Vascular parkinsonism (VP) is a parkinsonian syndrome characterized by lower body parkinsonism, marked gait difficulty, less tremor, less rigidity, better hand dexterity, relatively symmetrical symptomatic distribution, association with pyramidal tract signs, more frequent dementia, and poor response to levodopa treatment compared with Parkinson disease (PD).
1,2 The syndrome was first described by Critchley
3 in 1929 and is now generally accepted as a clinical entity
4,5 for which proper diagnostic criteria have been proposed.
6,7 Vascular parkinsonism is typically associated with multiple cerebral infarctions in basal ganglia or extensive white matter (WM) changes, or a combination of both, as shown on magnetic resonance imaging (MRI) and computed tomographic (CT) scans. The brain imaging changes have been shown to correlate with postmortem pathological changes.
2,8,9 Unfortunately, little is known about associations between the clinical status of VP and WM microstructural properties derived from imaging data for specific fiber bundles. Existing reports on VP are based on more conventional imaging protocols (eg, T2-weighted MRI) and can therefore only reveal nonspecific global structural WM abnormalities in these patients.
8-11 In addition, apparently similar vascular lesions noted on brain imaging data may be associated with parkinsonism in some patients, but not in others.
2,10,12 Recent developments of diffusion tensor imaging (DTI)
13-15 permit us to study directly the involvement of anatomically well-defined fiber tracts in VP patients. With DTI, the directionality and magnitude of random water movement in tissue can be estimated yielding several quantitative measures, such as the 3 principle diffusivities (ie, the eigenvalues of the diffusion tensor λ1 > λ2 > λ3), mean diffusivity ([λ1 + λ2 + λ3]/3 [MD]), transverse diffusivity ([λ2 + λ3]/2), axial diffusivity (λ1), and the degree of diffusion anisotropy (eg, the fractional anisotropy [FA]).
14 Without barriers, water molecules move uniformly in all directions, which results in isotropic diffusion. By contrast, in the presence of barriers, such as cell membranes, nerve fibers, or myelin sheets, the diffusion rate is typically larger in one direction than in another, which is then referred to as anisotropic diffusion.
16 Being quantitative in nature, these DTI-based measures are more sensitive to tissue abnormalities than the typical visual evaluation of WM hyperintensities observed in conventional MRI data.
17,18 To date, DTI studies have revealed WM alterations through measurements of decreased FA and/or increased MD in a variety of conditions, including aging,
18-20 multiple sclerosis,
21 schizophrenia,
22 traumatic brain injury,
23,24 amyotrophic lateral sclerosis,
25 and Alzheimer disease.
26 For an in-depth discussion of DTI and a more detailed description of several diffusion metrics (eg, FA and MD), we refer the interested reader to a recent review by Tournier et al.
15 In the present work, we investigated WM microstructural properties with DTI and associated the observed abnormalities in VP patients with the status or score of their clinical symptoms or signs. To this end, we applied (1) a global analysis (highly sensitive but not specific); (2) a voxel-based analysis (regionally specific but with relatively low sensitivity); and (3) a tract-based analysis (fiber bundle specific with relatively high sensitivity).
27 By combining these 3 complementary approaches to analyze the same data sets, we can provide a robust and more complete picture of the observed findings.