Radiobioinformatics: A novel bridge between basic research and clinical practice for clinical decision support in diffuse liver diseases

Pinggui Lei, Na Hu, Yuhui Wu, Maowen Tang, Chong Lin, Luoyi Kong, Lingfeng Zhang, Peng Luo, Lawrence Wing-Chi Chan

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

Abstract The liver is a multifaceted organ that is responsible for many critical functions encompassing amino acid, carbohydrate, and lipid metabolism, all of which make a healthy liver essential for the human body. Contemporary imaging methodologies have remarkable diagnostic accuracy in discerning focal liver lesions; however, a comprehensive understanding of diffuse liver diseases is a requisite for radiologists to accurately diagnose or predict the progression of such lesions within clinical contexts. Nonetheless, the conventional attributes of radiological features, including morphology, size, margin, density, signal intensity, and echoes, limit their clinical utility. Radiomics is a widely used approach that is characterized by the extraction of copious image features from radiographic depictions, which gives it considerable potential in addressing this limitation. It is worth noting that functional or molecular alterations occur significantly prior to the morphological shifts discernible by imaging modalities. Consequently, the explication of potential mechanisms by multiomics analyses (encompassing genomics, epigenomics, transcriptomics, proteomics, and metabolomics) is essential for investigating putative signal pathway regulations from a radiological viewpoint. In this review, we elaborate on the principal pathological categorizations of diffuse liver diseases, the evaluation of multiomics approaches pertaining to diffuse liver diseases, and the prospective value of predictive models. Accordingly, the overarching objective of this review is to scrutinize the interrelations between radiological features and bioinformatics as well as to consider the development of prediction models predicated on radiobioinformatics as integral components of clinical decision support systems for diffuse liver diseases.
Original languageEnglish
JournaliRADIOLOGY
Volumen/a
Issue numbern/a
DOIs
Publication statusPublished - Jun 2023

Keywords

  • artificial intelligence
  • basic research
  • clinical decision support
  • diffuse liver disease
  • radiobioinformatics

Fingerprint

Dive into the research topics of 'Radiobioinformatics: A novel bridge between basic research and clinical practice for clinical decision support in diffuse liver diseases'. Together they form a unique fingerprint.

Cite this