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

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

Status
UNKNOWN
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT03917017
Enrollment
100
Registered
2019-04-16
Start date
2019-01-01
Completion date
2024-12-31
Last updated
2022-02-15

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

Conditions

Liver Resection

Keywords

radiomics, Watson artificial intelligence, hepatocellular carcinoma, surgical decisions, prognosis

Brief summary

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

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.

Interventions

DEVICERadiomics and Watson artificial intelligence

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.

Sponsors

Zhujiang Hospital
Lead SponsorOTHER

Study design

Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
TREATMENT
Masking
NONE

Eligibility

Sex/Gender
ALL
Age
18 Years to 80 Years
Healthy volunteers
No

Inclusion criteria

1. 18 years≤ Age ≤80 years 2. Compling with the diagnosis criteria of complex hepatic carcinoma. 3. Primary hepatic carcinoma without intrahepatic or extrahepatic extensive cancer metastasis, the metastatic hepatic carcinoma whose primary focal has been controlled 4. Preoperative liver function is Child - Pugh grade A or B. 5. The patients are volunteered for the study.

Exclusion criteria

1. Patients with mental illness. 2. 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.) 3. The patients refused to take part in the study. 4. There are other co-existed malignant tumors. 5. Benign liver diseases. 6. Indocyanine green allergy

Design outcomes

Primary

MeasureTime frameDescription
Postoperative survival5 yearsSurvival after hepatectomy

Secondary

MeasureTime frameDescription
Disease-free survival5 yearsSurvival time without tumor after HCC resection

Other

MeasureTime frameDescription
Intraoperative blood lossintraoperativeOperative outcome

Countries

China

Contacts

Primary ContactChihua Fang, M.D;Ph.D
fangch_dr@163.com+8613609700805

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026