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      The Emerging Role of Radiomics in COPD and Lung Cancer

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          Abstract

          Medical imaging plays a key role in evaluating and monitoring lung diseases such as chronic obstructive pulmonary disease (COPD) and lung cancer. The application of artificial intelligence in medical imaging has transformed medical images into mineable data, by extracting and correlating quantitative imaging features with patients' outcomes and tumor phenotype − a process termed radiomics. While this process has already been widely researched in lung oncology, the evaluation of COPD in this fashion remains in its infancy. Here we outline the main applications of radiomics in lung cancer and briefly review the workflow from image acquisition to the evaluation of model performance. Finally, we discuss the current assessments of COPD and the potential application of radiomics in COPD.

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          Author and article information

          Journal
          Respiration
          Respiration
          RES
          Respiration
          S. Karger AG (Allschwilerstrasse 10, P.O. Box · Postfach · Case postale, CH–4009, Basel, Switzerland · Schweiz · Suisse, Phone: +41 61 306 11 11, Fax: +41 61 306 12 34, karger@karger.com )
          0025-7931
          1423-0356
          February 2020
          28 January 2020
          28 January 2020
          : 99
          : 2
          : 99-107
          Affiliations
          [1] aThe D-Lab, Department of Precision Medicine, GROW − School for Oncology and Developmental Biology, Maastricht University, Maastricht, The Netherlands
          [2] bDepartment of Diagnostic Radiology, Faculty of Applied Medical Sciences, Jazan University, Jazan, Saudi Arabia
          [3] cDepartment of Radiology and Nuclear Medicine, GROW − School for Oncology and Developmental Biology, Maastricht University Medical Centre+, Maastricht, The Netherlands
          [4] dDivision of Nuclear Medicine and Oncological Imaging, Department of Medical Physics, Centre Hospitalier Universitaire de Liège, Liège, Belgium
          [5] eDepartment of Nuclear Medicine and Comprehensive Diagnostic Center Aachen (CDCA), University Hospital RWTH Aachen University, Aachen, Germany
          [6] fDepartment of Pulmonary Diseases, GROW − School for Oncology and Developmental Biology, Maastricht University, Maastricht, The Netherlands
          [7] gDepartment of Thoracic Oncology, IRCCS Foundation National Cancer Institute, Milan, Italy
          Author notes
          *Turkey Refaee, The D-Lab, Department of Precision Medicine, GROW − School for Oncology and Developmental Biology, Maastricht University, NL–6229 ER, Universiteitssingel 40, Maastricht (The Netherlands), E-Mail t.refaee@ 123456maastrichtuniversity.nl
          Article
          PMC7949220 PMC7949220 7949220 res-0099-0099
          10.1159/000505429
          7949220
          31991420
          a71fc345-ab69-458b-b876-c4e5aae15a32
          Copyright © 2020 by S. Karger AG, Basel
          History
          : 30 September 2019
          : 12 December 2019
          : 2020
          Page count
          Figures: 2, References: 95, Pages: 9
          Categories
          Thematic Review Series

          Chronic obstructive pulmonary disease,Lung cancer,Radiomics

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