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Structural and Functional MRI in Familial Parkinson's Disease
1Movement Disorders Unit, Neurological Institute, Tel Aviv Medical Center, Tel Aviv, Israel; Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel; Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.
International Review of Neurobiology
|November 10, 2018
Summary
Genetic Parkinson disease (PD) research benefits from neuroimaging. This review explores magnetic resonance imaging (MRI) applications for genetically determined PD patients and at-risk relatives, aiming to identify biomarkers.
Area of Science:
- Neuroscience
- Genetics
- Medical Imaging
Background:
- 10-15% of Parkinson disease (PD) cases are linked to over 40 identified genetic mutations.
- Genetic PD provides unique patient cohorts for studying disease mechanisms and at-risk populations.
- Neuroimaging, particularly MRI, offers potential for early diagnosis, detection, and progression monitoring in PD.
Purpose of the Study:
- To review current neuroimaging options for genetically determined Parkinson disease.
- To summarize findings in genetically PD patients and their asymptomatic first-degree relatives.
- To explore potential compensatory mechanisms and future directions for MRI in genetic PD research.
Main Methods:
- Comprehensive review of structural and functional magnetic resonance imaging (MRI) techniques.
- Analysis of existing literature on MRI findings in genetically determined PD and at-risk individuals.
- Discussion of challenges in developing unified imaging biomarkers due to diverse methodologies.
Main Results:
- Structural and functional MRI show promise in aiding PD diagnosis and tracking disease progression.
- Studies in genetically determined PD and relatives reveal potential imaging biomarkers.
- Variability in imaging techniques and analysis hinders the establishment of a universal biomarker.
Conclusions:
- MRI is a valuable tool for researching genetic Parkinson disease, offering insights into disease mechanisms.
- Further research is needed to standardize MRI approaches and develop reliable imaging biomarkers.
- Understanding compensatory mechanisms in at-risk individuals can inform early intervention strategies.