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Multi-Institutional MR-Derived Radiomics to Predict Post-Exenteration Disease Recurrence in Patients With T4 Rectal

Niall J O'Sullivan1,2,3, Fariba Tohidinezhad4, Hugo C Temperley1,2

  • 1Department of Radiology, St. James's Hospital, Dublin, Ireland.

Cancer Medicine
|February 19, 2025
PubMed
Summary

This study developed an MRI radiomics nomogram to predict disease recurrence in advanced rectal cancer patients. The model shows promise for improving risk stratification and personalizing treatment strategies.

Keywords:
MRIRadiomicsadvanced rectal canceroncologyrecurrence

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Area of Science:

  • Oncology
  • Radiology
  • Medical Imaging

Background:

  • Advanced rectal cancer poses risks of local recurrence (10%) and distant metastasis (20-30%).
  • Radiomics offers quantitative imaging analysis for predictive clinical models.
  • Predicting recurrence is crucial for optimizing treatment in T4 rectal cancer.

Purpose of the Study:

  • To develop and validate an MRI-based radiomics nomogram.
  • To predict disease recurrence in patients with T4 rectal cancer after neoadjuvant chemoradiotherapy and surgery.
  • To enhance risk stratification and guide personalized treatment.

Main Methods:

  • Retrospective analysis of 55 T4 rectal cancer patients.
  • Extraction of radiomic features from pre-treatment T2-weighted MRI scans.
  • Construction and internal validation (1000 bootstrap samples) of predictive models.

Main Results:

  • Two radiomic signatures identified as strong predictors of recurrence.
  • The best model achieved an optimism-corrected AUC of 0.75, indicating good discriminative ability.
  • Satisfactory calibration and positive net benefit confirmed by decision curve analysis.

Conclusions:

  • An MRI-based radiomics nomogram is a promising tool for predicting recurrence in T4 rectal cancer.
  • The model can aid in risk stratification and personalized treatment planning.
  • Further validation in larger cohorts is necessary to confirm generalizability.