000907682 001__ 907682
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000907682 0247_ $$2doi$$a10.1055/s-0042-1746120
000907682 037__ $$aFZJ-2022-02155
000907682 1001_ $$0P:(DE-Juel1)181076$$aGutsche, R.$$b0$$ufzj
000907682 1112_ $$a60. Jahrestagung der Deutschen Gesellschaft für Nuklearmedizin$$cLeipzig$$d2022-04-27 - 2022-04-30$$wGermany
000907682 245__ $$aMultimodal PET/MRI radiomics and clinical parameters for overall survival prediction in patients with IDH wildtype glioblastoma
000907682 260__ $$c2022
000907682 3367_ $$0PUB:(DE-HGF)1$$2PUB:(DE-HGF)$$aAbstract$$babstract$$mabstract$$s1652361894_31067
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000907682 520__ $$aZiel/Aim Currently, most radiomics studies on survival prediction in brain tumor patients are based on MRI only. The goal of our study was to evaluate multimodal radiomics derived from amino acid PET and MRI and clinical parameters for survival prediction in patients with newly diagnosed IDH wildtype glioblastoma.Methodik/Methods Sixty-three patients with newly diagnosed IDH wildtype glioblastoma were evaluated retrospectively. At initial diagnosis, all patients underwent structural MRI and O-(2-[F-18]fluoroethyl)-L-tyrosine (FET) PET. Tumor volumes were automatically segmented using a deep learning-based tool followed by visual inspection. Predefined and deep radiomics features were extracted from both imaging modalities. Feature repeatability analyses and feature selection were performed to avoid overfitting. Cox regression models for overall survival were built from clinical parameters such as age or the extent of resection, radiomics features, and combinations thereof, and finally validated using 5-fold cross-validation.Ergebnisse/Results The median overall survival was 12 months (range, 0–64 months). Higher age and larger FET PET tumor volumes were significantly correlated with shorter overall survival (age, r=−0.39, p<0.001; volume, r=−0.31, p<0.05). Models solely based on predefined FET PET or MRI radiomics features showed a similar mean concordance index (C-index) as the model based on clinical parameters (C-indices, 0.68±0.04; 0.64±0.03; and 0.69±0.08, respectively). Multimodal radiomics based on predefined and deep features yielded improved C-indices of 0.75±0.06 and 0.72±0.09, respectively. A model based on multimodal radiomics and clinical parameters achieved the best prognostic performance (C-index, 0.80±0.04).Schlussfolgerungen/Conclusions Our results suggest an added clinical value of multimodal FET PET/MRI radiomics with clinical parameters for the non-invasive survival prediction in patients with IDH wildtype glioblastoma.
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000907682 7001_ $$0P:(DE-Juel1)159312$$aBauer, E. K.$$b1$$ufzj
000907682 7001_ $$0P:(DE-Juel1)173675$$aKocher, M.$$b2$$ufzj
000907682 7001_ $$aWerner, J. M.$$b3
000907682 7001_ $$0P:(DE-Juel1)131720$$aFink, G. R.$$b4$$ufzj
000907682 7001_ $$0P:(DE-Juel1)131794$$aShah, N. J.$$b5$$ufzj
000907682 7001_ $$0P:(DE-Juel1)131777$$aLangen, K. J.$$b6$$ufzj
000907682 7001_ $$0P:(DE-Juel1)143792$$aGalldiks, N.$$b7$$ufzj
000907682 7001_ $$0P:(DE-Juel1)145110$$aLohmann, P.$$b8$$eCorresponding author$$ufzj
000907682 773__ $$a10.1055/s-0042-1746120
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000907682 9141_ $$y2022
000907682 9201_ $$0I:(DE-Juel1)INM-4-20090406$$kINM-4$$lPhysik der Medizinischen Bildgebung$$x0
000907682 9201_ $$0I:(DE-Juel1)PGI-JCNS-TA-20110113$$kPGI-JCNS-TA$$lPGI Technische und administrative Infrastruktur$$x1
000907682 9201_ $$0I:(DE-Juel1)INM-3-20090406$$kINM-3$$lKognitive Neurowissenschaften$$x2
000907682 9201_ $$0I:(DE-Juel1)INM-11-20170113$$kINM-11$$lJara-Institut Quantum Information$$x3
000907682 9201_ $$0I:(DE-Juel1)VDB1046$$kJARA-BRAIN$$lJülich-Aachen Research Alliance - Translational Brain Medicine$$x4
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