What question did this study set out to answer?

This systematic review aims to assess the effectiveness of AI and ML models using MRI to predict pathological complete response in rectal cancer following chemoradiotherapy.

May 8, 2026ANZ Journal of Surgery

Artificial Intelligence Models Using Magnetic Resonance Imaging to Predict Response to Chemoradiotherapy in Rectal Cancer: A Systematic Review

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Authors

WLWinnie LayWestern Health HNHa My Ngoc NguyenRoyal Children's Hospital EEElias El‐BarhounWestern Health

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Implication

Systematic review evaluates AI and ML models predicting pathological complete response in rectal cancer, indicating potential but necessitating improved methodologies.

Key Points

This systematic review aims to assess the effectiveness of AI and ML models using MRI to predict pathological complete response in rectal cancer following chemoradiotherapy.
Conducted a systematic search on Embase, Medline, Cochrane, and Web of Science per PRISMA guidelines.
Included studies utilizing MRI-only AI or ML models for predicting pCR in adults with rectal cancer.
Assessed risk of bias with QUADAS-2 and extracted data independently by two reviewers.
Included 22 studies with 94 predictive models, predominantly retrospective in design.
Most utilized T2-weighted MRI, showing variable protocols and modelling methods, with only five studies performing external validation.
Achieved a median AUC of 0.801, with performance variability from poor (AUC 0.49) to excellent (AUC 0.997).

Cite This Study

Lay et al. (2026) studied this question.

synapsesocial.com/papers/69fd7fcdbfa21ec5bbf0873d https://doi.org/10.1111/ans.70724

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Implication

Systematic review evaluates AI and ML models predicting pathological complete response in rectal cancer, indicating potential but necessitating improved methodologies.

Artificial Intelligence Models Using Magnetic Resonance Imaging to Predict Response to Chemoradiotherapy in Rectal Cancer: A Systematic Review

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Key Points

Cite This Study

Artificial Intelligence Models Using Magnetic Resonance Imaging to Predict Response to Chemoradiotherapy in Rectal Cancer: A Systematic Review

Discussion

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Implication

Key Points

Cite This Study

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