000910521 001__ 910521
000910521 005__ 20221028130545.0
000910521 037__ $$aFZJ-2022-03904
000910521 1001_ $$0P:(DE-Juel1)145110$$aLohmann, Philipp$$b0$$eCorresponding author$$ufzj
000910521 1112_ $$aEAN 2022 – Vienna$$cVienna$$d2022-06-25 - 2022-06-25$$wAustria
000910521 245__ $$aCombining advanced MRI and PET
000910521 260__ $$c2022
000910521 3367_ $$0PUB:(DE-HGF)1$$2PUB:(DE-HGF)$$aAbstract$$babstract$$mabstract$$s1666942438_8013
000910521 3367_ $$033$$2EndNote$$aConference Paper
000910521 3367_ $$2BibTeX$$aINPROCEEDINGS
000910521 3367_ $$2DRIVER$$aconferenceObject
000910521 3367_ $$2DataCite$$aOutput Types/Conference Abstract
000910521 3367_ $$2ORCID$$aOTHER
000910521 520__ $$aABSTRACTNeuroimaging techniques such as magnetic resonance imaging (MRI) and positron emission tomography (PET) provide valuable diagnostic information in the follow-up of patients with glioma. Particularly PET using radiolabeled amino acids, advanced MRI techniques such as perfusion-weighted imaging, diffusion-weighted imaging or MR spectroscopy, and combinations thereof demonstrated their potential for a non-invasive assessment of biological characteristics of brain cancer. Considering the growing complexity of neuroimaging data, advanced statistical methods from the field of artificial intelligence such as radiomics play an important role for clinical decision-making and have the potential to significantly impact diagnosis and response assessment in neuro-oncology. Further, the increasing availability of hybrid PET/MRI systems and the advent of ultra-high field MRI scanners operating at magnetic field strengths of 7 Tesla or more opens new possibilities for improvements in metabolic imaging. The presentation summarizes the status of advanced MRI and PET, highlights the latest developments and methodological advancements, and envisions the future role of advanced neuroimaging in the follow-up of patients with glioma.
000910521 536__ $$0G:(DE-HGF)POF4-5253$$a5253 - Neuroimaging (POF4-525)$$cPOF4-525$$fPOF IV$$x0
000910521 909CO $$ooai:juser.fz-juelich.de:910521$$pVDB
000910521 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)145110$$aForschungszentrum Jülich$$b0$$kFZJ
000910521 9131_ $$0G:(DE-HGF)POF4-525$$1G:(DE-HGF)POF4-520$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5253$$aDE-HGF$$bKey Technologies$$lNatural, Artificial and Cognitive Information Processing$$vDecoding Brain Organization and Dysfunction$$x0
000910521 9141_ $$y2022
000910521 9201_ $$0I:(DE-Juel1)INM-4-20090406$$kINM-4$$lPhysik der Medizinischen Bildgebung$$x0
000910521 980__ $$aabstract
000910521 980__ $$aVDB
000910521 980__ $$aI:(DE-Juel1)INM-4-20090406
000910521 980__ $$aUNRESTRICTED