Sequential implementation of DSC-MR perfusion and dynamic [ 18 F]FET PET allows efficient differentiation of glioma prog
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ORIGINAL ARTICLE
Sequential implementation of DSC-MR perfusion and dynamic [18F] FET PET allows efficient differentiation of glioma progression from treatment-related changes Eike Steidl 1,2,3 & Karl-Josef Langen 5,6,7 & Sarah Abu Hmeidan 1,2 & Nenad Polomac 1,2 & Christian P. Filss 5,6 & Norbert Galldiks 4,8,14 & Philipp Lohmann 4,16 & Fee Keil 1,2 & Katharina Filipski 2,3,9 & Felix M. Mottaghy 6,7,10 & Nadim Jon Shah 5,11,12,15 & Joachim P. Steinbach 2,3,13 & Elke Hattingen 1,2,3 & Gabriele D. Maurer 2,3,13 Received: 10 September 2020 / Accepted: 8 November 2020 # The Author(s) 2020
Abstract Purpose Perfusion-weighted MRI (PWI) and O-(2-[18F]fluoroethyl-)-L-tyrosine ([18F]FET) PET are both applied to discriminate tumor progression (TP) from treatment-related changes (TRC) in patients with suspected recurrent glioma. While the combination of both methods has been reported to improve the diagnostic accuracy, the performance of a sequential implementation has not been further investigated. Therefore, we retrospectively analyzed the diagnostic value of consecutive PWI and [18F]FET PET. Methods We evaluated 104 patients with WHO grade II–IV glioma and suspected TP on conventional MRI using PWI and dynamic [18F]FET PET. Leakage corrected maximum relative cerebral blood volumes (rCBVmax) were obtained from dynamic susceptibility contrast PWI. Furthermore, we calculated static (i.e., maximum tumor to brain ratios; TBRmax) and dynamic [18F]FET PET parameters (i.e., Slope). Definitive diagnoses were based on histopathology (n = 42) or clinico-radiological follow-up (n = 62). The diagnostic performance of PWI and [18F]FET PET parameters to differentiate TP from TRC was evaluated by analyzing receiver operating characteristic and area under the curve (AUC). Results Across all patients, the differentiation of TP from TRC using rCBVmax or [18F]FET PET parameters was moderate (AUC = 0.69–0.75; p < 0.01). A rCBVmax cutoff > 2.85 had a positive predictive value for TP of 100%, enabling a correct TP diagnosis in 44 patients. In the remaining 60 patients, combined static and dynamic [18F]FET PET parameters (TBRmax, Slope) correctly discriminated This article is part of the Topical Collection on Oncology - Brain. * Eike Steidl [email protected] 1
Institute of Neuroradiology, University Hospital, Goethe University Frankfurt am Main, Schleusenweg 2-16, Frankfurt am Main 60528, Germany
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Dept. of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
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Institute of Neurology (Edinger Institute), University Hospital, Goethe University Frankfurt am Main, Frankfurt am Main, Germany
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Dept. of Radiology and Nuclear Medicine, Maastricht University Medical Center (MUMC+), Maastricht, The Netherlands
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Inst. of Neuroscience and Medicine, Molecular Neuroscience and Neuroimaging (INM-11), JARA, Research Center Juelich, Juelich, Germany
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University Cancer Center Frankfurt (UCT), University Hospital, Goethe University Frankfurt am Main, Frankfurt am Main, Germany
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German Cancer
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