Hybrid [18F]-F-DOPA PET/MRI Interpretation Criteria and Scores for Glioma Follow-up After Radiotherapy

Abstract

Objectives: F-DOPA PET is used in glioma follow-up after radiotherapy to discriminate treatment-related changes (TRC) from tumour progression (TP). We compared the performances of a combined PET and MRI analysis with F-DOPA current standard of Powered by Editorial Manager® and ProduXion Manager® from Aries Systems Corporation interpretation. Methods : We included 76 consecutive patients showing at least one gadolinium-enhancing lesion on T1-w MRI sequence (T1G). Two nuclear medicine physicians blindly analysed PET/MRI images. In addition to the conventional PET analysis, they looked for F-DOPA uptake(s) outside T1G-enhancing areas (T1G-/PET), in the white matter (WM/PET), for T1G-enhancing lesion(s) without sufficiently concordant F-DOPA uptake (T1G+/PET), and for F-DOPA uptake(s) away from haemorrhagic changes as shown with a Susceptibility Weighted Imaging sequence (SWI/PET). We measured lesions' F-DOPA uptake using healthy brain background (TBR) and striatum (T/S) as references, and lesions' perfusion with arterial spin labelling cerebral blood flow maps (rCBF). Scores were determined by logistic regression. Results: 53 and 23 patients were diagnosed with TP and TRC, respectively. The accuracies were 74% for T/S, 76% for TBR, and 84% for rCBF, with best cut-off values of 1.3, 3.7 and 1.25, respectively. For hybrid variables, best accuracies were obtained with conventional analysis (82%), T1G+/PET (82%) and SWI/PET (81%). T1G+/PET, SWI/PET and rCBF ≥ 1.25 were selected to construct a 3-point score. It outperformed conventional analysis and rCBF with an AUC of 0.94 and an accuracy of 87%. Conclusions : Our scoring approach combining F-DOPA PET and MRI provided better accuracy than conventional PET analyses for distinguishing TP from TRC in our patients after radiation therapy. Response to Reviewers:Once again, we would like to thank the reviewers and the editorial team for their work.As requested, the manuscript was fully checked with the Grammarly software and modified accordingly.

Assessing the added value of apparent diffusion coefficient, cerebral blood volume, and radiomic magnetic resonance features for differentiation of pseudoprogression versus true tumor progression in patients with glioblastoma

“…We performed a study based on a larger dataset (compared to previous works) using an (almost) fully automatic pipeline and failed to demonstrate a satisfactory performance for models based on ADC or nrCBV or for ML models based on multiparametric MR imaging and radiomics and imaging DL models. Future studies with larger, multicentric cohorts alongside novel or hybrid imaging techniques 42 , 43 should be encouraged to develop a better understanding of the real performance and generalizability of supervised ML and DL models in a real life scenario; decentralized techniques for model building such as federated or swarm learning, should also be explored with the aim of building more reliable and clinically translatable models.…”

Tracers progress for positron emission tomography imaging of glial-related disease

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Exploring the mechanism of 18F‐fluorodopa uptake in recurrent high‐grade gliomas: A comprehensive histomolecular‐positron emission tomography analysis

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“…Metabolic tumor volume (MTV) was automatically delineated on the SyngoVia® software using a threshold of 1.6 × contralateral cortex mean standardized uptake value (SUVmean), as previously described [12]. Reference regions were delineated in the unaffected contralateral parietal cortex (region of interest [ROI] of 3 cm 3 ) and in the contralateral striatum as previously described [13].…”