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A Multimodal Imaging- and Stimulation-based Method of Evaluating Connectivity-related Brain Excitability in Patients with Epilepsy
Published on: November 13, 2016
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Image data harmonization tools for the analysis of post-traumatic epilepsy development in preclinical multisite MRI
Sweta Bhagavatula1, Ryan Cabeen1, Neil G Harris2
1USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA.
Epilepsy Research
|August 10, 2023
Summary
Multisite preclinical MRI data harmonization is crucial for identifying biomarkers of post-traumatic epilepsy (PTE). Standardizing imaging data across international sites enhances statistical power and data sharing for epilepsy research.
Area of Science:
- Neuroscience
- Medical Imaging
- Bioinformatics
Background:
- Preclinical MRI studies are vital for discovering biomarkers predicting post-traumatic epilepsy (PTE).
- Single-site studies often lack statistical power due to limited, homogeneous datasets.
- Multisite studies, like EpiBioS4Rx, generate large, heterogeneous datasets for robust findings.
Purpose of the Study:
- To describe the tools and procedures for harmonizing multisite, multimodal preclinical imaging data.
- To ensure statistically significant and generalizable results from international collaborative studies.
- To enable cohesive data analysis and strengthen statistical power in preclinical epilepsy research.
Main Methods:
- Utilized Python tools and bash scripts for harmonizing file formats, naming conventions, and coordinate systems.
- Implemented diffusion tensor imaging (DTI) metrics harmonization by estimating voxel values to generate histograms.
- Employed Quantitative Imaging Toolkit (QIT) modules to scale DTI metric histograms and standardize data.
Main Results:
- Qualitatively assessed and confirmed the standardization of file formats, naming conventions, coordinate systems, and DTI metrics.
- Generated DTI metric histograms for individual rodents and averaged scans per site for inter-site analysis.
- Demonstrated consistent harmonization factors across sham and traumatic brain injury (TBI) cohorts.
Conclusions:
- The described harmonization processes effectively standardize multisite, multimodal preclinical imaging data.
- Standardization facilitates data sharing and strengthens the statistical power of multisite research.
- Disseminated tools and procedures can benefit broader research communities analyzing complex imaging datasets.
