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

Johannes Lohmeier*, Helena Radbruch, Winfried Brenner, Bernd Hamm, Brian Hansen, Anna Tietze, Marcus R. Makowski

*Corresponding author for this work

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

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- 18F-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 18F-FET PET and a fast-DKI variant. PET and advanced diffusion metrics of metabolically defined (80–100% and 60–75% areas of 18F-FET uptake) compartments were assessed. Comparative analysis was performed using Mann–Whitney U tests with Holm-Šídák 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 18F-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 18F-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. Clinical relevance statement: A multimodal and integrative 18F-FET PET/fast-DKI approach for the non-invasive microstructural characterization of metabolic compartments provided improved diagnostic capability for differentiation between recurrent glioma and post-treatment-related changes, suggesting a role for the diagnostic workup of patients in post-treatment settings. Key Points: • Multimodal PET/MRI with integrative analysis of 18F-FET PET and fast-DKI presents clinical benefit for the assessment of CNS cancer, particularly for the detection of recurrent high-grade glioma. • Microstructure markers of the metabolic periphery yielded biologically pertinent estimates characterising the tumour microenvironment, and, thereby, presented improved diagnostic accuracy with similar accuracy to amino acid PET. • Combined 18F-FET PET/fast-DKI achieved the best diagnostic performance for detection of high-grade glioma relapse with significant benefit to the assessment based on PET alone.

Original languageEnglish
JournalEuropean Radiology
Volume34
Issue4
Pages (from-to)2487–2499
Number of pages13
ISSN0938-7994
DOIs
Publication statusPublished - Apr 2024

Keywords

  • Diffusion magnetic resonance imaging
  • Glioma
  • Metabolism
  • Multimodal imaging
  • Positron-emission tomography

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