A Digital Tongue Diagnosis Model for High- and Low-risk Esophagogastroduodenal Varices in Cirrhosis

Summary

The aim of this observational study is to establish an AI deep learning model that can dianosie high-risk varices for patients with cirrhosis effeciently.

The main question of this study is to esplore:

question 1: Developing a digital tongue diagnosis model, specifically a deep learning model to diagnose high-risk esophageal and gastric varices (HRV) associated with cirrhosis using sublingual vein images. Answering the question of whether the new tongue diagnosis method can accurately diagnose.

Question 2: Compare the diagnostic efficacy digital tongue diagnosis model with diagnostic models constructed using other biochemical indicators for HRV in cirrhosis, and answer the question of "how to use it optimally."

Question 3: Exploring the correlation between sublingual vein characteristics and Hepatic venous pressure gradient (HVPG).

Question 4: Compared with endoscopic examination results, validate the diagnostic performance of the model (AUC ≥ 0.90) and screen for key parameters of sublingual vein characteristics (such as sublingual vein varicosity diameter, vein length, color, etc.).

Question 5: Follow-up tongue examination images of patients with cirrhosis who underwent treatment (e.g., endoscopy, splenic embolization, TIPS, etc.) at 1, 2, and 3 years post-treatment were evaluated to assess the efficacy of digital tongue examination models in predicting high-risk esophageal and gastric variceal bleeding at 1, 2, and 3 years post-treatment, as well as the efficacy in predicting endoscopic treatment failure rates and patient mortality associated with bleeding.

Conditions

• Esophageal Varices
• Liver Cirrhosis
• Sublingual Varices
• Portal Hypertension

Interventions

DIAGNOSTIC_TEST

tongue diagnosis

The tongue image of participants will be collected via camera, and tongue images will be used for AI deep model learning analysis.

Sponsors & Collaborators

• Shanghai Changzheng Hospital

  collaborator OTHER

• Shanghai East Hospital of Tongji University

  collaborator OTHER

• Eighth Affiliated Hospital, Sun Yat-sen University

  collaborator OTHER

• Meng Chao Hepatobiliary Hospital of Fujian Medical University

  collaborator OTHER

• Tianjin Medical University General Hospital

  collaborator OTHER

• Army Medical Center of PLA

  collaborator OTHER_GOV

• Shandong Provincial Hospital

  collaborator OTHER_GOV

• Qianfoshan Hospital

  collaborator OTHER

• Shandong Public Health Clinical Center

  collaborator OTHER_GOV

• The 960th Hospital of the PLA Joint Logistics Support Force

  collaborator UNKNOWN

• Jinan Central Hospital

  collaborator OTHER

• Weifang People's Hospital

  collaborator OTHER

• Liaocheng People's Hospital

  collaborator OTHER

• The Second Affiliated Hospital of Shandong First Medical University

  collaborator OTHER

• Jining First People's Hospital

  collaborator OTHER

• Qilu Hospital of Shandong University

  lead OTHER

Principal Investigators

• Yanjing Gao, PhD MD · Qilu Hospital of Shandong University

Eligibility

Min Age

18 Years

Max Age

75 Years

Sex

ALL

Healthy Volunteers

No

Timeline & Regulatory

Start

2023-07-01

Primary Completion

2029-10-31

Completion

2029-12-31

Countries

• China

Study Locations