CT and MRI of pancreatic tumors: an update in the era of radiomics
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INVITED REVIEW
CT and MRI of pancreatic tumors: an update in the era of radiomics Marion Bartoli1 · Maxime Barat1,2 · Anthony Dohan1,2 · Sébastien Gaujoux2,3 · Romain Coriat2,4 · Christine Hoeffel5 · Christophe Cassinotto6 · Guillaume Chassagnon1,2 · Philippe Soyer1,2 Received: 6 October 2020 / Accepted: 8 October 2020 © Japan Radiological Society 2020
Abstract Radiomics is a relatively new approach for image analysis. As a part of radiomics, texture analysis, which consists in extracting a great amount of quantitative data from original images, can be used to identify specific features that can help determining the actual nature of a pancreatic lesion and providing other information such as resectability, tumor grade, tumor response to neoadjuvant therapy or survival after surgery. In this review, the basic of radiomics, recent developments and the results of texture analysis using computed tomography and magnetic resonance imaging in the field of pancreatic tumors are presented. Future applications of radiomics, such as artificial intelligence, are discussed. Keywords Radiomics · Texture analysis · Pancreatic neoplams · Artificial intelligence Abbreviations 2D Two dimensions 3D Three dimensions ACM Angle co-occurrence matrices ADC Apparent diffusion coefficient AIP Auto-immune pancreatitis AUC Area under receiver operating characteristic curve CA Cancer antigen CT Computed tomography DFS Disease-free survival DWI Diffusion-weighted imaging
GLCM Gray-level co-occurrence matrix GLRLM Gray-level run length matrix IPAS Intrapancreatic accessory spleen IPMN Intraductal papillary mucinous neoplasm LASSO Least absolute shrinkage and selection operator MRI Magnetic resonance imaging NEC Neuroendocrine carcinoma NEN Neuroendocrine neoplasm NET Neuroendocrine tumor NGTDM Neighborhood gray-tone difference matrix PDAC Pancreatic ductal adenocarcinoma PET Positron emission tomography
* Philippe Soyer [email protected]
Guillaume Chassagnon [email protected]
Marion Bartoli [email protected]
1
Maxime Barat [email protected]
Department of Radiology, Cochin Hospital, AP-HP, 27 Rue du Faubourg Saint‑Jacques, 75014 Paris, France
2
Université de Paris, Descartes‑Paris 5, F‑75006 Paris, France
3
Department of Abdominal Surgery, Cochin Hospital, AP-HP, 75014 Paris, France
4
Department of Gastroenterology, Cochin Hospital, AP-HP, 75014 Paris, France
5
Department of Radiology, Robert Debré Hospital, 51092 Reims, France
6
Department of Radiology, CHU Montpellier, University of Montpellier, Saint-Éloi Hospital, 34000 Montpellier, France
Anthony Dohan [email protected] Sébastien Gaujoux [email protected] Romain Coriat [email protected] Christine Hoeffel choeffel‑fornes@chu‑reims.fr Christophe Cassinotto c‑cassinotto@chu‑montpellier.fr
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PNEN Pancreatic neuroendocrine neoplasm ROI Region of interest RLM Run-length matrices TA Texture analysis WHO World Health Organization
Introduction The pancreas can
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