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Is Diffusion Tensor Imaging a Good Biomarker for Early Parkinson's Disease?
Rachel P Guimarães1,2, Brunno M Campos2, Thiago J de Rezende3
1Department of Neurology, University of Campinas, Campinas, Brazil.
Frontiers in Neurology
|September 7, 2018
Summary
Diffusion tensor imaging (DTI) can differentiate Parkinson's disease stages and track progression, but is less effective for early detection of white matter changes.
Area of Science:
- Neuroimaging
- Neurology
- Biomedical Engineering
Background:
- Parkinson's disease (PD) is a neurodegenerative disorder characterized by motor and non-motor symptoms.
- White matter abnormalities are increasingly recognized in PD, but their early detection remains challenging.
Purpose of the Study:
- To assess white matter integrity in Parkinson's disease using diffusion tensor imaging (DTI).
- To evaluate DTI's utility in differentiating disease stages and detecting early alterations in PD.
Main Methods:
- 132 PD patients and 137 healthy controls underwent MRI.
- Tract-Based Spatial Statistics (TBSS) and Region of Interest (ROI) analysis with tractography were performed.
- Patients were categorized into early, moderate, and severe PD groups.
Main Results:
- TBSS revealed widespread white matter abnormalities in PD patients, including reduced fractional anisotropy (FA) and increased axial diffusivity (AD) and radial diffusivity (RD).
- ROI analysis showed significant abnormalities across all tracts, particularly in the severe PD group compared to controls and milder stages.
- Abnormalities were most pronounced in severe PD, suggesting DTI's limited sensitivity for early-stage detection.
Conclusions:
- DTI is not optimal for detecting early white matter changes in PD.
- DTI can effectively differentiate between PD disease stages and serves as a valuable marker for disease progression.
- DTI holds potential for use in clinical trials as a surrogate marker for assessing PD progression.