HCC-MPDS Multimodal Deep Learning Prognostic Model for Resectable HCC

Brief summary (registry, in English)

This is a completed multi-center retrospective observational study focusing on patients who received curative surgical resection for hepatocellular carcinoma (HCC). We collected anonymized historical clinical data, preoperative gadoxetic acid-enhanced MRI scans and digital pathological whole-slide images from three Chinese medical centers and the public TCGA-LIHC database. We developed a multimodal hybrid deep learning prognostic model (named HCC-MPDS) integrating multi-source medical data to stratify HCC patients into high-risk and low-risk recurrence groups after surgery. The primary goal of this study is to compare postoperative recurrence-free survival (RFS) and overall survival (OS) between the two risk subgroups, and evaluate whether this artificial intelligence prediction system can help clinicians identify patients who may benefit from postoperative adjuvant therapy. No new experimental drugs or interventional treatments were provided to participants; all data were retrospectively extracted from archived medical records under institutional ethics approval, with waived written informed consent for de-identified historical samples and images.

What you commit to

• Study type: Observational
• Participants enrolled: 555
• From 1 Jan 2020 to the primary completion date, 31 Dec 2024
• 1 site in 1 country
• Visits and tests: ask the trial team, the registry does not list them

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Who the study is looking for

Age in the registry: 18 years to - · Sex: All

Full criteria on ClinicalTrials.gov

Sites (1)

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