AI-Based Prediction of Liver Metastasis in Colorectal Cancer (A Retrospective Study)

Recruiting now

Conditions studied: Colorectal Cancer Liver Metastases (CRLM)

In brief

This multicenter, retrospective study aims to develop and validate a multimodal deep learning model for predicting the risk of metachronous liver metastasis in patients with stage I-III colorectal cancer following curative resection. The model will integrate preoperative contrast-enhanced CT imaging, digitized histopathological whole-slide images, and standard clinical-pathological data. The primary objective is to assess the model's discriminatory performance, measured by the area under the receiver operating characteristic curve (AUC), and to compare its predictive accuracy against traditional prognostic factors such as TNM staging and serum carcinoembryonic antigen levels. This research utilizes existing archival data; no direct patient contact or intervention is involved. The ultimate goal is to provide a robust, data-driven tool for improved risk stratification, which could potentially guide personalized surveillance strategies and adjuvant therapy decisions in the future.

Key facts

Study ID
NCT07399236
Run by
Tongji Hospital
People needed
1500
Starts
2015-01-01
Expected to finish
2026-01-30
Last updated by the study team
2026-02-10

Who can join

Age: 18 and older, up to 75. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

You may not qualify if…

Where it is running

Full record on ClinicalTrials.gov

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