Leveraging Artificial Intelligence and Radiomics for Improved Nasopharyngeal Carcinoma Prognostication.

ABSTRACT:

Introduction

Nasopharyngeal carcinoma (NPC) typically presents as advanced disease due to the lack of significant symptoms in the early stages. Accurate prognostication is therefore challenging as current methods based on anatomical staging often lack the granularity to differentiate between patients with differing prognoses. This study investigates the potential of radiomics to improve the prediction of locoregional recurrence (LRR) and overall survival in patients with NPC.

Methods

Radiomic features were extracted from radiotherapy planning CT scans for 294 NPC patients divided into training (n = 147) and validation (n = 147) sets. A feature selection step utilising feature clustering and mutual information classifier to select six key radiomic features was employed to red

SUBMITTER: Shannon NB 

PROVIDER: S-EPMC11921138 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature