Prediction of Significant Liver Fibrosis (PSLF)
Multimodal Digital Image Fusion Technology Based on Deep Learning to Predict Significant Liver Fibrosis and Its Application in Multi-center Research
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
Study Type
Study Type
Enrollment (Estimated)
Enrollment
Contacts and Locations
Study Contact
Study Contact
- Name: Haijun Huang
- Phone Number: 13758186635
- Email: huanghaijun0826@163.com
Study Locations
-
-
Zhejiang
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Hangzhou, Zhejiang, China, 310014
- Recruiting
- Haijun Huang
-
Contact:
- Haijun Huang
- Phone Number: 13758186635
- Email: huanghaijun0826@163.com
-
-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- Age of 18-60 years old
- The diagnosis of chronic hepatitis B is in line with the diagnostic criteria of China's 2019 Chronic Hepatitis B Prevention and Treatment Guidelines, and the diagnosis of non-alcoholic fatty liver is in line with the Asian Pacific Hepatology Association guidelines
- Imaging showed no liver cancer
Exclusion Criteria:
- There are contraindications for liver biopsy
- Liver pathology did not meet the criteria
Study Plan
How is the study designed?
Design Details
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
|---|
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mild fibrosis
S0-1
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significant liver fibrosis
S2
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Advanced liver fibrosis
S3-4
|
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Model development
Time Frame: 2024.6-2024.12
|
Imaging (such as CT scan, MRI, X-ray, etc.) features and clinical parameters of patients were extracted, including population baseline characteristics (such as age, gender, comorbiditions, etc.), blood biochemical indicators (such as blood glucose, lipids, liver function indicators, etc.), and blood cytology indicators (such as white blood cell count, red blood cell count, etc.).
Completed case selection and cohort establishment, multi-modal feature extraction and model development
|
2024.6-2024.12
|
Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Build a multi-modal big data liver fibrosis early warning cloud platform system
Time Frame: 2025.1-2025.12
|
We intend to design a cloud platform with data storage, processing and analysis components.Select the appropriate technology stack to ensure that the platform has the ability to handle large-scale data, and has good scalability and performance.The previously built multimodal liver fibrosis precision typing model was then embedded into the platform, ensuring that the model could handle a variety of data types and integrate seamlessly with other components of the platform.At the same time, the stream processing technology is used to integrate the real-time monitoring and analysis function of the platform, so as to make rapid prediction and classification of the newly acquired liver fibrosis case data.The accuracy and stability of the model were further verified in the multi-center clinical data, and the multi-modal big data liver fibrosis early warning cloud platform system was built
|
2025.1-2025.12
|
Other Outcome Measures
Other Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Evaluation Multi-modal big data liver fibrosis warning platform system effectiveness
Time Frame: 2026.1-2026.12
|
To test the effectiveness of the multi-modal big data liver fibrosis warning platform system in a real multi-center clinical environment.
We will also explore the possibility of using the platform for long-term follow-up of patients, remote testing of patients and regular assessment of disease progression
|
2026.1-2026.12
|
Collaborators and Investigators
Sponsor
Sponsor
Collaborators
Collaborators
Study record dates
Study Major Dates
Study Start (Estimated)
Study Start
Primary Completion (Estimated)
Primary Completion
Study Completion (Estimated)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- KY2024072
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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