Clinical Decision Biological Biomarker and Prognosis Prediction of Hepatocellular Carcinoma by Deep Learning
NCT ID: NCT05257694
Last Updated: 2022-10-21
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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RECRUITING
1 participants
OBSERVATIONAL
2022-01-01
2025-12-31
Brief Summary
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Detailed Description
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Developing a deep learning model based on CEUS to predict the prognosis of HCC. Developing a deep learning model based on CEUS to choose a better operation (ablation or surgery) of HCC patients.
Then, validating the deep learning model in the prospective data.
Conditions
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Study Design
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COHORT
PROSPECTIVE
Interventions
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Surgery
hepatectomy
Ablation (Microwave ablation or Radiofrequency ablation)
image-guided ablation
Eligibility Criteria
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Inclusion Criteria
* without macro-vascular invasion
* Child-Pugh A/B grade
* HCC is proved by pathological examination or two enhanced imaging
* CEUS (Sonovue or Sonozoid) images are performed two weeks before the operation
* Invasive biomarker or prognosis of HCC available
* CEUS images are included in at least three stages (Arterial phase, Portal phase, and Late phase)
Exclusion Criteria
* patients with co-malignancy
* poor images quality for analyzing
18 Years
ALL
No
Sponsors
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Ping Liang
OTHER
Responsible Party
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Ping Liang
Chief of department of interventional ultrasound
Locations
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Chinese PLA General Hospital
Beijing, Beijing Municipality, China
Countries
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Central Contacts
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Facility Contacts
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Ping Liang, Doctor
Role: primary
Other Identifiers
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S2022-002
Identifier Type: -
Identifier Source: org_study_id
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