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

Study Overview
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Brief Summary
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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.

Detailed Description
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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.

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

Conditions
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Portal Hypertension

Intervention / Treatment
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* Diagnostic Test: Hepatic venous pressure gradient


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: age above or equal to 18-year-old; fulfilled diagnosis of cirrhosis based on radiological, histological features of liver cirrhosis and clinical manifestations; with HVPG examination in the past 6 months; applied a patented technology based on mobile phone for collecting and analyzing tongue-eye-palm images signed informed consent. Exclusion Criteria: contradictions for HVPG examination; accepted primary prevention (non-selective beta blockers or endoscopic variceal ligation); accepted transjugular intrahepatic portosystemic shunt; diagnosed as hepatocellular carcinoma.

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 75 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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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Training cohort<br>Patients were fulfilled diagnosis of cirrhosis based on radiological, histological features of liver cirrhosis and clinical manifestations. | Diagnostic Test: Hepatic venous pressure gradient<br>* All patients underwent measurement of HVPG under local anesthesia.<br>|
| Validation cohort<br>Patients were fulfilled diagnosis of cirrhosis based on radiological, histological features of liver cirrhosis and clinical manifestations. | Diagnostic Test: Hepatic venous pressure gradient<br>* All patients underwent measurement of HVPG under local anesthesia.<br>|

What is the study measuring?
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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. | 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. | To assess the precise evaluation method of traditional Chinese and western medicine to avoid unnecessary endoscopies in patients with cirrhosis. | 1 year | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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cirrhosis, Traditional Chinese Medicine, artificial intelligence, portal hypertension, hepatic venous pressure gradient