Anagha Deshmane1, Kunio Nakamura2, Deepti K Guruprakash2, Yun Jiang 1, Dan Ma3, Jar-Chi Lee 4, Elizabeth Fisher 5, Richard A. Rudick 5, Jeffrey A. Cohen6, Mark J. Lowe6, Daniel Ontaneda6, Mark A. Griswold1,3, and Vikas Gulani1,7
1Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States, 2Biomedical Engineering, Cleveland Clinic, Cleveland, OH, United States, 3Radiology, Case Western Reserve University, Cleveland, OH, United States, 4Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH, United States, 5Biogen, Boston, MA, United States, 6Mellen Center for Multiple Sclerosis Research and Treatment, Cleveland Clinic, Cleveland, OH, United States, 7Radiology, University Hospitals, Cleveland, OH, United States
Synopsis
Magnetic Resonance Fingerprinting (MRF) is used to simultaneously map T1, T2, and spin density in the normal appearing white matter and normal appearing grey matter of multiple sclerosis patients and healthy controls. Relaxation parameters measured by MRF are found to be significantly different between MS subjects and healthy controls, to distinguish between relapsing remitting MS and secondary progressive MS in certain brain structures, and to correlate with clinical measures of function and disability.Background
Multiple sclerosis (MS) is a chronic demyelinating disease of the central nervous system and is the leading cause of non-traumatic disability among young adults.1,2 While MRI is sensitive to focal white matter lesions in relapsing forms of MS, there is a poor correlation between lesional measures and clinical disability owing to the limited pathological specificity of the method.3 Conventional MRI is not sufficiently sensitive to tissue injury in the grey matter or non-lesional tissue (normal appearing white matter,NAWM, and normal appearing grey matter, NAGM).4 There currently is also no standard quantitative method for detecting tissue change over time. Such a tool is critical for the development of neuroprotective agents for the treatment of MS. Attempts to measure T1 and T2 relaxation have been studied, but most methods require significant time expenditure for acquisition and post-processing.
Magnetic resonance fingerprinting (MRF)5 is a new quantitative MR approach that provides rapid, simultaneous estimation of multiple of tissue relaxation properties. In this work, MRF was used to measure relaxation times in NAWM and NAGM and relationships between tissue properties, brain structures, and disease states were preliminarily explored.
Methods
Nineteen subjects (8 Relapsing remitting MS (RRMS), 4 Secondary progressive MS (SPMS), 2 Clinically Isolated Syndrome (CIS), and 5 age-matched healthy controls (HC)) were scanned at 3T (Trio, Siemens Medical Solutions, Erlangen, Germany) under written informed consent in an IRB-approved study. Subjects were scanned with a FISP-based MRF sequence6 (1000 images, flip angle range 0-74°, TR range 11.1-13.7ms, 128x128 matrix, 2.3x2.3mm in-plane resolution, 5mm slice thickness, 21 slices, 1mm slice gap, imaging time 5min 15sec). Data were reconstructed and processed offline in MATLAB (The Mathworks, Natick, Massachusetts). A dictionary with 47,049 elements (T1 range 20-5000ms, T2 range 10-500ms) was used for pattern matching to generate quantitative T1, T2, and spin density (SD) maps.
Regions of Interest (ROIs) were manually drawn on MRF T1 maps in 2-3 contiguous slices for NAWM in the frontal lobe and corpus callosum (CC, genu and splenium) as well as NAGM in the caudate and thalamus. Analysis was blinded to subject type. We measured the mean T1, T2, and SD in each of 4 combined ROIs from 19 subjects. Differences between HC and MS, RRMS and HC, RRMS and SPMS were analyzed by ANCOVA. We also investigated the correlation between relaxation times and clinical measures (multiple sclerosis functional composite (MSFC) and expanded disability status scale (EDSS)).
Results
Representative conventional FLAIR, T1-weighted, and T2-weighted images from SPMS, RRMS, and HC subjects are shown in Figure 1. MRF-derived maps in these subjects are shown in Figures 2 and 3, respectively. ROIs drawn on T1 maps are indicated by yellow circles.
After correcting for multiple comparisons, significant differences were found between MS and HC in caudate T1 values (1236 vs. 1167ms, respectively, p=0.028) and frontal NAWM T2 values (63 vs. 55ms, p=0.019). Differences between SPMS and RRMS were found in T1 from the frontal NAWM (p=0.04), and both T1 and T2 from the CC (p=0.008, p=0.0005). T1 in CC correlated with both MSFC (r=-0.736, p=0.003) and EDSS (r=0.615, p=0.012) (Figure 4).
Discussion
MRF provides simultaneously acquired and intrinsically registered maps of multiple relaxation parameters. In agreement with previous T
1-mapping techniques,
7-9 we also found increased T
1 in normal-appearing structures. T
2 was increased in certain normal-appearing regions similar to prior evidence which showed changes in NAWM, but not deep grey matter structures.
10 In addition to demonstrating differences between HC and MS, MRF distinguishes the clinical course of disease. This effect is seen despite a small sample size, which could indicate a high sensitivity to detect underlying non-lesional changes in MS and may provide a window into the pathophysiology of the disease. Significant correlations with the MSFC and EDSS suggest the measures capture a clinically meaningful change in normal-appearing tissue.
Conclusion
This was the first application of MRF in MS, and the results show that quantitative MRF-based measurements differentiate MS subjects from HC, distinguish disease courses, and correlate with MS disability. Since quantitative measures are theoretically reproducible across scanners and centers, MRF may offer significant advantages over conventional MRI in the assessment of MS patients, and may be used as a potential outcome metric to measure neurodegeneration and potential neural repair in the development of agents for the treatment of MS and related diseases.
Acknowledgements
This research was supported by NIH 1R01EB016728-01A1, NIH NINDS P01 NS38667, RG 3548 (National Multiple Sclerosis Society), KL2TR000440/TR/NCATS NIH, HHS/United States, and Siemens Healthcare.References
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