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HCC-MPDS Multimodal Deep Learning Prognostic Model for Resectable HCC

NCT07700082 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 555

Last updated 2026-07-13

No results posted yet for this study

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.

Conditions

  • Hepatocellular Carcinoma (HCC)

Sponsors & Collaborators

  • Anhui Provincial Hospital

    lead OTHER_GOV

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2020-01-01
Primary Completion
2024-12-31
Completion
2026-01-01

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07700082 on ClinicalTrials.gov