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Bridging Huntington's disease research with big data science: Harmonized neuroimaging datasets from multiple studies
Dorian Pustina1, Sandhitsu Das2, Dan Rozelle3
1CHDI Management, Inc. (the company that manages the scientific activities of CHDI Foundation, Inc.), Princeton, NJ, United States.
Imaging Neuroscience (Cambridge, Mass.)
|August 13, 2025
Summary
This study presents a new platform for harmonizing Huntington's disease (HD) neuroimaging data, making it accessible for research. The platform standardizes data formats and combines information from multiple studies for easier analysis.
Area of Science:
- Neuroscience
- Medical Imaging
- Data Science
Background:
- Publicly available neuroimaging datasets for Huntington's disease (HD) exist but suffer from format inconsistencies, missing metadata, and data corruption.
- These limitations hinder collaborative research and the full utilization of valuable HD neuroimaging data.
Purpose of the Study:
- To develop and present a centralized platform for curating, harmonizing, and distributing neuroimaging datasets from multiple Huntington's disease studies.
- To improve data accessibility and usability for the research community by standardizing data formats and quality control.
Main Methods:
- Integrated neuroimaging data from eight distinct Huntington's disease studies.
- Converted raw data into the Brain Imaging Data Structure (BIDS) format.
- Utilized processing pipelines like Freesurfer and fmriprep for processed data.
- Combined longitudinal data from studies tracking the same participants.
Main Results:
- Created a unified platform offering three levels of data access: raw, processed, and harmonized.
- Generated six final BIDS-compliant datasets encompassing 2,216 participants and 7,073 sessions.
- Successfully harmonized data from TRACK-HD, TRACKOn-HD, PREDICT-HD, IMAGE-HD, HD-YAS, SHIELD-HD, PEARL-HD, and LONGPDE10 studies.
Conclusions:
- The developed platform significantly enhances the accessibility and utility of Huntington's disease neuroimaging data.
- Established a robust framework for future data management and sharing in HD research.
- Provides a valuable resource for advancing our understanding of Huntington's disease through standardized neuroimaging analysis.
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