Fluorodeoxyglucose PET/CT-derived Metabolic Peritoneal Cancer Index for survival assessment in peritoneal carcinomatosis.

OBJECTIVE

To evaluate the association between the Metabolically active Peritoneal Cancer Index (M-PCI) derived from 18F-fluorodeoxyglucose PET/computed tomography (18F-FDG PET/CT) and to assess its ability to predict overall survival (OS) in patients with peritoneal carcinomatosis.

METHODS

This retrospective study included 107 patients with pathologically confirmed peritoneal carcinomatosis who underwent 18F-FDG PET/CT between October 2022 and July 2025. M-PCI was calculated using a PET-adapted Peritoneal Cancer Index approach based on metabolically active peritoneal lesions across 13 anatomical regions. Patients were stratified using an M-PCI cutoff value of 20, with the appropriateness of this threshold additionally explored using receiver operating characteristic analysis. Survival analysis was performed using Kaplan-Meier analysis and univariable and multivariable Cox regression models.

RESULTS

During a median follow-up of 22 months, 78 deaths (72.9%) occurred. The median OS was 9 months. M-PCI was significantly associated with OS [hazard ratio = 1.050 per unit increase; 95% confidence interval (CI) = 1.019-1.082; P = 0.001]. Patients with M-PCI > 20 had significantly worse survival compared with those with M-PCI ≤ 20 (median OS = 3 vs. 10 months; log-rank P = 0.010), with nearly a two-fold increase in mortality risk (hazard ratio = 1.94; 95% CI = 1.14-3.32; P = 0.015). The prognostic impact of M-PCI was particularly pronounced in the gynecologic subgroup. In multivariable Cox regression analysis, M-PCI remained independently associated with OS after adjustment for tumor origin, treatment, extent of disease, ascites, and timing of peritoneal carcinomatosis (adjusted hazard ratio = 1.040; 95% CI = 1.002-1.080; P = 0.042).

CONCLUSION

M-PCI derived from 18F-FDG PET/CT is a significant predictor of OS in patients with peritoneal carcinomatosis. By integrating metabolic activity with spatial disease distribution, M-PCI may provide clinically relevant prognostic information and improve risk stratification in this patient population.