Combined 18F-FET PET and diffusion kurtosis MRI in posttreatment glioblastoma: differentiation of true progression from treatment-related changes. Issue 1 (10th March 2021)

• Record Type: Journal Article
• Authors: D'Amore, Francesco; Grinberg, Farida; Mauler, Jörg; Galldiks, Norbert; Blazhenets, Ganna; Farrher, Ezequiel; Filss, Christian; Stoffels, Gabriele; Mottaghy, Felix M; Lohmann, Philipp; Shah, Nadim Jon; Langen, Karl-Josef
• Is Part Of: Neuro-oncology advances. Volume 3:Issue 1(2021)
• Publication Date: 2021-03-10
• Subjects: amino acid PET -- brain tumor -- diffusion kurtosis MRI -- pseudoprogression -- tumor progression; 616.99481
• DOI: 10.1093/noajnl/vdab044
• Languages: English
• ISSNs: 2632-2498

Abstract

Abstract: Background: Radiological differentiation of tumor progression (TPR) from treatment-related changes (TRC) in pretreated glioblastoma is crucial. This study aimed to explore the diagnostic value of diffusion kurtosis MRI combined with information derived from O -(2-[ 18 F]-fluoroethyl)-l -tyrosine ( 18 F-FET) PET for the differentiation of TPR from TRC in patients with pretreated glioblastoma. Methods: Thirty-two patients with histomolecularly defined and pretreated glioblastoma suspected of having TPR were included in this retrospective study. Twenty-one patients were included in the TPR group, and 11 patients in the TRC group, as assessed by neuropathology or clinicoradiological follow-up. Three-dimensional (3D) regions of interest were generated based on increased 18 F-FET uptake using a tumor-to-brain ratio of 1.6. Furthermore, diffusion MRI kurtosis maps were obtained from the same regions of interest using co-registered 18 F-FET PET images, and advanced histogram analysis of diffusion kurtosis map parameters was applied to generated 3D regions of interest. Diagnostic accuracy was analyzed by receiver operating characteristic curve analysis and combinations of PET and MRI parameters using multivariate logistic regression. Results: Parameters derived from diffusion MRI kurtosis maps show high diagnostic accuracy, up to 88%, for differentiating between TPR and TRC. Logistic regression revealed that the highest diagnostic accuracy of 94% (area under the curve, 0.97; sensitivity, 94%; specificity, 91%) was achieved by combining the maximum tumor-to-brain ratio of 18 F-FET uptake and diffusion MRI kurtosis metrics. Conclusions: The combined use of 18 F-FET PET and MRI diffusion kurtosis maps appears to be a promising approach to improve the differentiation of TPR from TRC in pretreated glioblastoma and warrants further investigation.