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  • Title: Intra-tumor metabolic heterogeneity of gastric cancer on 18F-FDG PETCT indicates patient survival outcomes.
    Author: Liu G, Yin H, Cheng X, Wang Y, Hu Y, Liu T, Shi H.
    Journal: Clin Exp Med; 2021 Feb; 21(1):129-138. PubMed ID: 32880779.
    Abstract:
    The present study aimed to investigate the prognostic value of intra-tumor metabolic heterogeneity on 2-[18F] Fluoro-2-deoxy-D-glucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) for patients with gastric cancer. Fifty-five patients with advanced gastric cancer that had received neoadjuvant chemotherapy and radical surgery were included. Clinicopathological information, 18F-FDG PET/CT before chemotherapy, pathological response, recurrence or metastasis, progression-free survival (PFS), and overall survival (OS) of the patients were collected. The maximum, peak, and mean standardized uptake values (SUVmax, SUVpeak, and SUVmean), tumor-to-liver ratio (TLR), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) on PET/CT were measured. Heterogeneity index-1 (HI-1) was calculated as SUVmean divided by the standard deviation, and heterogeneity index-2 (HI-2) was evaluated through linear regressions of MTVs according to different SUV thresholds. Associations between these parameters and patient survival outcomes were analyzed. None of the parameters on PET were associated with tumor recurrence. Pathological responders had significantly smaller TLR, MTV and HI-2 values than non-responders (P = 0.017, 0.017 and 0.013, respectively). In multivariate analysis of PFS, only HI-2 was an independent factor (hazard ratio [HR] = 2.693, P = 0.005) after adjusting for clinical tumor-node-metastasis (TNM) stage. In multivariate analysis of OS, HI-2 was also an independent predictive factor (HR = 2.281, P = 0.009) after adjusting for tumor recurrence. Thus, HI-2 generated from baseline 18F-FDG PET/CT is significantly associated with survival of patients with gastric cancer. Preoperative assessment of HI-2 by 18F-FDG PET/CT might be promising to identify patients with poor prognosis.
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