TY  - JOUR
AU  - Lohmann, Philipp
AU  - Kocher, Martin
AU  - Ruge, Maximillian I.
AU  - Visser-Vandewalle, Veerle
AU  - Shah, N. Jon
AU  - Fink, Gereon R.
AU  - Langen, Karl-Josef
AU  - Galldiks, Norbert
TI  - PET/MRI Radiomics in Patients With Brain Metastases
JO  - Frontiers in neurology
VL  - 11
SN  - 1664-2295
CY  - Lausanne
PB  - Frontiers Research Foundation
M1  - FZJ-2020-01448
SP  - 1
PY  - 2020
AB  - Although a variety of imaging modalities are used or currently being investigated for patients with brain tumors including brain metastases, clinical image interpretation to date uses only a fraction of the underlying complex, high-dimensional digital information from routinely acquired imaging data. The growing availability of high-performance computing allows the extraction of quantitative imaging features from medical images that are usually beyond human perception. Using machine learning techniques and advanced statistical methods, subsets of such imaging features are used to generate mathematical models that represent characteristic signatures related to the underlying tumor biology and might be helpful for the assessment of prognosis or treatment response, or the identification of molecular markers. The identification of appropriate, characteristic image features as well as the generation of predictive or prognostic mathematical models is summarized under the term radiomics. This review summarizes the current status of radiomics in patients with brain metastases.
LB  - PUB:(DE-HGF)16
C6  - pmid:32116995
UR  - <Go to ISI:>//WOS:000517298900001
DO  - DOI:10.3389/fneur.2020.00001
UR  - https://juser.fz-juelich.de/record/874447
ER  -