Journal Article

FZJ-2020-02275

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Radiomics in neuro-oncology: Basics, workflow, and applications

Lohmann, P. (Corresponding author)FZJ* ; Galldiks, N.FZJ* ; Kocher, M.FZJ* ; Heinzel, A.FZJ* ; Filss, C. P.FZJ* ; Stegmayr, C.FZJ* ; Mottaghy, F. M.FZJ* ; Fink, G. R.FZJ* ; Shah, N. J.FZJ* ; Langen, K.-J.FZJ*

2021
Academic Press Orlando, Fla.

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Please use a persistent id in citations: http://hdl.handle.net/2128/27387  doi:10.1016/j.ymeth.2020.06.003

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 time-consuming 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.

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Contributing Institute(s):

1. Physik der Medizinischen Bildgebung (INM-4)
2. Jara-Institut Quantum Information (INM-11)
3. JARA-BRAIN (JARA-BRAIN)
4. Kognitive Neurowissenschaften (INM-3)

Research Program(s):

1. 5253 - Neuroimaging (POF4-525) (POF4-525)
2. 5252 - Brain Dysfunction and Plasticity (POF4-525) (POF4-525)
3. DFG project 428090865 - Radiomics basierend auf MRT und Aminosäure PET in der Neuroonkologie (428090865)

Appears in the scientific report 2021

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Database coverage:
; ; ; BIOSIS Previews ; Biological Abstracts ; Clarivate Analytics Master Journal List ; Current Contents - Life Sciences ; Ebsco Academic Search ; Essential Science Indicators ; IF < 5 ; JCR ; NCBI Molecular Biology Database ; Nationallizenz ; SCOPUS ; Science Citation Index ; Science Citation Index Expanded ; Web of Science Core Collection

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