Introduction/Background The aim of this study was to analyse the clinical applicability of 2-[18F]FDG PET/CT volumetric parameters to anticipate surgical peritoneal cancer index (PCI), by studying their correlation in advanced high-grade serous or undifferentiated epithelial ovarian cancer (EOC) patients before primary treatment. The secondary aim was to evaluate the capacity of metabolic tumour volume (MTV) and total lesion glycolysis (TLG) to predict high or low PCI values.

Methodology We patients with advanced-stage high-grade EOC, that were admitted between 01/2013 and 12/2018, received a 2-[18F]FDG PET/CT and a surgical procedure to estimate PCI before primary treatment.

The peritoneal carcinomatosis MTV (car_MTV) and TLG (car_TLG) were computed for the whole abdominal cavity as the sum of every intraperitoneal VOI’s MTV and TLG respectively. Furthermore, PET/CT images were partitioned into nine regions based on the anatomical boundaries described by Sugarbaker. MTV and TLG were subsequently calculated for each region.

Results 45 patients were evaluated. 88.9% had high-grade serous ovarian cancer. 33.3% underwent primary debulking surgery (PDS) and 66.7% neoadjuvant chemotherapy (NACT). Mean PCI were 12.79 for PDS and 18.17 for NACT. Volumetric parameters from PET/CT, especially car_MTV40 and car_MTV50, showed strong correlations with PCI, facilitating predictions of PCI below or above 14 and 20, with sensitivities ranging from 55% to 66% and specificities from 69% to 75%.

Parameters from upper-abdominal regions exhibited stron correlation with PCI and predictive abilities for PCI lower or higher than 14 and 20, with sensitivities between 65% and 79% and specificities from 75% to 79%. Subanalysis within the PDS subgroup revealed notably higher and statistically significant correlations between these volumetric parameters and PCI.

Conclusion The present study highlights the promising potential of PET/CT parameters, particularly, car_MTV, and quadrant-specific MTV and TLG values, in predicting disease burden non-invasively and aiding treatment decisions in advanced ovarian cancer.

Disclosures No.