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Deep learning Based on the Fusion of radiomics and pathomics for Heterogeneity Analysis and Prognosis Prediction of liver Cancer: A multicenter study

Deep learning Based on the Fusion of radiomics and pathomics for Heterogeneity Analysis and Prognosis Prediction of liver Cancer: A multicenter study

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600115885
Enrollment
Unknown
Registered
2026-01-03
Start date
2026-01-04
Completion date
Unknown
Last updated
2026-01-05

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Hepatocellular carcinoma (HCC

Interventions

Sponsors

The First Affiliated Hospital of Nanchang University
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: 1.A patient who underwent focal hepatectomy in a tertiary hospital and was pathologically diagnosed with liver cancer; 2. At least one high recurrence risk factor is combined: multiple nodular tumors (>=2), maximum tumor diameter >5cm, accompanied by MVI, accompanied by satellite nodules, combined with large vessel tumor thrombus, poor pathological differentiation (Edmondson grade ? - ?); 3. After hepatectomy, the patient received adjuvant therapy with TKIs combined with ICIs, or did not receive any postoperative adjuvant therapy (except antiviral therapy).

Exclusion criteria

Exclusion criteria: 1.Recurrent liver cancer or pathologically confirmed as a mixed type of liver cancer and intrahepatic cholangiocarcinoma; 2. Combined with extrahepatic metastasis or other malignant tumors; 3. Combined with severe organ failure of the heart, lungs, brain, kidneys, etc. 4. Before the operation, anti-tumor treatment for liver cancer was carried out, including TACE, hepatic artery infusion chemotherapy, targeted therapy, immunotherapy, etc., except for antiviral treatment.

Design outcomes

Primary

MeasureTime frame
Recurrence-free survival (RFS;Overall survival (OS;

Secondary

MeasureTime frame
Treat related adverse events;

Countries

China

Contacts

Public ContactTan Yongming

The First Affiliated Hospital of Nanchang University

627871378@qq.com+86 791 8869 9383

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026