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The Effect of Voxel Volume and Voxel Shape on Cardiac Diffusion Tensor Imaging Metrics.

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Title: The Effect of Voxel Volume and Voxel Shape on Cardiac Diffusion Tensor Imaging Metrics.
Authors: Hannum, Ariel J.1,2,3,4 (AUTHOR) ahannum@stanford.edu, Cork, Tyler E.1,2,3,4 (AUTHOR), Setsompop, Kawin1,5 (AUTHOR), Ennis, Daniel B.1,2,3,4 (AUTHOR)
Source: Magnetic Resonance in Medicine. Apr2026, Vol. 95 Issue 4, p2063-2077. 15p.
Subjects: Diffusion tensor imaging, Signal-to-noise ratio, Anisotropy, Volume (Cubic content), Diffusion coefficients, Physiology, TOPSIS method
Abstract: Purpose: Cardiac diffusion tensor imaging (cDTI) is signal‐to‐noise ratio (SNR)‐limited due to diffusion signal attenuation, long echo times from gradient moment nulling, and moderate myocardial T 2$$ {}_2 $$. Increasing voxel volume improves SNR but reduces spatial sensitivity and introduces physiological bias. This work aimed to identify the voxel configuration (volume and shape) yielding the most precise cDTI metrics. Methods: Spin‐echo cDTI protocols spanning nine voxel volumes were evaluated in healthy subjects (N = 11) at 3T. A gel phantom was scanned to compare SNR in a non‐physiologic environment. Temporal SNR and regression fits were computed. Mean diffusivity (MD), fractional anisotropy (FA), bootstrapped uncertainties (dMD$$ dMD $$, dFA$$ dFA $$), Helix angle pitch (HAP), and the primary eigenvector's uncertainty (de→1$$ d{\overrightarrow{e}}_1 $$) were then calculated, and significant (p<0.05$$ p<0.05 $$) differences were assessed. Technique for order preference by similarity to ideal solution (TOPSIS) ranked configurations by uncertainties. Results: Phantom SNR trends corresponded to theory, with consistent SNR increases. In vivo SNR increases differed between in‐plane resolutions, in which 2×2$$ 2\times 2 $$ mm 2$$ {}^2 $$ in‐plane resolutions had the steepest slope. Higher in‐plane resolutions (2×2$$ 2\times 2 $$ mm 2$$ {}^2 $$) yielded lower MD than lower resolutions (3×3$$ 3\times 3 $$ mm 2$$ {}^2 $$). Higher in‐plane resolutions with thicker slices produced higher FA (2×2×8$$ 2\times 2\times 8 $$ mm 3$$ {}^3 $$). HAP was steepest at moderate voxel sizes (2.5×2.5×5$$ 2.5\times 2.5\times 5 $$ mm 3$$ {}^3 $$). All uncertainties decreased with 8 mm slices. TOPSIS ranked 2.5×2.5×8$$ 2.5\times 2.5\times 8 $$ mm 3$$ {}^3 $$ highest (0.91), then 2.0×2.0×8$$ 2.0\times 2.0\times 8 $$ (0.83). Conclusion: In vivo differences in SNR slopes suggest a physiological bias‐dominated environment. The 2.5×2.5×8$$ 2.5\times 2.5\times 8 $$ mm 3$$ {}^3 $$ voxel configuration had the lowest uncertainties (highest TOPSIS score), followed by 2.0×2.0×8$$ 2.0\times 2.0\times 8 $$ mm 3$$ {}^3 $$. This work provides a framework for evaluating the best cDTI voxel configuration. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
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Abstract:Purpose: Cardiac diffusion tensor imaging (cDTI) is signal‐to‐noise ratio (SNR)‐limited due to diffusion signal attenuation, long echo times from gradient moment nulling, and moderate myocardial T 2$$ {}_2 $$. Increasing voxel volume improves SNR but reduces spatial sensitivity and introduces physiological bias. This work aimed to identify the voxel configuration (volume and shape) yielding the most precise cDTI metrics. Methods: Spin‐echo cDTI protocols spanning nine voxel volumes were evaluated in healthy subjects (N = 11) at 3T. A gel phantom was scanned to compare SNR in a non‐physiologic environment. Temporal SNR and regression fits were computed. Mean diffusivity (MD), fractional anisotropy (FA), bootstrapped uncertainties (dMD$$ dMD $$, dFA$$ dFA $$), Helix angle pitch (HAP), and the primary eigenvector's uncertainty (de→1$$ d{\overrightarrow{e}}_1 $$) were then calculated, and significant (p<0.05$$ p<0.05 $$) differences were assessed. Technique for order preference by similarity to ideal solution (TOPSIS) ranked configurations by uncertainties. Results: Phantom SNR trends corresponded to theory, with consistent SNR increases. In vivo SNR increases differed between in‐plane resolutions, in which 2×2$$ 2\times 2 $$ mm 2$$ {}^2 $$ in‐plane resolutions had the steepest slope. Higher in‐plane resolutions (2×2$$ 2\times 2 $$ mm 2$$ {}^2 $$) yielded lower MD than lower resolutions (3×3$$ 3\times 3 $$ mm 2$$ {}^2 $$). Higher in‐plane resolutions with thicker slices produced higher FA (2×2×8$$ 2\times 2\times 8 $$ mm 3$$ {}^3 $$). HAP was steepest at moderate voxel sizes (2.5×2.5×5$$ 2.5\times 2.5\times 5 $$ mm 3$$ {}^3 $$). All uncertainties decreased with 8 mm slices. TOPSIS ranked 2.5×2.5×8$$ 2.5\times 2.5\times 8 $$ mm 3$$ {}^3 $$ highest (0.91), then 2.0×2.0×8$$ 2.0\times 2.0\times 8 $$ (0.83). Conclusion: In vivo differences in SNR slopes suggest a physiological bias‐dominated environment. The 2.5×2.5×8$$ 2.5\times 2.5\times 8 $$ mm 3$$ {}^3 $$ voxel configuration had the lowest uncertainties (highest TOPSIS score), followed by 2.0×2.0×8$$ 2.0\times 2.0\times 8 $$ mm 3$$ {}^3 $$. This work provides a framework for evaluating the best cDTI voxel configuration. [ABSTRACT FROM AUTHOR]
ISSN:07403194
DOI:10.1002/mrm.70189