Journal Article

FZJ-2021-00816

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png FET PET Radiomics for Differentiating Pseudoprogression from Early Tumor Progression in Glioma Patients Post-Chemoradiation

Lohmann, P. (Corresponding author)FZJ* ; Elahmadawy, M. A. ; Gutsche, R.FZJ* ; Werner, J.-M. ; Bauer, E. K. ; Ceccon, G. ; Kocher, M.FZJ* ; Lerche, C. W.FZJ* ; Rapp, M. ; Fink, G. R.FZJ* ; Shah, N. J.FZJ* ; Langen, K.-J.FZJ* ; Galldiks, N.FZJ*

2020
MDPI Basel

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Please use a persistent id in citations: http://hdl.handle.net/2128/27048  doi:10.3390/cancers12123835

Abstract: Currently, a reliable diagnostic test for differentiating pseudoprogression from early tumor progression is lacking. We explored the potential of O-(2-[18F]fluoroethyl)-L-tyrosine (FET) positron emission tomography (PET) radiomics for this clinically important task. Thirty-four patients (isocitrate dehydrogenase (IDH)-wildtype glioblastoma, 94%) with progressive magnetic resonance imaging (MRI) changes according to the Response Assessment in Neuro-Oncology (RANO) criteria within the first 12 weeks after completing temozolomide chemoradiation underwent a dynamic FET PET scan. Static and dynamic FET PET parameters were calculated. For radiomics analysis, the number of datasets was increased to 102 using data augmentation. After randomly assigning patients to a training and test dataset, 944 features were calculated on unfiltered and filtered images. The number of features for model generation was limited to four to avoid data overfitting. Eighteen patients were diagnosed with early tumor progression, and 16 patients had pseudoprogression. The FET PET radiomics model correctly diagnosed pseudoprogression in all test cohort patients (sensitivity, 100%; negative predictive value, 100%). In contrast, the diagnostic performance of the best FET PET parameter (TBRmax) was lower (sensitivity, 81%; negative predictive value, 80%). The results suggest that FET PET radiomics helps diagnose patients with pseudoprogression with a high diagnostic performance. Given the clinical significance, further studies are warranted

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Contributing Institute(s):

1. Kognitive Neurowissenschaften (INM-3)
2. Physik der Medizinischen Bildgebung (INM-4)
3. Jara-Institut Quantum Information (INM-11)

Research Program(s):

1. 572 - (Dys-)function and Plasticity (POF3-572) (POF3-572)
2. DFG project 428090865 - Radiomics basierend auf MRT und Aminosäure PET in der Neuroonkologie (428090865)

Appears in the scientific report 2020

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