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

NCT05402410 | Unknown

• 1 other identifier: CHESS2203
• Study Type: observational
• Target: 1,000
• Locations: 1 country
• Sites: 2

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.

Conditions

Portal Hypertension

Keywords

cirrhosis; Traditional Chinese Medicine; artificial intelligence; portal hypertension; hepatic venous pressure gradient

Outcome Measures

Primary Outcomes (1)

• 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 Outcomes (1)

• 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.

  1 year

Study Arms (2)

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

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

Interventions

Hepatic venous pressure gradient DIAGNOSTIC_TEST

All patients underwent measurement of HVPG under local anesthesia.

Training cohort; Validation cohort

Eligibility Criteria

• Age: 18 Years - 75 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

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

You may qualify if:

• 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.

You may not qualify if:

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

Sponsors & Collaborators

• Hepatopancreatobiliary Surgery Institute of Gansu Province: lead
• The Third People's Hospital of Taiyuan: collaborator
• QuFu People's Hospital: collaborator
• Shenyang Sixth People's Hospital: collaborator
• LanZhou University: collaborator
• Hospital of Chengdu Office of People's Government of Tibetan Autonomous Region: collaborator
• Fifth Medical Center of Chinese PLA General Hospital: collaborator
• Tsinghua University: collaborator

Study Sites (2)

CHESS

Beijing, Beijing Municipality, 1000000, China

RECRUITING

Institute for TCM-X, MOE Key Laboratory of Bioinformatics/Bioinformatics Division, BNRIST, Department of Automation, Tsinghua University

Beijing, Beijing Municipality, 100000, China

NOT YET RECRUITING

Related Publications (6)

• 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.

  PMID: 30215362 BACKGROUND

• Garcia-Tsao G, Abraldes JG, Berzigotti A, Bosch J. Portal hypertensive bleeding in cirrhosis: Risk stratification, diagnosis, and management: 2016 practice guidance by the American Association for the study of liver diseases. Hepatology. 2017 Jan;65(1):310-335. doi: 10.1002/hep.28906. Epub 2016 Dec 1. No abstract available.

  PMID: 27786365 BACKGROUND

• Abraldes JG, Bureau C, Stefanescu H, Augustin S, Ney M, Blasco H, Procopet B, Bosch J, Genesca J, Berzigotti A; Anticipate Investigators. Noninvasive tools and risk of clinically significant portal hypertension and varices in compensated cirrhosis: The "Anticipate" study. Hepatology. 2016 Dec;64(6):2173-2184. doi: 10.1002/hep.28824. Epub 2016 Oct 27.

  PMID: 27639071 BACKGROUND

• Pons M, Augustin S, Scheiner B, Guillaume M, Rosselli M, Rodrigues SG, Stefanescu H, Ma MM, Mandorfer M, Mergeay-Fabre M, Procopet B, Schwabl P, Ferlitsch A, Semmler G, Berzigotti A, Tsochatzis E, Bureau C, Reiberger T, Bosch J, Abraldes JG, Genesca J. Noninvasive Diagnosis of Portal Hypertension in Patients With Compensated Advanced Chronic Liver Disease. Am J Gastroenterol. 2021 Apr;116(4):723-732. doi: 10.14309/ajg.0000000000000994.

  PMID: 33982942 BACKGROUND

• 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.

  PMID: 35120736 BACKGROUND

• 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.

  PMID: 33509389 BACKGROUND

MeSH Terms

Conditions

Hypertension, Portal; Fibrosis

Condition Hierarchy (Ancestors)

Liver Diseases; Digestive System Diseases; Pathologic Processes; Pathological Conditions, Signs and Symptoms

Central Study Contacts

Xiaolong Qi, M.D.

CONTACT

+8618588602600; qixiaolong@vip.163.com

Chuan Liu, MD

CONTACT

+8615626415443; 845424585@qq.com

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Prof.

Study Record Dates

• First Submitted: May 30, 2022
• First Posted: June 2, 2022
• Study Start: May 1, 2022
• Primary Completion: April 30, 2023
• Study Completion: April 30, 2023
• Last Updated: June 2, 2022

Record last verified: 2022-05

Locations

CN (2)