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. 2022 Sep 27;12(10):2331.
doi: 10.3390/diagnostics12102331.

Multiparametric Characterization of Intracranial Gliomas Using Dynamic [18F]FET-PET and Magnetic Resonance Spectroscopy

Thomas Pyka  1   2   3 , Iwona Krzyzanowska  4 , Axel Rominger  3 , Claire Delbridge  5 , Bernhard Meyer  4 , Tobias Boeckh-Behrens  2 , Claus Zimmer  2 , Jens Gempt  4
Affiliations

Multiparametric Characterization of Intracranial Gliomas Using Dynamic [18F]FET-PET and Magnetic Resonance Spectroscopy

Thomas Pyka et al. Diagnostics (Basel). .

Abstract

Both static and dynamic O-(2-[18F]fluoroethyl)-l-tyrosine-(FET)-PET and 1H magnetic resonance spectroscopy (MRS) are useful tools for grading and prognostication in gliomas. However, little is known about the potential of multimodal imaging comprising both procedures. We therefore acquired NAA/Cr and Cho/Cr ratios in multi-voxel MRS as well as FET-PET parameters in 67 glioma patients and determined multiparametric parameter combinations. Using receiver operating characteristics, differentiation between low-grade and high-grade glioma was possible by static FET-PET (area under the curve (AUC) 0.86, p = 0.001), time-to-peak (TTP; AUC 0.79, p = 0.049), and using the Cho/Cr ratio (AUC 0.72, p = 0.039), while the multimodal analysis led to improved discrimination with an AUC of 0.97 (p = 0.001). In order to distinguish glioblastoma from non-glioblastoma, MRS (NAA/Cr ratio, AUC 0.66, p = 0.031), and dynamic FET-PET (AUC 0.88, p = 0.001) were superior to static FET imaging. The multimodal analysis increased the accuracy with an AUC of 0.97 (p < 0.001). In the survival analysis, PET parameters, but not spectroscopy, were significantly correlated with overall survival (OS, static PET p = 0.014, TTP p = 0.012), still, the multiparametric analysis, including MRS, was also useful for the prediction of OS (p = 0.002). In conclusion, FET-PET and MRS provide complementary information to better characterize gliomas before therapy, which is particularly interesting with respect to the increasing use of hybrid PET/MRI for brain tumors.

Keywords: glioma; magnetic resonance imaging; magnetic resonance spectroscopy; multiparametric imaging; positron emission tomography.

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Conflict of interest statement

J.G. and B.M. report personal fees for consultancy from Brain Lab AG, outside of the submitted work.

Figures

Figure 1
Figure 1
Example MR spectroscopy and FET-PET in a patient with glioblastoma; 53-year-old patient with untreated left frontal glioblastoma (WHO grade IV). (a) Multi-voxel 1H-MRS with spectroscopy grid and representative spectrum from a tumor voxel with signal intensities and ratios for Cho, Cr, and NAA, showing an elevated Cho/Cr ratio. Yellow line—unsmoothed, green line—smoothed values, purple - baseline. (b) Static FET-PET scan 30 min after injection with intense tracer enhancement (TBR 3.5). (c) Dynamic FET-PET over 40 min shows a linearly ascending activity slope in the tumor, untypical for glioblastoma. Interestingly, this patient had an unusual benign course with one relapse but long-term survival over several years and no further recurrence so far.
Figure 2
Figure 2
ROC curves for differentiation between low-grade and high-grade gliomas.
Figure 3
Figure 3
ROC curves for differentiation between glioblastoma and non-glioblastoma.
Figure 4
Figure 4
Kaplan–Meier plot showing low- and high-risk groups according to static FET-PET (TBR).
Figure 5
Figure 5
Kaplan–Meier plot showing low- and high-risk groups according to dynamic FET-PET (TTP).
Figure 6
Figure 6
Kaplan–Meier plot showing low- and high-risk groups according to multiparametric combination.
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