Ultrasonic radiomics-based nomogram for preoperative prediction of residual tumor in advanced epithelial ovarian cancer: a multicenter retrospective study.

ABSTRACT:

Objectives

To identify radiomic features extracted from ultrasound images and to develop and externally validate a comprehensive model that combines clinical data with ultrasound radiomics features to predict the residual tumor status in patients with advanced epithelial ovarian cancer (OC).

Methods

The study included 112 patients with advanced epithelial OC who underwent preoperative transvaginal ultrasound. Of these, 78 patients were assigned to the development cohort and 34 to the external validation cohort. Tumor contours were manually delineated as regions of interest (ROI) on the ultrasound images, and radiomic features were extracted. The final set of variables was identified using LASSO (least absolute shrinkage and selection operator) regression. Clinical features w

SUBMITTER: Li S 

PROVIDER: S-EPMC11832395 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature