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Diffusion Imaging in the Rat Cervical Spinal Cord
Published on: April 7, 2015
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Adaptive anisotropic gaussian filtering to reduce acquisition time in cardiac diffusion tensor imaging
Ria Mazumder1,2, Bradley D Clymer1, Xiaokui Mo3
1Department of Electrical and Computer Engineering, The Ohio State University, 205 Dreese Laboratories, 2015 Neil Avenue, Columbus, OH, 43210, USA.
The International Journal of Cardiovascular Imaging
|February 5, 2016
Summary
A novel 3D adaptive anisotropic Gaussian filter (AAGF) reduces diffusion tensor imaging (DTI) acquisition time for myocardial helical angle (HA) mapping. This method achieves accurate HA quantification with fewer excitations (NEX) and diffusion encoding directions (DED), preserving microstructural integrity.
Area of Science:
- Cardiovascular Imaging
- Biomedical Engineering
- Diffusion Tensor Imaging
Background:
- Diffusion tensor imaging (DTI) quantifies myocardial fiber orientation via helical angles (HA).
- Accurate HA measurements typically require high numbers of excitations (NEX) and diffusion encoding directions (DED), increasing acquisition time (TA).
- Reducing TA is crucial for clinical applicability and patient comfort.
Purpose of the Study:
- To introduce and evaluate a 3D adaptive anisotropic Gaussian filter (AAGF) for reducing TA in DTI-based HA mapping.
- To assess the efficacy of AAGF in preserving myocardial microstructure integrity.
- To compare AAGF performance against traditional mean (AVF) and median filters (MF).
Main Methods:
- DTI data were acquired from ex-vivo healthy and infarcted porcine hearts with varying NEX and DED.
- AAGF, AVF, and MF were applied to diffusion tensor primary eigenvectors before HA estimation.
- Quantitative metrics including RMSE, concordance correlation coefficients, and Bland-Altman analysis were used for comparison.
Main Results:
- AAGF demonstrated lower root mean square error (RMSE) in HA estimation compared to AVF and MF.
- Post-filtering with AAGF, fewer DED and NEX were needed to obtain high-integrity HA maps.
- AAGF successfully preserved pathological alterations in HA orientation in myocardial infarction models.
Conclusions:
- The 3D AAGF effectively reduces acquisition time for DTI-based HA mapping.
- AAGF maintains the integrity of myocardial microstructure and accurately reflects pathological changes.
- This filtering technique offers a promising approach for efficient and accurate cardiac DTI analysis.
