MINI REVIEW article
Front. Med.
Sec. Hepatobiliary Diseases
Liver biopsy in the modern era: from traditional techniques to artificial intelligence and multi-omics integration
Provisionally accepted- College of Medicine and Health Science, Sultan Qaboos University, Muscat, Oman
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Liver biopsy remains a cornerstone in the diagnosis and management of various hepatic disorders. This mini-review provides a concise overview of traditional liver biopsy techniques, percutaneous, plugged, transjugular, and laparoscopic, highlighting their clinical indications, histopathological evaluation, and limitations. The review also explores recent advancements, including the integration of artificial intelligence in imaging modalities such as ultrasound, MRI, and CT, as well as its emerging role in histopathological analysis, particularly for assessing fibrosis, steatosis, inflammation, and cancer. In parallel, the application of multi-omics technologies is discussed as a promising complement to histology, offering molecular-level insights into disease progression and therapeutic response. Despite these technological steps, there remains a gap in the literature regarding how traditional biopsy methods are being effectively integrated with these emerging tools, and how liver biopsy continues to retain its clinical relevance in the era of artificial intelligence and multi-omics approaches. This review underscores the evolving landscape of liver biopsy and calls for harmonized frameworks that combine conventional techniques with digital innovations to enhance diagnostic accuracy, standardization, and patient care.
Keywords: liver biopsy, artificial intelligence, multi-omics, Hepatology, digital pathology, Histological quantification
Received: 03 Aug 2025; Accepted: 11 Nov 2025.
Copyright: © 2025 Alwahaibi and Alwahaibi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Nasar Alwahaibi, nasar@squ.edu.om
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
