TY  - JOUR
AU  - Lohmann, Philipp
AU  - Meißner, Anna-Katharina
AU  - Kocher, Martin
AU  - Bauer, Elena K
AU  - Werner, Jan-Michael
AU  - Fink, Gereon R
AU  - Shah, Nadim J
AU  - Langen, Karl-Josef
AU  - Galldiks, Norbert
TI  - Feature-based PET/MRI radiomics in patients with brain tumors
JO  - Neuro-oncology advances
VL  - 2
IS  - Supplement_4
SN  - 2632-2498
CY  - Oxford
PB  - Oxford University Press868239
M1  - FZJ-2021-00883
SP  - iv15 - iv21
PY  - 2020
AB  - Radiomics allows the extraction of quantitative features from medical images such as CT, MRI, or PET, thereby providing additional, potentially relevant diagnostic information for clinical decision-making. Because the computation of these features is performed highly automated on medical images acquired during routine follow-up, radiomics offers this information at low cost. Further, the radiomics features can be used alone or combined with other clinical or histomolecular parameters to generate predictive or prognostic mathematical models. These models can then be applied for various important diagnostic indications in neuro-oncology, for example, to noninvasively predict relevant biomarkers in glioma patients, to differentiate between treatment-related changes and local brain tumor relapse, or to predict treatment response. In recent years, amino acid PET has become an important diagnostic tool in patients with brain tumors. Therefore, the number of studies in patients with brain tumors investigating the potential of PET radiomics or combined PET/MRI radiomics is steadily increasing. This review summarizes current research regarding feature-based PET as well as combined PET/MRI radiomics in neuro-oncology.
LB  - PUB:(DE-HGF)16
C6  - 33521637
UR  - <Go to ISI:>//WOS:000897684800003
DO  - DOI:10.1093/noajnl/vdaa118
UR  - https://juser.fz-juelich.de/record/890310
ER  -