Next move in movement disorders: neuroimaging protocols for hyperkinetic movement disorders

Area of Science:

• Neuroscience
• Medical Imaging
• Machine Learning

Background:

• Hyperkinetic movement disorders, including tremor, myoclonus, dystonia, and myoclonus-dystonia, present complex diagnostic challenges.
• Current understanding of the brain pathophysiology underlying these disorders requires further elucidation.
• The Next Move in Movement Disorders (NEMO) study was initiated to address these knowledge gaps.

Purpose of the Study:

• To develop a computer-aided tool for precise and consistent classification of hyperkinetic movement disorder phenotypes.
• To deepen the understanding of brain pathophysiology in movement disorders using advanced neuroimaging techniques.
• To establish a standardized neuroimaging approach for future comparative studies.

Main Methods:

• Utilized multiple neuroimaging modalities: T1-weighted structural MRI, resting-state fMRI, motor task fMRI, and 18F-FDG PET scans.
• Focused on enhancing data quality by addressing challenges such as head motion during acquisition.
• Developed standardized data preprocessing pipelines for consistent analysis.

Main Results:

• The study outlines procedures for acquiring and preprocessing multimodal neuroimaging data.
• Standardized approach is established for the first time across these specific patient groups.
• Data collected will inform the development of a machine learning classification tool.

Conclusions:

• The NEMO study protocol details a pioneering approach to applying machine learning in movement disorder research.
• The collected neuroimaging data will significantly contribute to understanding disorder-specific neurobiology.
• Findings are expected to advance the classification and treatment of hyperkinetic movement disorders.