Burton, P

Howell, M

Mangia, S

Michaeli, S

Nestrasil, I

Nissi, M

Shmueli, K

Sierra, A

Tuite, P

UCL Discovery

Maximizing Tissue Contrast For MRI Evaluation of Parkinson’s Disease Silvia Mangia1, Philip Burton1, Igor Nestrail1, Mikko Nissi1,2, Alejandra Sierra3, Karin Shmueli4, Michael Howell5, Paul Tuite5, and Shalom Michaeli1 1CMRR, University of Minnesota, Minneapolis, Minnesota, United States, 2University of Oulu, Oulu, Finland, 3A.I.Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland, 4University College London, London, United Kingdom, 5Department of Neurology, University of Minnesota, Minneapolis, Minnesota, United States  Introduction: There is a need for early diagnostic techniques for Parkinson’s disease (PD) as well as a means to track its course and response to experimental therapies. Following Braak et. al's hypothesis [1], it is thought that PD pathology spreads through transmission of pathogenic forms of α-synuclein protein in a caudal-rostral manner. However, to date there is no synuclein radioligand to follow this process. In addition to abnormal synuclein aggregation (which can manifest as Lewy pathology), there is iron deposition, gliosis and neuronal loss that occurs in PD. MRI, which can image brain structures as well as brain function, could conceivably map changes in tissue composition, microstructure and functional connectivity and thereby provide a comprehensive characterization of the PD brain. In this work we employed MRI modalities that are specifically sensitive to various brain tissue properties, such as microstructural integrity, iron loads, and functional connectivity. Namely, we used diffusion tensor imaging (DTI), novel rotating frame relaxation mapping methods including adiabatic T1ρ, T2ρ  [2] and RAFF4 (Relaxation Along a Fictitious Field in the rotating frame of rank 4)[3], and quantitative susceptibility mapping (QSM) [4]. Finally, we acquired resting state fMRI (rsfMRI) data [5] with the goal of correlating functional with microstructural information.  Materials and Methods:  Three mild-moderate advanced (Hoehn & Yahr Stage I-II; on medications) individuals with PD and three age matched healthy controls participated in this study and underwent MRI scanning. Scans were performed on a 3 T/ 90 cm bore, Siemens Prisma console, 64-channel receive system. Adiabatic T1ρ, T2ρ and RAFF4 measurements were collected from a 30 AC-PC aligned oblique axial slices between the brainstem and basal ganglia, whereas T1-weighted, T2-weighted images, DTI, QSM and rsfMRI were collected throughout the brain. For T1ρ, T2ρ and RAFF4 acquisitions, 30 slices in the midbrain-region were acquired with segmented GRE readout (4 segments), voxel size: 1.6 x 1.6 x 3.6 mm3, GRAPPA= 3, TE=3.18 ms; TR=2s. For adiabatic relaxation measurements, Hyperbolic Secant (HS) pulses were used, with R=10, BW=1.6 kHz, pulse duration Tp= 6 ms, ω1max /(2π) = 800 Hz, 5 acquisitions with number of pulses = 0, 4, 8, 12, 16, MLEV4 phase cycling; for RAFF4, Tp was 4.56 ms for one P-packet, number of P-packets 0, 4, 8, 12, 16, ω1max /(2π) =323 Hz. Parameters for QSM were: voxel size: 1.6 x 1.6 x 1.6 mm3, 96 slices, TR=51 ms, TE=10, 19, 27, 36, 45 ms, GRAPPA 3; Flip Angle 15o; for DTI: 128 directions, with 5 additional non-diffusion weighed (b0) images, b-value=1500s/mm2, voxel size 1.8x1.8x1.8mm3, TR=2820 ms, TE=72.6 ms; multi band (MB)=4; for rsfMRI: EPI, TR=900 ms, multi band (MB)=4; TE=30 ms; voxel size=3 x 3 x 3 mm3, matrix size=64x64, 48 AC-PC aligned single oblique axial slices with interleaved slice acquisition, 502 volumes. Seed analysis from each of the defined ROIs was performed to extract functional connectivity measures. The various MRI parameters were calculated from a set of 26 brain areas relevant for PD (Fig. 1A), and compared among the subject groups.  Results and Discussion:      Figure 1. 3D rendered and multislice images with superimposed ROIs used for extracting MRI metrics from different MRI modalities (A); Relaxation time constants maps for RAFF4, T1ρ, T2ρ, and T2* (B-D), fractional anisotropy, FA, obtained from DTI (E), and correlation maps (F) from rsfMRI.    Representative maps from one control subject are shown in Fig. 1. RAFF4 was found to have greater sensitivity than T1ρ, T2ρ, T2* and DTI to detect differences in several ROIs (such as caudate, thalamus and brainstem)(Fig. 2). T1ρ also differentiated between PD and controls in the same areas, and both RAFF4 and T1ρ methods exceeded other MRI techniques (e.g., FA and T2*) in differentiating PD from controls. The chosen MRI methodologies provide quantitative measures of a variety of relaxation, diffusion and susceptibility parameters which allow robust characterization of the microstructural properties and iron content of the brains of our subject populations.  Functional connectivity measures did not show differences between the subject groups, likely due to the limited number of subjects studied so far or related to the possibility that PD subjects were scanned while on their antiparkinsonian medications.  Conclusion: These results demonstrate the feasibility of adiabatic T1ρ, T2ρ and RAFF4 to characterize the microstructural integrity and functional connectivity of PD subjects compared to healthy controls.  Acknowledgments: NIH Grants BTRC which are P41 RR008079, P41 EB015894, P30 NS057091, R01 NS061866 and  Academy of Finland, Sigrid Juselius Foundation. References: [1] Braak H et. al, Neurobiol Aging 2003;24:197-211; [2] Michaeli S et al, Curr Anal Chem 2008;4:8-25; [3] Liimatainen Tet al. Magn Reson Med 2014:in press; [4] Shmueli K, Magn Reson Med 2009;62:1510-22; [5] Ellmore TM Sleep 2013;36:1885-92.   0200400600800100012001400TRAFF4controlsPDFigure 2. RAFF4 relaxation times measured in PD and controls in different areas of the brain. Data are mean ± SEM; left and right ROIs (where applicable) were pooled. Proc. Intl. Soc. Mag. Reson. Med. 23 (2015)    2212.

Maximizing Tissue Contrast for MRI Evaluation of Parkinson’s Disease

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Maximizing Tissue Contrast for MRI Evaluation of Parkinson’s Disease

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