Prediction of BRAF and TERT status in PTCs by machine learning-based ultrasound radiomics methods: A multicenter study.

ABSTRACT:

Background

Preoperative identification of genetic mutations is conducive to individualized treatment and management of papillary thyroid carcinoma (PTC) patients. Purpose: To investigate the predictive value of the machine learning (ML)-based ultrasound (US) radiomics approaches for BRAF V600E and TERT promoter status (individually and coexistence) in PTC.

Methods

This multicenter study retrospectively collected data of 1076 PTC patients underwent genetic testing detection for BRAF V600E and TERT promoter between March 2016 and December 2021. Radiomics features were extracted from routine grayscale ultrasound images, and gene status-related features were selected. Then these features were included to nine different ML models to predicting different mutations, and opti

SUBMITTER: Shi H 

PROVIDER: S-EPMC12002893 | biostudies-literature | 2025 Jun

REPOSITORIES: biostudies-literature