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Related Experiment Video

Updated: Jul 15, 2026

Advanced Animal Model of Colorectal Metastasis in Liver: Imaging Techniques and Properties of Metastatic Clones

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Published on: November 30, 2016

Habitat Radiomics Based on MRI for Predicting Metachronous Liver Metastasis in Locally Advanced Rectal Cancer: a

Shengming Shi¹, Tao Jiang², Han Liu¹

¹Department of Magnetic resonance imaging diagnostic, The Second Affiliated Hospital of Harbin Medical University, No. 246, Xuefu Road, Nangang, Harbin 150086, China.

Academic Radiology

|April 9, 2025

Summary

Magnetic resonance imaging (MRI) habitat radiomics effectively predicts metachronous liver metastasis (MLM) in locally advanced rectal cancer (LARC) patients. An integrated nomogram significantly enhances predictive accuracy for better patient outcomes.

Keywords:

Habitat Locally advanced rectal cancer Metachronous liver metastasis Nomogram Radiomics

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Area of Science:

Oncology
Radiology
Medical Imaging

Background:

Locally advanced rectal cancer (LARC) poses a risk of metachronous liver metastasis (MLM).
Accurate prediction of MLM is crucial for timely treatment adjustments and improved patient management.

Purpose of the Study:

To evaluate the feasibility of using magnetic resonance imaging (MRI)-based habitat radiomics for predicting MLM in LARC patients.
To develop and validate an integrated nomogram combining radiomics and clinical factors for enhanced MLM prediction.

Main Methods:

Retrospective analysis of 385 LARC patients from two centers.
Application of K-means clustering on T2-weighted MRI images for habitat radiomics feature extraction.
Development of radiomics models using machine learning algorithms and an integrated nomogram incorporating clinical predictors.
Performance evaluation using Area Under the Curve (AUC), calibration curves, and Decision Curve Analysis (DCA).

Main Results:

Habitat radiomics models demonstrated high predictive performance for MLM.
The integrated nomogram achieved superior AUCs (0.959 training, 0.925 internal validation, 0.889 external validation) compared to single models.
DCA and calibration analysis confirmed the nomogram's clinical utility and accuracy.

Conclusions:

MRI-based habitat radiomics is a feasible and effective tool for predicting MLM in LARC.
The integrated nomogram offers optimal predictive performance and significantly improves accuracy in identifying patients at risk of liver metastasis.