CT-Based Radiomics and Deep Learning for BRCA Mutation and Progression-Free Survival Prediction in Ovarian Cancer Using a Multicentric Dataset

ABSTRACT:

Simple Summary

Ovarian cancer has a heterogeneous response to treatment, and relapse may vary considerably. Different studies investigated the role of radiomics in ovarian cancer. However, many of them were performed in a single center, and solid external validation of findings is still missing. We used a multicentric database of high-grade serous ovarian cancer to build predictive radiomic and deep-learning models for early relapse and BRCA mutation, validating them in a different set of cases coming from other institutions. In our multicentric dataset, representative of a real-life clinical scenario, we could not find a good radiomic predicting model for PFS and BRCA mutational status with both traditional radiomics and deep learning methods. This study highlights that to implem

SUBMITTER: Avesani G 

PROVIDER: S-EPMC9179845 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature