Evaluation of striatonigral connectivity using probabilistic tractography in Parkinson's disease

Frances Theisen, Rebecca Leda, Vincent Pozorski, Jennifer M Oh, Nagesh Adluru, Rachel Wong, Ozioma Okonkwo, Douglas C Dean 3rd, Barbara B Bendlin, Sterling C Johnson, Andrew L Alexander, Catherine L Gallagher, Frances Theisen, Rebecca Leda, Vincent Pozorski, Jennifer M Oh, Nagesh Adluru, Rachel Wong, Ozioma Okonkwo, Douglas C Dean 3rd, Barbara B Bendlin, Sterling C Johnson, Andrew L Alexander, Catherine L Gallagher

Abstract

The cardinal movement abnormalities of Parkinson's disease (PD), including tremor, muscle rigidity, and reduced speed and frequency of movements, are caused by degeneration of dopaminergic neurons in the substantia nigra that project to the putamen, compromising information flow through frontal-subcortical circuits. Typically, the nigrostriatal pathway is more severely affected on the side of the brain opposite (contralateral) to the side of the body that manifests initial symptoms. Several studies have suggested that PD is also associated with changes in white matter microstructural integrity. The goal of the present study was to further develop methods for measuring striatonigral connectivity differences between PD patients and age-matched controls using diffusion weighted magnetic resonance imaging (MRI). In this cross-sectional study, 40 PD patients and 44 controls underwent diffusion weighted imaging (DWI) using a 40-direction MRI sequence as well as an optimized 60-direction sequence with overlapping slices. Regions of interest (ROIs) encompassing the putamen and substantia nigra were hand drawn in the space of the 40-direction data using high-contrast structural images and then coregistered to the 60-direction data. Probabilistic tractography was performed in the native space of each dataset by seeding the putamen ROI with an ipsilateral substantia nigra classification target. The effect of disease group (PD versus control) on mean putamen-SN connection probability and streamline density were then analyzed using generalized linear models controlling for age, gender, education, as well as seed and target region characteristics. Mean putamen-SN streamline density was lower in PD on both sides of the brain and in both 40- and 60-direction data. The optimized sequence provided a greater separation between PD and control means; however, individual values overlapped between groups. The 60-direction data also yielded mean connection probability values either trending (ipsilateral) or significantly (contralateral) lower in the PD group. There were minor between-group differences in average diffusion measures within the substantia nigra ROIs that did not affect the results of the GLM analyses when included as covariates. Based on these results, we conclude that mean striatonigral structural connectivity differs between PD and control groups and that use of an optimized 60-direction DWI sequence with overlapping slices increases the sensitivity of the technique to putative disease-related differences. However, overlap in individual values between disease groups limits its use as a classifier.

Keywords: ADRC, Alzheimer's Disease Research Center; AFNI, Analysis of Functional NeuroImages; Aged brain/metabolism/*pathology; BET, brain extraction tool; DWI, diffusion-weighted imaging; Diffusion tensor imaging/*methods; FA, fractional anisotropy; FLAIR, fluid attenuated inversion recovery; FOV, field of view; FSL, Oxford Centre for Functional MRI of the Brain Software Library; GE, general electric; HY, Hoehn and Yahr; Humans; ICC, interclass correlation coefficient; IRB, institutional review board; LMPD, longitudinal MRI biomarkers in Parkinson's disease study; MD, mean diffusivity; MRI, magnetic resonance imaging; PD, Parkinson's disease; PET, Positron Emission Tomography; Parkinson disease/classification/*pathology; RD, radial diffusivity; ROI, region of interest; SD, standard deviation; SN, substantia nigra; SNR, signal to noise ratio; SPECT, single photon emission tomography; SPM, Statistical Parametric Mapping software; Severity of illness index; TE, echo time; TFCE, threshold-free cluster enhancement; TI, inversion time; TR, repetition time; UPDRS, Unified Parkinson Disease Rating Scale; VA, Veterans Affairs.

Figures

Fig. 1
Fig. 1
Method for Defining Regions of Interest (ROIs). 1. High contrast structural images were coregistered to the 40-direction DWI data. 2. The putamen ROI (blue, upper left) was outlined on sequential T1-weighted axial images extending from top of lateral ventricles to the anterior commissure. 3. The substantia nigra (SN) ROI (red, lower left) was outlined on axial FLAIR images from the level of the red nucleus to superior cerebellar peduncle. 4. The putamen and SN ROIs were inspected and revised against the 40-direction FA maps (center). 5. Putamen and SN ROIs were coregistered to the 60-direction DWI data (right) and visually inspected against the 60-direction FA map.
Fig. 2
Fig. 2
Probabilistic Tractography in a Parkinson's subject. A substantia nigra (SN) target region (red) and result map (blue/orange) from the probabilistic tracking approach are shown superimposed on the 60-direction FA map. The inset at right shows the magnified result map, in which blue areas represent voxels in the seed ROI (putamen) that do not generate streamlines and thus have values of zero. Values of the yellow-orange voxels (color scale at right) represent the number of seeding events (of 5000 trials) that reach the SN.
Fig. 3
Fig. 3
Streamline density measures from 40- and 60- direction DWI data. The distribution of the streamline density index for controls (averaged across brain hemispheres) in comparison to PD for brain hemispheres ipsilateral (Ipsi) and contralateral (Contra) to initial motor symptoms. Horizontal bars indicate the mean and SD for each distribution. Although means were significantly different between disease groups (40-direction P 

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