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Radiomics for the Diagnosis and Differentiation of Pancreatic Cystic Lesions.

Authors
  • Machicado, Jorge D1
  • Koay, Eugene J2
  • Krishna, Somashekar G3
  • 1 Division of Gastroenterology and Hepatology, Mayo Clinic Heath System, Eau Claire, WI 54703, USA.
  • 2 Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
  • 3 Division of Gastroenterology, Hepatology and Nutrition, The Ohio State University Wexner Medical Center, Columbus, OH 43210, USA.
Type
Published Article
Journal
Diagnostics
Publisher
MDPI AG
Publication Date
Jul 21, 2020
Volume
10
Issue
7
Identifiers
DOI: 10.3390/diagnostics10070505
PMID: 32708348
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

Radiomics, also known as quantitative imaging or texture analysis, involves extracting a large number of features traditionally unmeasured in conventional radiological cross-sectional images and converting them into mathematical models. This review describes this approach and its use in the evaluation of pancreatic cystic lesions (PCLs). This discipline has the potential of more accurately assessing, classifying, risk stratifying, and guiding the management of PCLs. Existing studies have provided important insight into the role of radiomics in managing PCLs. Although these studies are limited by the use of retrospective design, single center data, and small sample sizes, radiomic features in combination with clinical data appear to be superior to the current standard of care in differentiating cyst type and in identifying mucinous PCLs with high-grade dysplasia. Combining radiomic features with other novel endoscopic diagnostics, including cyst fluid molecular analysis and confocal endomicroscopy, can potentially optimize the predictive accuracy of these models. There is a need for multicenter prospective studies to elucidate the role of radiomics in the management of PCLs.

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