Diffusion tensor imaging in Parkinson's disease: Review and meta-analysis

Abstract

Background: Neuroimaging studies help us better understand the pathophysiology and symptoms of Parkinson's disease (PD). In several of these studies, diffusion tensor imaging (DTI) was used to investigate structural changes in cerebral tissue. Although data have been provided as regards to specific brain areas, a whole brain meta-analysis is still missing.

Methods: We compiled 39 studies in this meta-analysis: 14 used fractional anisotropy (FA), 1 used mean diffusivity (MD), and 24 used both indicators. These studies comprised 1855 individuals, 1087 with PD and 768 healthy controls. Regions of interest were classified anatomically (subcortical structures; white matter; cortical areas; cerebellum). Our statistical analysis considered the disease effect size (D_ES) as the main variable; the heterogeneity index (I²) and Pearson's correlations between the D_ES and co-variables (demographic, clinical and MRI parameters) were also calculated.

Results: Our results showed that FA-D_ES and MD-D_ES were able to distinguish between patients and healthy controls. Significant differences, indicating degenerations, were observed within the substantia nigra, the corpus callosum, and the cingulate and temporal cortices. Moreover, some findings (particularly in the corticospinal tract) suggested opposite brain changes associated with PD. In addition, our results demonstrated that MD-D_ES was particularly sensitive to clinical and MRI parameters, such as the number of DTI directions and the echo time within white matter.

Conclusions: Despite some limitations, DTI appears as a sensitive method to study PD pathophysiology and severity. The association of DTI with other MRI methods should also be considered and could benefit the study of brain degenerations in PD.

Keywords: Diffusion tensor imaging; Fractional anisotropy; Idiopathic Parkinson's disease; Mean diffusivity; Neuroimaging.

Fig. 1

Study selection for the meta-analysis. *No data available: for these studies, the means and standard deviations of FA and MD, for healthy controls and PD patients, were not directly available in the articles. **Surgical studies: these articles involved PD patients with brain lesions.

Fig. 2

Brain areas identified following the meta-analysis and associated with significant differences between PD patients and healthy controls for FA-D_ES and MD-D_ES, performed together or separately. The framed results correspond to an opposite pattern of results (i.e. FA-D_ES increase and MD-D_ES decrease for the corticospinal tract; FA-D_ES increase for the caudate nucleus).

Fig. 3

Significant positive (red) and negative (blue) correlations between the main variables (FA-D_ES and MD-D_ES) and the selected co-variables, according to the pre-defined anatomical clusters. How to read this figure? For example: in cortical areas, there is a positive correlation between the FA-D_ES and the voxel size used for the MRI acquisition of the DTI and in white matter, there is a negative correlation between the MD-D_ES and the age of the participants. The larger the dot, the stronger the correlation. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Fig. 4

FA-D_ES (in pink) and MD-D_ES (in green) in the Substantia Nigra of PD patients with (On) and without (Off) medication.Each dot corresponds to the Z-scored D_ES calculated from the data provided by the selected studies. The more FA dots there are on the left, the smaller the FA is for PD patients compared with healthy controls. D_ES: disease effect size (Z-scored); FA: fractional anisotropy; MD: Mean diffusivity.