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@ARTICLE{Lohmann:850813,
author = {Lohmann, Philipp and Kocher, M. and Steger, J. and
Galldiks, N.},
title = {{R}adiomics derived from amino acid {PET} and conventional
{MRI} in patients with high-grade gliomas},
journal = {The quarterly journal of nuclear medicine and molecular
imaging},
volume = {62},
number = {3},
issn = {0392-0208},
address = {Torino},
publisher = {Ed. Minerva Medica},
reportid = {FZJ-2018-04584},
pages = {272-80},
year = {2018},
abstract = {Radiomics is a technique that uses high-throughput
computing to extract quantitative features from tomographic
medical images such as MRI and PET that usually are beyond
visual perception. Importantly, the radiomics approach can
be performed using neuroimages that have already been
acquired during the routine follow-up of the patients
allowing an additional data evaluation at low cost. In
Neuro-Oncology, these features can potentially be used for
differential diagnosis of newly diagnosed cerebral lesions
suggestive for brain tumors or for the prediction of
response to a neurooncological treatment option.
Furthermore, especially in the light of the recent update of
the World Health Organization classification of brain
tumors, radiomics also has the potential to non-invasively
assess important prognostic and predictive molecular markers
such as a mutation in the isocitrate dehydrogenase gene or a
1p/19q codeletion which are not accessible by conventional
visual interpretation of MRI or PET findings. This review
summarizes the current status of the rapidly evolving field
of radiomics with a special focus on patients with
high-grade gliomas.},
cin = {INM-3 / INM-4},
ddc = {570},
cid = {I:(DE-Juel1)INM-3-20090406 / I:(DE-Juel1)INM-4-20090406},
pnm = {572 - (Dys-)function and Plasticity (POF3-572)},
pid = {G:(DE-HGF)POF3-572},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:29869488},
UT = {WOS:000445240400006},
doi = {10.23736/S1824-4785.18.03095-9},
url = {https://juser.fz-juelich.de/record/850813},
}