Deep learning based on MRI for assessing the prognostic value of lateral lymph nodes in rectal cancer.

ABSTRACT:

Objectives

Accurate preoperative evaluation of positive lateral lymph node (LLN) is crucial for optimizing treatment strategies in rectal cancer. Traditional methods, such as MRI T2-weighted imaging (T2WI), face limitations like interobserver variability and difficulty detecting small or occult metastases. Deep learning (DL) may provide a more efficient and precise alternative.

Methods

In this multicenter, retrospective study, images from 1,000 patients across five centers were annotated to train a DL model for identifying and segmenting LLN. The model was tested on images from 480 patients in a validation cohort. Kaplan-Meier analysis compared disease-free survival (DFS) and overall survival (OS) between LLN-positive and LLN-negative groups, while Cox regression identified

SUBMITTER: Qiao G 

PROVIDER: S-EPMC12643854 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature