FET PET Radiomics for Differentiating Pseudoprogression from Early Tumor Progression in Glioma Patients Post-Chemoradiation

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.

Diagnostic Accuracy of PET for Differentiating True Glioma Progression From Post Treatment-Related Changes: A Systematic Review and Meta-Analysis

“…Precise image segmentation and feature extraction using different classification methods make it more accuracy in diagnosis. However, many studies demonstrated that a PET radiomics model had higher accuracy than the PET single parameter analysis in differentiating TPR from PTRC ( 70 , 71 ). Feature-based PET/MRI radiomics also showed higher accuracy ( 72 ).…”

TERT-Promoter Mutational Status in Glioblastoma – Is There an Association With Amino Acid Uptake on Dynamic 18F-FET PET?

“…Moreover, a vast body of literature exists dealing with radiomics, deep learning and machine learning with special emphasis on ( 18 F-FET) PET and hybrid imaging in neurooncology (43)(44)(45)(46)(47)(48)(49), not just for the differentiation of treatmentrelated changes from real progression (44,50,51), but also for the predication of prognostically relevant mutations such as the IDH-mutation (52). Hence, it needs to be evaluated, if further PET-based analyses with the extraction of radiomic features may add value to the conventional image analysis in order to noninvasively identify the TERTp-mutational status.…”

Advanced Imaging Techniques for Radiotherapy Planning of Gliomas

“…A large CTV, which includes possible pathology not visible on standard MRI imaging, has the potential to better fit all microscopic tumor infiltration; however, this approach may increase the risk of neurocognitive decline and worsen the quality of life [ 28 ]. Moreover, conventional MRI techniques have clear limitations in the evaluation of glioma heterogeneity among different regions of the same tumor, such as metabolic changes and proliferative activity, hypoxia, and neovascularization/angiogenesis, which can, at least in part, explain their resistance to RT, and that can be specifically investigated using advanced MRI and PET imaging [ 23 , 29 , 30 , 31 , 32 , 33 ].…”