CT-Based Radiomics Signatures for Predicting the Risk Categorization of Thymic Epithelial Tumors.

ABSTRACT:

Objectives

This study aims to assess the performance of radiomics approaches based on 3D computed tomography (CT), clinical and semantic features in predicting the pathological classification of thymic epithelial tumors (TETs).

Methods

A total of 190 patients who underwent surgical resection and had pathologically confirmed TETs were enrolled in this retrospective study. All patients underwent non-contrast-enhanced CT (NECT) scans and contrast-enhanced CT (CECT) scans before treatment. A total of 396 hand-crafted radiomics features of each patient were extracted from the volume of interest in NECT and CECT images. We compared three clinical features and six semantic features (observed radiological traits) between patients with TETs. Two triple-classification radiomics models

SUBMITTER: Liu J 

PROVIDER: S-EPMC7953900 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature