MR Fingerprinting-A Radiogenomic Marker for Diffuse Gliomas

Elisabeth Springer; Pedro Lima Cardoso; Bernhard Strasser; Wolfgang Bogner; Matthias Preusser; Georg Widhalm; Mathias Nittka; Gregor Koerzdoerfer; Pavol Szomolanyi; Gilbert Hangel; Johannes A Hainfellner; Wolfgang Marik; Siegfried Trattnig

doi:10.3390/cancers14030723

MR Fingerprinting-A Radiogenomic Marker for Diffuse Gliomas

Cancers (Basel). 2022 Jan 30;14(3):723. doi: 10.3390/cancers14030723.

Authors

Elisabeth Springer^{1

2}, Pedro Lima Cardoso¹, Bernhard Strasser¹, Wolfgang Bogner¹, Matthias Preusser³, Georg Widhalm⁴, Mathias Nittka⁵, Gregor Koerzdoerfer⁵, Pavol Szomolanyi^{1

6}, Gilbert Hangel^{1

4}, Johannes A Hainfellner⁷, Wolfgang Marik⁸, Siegfried Trattnig^{1

9}

Affiliations

¹ High-Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria.
² Institute of Radiology, Hietzing Hospital, 1130 Vienna, Austria.
³ Division of Oncology, Department of Internal Medicine I, Medical University of Vienna, 1090 Vienna, Austria.
⁴ Department of Neurosurgery, Medical University of Vienna, 1090 Vienna, Austria.
⁵ Siemens Healthineers, 91052 Erlangen, Germany.
⁶ Department of Imaging Methods, Institute of Measurement Science, Slovak Academy of Sciences, 84104 Bratislava, Slovakia.
⁷ Division of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, 1090 Vienna, Austria.
⁸ Division of Neuroradiology and Musculoskeletal Radiology, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria.
⁹ Christian Doppler Laboratory for Clinical Molecular MR Imaging, Medical University of Vienna, 1090 Vienna, Austria.

Abstract

(1) Background: Advanced MR imaging (MRI) of brain tumors is mainly based on qualitative contrast images. MR Fingerprinting (MRF) offers a novel approach. The purpose of this study was to use MRF-derived T1 and T2 relaxation maps to differentiate diffuse gliomas according to isocitrate dehydrogenase (IDH) mutation. (2) Methods: Twenty-four patients with histologically verified diffuse gliomas (14 IDH-mutant, four 1p/19q-codeleted, 10 IDH-wildtype) were enrolled. MRF T1 and T2 relaxation times were compared to apparent diffusion coefficient (ADC), relative cerebral blood volume (rCBV) within solid tumor, peritumoral edema, and normal-appearing white matter (NAWM), using contrast-enhanced MRI, diffusion-, perfusion-, and susceptibility-weighted imaging. For perfusion imaging, a T2* weighted perfusion sequence with leakage correction was used. Correlations of MRF T1 and T2 times with two established conventional sequences for T1 and T2 mapping were assessed (a fast double inversion recovery-based MR sequence ('MP2RAGE') for T1 quantification and a multi-contrast spin echo-based sequence for T2 quantification). (3) Results: MRF T1 and T2 relaxation times were significantly higher in the IDH-mutant than in IDH-wildtype gliomas within the solid part of the tumor (p = 0.024 for MRF T1, p = 0.041 for MRF T2). MRF T1 and T2 relaxation times were significantly higher in the IDH-wildtype than in IDH-mutant gliomas within peritumoral edema less than or equal to 1cm adjacent to the tumor (p = 0.038 for MRF T1 mean, p = 0.010 for MRF T2 mean). In the solid part of the tumor, there was a high correlation between MRF and conventionally measured T1 and T2 values (r = 0.913, p < 0.001 for T1, r = 0.775, p < 0.001 for T2), as well as between MRF and ADC values (r = 0.813, p < 0.001 for T2, r = 0.697, p < 0.001 for T1). The correlation was weak between the MRF and rCBV values (r = -0.374, p = 0.005 for T2, r = -0.181, p = 0.181 for T1). (4) Conclusions: MRF enables fast, single-sequence based, multi-parametric, quantitative tissue characterization of diffuse gliomas and may have the potential to differentiate IDH-mutant from IDH-wildtype gliomas.

Keywords: MR fingerprinting; T1 and T2 relaxation times; brain/central nervous system cancers; gliomas; quantitative maps.

Abstract

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