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HCC-MPDS Multimodal Deep Learning Prognostic Model for Resectable HCC
Sponsor: Anhui Provincial Hospital
Summary
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.
Official title: Multimodal Hybrid Deep Learning-based Prognostic Decision System to Guide Adjuvant Therapy in Hepatocellular Carcinoma After Surgical Resection
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
OBSERVATIONAL
Enrollment
555
Start Date
2020-01-01
Completion Date
2026-01-01
Last Updated
2026-07-13
Healthy Volunteers
Not specified
Conditions
Locations (1)
The First Affiliated Hospital of University of Science and Technology of China
Hefei, Anhui, China