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Hepatol Int. 2019 Sep;13(5):546-559. doi: 10.1007/s12072-019-09973-0. Epub 2019 Aug 31.

Radiomics in hepatocellular carcinoma: a quantitative review.

Author information

1
Institut de Recherche Contre les Cancers de l'Appareil Digestif (IRCAD), Strasbourg, France.
2
Institut hospitalo-universitaire (IHU), Institute for Minimally Invasive Hybrid Image-Guided Surgery, Université de Strasbourg, 1 Place de l'Hôpital, 67000, Strasbourg, France.
3
General, Digestive, and Endocrine Surgery, Nouvel Hôpital Civil, Université de Strasbourg, Strasbourg, France.
4
Inserm, U1110, Institut de Recherche sur les Maladies Virales et Hépatiques, Université de Strasbourg, Strasbourg, France.
5
Pôle Hépato-digestif, Hôpitaux Universitaires, Strasbourg, France.
6
Department of Diagnostic Radiology, McGill University, Montreal, Canada.
7
Institut hospitalo-universitaire (IHU), Institute for Minimally Invasive Hybrid Image-Guided Surgery, Université de Strasbourg, 1 Place de l'Hôpital, 67000, Strasbourg, France. benoit.gallix@ihu-strasbourg.eu.
8
Department of Diagnostic Radiology, McGill University, Montreal, Canada. benoit.gallix@ihu-strasbourg.eu.

Abstract

Radiomics is an emerging field which extracts quantitative radiology data from medical images and explores their correlation with clinical outcomes in a non-invasive manner. This review aims to assess whether radiomics is a useful and reproducible method for clinical management of hepatocellular carcinoma (HCC) by reviewing the strengths and weaknesses of current radiomics literature pertaining specifically to HCC. From an initial set of 48 articles recovered through database searches, 23 articles were retained to be included in this review after full screening. Among these 23 studies, 7 used a radiomics approach in magnetic resonance imaging (MRI). Only two studies applied radiomics to positron emission tomography-computed tomography (PET-CT). In the remaining 14 articles, a radiomics analysis was performed on computed tomography (CT). Eight studies dealt with the relationship between biological signatures and imaging findings, and can be classified as radiogenomic studies. For each study included in our review, we computed a Radiomics Quality Score (RQS) as proposed by Lambin et al. We found that the RQS (mean ± standard deviation) was 8.35 ± 5.38 (out of a possible maximum value of 36). Although these scores are fairly low, and radiomics has not yet reached clinical utility in HCC, it is important to underscore the fact that these early studies pave the way for the radiomics field with a focus on HCC. Radiomics is still a very young field, and is far from being mature, but it remains a very promising technology for the future for developing adequate personalized treatment as a non-invasive approach, for complementing or replacing tumor biopsies, as well as for developing novel prognostic biomarkers in HCC patients.

KEYWORDS:

Hepatocellular carcinoma; Radiogenomics; Radiomics; Tumor heterogeneity

PMID:
31473947
DOI:
10.1007/s12072-019-09973-0
[Indexed for MEDLINE]

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