Prediction of Non-Response to Neoadjuvant Chemoradiotherapy in Esophageal Cancer Patients with ¹⁸F-FDG PET Radiomics Based Machine Learning Classification.

ABSTRACT:

Background

Approximately 26% of esophageal cancer (EC) patients do not respond to neoadjuvant chemoradiotherapy (nCRT), emphasizing the need for pre-treatment selection. The aim of this study was to predict non-response using a radiomic model on baseline ¹⁸F-FDG PET.

Methods

Retrospectively, 143 ¹⁸F-FDG PET radiomic features were extracted from 199 EC patients (T1N1-3M0/T2-4aN0-3M0) treated between 2009 and 2019. Non-response (n = 57; 29%) was defined as Mandard Tumor Regression Grade 4-5 (n = 44; 22%) or interval progression (n = 13; 7%). Randomly, 139 patients (70%) were allocated to explore all combinations of 24 feature selection strategies and 6 classification methods towards the cross-validated average precision (AP). The pred

SUBMITTER: Beukinga RJ 

PROVIDER: S-EPMC9139915 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature