- Download 80
- File Size 74.02 KB
- File Count 1
- Create Date June 22, 2018
- Last Updated June 22, 2018
Novel diffusion-derived biomarkers in Parkinson’s disease with and without freezing of gait
Virendra Mishra1, Ece Bayram1, Karthik Sreenivasan1, Xiaowei Zhuang1, Zhengshi Yang1, Christopher Bird1, Irene Litvan2, Sarah J Banks1, Dietmar Cordes1, Brent Bluett1
Background and Objective: Diffusion magnetic resonance imaging analysis (dMRI) using a bi-tensor model can estimate the fractional volume of free-water (fiso) within a voxel, and has been shown as a predictive biomarker in de-novo Parkinson’s disease (PD) patients. We investigated the brain regions thought to be affected in PD with freezing of gait (PD-FOG) using conventional single-tensor methods, fiso, and a novel weighted fractional anisotropy (FAwt), compared to PD without freezing of gait (PD-nFOG) and healthy controls (HC).
Methods: Age, gender, and education-matched 10 HC, 9 PD-FOG, and 10 PD-nFOG were recruited at our center. PD-FOG and PD-nFOG were matched on disease severity and duration. 71 direction dMRI and 8 non-diffusion encoded (b0) was acquired on a 3T Siemens Skyra scanner with three-shell (500s/mm2, 1000s/mm2, and 2500s/mm2). 1 b0 image was acquired with opposite phase-encode to correct for eddy-current distortion. 15 bilateral ROIs comprising of the cortical, striatal, and brainstem regions were used. Conventional single-tensor measures of FA, mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AxD), along with fiso, and FAwt were computed and compared between the groups.
Results: FAwt in the right putamen was significantly lower in PD-nFOG compared to PD-FOG. A significant negative association of FA in right precentral gyrus was obtained with UPDRS-ON. No difference in fiso was observed.
Discussion and Conclusions: Novel FAwt may be more sensitive than fiso identifying structural breakdown in regions associated with PD-FOG. Our study opens new avenues to understand the pathophysiology of PD-FOG with novel diffusion derived measures.
Acknowledgements: This study was supported by IDeA award from NIH under grant number 5P20GM109025.