The Evaluation of Surgical Decisions and Prognosis of the Radiomics and Watson Artificial Intelligence in Patients With Hepatocellular Carcinoma

Study Overview
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Brief Summary
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The aim of this study was to evaluate the surgical decisions and prognosis of the radiomics and Watson artificial intelligence in patients with hepatocellular carcinoma.

Detailed Description
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Hepatectomy is an effective treatment for patients with hepatocellular carcinoma, but liver failure after hepatectomy may lead to increased postoperative mortality.Therefore, it is very important to make preoperative surgical decisions, evaluate the safety of the operation and identify which patients are likely to suffer from liver failure.Imaging omics is a newly emerging research method in recent years, which has great potential in cancer diagnosis and treatment, and can monitor treatment and predict the prognosis of patients, so as to better realize accurate diagnosis and treatment of diseases.The artificial intelligence platform developed by IBM Watson for Watson tumor treatment decisions can provide treatment decisions and corresponding theoretical basis to guide surgical decisions based on the key clinical data of liver cancer patients.

Official Title
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The Evaluation of Surgical Decisions and Prognosis of the Radiomics and Watson Artificial Intelligence in Patients With Hepatocellular Carcinoma

Conditions
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Liver Resection

Intervention / Treatment
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* Device: Radiomics and Watson artificial intelligence


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: 18 years≤ Age ≤80 years Compling with the diagnosis criteria of complex hepatic carcinoma. Primary hepatic carcinoma without intrahepatic or extrahepatic extensive cancer metastasis, the metastatic hepatic carcinoma whose primary focal has been controlled Preoperative liver function is Child - Pugh grade A or B. The patients are volunteered for the study. Exclusion Criteria: Patients with mental illness. Patients can't tolerate the operation owe to a variety of basic diseases (such as severe cardiopulmonary insufficiency, renal insufficiency, cachexia and blood system diseases, etc.) The patients refused to take part in the study. There are other co-existed malignant tumors. Benign liver diseases. Indocyanine green allergy

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 80 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Treatment
Intervention Model: Single Group Assignment
Masking: None (Open Label)


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Experimental: Radiomics and Watson artificial intelligence<br> | Device: Radiomics and Watson artificial intelligence<br>* The artificial intelligence platform developed by IBM Watson can provide treatment decisions and corresponding theoretical basis to guide surgical decisions based on the key clinical data of liver cancer patients. The imaging histology can be used to conduct intraoperative navigation surgical resection and treatment monitoring, and established a prognosis model to predict the prognosis of patients by grading the results of postoperative follow-up and microvascular invasion of pathological liver cancer, so as to better achieve accurate diagnosis and treatment of the disease.<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Postoperative survival | Survival after hepatectomy | 5 years | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Disease-free survival | Survival time without tumor after HCC resection | 5 years | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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radiomics, Watson artificial intelligence, hepatocellular carcinoma, surgical decisions, prognosis