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Construction and Clinical Validation of a Predictive Model for Postoperative Adjuvant Therapy in Hepatocellular Carcinoma Based on Whole-Slide Digital Pathological Images and Deep Learning

Recruitingn/aAges 18 Years - anyAllSecond Affiliated Hospital, Zhejiang University, …
NCT07417800 on ClinicalTrials.gov ↗
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In plain words

What the trial is, and whether it could suit you

Hepatocellular carcinoma (HCC) is a high-mortality global malignancy with a heavy disease burden in China. Although curative surgical resection improves survival for early-stage HCC patients, the 5-year postoperative recurrence rate remains as high as 50%-70%. Postoperative adjuvant TACE and systemic TKIs are standard treatments for high-risk HCC, yet both therapies have prominent drawbacks, including limited response rates, unavoidable toxicities, and inconsistent clinical benefits. Current treatment decisions rely on conventional clinical and pathological features without precise biomarkers, leading to inadequate individualized therapy and wasted medical resources. Tumor immune microenvironment and multimodal imaging-pathological features critically determine HCC treatment sensitivity. Artificial intelligence and deep learning based on preoperative radiomics and postoperative H\&E who

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📋 Eligibility rules (as published)
Inclusion Criteria: * Histopathologically confirmed hepatocellular carcinoma; * Aged more than 18 years; * Underwent radical resection of primary liver cancer (R0 resection); * Availability of postoperative H\&E-stained paraffin embedded tissue sections suitable for digital whole-slide imaging; * Had complete and accessible clinicopathological data and follow-up data; * Has complete and evaluable preoperative and postoperative contrast-enhanced CT or MRI imaging with standardized scanning parameters and no severe artifacts, meeting the quality requirements for radiomic and artificial intelligence analysis. Exclusion Criteria: * Significant missing clinical or follow-up data; * Concurrent primary malignancy in other organs; * Positive surgical margin (R1 or R2 resection); * Tissue sections of poor quality (e.g., severe fading, folding, damage) unsuitable for digital scanning or analysis;
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What it tests

  • AI adjuvant therapy
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Where

1 site
the Second Affiliated Hospital Zhejiang University School of Medicine
Hangzhou, China
🤝 Taking part is your choice, and you can leave at any time. Only the trial team can confirm you are eligible — always decide together with your own doctor.
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