Detection of recurrent high-grade glioma using microstructure characteristics of distinct metabolic compartments in a multimodal and integrative 18F-FET PET/fast-DKI approach

Abstract

Objectives: Differentiation between high-grade glioma (HGG) and post-treatment-related effects (PTRE) is challenging, but advanced imaging techniques were shown to provide benefit. We aim to investigate microstructure characteristics of metabolic compartments identified from amino acid PET and to evaluate the diagnostic potential of this multimodal and integrative O-(2-F-18-fluoroethyl)-l-tyrosine-(FET)-PET and fast diffusion kurtosis imaging (DKI) approach for the detection of recurrence and IDH genotyping. Methods: Fifty-nine participants with neuropathologically confirmed recurrent HGG (n=39) or PTRE (n=20) were investigated using static F-18-FET PET and a fast-DKI variant. PET and advanced diffusion metrics of metabolically defined (80-100% and 60-75% areas of F-18-FET uptake) compartments were assessed. Comparative analysis was performed using Mann-Whitney U tests with Holm-Sidak multiple-comparison test and Wilcoxon signed-rank test. Receiver operating characteristic (ROC) curves, regression, and Spearman's correlation analysis were used for statistical evaluations. Results: Compared to PTRE, recurrent HGG presented increased F-18-FET uptake and diffusivity (MD60), but lower (relative) mean kurtosis tensor (rMKT60) and fractional anisotropy (FA60) (respectively p<.05). Diffusion metrics determined from the metabolic periphery showed improved diagnostic performance - most pronounced for FA60 (AUC=0.86, p<.001), which presented similar benefit to F-18-FET PET (AUC=0.86, p<.001) and was negatively correlated with amino acid uptake (rs=-0.46, p<.001). When PET and DKI metrics were evaluated in a multimodal biparametric approach, TBRmax+FA60 showed highest diagnostic accuracy (AUC=0.93, p<.001), which improved the detection of relapse compared to PET alone (difference in AUC=0.069, p=.04). FA60 and MD60 distinguished the IDH genotype in the post-treatment setting. Conclusion: Detection of glioma recurrence benefits from a multimodal and integrative PET/DKI approach, which presented significant diagnostic advantage to the assessment based on PET alone.