Surgeons' Ability to Predict Pathological and Molecular Features of Peritoneal Carcinomatosis in Ovarian Cancer

Overview

Epithelial ovarian cancer (EOC) presents with peritoneal carcinomatosis (PC) at diagnosis in approximately two-thirds of cases. Diagnostic laparoscopy is pivotal to assess disease extent and to guide the choice between primary cytoreductive surgery (PCS) and neoadjuvant chemotherapy followed by interval cytoreductive surgery (ICS). The Predictive Index Value (PIV) provides a quantitative estimate of resectability, but it does not systematically capture qualitative intraoperative descriptors. Growing evidence suggests that macroscopic features (e.g., nodularity, plaques, omental cake, infiltrative vs expansile growth, margin definition, vascularization, and tissue retraction) may correlate with histotype and molecular profile, and possibly with chemosensitivity. However, surgeons' ability to recognize these visual patterns in a standardized manner has not been systematically investigated. This cross-sectional survey will assess whether gynecologic oncologic surgeons managing PC can: distinguish malignant metastases from benign tumor-like lesions; associate morphologic patterns with tumor histotypes (type I vs type II EOC and ovarian metastases from other primaries); classify high-grade serous ovarian cancer (HGSOC) growth pattern as infiltrative vs exophytic/expansile; and infer molecular status from macroscopic appearance. The secondary objective is to compare accuracy and confidence between senior and junior surgeons. Seventy to eighty surgeons will complete an online survey (Microsoft Forms) presenting anonymized laparoscopic images retrospectively selected from routinely recorded diagnostic-laparoscopy videos of 19 consented patients with advanced EOC and PC. Participants will classify each case using predefined categories and rate confidence on a 5-point Likert scale. Analyses will be primarily descriptive (counts/percentages); senior vs junior comparisons will use χ²/Fisher's exact tests for categorical variables and the Mann-Whitney U test for ordinal measures, as appropriate.

Conditions