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Artificial intelligence in the diagnosis of cirrhosis and portal hypertension

  • Special Feature: Review Article
  • Imaging-based diagnosis and management of cirrhosis/portal hypertension
  • Published:
Journal of Medical Ultrasonics Aims and scope Submit manuscript

Abstract

Clinically significant portal hypertension is associated with an increased risk of developing gastroesophageal varices and hepatic decompensation. Hepatic venous pressure gradient measurement and esophagogastroduodenoscopy are the gold-standard methods for assessing clinically significant portal hypertension and gastroesophageal varices, respectively. However, invasiveness, cost, and feasibility limit their widespread use, especially if repeated and serial evaluations are required to assess the efficacy of pharmacotherapy. Artificial intelligence describes a range of techniques that allow machines to perform tasks typically thought to require human reasoning and problem-solving skills. Artificial intelligence has made great strides in the field of medicine, and is also involved in portal hypertension diagnosis. Artificial intelligence tools will potentially transform our practice by leveraging massive amounts of data to personalize care to the right patient, in the right amount, at the right time. This review focuses on the recent advances in artificial intelligence for the noninvasive diagnosis of portal hypertension and gastroesophageal varices and monitoring of risk assessment of its complications in clinical practice.

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Authors and Affiliations

  1. CHESS Center, Institute of Portal Hypertension, The First Hospital of Lanzhou University, Lanzhou, China

    Xiaoguo Li, Ning Kang, Xiaolong Qi & Yifei Huang

Authors
  1. Xiaoguo Li
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  2. Ning Kang
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  3. Xiaolong Qi
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  4. Yifei Huang
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Contributions

XQ and YH were responsible for the concept and design of the review. XQ, YH, XL, and NK were responsible for data acquisition and literature research, drafting of the manuscript, critical revision of the manuscript, and final approval of the manuscript.

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Correspondence to Xiaolong Qi or Yifei Huang.

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XQ, YH, XL, and NK declare that they have no conflicts of interest.

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This article does not contain any studies with human or animal subjects performed by any of the authors.

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Li, X., Kang, N., Qi, X. et al. Artificial intelligence in the diagnosis of cirrhosis and portal hypertension. J Med Ultrasonics 49, 371–379 (2022). https://doi.org/10.1007/s10396-021-01153-8

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  • DOI: https://doi.org/10.1007/s10396-021-01153-8

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