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Updated: Jul 9, 2025
Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Published on: July 28, 2013
Traveling Subject-Informed Harmonization Increases Reliability of Brain Diffusion Tensor and Neurite Mapping
Yuya Saito1, Koji Kamagata1, Christina Andica2
1Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo Japan.
Abstract:
Diffusion-weighted magnetic resonance imaging (dMRI) of brain has helped elucidate the microstructural changes of psychiatric and neurodegenerative disorders. Inconsistency between MRI models has hampered clinical application of dMRI-based metrics. Using harmonized dMRI data of 300 scans from 69 traveling subjects (TS) scanning the same individuals at multiple conditions with 13 MRI models and 2 protocols, the widely-used metrics such as diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) were evaluated before and after harmonization with a combined association test (ComBat) or TS-based general linear model (TS-GLM). Results showed that both ComBat and TS-GLM significantly reduced the effects of the MRI site, model, and protocol for diffusion metrics while maintaining the intersubject biological effects. The harmonization power of TS-GLM based on TS data model is more powerful than that of ComBat. In conclusion, our research demonstrated that although ComBat and TS-GLM harmonization approaches were effective at reducing the scanner effects of the site, model, and protocol for DTI and NODDI metrics in WM, they exhibited high retainability of biological effects. Therefore, we suggest that, after harmonizing DTI and NODDI metrics, a multisite study with large cohorts can accurately detect small pathological changes by retaining pathological effects.
Insights
Harmonizing brain diffusion MRI metrics using ComBat or TS-GLM reduces scanner variability while preserving biological differences. TS-GLM offers superior harmonization for diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) in white matter.
Area of Science:
- Neuroimaging
- Biomedical Engineering
- Radiology
Background:
- Diffusion-weighted magnetic resonance imaging (dMRI) reveals brain microstructural changes in neurological and psychiatric disorders.
- Inconsistencies across MRI models hinder the clinical use of dMRI metrics.
- Harmonization is crucial for reliable dMRI data analysis in multi-site studies.
Purpose of the Study:
- To evaluate the effectiveness of ComBat and TS-GLM harmonization methods for dMRI metrics.
- To compare the harmonization performance of ComBat and TS-GLM.
- To assess the impact of harmonization on intersubject biological effects and scanner-induced variability.
Main Methods:
- Utilized harmonized dMRI data from 300 scans across 69 traveling subjects (TS).
- Evaluated 13 MRI models and 2 protocols, focusing on diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) metrics.
- Applied ComBat and TS-GLM harmonization techniques and compared their efficacy.
Main Results:
- Both ComBat and TS-GLM significantly reduced site, model, and protocol effects for diffusion metrics.
- TS-GLM demonstrated superior harmonization power compared to ComBat.
- Harmonization methods effectively preserved intersubject biological effects.
Conclusions:
- ComBat and TS-GLM effectively reduce scanner effects in DTI and NODDI white matter metrics.
- These harmonization approaches retain crucial biological and pathological effects.
- Harmonized dMRI metrics enable accurate detection of subtle pathological changes in large, multi-site studies.
