Clinical trial NCT05402410: An AI Model Based on Smartphone-derived Multimodality Images to Evaluate Portal Hypertension in Patients With Cirrhosis (CHESS2203)
Official title: An AI Model Based on Smartphone-derived Multimodality Images to Evaluate Portal Hypertension in Patients With Cirrhosis (CHESS2203)
Study type: OBSERVATIONAL
Overall status: UNKNOWN
Conditions: Portal Hypertension
Keywords: cirrhosis
Traditional Chinese Medicine
artificial intelligence
portal hypertension
hepatic venous pressure gradient
Lead sponsor: Hepatopancreatobiliary Surgery Institute of Gansu Province
Sponsor class: OTHER
Collaborators: name: The Third People's Hospital of Taiyuan
name: QuFu People's Hospital
name: Shenyang Sixth People's Hospital
name: LanZhou University
name: Hospital of Chengdu Office of People's Government of Tibetan Autonomous Region
name: Fifth Medical Center of Chinese PLA General Hospital
name: Tsinghua University
First posted: 2022-06-02
Enrollment: 1000
Sex: ALL
Minimum age (years): 18
Maximum age (years): 75
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: RETROSPECTIVE
Sampling method: PROBABILITY_SAMPLE
Study population: Patients was fulfilled the diagnosis of cirrhosis based on radiological, histological features of liver cirrhosis and clinical manifestations.

Brief summary: 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: 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.

Eligibility criteria: 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.

Primary outcomes:
measure: 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.
timeFrame: 1 year
Secondary outcomes:
measure: 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.
timeFrame: 1 year
Other outcomes:
Locations:
city: Beijing
country: China
facility: CHESS
state: Beijing
city: Beijing
country: China
facility: Institute for TCM-X, MOE Key Laboratory of Bioinformatics/Bioinformatics Division, BNRIST, Department of Automation, Tsinghua University
state: Beijing
Study officials:
References:
citation: Qi X, Berzigotti A, Cardenas A, Sarin SK. Emerging non-invasive approaches for diagnosis and monitoring of portal hypertension. Lancet Gastroenterol Hepatol. 2018 Oct;3(10):708-719. doi: 10.1016/S2468-1253(18)30232-2.
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citation: de Franchis R, Bosch J, Garcia-Tsao G, Reiberger T, Ripoll C; Baveno VII Faculty. Baveno VII - Renewing consensus in portal hypertension. J Hepatol. 2022 Apr;76(4):959-974. doi: 10.1016/j.jhep.2021.12.022. Epub 2021 Dec 30.
citation: Xiao W, Huang X, Wang JH, Lin DR, Zhu Y, Chen C, Yang YH, Xiao J, Zhao LQ, Li JO, Cheung CY, Mise Y, Guo ZY, Du YF, Chen BB, Hu JX, Zhang K, Lin XS, Wen W, Liu YZ, Chen WR, Zhong YS, Lin HT. Screening and identifying hepatobiliary diseases through deep learning using ocular images: a prospective, multicentre study. Lancet Digit Health. 2021 Feb;3(2):e88-e97. doi: 10.1016/S2589-7500(20)30288-0.