Lohmann, Philipp ORCID: 0000-0002-5360-046X, Galldiks, Norbert, Kocher, Martin, Heinzel, Alexander, Filss, Christian P., Stegmayr, Carina, Mottaghy, Felix M., Fink, Gereon R. ORCID: 0000-0002-8230-1856, Shah, N. Jon ORCID: 0000-0002-8151-6169 and Langen, Karl-Josef (2021). Radiomics in neuro-oncology: Basics, workflow, and applications. Methods, 188. S. 112 - 122. SAN DIEGO: ACADEMIC PRESS INC ELSEVIER SCIENCE. ISSN 1095-9130

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Abstract

Over the last years, the amount, variety, and complexity of neuroimaging data acquired in patients with brain tumors for routine clinical purposes and the resulting number of imaging parameters have substantially increased. Consequently, a timely and cost-effective evaluation of imaging data is hardly feasible without the support of methods from the field of artificial intelligence (AI). AI can facilitate and shorten various timeconsuming steps in the image processing workflow, e.g., tumor segmentation, thereby optimizing productivity. Besides, the automated and computer-based analysis of imaging data may help to increase data comparability as it is independent of the experience level of the evaluating clinician. Importantly, AI offers the potential to extract new features from the routinely acquired neuroimages of brain tumor patients. In combination with patient data such as survival, molecular markers, or genomics, mathematical models can be generated that allow, for example, the prediction of treatment response or prognosis, as well as the noninvasive assessment of molecular markers. The subdiscipline of AI dealing with the computation, identification, and extraction of image features, as well as the generation of prognostic or predictive mathematical models, is termed radiomics. This review article summarizes the basics, the current workflow, and methods used in radiomics with a focus on feature-based radiomics in neuro-oncology and provides selected examples of its clinical application.

Item Type: Journal Article
Creators:
CreatorsEmailORCIDORCID Put Code
Lohmann, PhilippUNSPECIFIEDorcid.org/0000-0002-5360-046XUNSPECIFIED
Galldiks, NorbertUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Kocher, MartinUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Heinzel, AlexanderUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Filss, Christian P.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Stegmayr, CarinaUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Mottaghy, Felix M.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Fink, Gereon R.UNSPECIFIEDorcid.org/0000-0002-8230-1856UNSPECIFIED
Shah, N. JonUNSPECIFIEDorcid.org/0000-0002-8151-6169UNSPECIFIED
Langen, Karl-JosefUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
URN: urn:nbn:de:hbz:38-598572
DOI: 10.1016/j.ymeth.2020.06.003
Journal or Publication Title: Methods
Volume: 188
Page Range: S. 112 - 122
Date: 2021
Publisher: ACADEMIC PRESS INC ELSEVIER SCIENCE
Place of Publication: SAN DIEGO
ISSN: 1095-9130
Language: English
Faculty: Unspecified
Divisions: Unspecified
Subjects: no entry
Uncontrolled Keywords:
KeywordsLanguage
Biochemical Research Methods; Biochemistry & Molecular BiologyMultiple languages
URI: http://kups.ub.uni-koeln.de/id/eprint/59857

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