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September 17, 2025Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition

Predicting treatment outcome and prognosis in locally advanced rectal cancer using pretreatment MRI and pathology based machine learning models

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Authors

LDLuu-Ngoc DoIPIlwoo ParkSHSuk Hee Heo

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Overview

Research demonstrates machine learning effectively predicts treatment outcomes in rectal cancer, indicating a new approach to patient care.

Key Points

  • Proposed machine learning models effectively predict pathologic complete response and recurrence in rectal cancer treatment.
  • Models achieved high performance metrics, emphasizing the reliability of using MRI and pathology data for predictions.
  • Integration of MRI-derived radiomics and pathology information showcases the potential for better treatment outcome predictions.
  • Findings suggest that using machine learning can lead to tailored and timely interventions for rectal cancer patients.

Cite This Study

Do et al. (2025) studied this question.

synapsesocial.com/papers/68d4596631b076d99fa5c1fdhttps://doi.org/10.58530/2025/2675
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Improving prediction of pathological downstaging in rectal cancer using deep learning with preoperative MRI and clinicopathological data2025
  2. 2Machine Learning-Based Algorithms for Enhanced Prediction of Local Recurrence and Metastasis in Low Rectal Adenocarcinoma Using Imaging, Surgical, and Pathological Data2024 · 6 citations
  3. 3Progress of MRI‑based radiomics and deep learning for predicting the prognosis of locally advanced rectal cancer (Review)2025
  4. 4MRI-Based Radiomics and Machine Learning for Predicting Pathological Tumor Invasion and Nodal Status in Rectal Cancer: A Retrospective Study2026
  5. 5<scp>MRI</scp> Based Radiomics as an Imaging Biomarker for Locally Advanced Carcinoma Rectum: Predicting Tumor Response Following Neoadjuvant Chemoradiotherapy as an Organ Preservation Strategy2026