Role of radiomics in predicting lung cancer spread through air spaces in a heterogeneous dataset.

ABSTRACT:

Background

Spread through air spaces (STAS) has been reported as a negative prognostic factor in patients with lung cancer undergoing sublobar resection. Radiomics has been recently proposed to predict STAS using preoperative computed tomography (CT). However, limitations of previous studies included the strict selection of imaging acquisition protocols, leading to results hardly applicable to daily clinical practice. The aim of this study is to test a radiomics-based prediction model of STAS in a practice-based dataset.

Methods

A training cohort of 99 consecutive patients (65 STAS+ and 34 STAS-) with resected lung adenocarcinoma (ADC) was retrospectively collected. Preoperative CT images were collected from different centers regardless model and scanner manufacture, acquisi

SUBMITTER: Bassi M 

PROVIDER: S-EPMC9073736 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature