An AI Model Based on Smartphone-derived Multimodality Images to Evaluate Portal Hypertension in Patients With Cirrhosis (CHESS2203)

May 30, 2022 updated by: Xiaolong Qi, Hepatopancreatobiliary Surgery Institute of Gansu Province

Portal hypertension contributed to the main complications of liver cirrhosis. Currently, hepatic venous pressure gradient (HVPG) was the reference standard for evaluating portal pressure in patients with cirrhosis. However, the practice of HVPG is limited to require the extensive experience and highly specialized centers. In recent years, non-invasive methods were proposed to predict the degree of cirrhotic portal hypertension. Liver stiffness is currently the most widely used method for noninvasive assessment of portal hypertension. The renewing Baveno VII recommended that liver stiffness ≥ 25 kPa by transient elastography is sufficient to identify clinically significant portal hypertension (specificity and positive predictive value > 90%). Although liver stiffness has a good predictive value for evaluation of clinically significant portal hypertension, it is difficult to apply in primary hospitals due to expensive equipment.

Recently, a multicenter study has shown that artificial intelligence analysis based on ocular images can aid to screening and diagnosis hepatobiliary diseases. The patented technology of collecting and analyzing diagnostic images of Traditional Chinese Medicine (TCM) based on mobile phone terminals has been realized. This technology mainly includes image acquisition, quality control and analysis, and clinical information collection. Liver cirrhosis belongs to the diseases of bulging and accumulation in TCM, and the most common symptoms are the liver and gallbladder damp-heat and liver stagnation and spleen deficiency. The main contents of inspection diagnosis in TCM for liver disease include the images of the tongue, eye and palms. In our study, the patented technology of TCM based on artificial intelligence is applied to establish a precise evaluation model of traditional Chinese and western medicine for portal hypertension with cirrhosis by combining the macroscopic characteristics of images and microscopic pathological indicators.

Study Overview

Status

Recruiting

Conditions

Intervention / Treatment

Detailed Description

Portal hypertension contributed to the main complications of liver cirrhosis. Currently, hepatic venous pressure gradient (HVPG) was the reference standard for evaluating portal pressure in patients with cirrhosis. However, the practice of HVPG is limited to require the extensive experience and highly specialized centers. In recent years, non-invasive methods were proposed to predict the degree of cirrhotic portal hypertension. Liver stiffness is currently the most widely used method for noninvasive assessment of portal hypertension. The renewing Baveno VII recommended that liver stiffness ≥ 25 kPa by transient elastography is sufficient to identify clinically significant portal hypertension (specificity and positive predictive value > 90%). Although liver stiffness has a good predictive value for evaluation of clinically significant portal hypertension, it is difficult to apply in primary hospitals due to expensive equipment.

Recently, a multicenter study has shown that artificial intelligence analysis based on ocular images can aid to screening and diagnosis hepatobiliary diseases. The patented technology of collecting and analyzing diagnostic images of Traditional Chinese Medicine based on mobile phone terminals has been realized. This technology mainly includes image acquisition, quality control and analysis, and clinical information collection. Liver cirrhosis belongs to the diseases of bulging and accumulation in Traditional Chinese Medicine, and the most common symptoms are the liver and gallbladder damp-heat and liver stagnation and spleen deficiency. The main contents of inspection diagnosis in Traditional Chinese Medicine for liver disease include the images of the tongue, eye and palms. In our study, the patented technology of Traditional Chinese Medicine based on artificial intelligence is applied to establish a precise evaluation model of traditional Chinese and western medicine for portal hypertension with cirrhosis by combining the macroscopic characteristics of images and microscopic pathological indicators.

Study Type

Observational

Enrollment (Anticipated)

1000

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Locations

  • China
    • Beijing
      • Beijing, Beijing, China, 1000000
        • Recruiting
        • CHESS
        • Principal Investigator:
          • Xiaolong Qi, Prof
      • Beijing, Beijing, China, 100000
        • Not yet recruiting
        • Institute for TCM-X, MOE Key Laboratory of Bioinformatics/Bioinformatics Division, BNRIST, Department of Automation, Tsinghua University
        • Principal Investigator:
          • Shao Li, Prof

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years to 75 years (ADULT, OLDER_ADULT)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Sampling Method

Probability Sample

Study Population

Patients was fulfilled the diagnosis of cirrhosis based on radiological, histological features of liver cirrhosis and clinical manifestations.

Description

Inclusion Criteria:

  1. age above or equal to 18-year-old;
  2. fulfilled diagnosis of cirrhosis based on radiological, histological features of liver cirrhosis and clinical manifestations;
  3. with HVPG examination in the past 6 months;
  4. applied a patented technology based on mobile phone for collecting and analyzing tongue-eye-palm images
  5. signed informed consent.

Exclusion Criteria:

  1. contradictions for HVPG examination;
  2. accepted primary prevention (non-selective beta blockers or endoscopic variceal ligation);
  3. accepted transjugular intrahepatic portosystemic shunt;
  4. diagnosed as hepatocellular carcinoma.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
Training cohort
Patients were fulfilled diagnosis of cirrhosis based on radiological, histological features of liver cirrhosis and clinical manifestations.
Diagnostic test: Hepatic venous pressure gradient
All patients underwent measurement of HVPG under local anesthesia.
Validation cohort
Patients were fulfilled diagnosis of cirrhosis based on radiological, histological features of liver cirrhosis and clinical manifestations.
Diagnostic test: Hepatic venous pressure gradient
All patients underwent measurement of HVPG under local anesthesia.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Accuracy of the precise evaluation method of traditional Chinese and western medicine for portal hypertension with cirrhosis by combining the macroscopic characteristics of images and microscopic pathological indicators.
Time Frame: 1 year
In HVPG (mmHg) as reference method in evaluating portal pressure measured by intervention specialist, to develop a new traditional Chinese and western medicine method based on the macroscopic characteristics of images and microscopic pathological indicators and evaluate the accuracy in diagnosing portal hypertension.
1 year

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Accuracy of the precise evaluation method of traditional Chinese and western medicine for high risk varices with cirrhosis by combining the macroscopic characteristics of images and microscopic pathological indicators.
Time Frame: 1 year
To assess the precise evaluation method of traditional Chinese and western medicine to avoid unnecessary endoscopies in patients with cirrhosis.
1 year

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Hepatopancreatobiliary Surgery Institute of Gansu Province

Collaborators

LanZhou University
Tsinghua University
The Third People's Hospital of Taiyuan
QuFu People's Hospital
Shenyang Sixth People's Hospital
Hospital of Chengdu Office of People's Government of Tibetan Autonomous Region
Fifth Medical Center of Chinese PLA General Hospital

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (ACTUAL)

May 1, 2022

Primary Completion (ANTICIPATED)

April 30, 2023

Study Completion (ANTICIPATED)

April 30, 2023

Study Registration Dates

First Submitted

May 30, 2022

First Submitted That Met QC Criteria

May 30, 2022

First Posted (ACTUAL)

June 2, 2022

Study Record Updates

Last Update Posted (ACTUAL)

June 2, 2022

Last Update Submitted That Met QC Criteria

May 30, 2022

Last Verified

May 1, 2022

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • CHESS2203

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

UNDECIDED

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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