A multimodal interpretable deep learning-radiomics framework for predicting lymph node metastasis following neoadjuvant chemoradiotherapy in locally advanced rectal cancer: a multicenter validation study.
A validated AI tool using standard imaging helps surgeons decide which rectal cancer patients need surgery after chemotherapy, moving precision surgery closer to clinic.
A multimodal deep learning-radiomics model combining imaging features was validated across multiple centers for predicting lymph node metastasis in rectal cancer patients after neoadjuvant chemoradiotherapy. The interpretable framework design and multicenter validation represent practical steps toward clinical deployment of AI-assisted surgical decision-making in rectal cancer.
What the study was
- Study design
- Multicenter diagnostic validation study (deep learning-radiomics)
- Population
- Locally advanced rectal cancer patients post-neoadjuvant CRT; multicenter China
- Category
- Diagnostics
- Maturity
- Validated
- Journal
- NPJ precision oncology
Why it surfaced
Multicenter-validated AI imaging tool for treatment-critical surgical decision; interpretability feature is clinically relevant differentiator. Rectal cancer post-CRT LNM prediction has direct surgical impact.
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