Work

Artificial Intelligence Applications in the Diagnosis and Management of Cirrhosis and Portal Hypertension: A Narrative Review

Year: 2025

Type: review

Abstract: Cirrhosis and portal hypertension remain major challenges in interventional radiology, with current diagnostic and therapeutic approaches limited by requiring invasive assessment, variability inherent to imaging modalities, and suboptimal risk stratification. For instance, traditional risk scoring systems, such as the Model for End-Stage Liver Disease, are not sufficient to predict complications after interventions such as transjugular intrahepatic portosystemic shunt (TIPS) insertion. Similarly, imaging via Doppler ultrasound, computed tomography, and magnetic resonance imaging provide valuable insights but suffer from operator dependence, inconsistent sensitivity, and accessibility constraints. This narrative review summarizes the current state of the art with regard to leveraging artificial intelligence (AI) to diagnose and predict outcomes in patients with cirrhosis or portal hypertension as well as to optimize outcomes in patients undergoing TIPS placement for the treatment of these conditions. The implementation of AI into clinical practice could potentially significantly transform the treatment of cirrhosis and portal hypertension by optimizing diagnostic accuracy, procedural safety, and long-term outcomes.

Source: Techniques in vascular and interventional radiology

DOI: 10.1016/j.tvir.2025.101078

Authors: Amrit Khooblall, Satish E. Viswanath, Layth Khawaja, Sameer Gadani

Institutions: Cleveland Clinic, Louis Stokes Cleveland VA Medical Center, Case Western Reserve University, Northeast Ohio Medical University, Cleveland Clinic Research

Language: English

Topic: Liver Disease and Transplantation

Subfield: Hepatology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $3,450