). In multivariate analysis for RFS including all patients, SUVmax (p = 0.022), TLR (p = 0.010), and PET score (p = 0.003) were independent prognostic factors. In post hoc analysis of PET score, significant differences in RFS were observed between PET scores 2 and 3 as well as scores 1 and 3. No significant difference in RFS was observed between scores 1 and 2. Only PET score was statistically significant for OS in univariate analysis. None of the PET parameters were statistically significant for OS in multivariate analysis.CONCLUSION: High SUVmax and high MTV of the primary tumor suggest a high risk of recurrence for AGC patients. Even if SUVmax is similar, the prognosis may vary depending on MTV. Combining PET parameters results in a better prediction for prognosis.