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Objective: We aimed to investigate the predictive value of pre-treatment 18F-FDG PET/CT multi-metabolic parameters and tumor metabolic heterogeneity for gastric cancer prognosis. Methods: Seventy-one patients with gastric cancer were included. All patients underwent 18F-FDG PET/CT whole-body scans prior to treatment and had pathologically confirmed gastric adenocarcinomas. Each metabolic parameter, including SUVmax, SUVmean, MTV, and TLG, were collected from the primary lesions of gastric cancer in all patients, and the slope of linear regression between the MTV corresponding to different SUVmax thresholds (40% × SUVmax, 80% × SUVmax) of the primary lesions was calculated. The absolute value of the slope was regarded as the metabolic heterogeneity of the primary lesions, expressed as the heterogeneity index HI-1, and the coefficient of variance of the SUVmean of the primary lesions was regarded as HI-2. Patient prognosis was assessed by PFS and OS, and a nomogram of the prognostic prediction model was constructed, after which the clinical utility of the model was assessed using DCA. Results: A total of 71 patients with gastric cancer, including 57 (80.3%) males and 14 (19.7%) females, had a mean age of 61 ± 10 years; disease progression occurred in 27 (38.0%) patients and death occurred in 24 (33.8%) patients. Multivariate Cox regression analysis showed that HI-1 alone was a common independent risk factor for PFS (HR: 1.183; 95% CI: 1.010–1.387, P < 0.05) and OS (HR: 1.214; 95% CI: 1.016–1.450, P < 0.05) in patients with gastric cancer. A nomogram created based on the results of Cox regression analysis increased the net clinical benefit for patients. Considering disease progression as a positive event, patients were divided into low-, intermediate-, and high-risk groups, and Kaplan–Meier survival analysis showed that there were significant differences in PFS among the three groups. When death was considered a positive event and patients were included in the low- and high-risk groups, there were significant differences in OS between the two groups. Conclusion: The heterogeneity index HI-1 of primary gastric cancer lesions is an independent risk factor for patient prognosis. A nomogram of prognostic prediction models constructed for each independent factor can increase the net clinical benefit and stratify the risk level of patients, providing a reference for guiding individualized patient treatment.

Objective: We aimed to investigate the predictive value of pre-treatment 18 F-FDG PET/CT multi-metabolic parameters and tumor metabolic heterogeneity for gastric cancer prognosis.Methods: Seventy-one patients with gastric cancer were included. All patients underwent 18 F-FDG PET/CT whole-body scans prior to treatment and had pathologically con rmed gastric adenocarcinomas. Each metabolic parameter, including SUVmax, SUVmean, MTV, and TLG, were collected from the primary lesions of gastric cancer in all patients, and the slope of linear regression between the MTV corresponding to different SUVmax thresholds (40% × SUVmax, 80% × SUVmax) of the primary lesions was calculated. The absolute value of the slope was regarded as the metabolic heterogeneity of the primary lesions, expressed as the heterogeneity index HI-1, and the coe cient of variance of the SUVmean of the primary lesions was regarded as HI-2. Patient prognosis was assessed by PFS and OS, and a nomogram of the prognostic prediction model was constructed, after which the clinical utility of the model was assessed using DCA.Results: A total of 71 patients with gastric cancer, including 57 (80.3%) males and 14 (19.7%) females, had a mean age of 61 ± 10 years; disease progression occurred in 27 (38.0%) patients and death occurred in 24 (33.8%) patients. Multivariate Cox regression analysis showed that HI-1 alone was a common independent risk factor for PFS (HR: 1.183; 95% CI: 1.010-1.387, P < 0.05) and OS (HR: 1.214; 95% CI: 1.016-1.450, P < 0.05) in patients with gastric cancer. A nomogram created based on the results of Cox regression analysis increased the net clinical bene t for patients. Considering disease progression as a positive event, patients were divided into low-, intermediate-, and high-risk groups, and Kaplan-Meier survival analysis showed that there were signi cant differences in PFS among the three groups. When death was considered a positive event and patients were included in the low-and high-risk groups, there were signi cant differences in OS between the two groups. Conclusion:The heterogeneity index HI-1 of primary gastric cancer lesions is an independent risk factor for patient prognosis. A nomogram of prognostic prediction models constructed for each independent factor can increase the net clinical bene t and stratify the risk level of patients, providing a reference for guiding individualized patient treatment.