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Updated: Apr 19, 2026
Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Published on: July 28, 2013
Diffusion tensor imaging parameters' changes of cerebellar hemispheres in Parkinson's disease
Enricomaria Mormina1, Alessandro Arrigo, Alessandro Calamuneri
1Department of Biomedical Science and Morphological and Functional Images, University of Messina, via Consolare Valeria, 1 c/o A.O.U. Policlinico "G. Martino", 98125, Messina, Italy.
Introduction:
Studies with diffusion tensor imaging (DTI) analysis have produced conflicting information about the involvement of the cerebellar hemispheres in Parkinson's disease (PD). We, thus, used a new approach for the analysis of DTI parameters in order to ascertain the involvement of the cerebellum in PD.
Methods:
We performed a fiber tract-based analysis of cerebellar peduncles and cerebellar hemispheres in 16 healthy subjects and in 16 PD patients with more than 5 years duration of disease, using a 3T MRI scanner and a constrained spherical deconvolution (CSD) approach for tractographic reconstructions. In addition, we performed statistical analysis of DTI parameters and fractional anisotropy (FA) XYZ direction samplings.
Results:
We found a statistically significant decrement of FA values in PD patients compared to controls (p < 0.05). In addition, extrapolating and analyzing FA XYZ direction samplings for each patient and each control, we found that this result was due to a stronger decrement of FA values along the Y axis (antero-posterior direction) (p < 0.01); FA changes along X and Z axes were not statistically significant (p > 0.05). We confirmed also no statistically significant differences of FA and apparent diffusion coefficient (ADC) for cerebellar peduncles in PD patients compared to healthy controls.
Conclusions:
The DTI-based cerebellar abnormalities in PD could constitute an advance in the knowledge of this disease. We demonstrated a statistically significant reduction of FA in cerebellar hemispheres of PD patients compared to healthy controls. Our work also demonstrated that the use of more sophisticated approaches in the DTI parameter analysis could potentially have a clinical relevance.
