Abstract
Structural brain white matter (WM) changes such as axonal caliber, density, myelination, and orientation, along with WM-dependent structural connectivity, may be impacted early in Parkinson disease (PD). Diffusion magnetic resonance imaging (dMRI) has been used extensively to understand such pathological WM changes, and the focus of this systematic review is to understand both the methods utilized and their corresponding results in the context of early-stage PD. Diffusion tensor imaging (DTI) is the most commonly utilized method to probe WM pathological changes. Previous studies have suggested that DTI metrics are sensitive in capturing early disease-associated WM changes in preclinical symptomatic regions such as olfactory regions and the substantia nigra, which is considered to be a hallmark of PD pathology and progression. Postprocessing analytic approaches include region of interest–based analysis, voxel-based analysis, skeletonized approaches, and connectome analysis, each with unique advantages and challenges. While DTI has been used extensively to study WM disorganization in early-stage PD, it has several limitations, including an inability to resolve multiple fiber orientations within each voxel and sensitivity to partial volume effects. Given the subtle changes associated with early-stage PD, these limitations result in inaccuracies that severely impact the reliability of DTI-based metrics as potential biomarkers. To overcome these limitations, advanced dMRI acquisition and analysis methods have been employed, including diffusion kurtosis imaging and q-space diffeomorphic reconstruction. The combination of improved acquisition and analysis in DTI may yield novel and accurate information related to WM-associated changes in early-stage PD. In the current article, we present a systematic and critical review of dMRI studies in early-stage PD, with a focus on recent advances in DTI methodology. Yielding novel metrics, these advanced methods have been shown to detect diffuse WM changes in early-stage PD. These findings support the notion of early axonal damage in PD and suggest that WM pathology may go unrecognized until symptoms appear. Finally, the advantages and disadvantages of different dMRI techniques, analysis methods, and software employed are discussed in the context of PD-related pathology.
Highlights
Parkinson disease (PD) is a chronic progressive neurodegenerative disease that affects more than 10 million people worldwide [1,2,3]
Parkinson disease pathology is characterized by Lewy body aggregates and neurites [4, 5], which play a causative role in degeneration of dopaminergic neurons in the substantia nigra (SN); motor symptoms associated with PD have been primarily attributed to this process [6]
The diffusion tensor is completely characterized by these eigenvalues, which describe the length of the three axes of the diffusion ellipsoid, and their corresponding eigenvectors, which describe the orientation of these axes in space
Summary
Parkinson disease (PD) is a chronic progressive neurodegenerative disease that affects more than 10 million people worldwide [1,2,3]. Imaging-based biomarkers for PD can yield insight into atrophy, microstructural changes, neuronal activity, and vascular hemodynamics. Altered patterns of neuronal activation, measured via functional MRI (fMRI), have been observed in multiple regions of the cortex in PD using a range of motoric tasks [12,13,14]. Resting-state fMRI is measured in the absence of tasks and can identify abnormalities in spontaneous neuronal activity [15]. This approach has revealed changes in the corticosubcortical functional connectivity in PD compared with healthy controls (HCs) [16]
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