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Review
. 2020 Oct 7;12(10):2881.
doi: 10.3390/cancers12102881.

Radiomics of Liver Metastases: A Systematic Review

Francesco Fiz  1 , Luca Viganò  2   3 , Nicolò Gennaro  3   4 , Guido Costa  2 , Ludovico La Bella  3 , Alexandra Boichuk  3 , Lara Cavinato  5 , Martina Sollini  1   3 , Letterio S Politi  3   4 , Arturo Chiti  1   3 , Guido Torzilli  2   3
Affiliations
Review

Radiomics of Liver Metastases: A Systematic Review

Francesco Fiz et al. Cancers (Basel). .

Abstract

Multidisciplinary management of patients with liver metastases (LM) requires a precision medicine approach, based on adequate profiling of tumor biology and robust biomarkers. Radiomics, defined as the high-throughput identification, analysis, and translational applications of radiological textural features, could fulfill this need. The present review aims to elucidate the contribution of radiomic analyses to the management of patients with LM. We performed a systematic review of the literature through the most relevant databases and web sources. English language original articles published before June 2020 and concerning radiomics of LM extracted from CT, MRI, or PET-CT were considered. Thirty-two papers were identified. Baseline higher entropy and lower homogeneity of LM were associated with better survival and higher chemotherapy response rates. A decrease in entropy and an increase in homogeneity after chemotherapy correlated with radiological tumor response. Entropy and homogeneity were also highly predictive of tumor regression grade. In comparison with RECIST criteria, radiomic features provided an earlier prediction of response to chemotherapy. Lastly, texture analyses could differentiate LM from other liver tumors. The commonest limitations of studies were small sample size, retrospective design, lack of validation datasets, and unavailability of univocal cut-off values of radiomic features. In conclusion, radiomics can potentially contribute to the precision medicine approach to patients with LM, but interdisciplinarity, standardization, and adequate software tools are needed to translate the anticipated potentialities into clinical practice.

Keywords: computer-assisted diagnosis; gray level matrices; liver metastases; overall and recurrence-free survival; radiomics; response to chemotherapy; texture analysis.

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Conflict of interest statement

A.C. received speaker's honoraria from the following companies: Advanced Accelerator Applications, General Electric Healthcare, Sirtex Medical Europe, AmGen Europe, travel grants form General Electric Healthcare and Sirtex Medical Europe; he is a member of Blue Earth Diagnostics' and Advanced Accelerator Applications' advisory boards and received scientific support, in terms of a three-year Ph.D. fellowship, from the Sanofi Genzyme. F.F. acts as a consultant for the MSD Sharp & Dohme GmbH (LLC). All remaining authors have declared no conflicts of interest.

Figures

Figure 1
Figure 1
PRISMA Flowchart of study selection.
Figure 2
Figure 2
Outline of the selected studies organization. CRC: colorectal cancer, GLSZM: gray level size zone matrices, GLCM: gray level co-occurrence matrices, GLRLM: gray-level run-length matrices.
Figure 3
Figure 3
Present and potential future contribution of radiomics to clinical practice.
See this image and copyright information in PMC

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