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Article Abstract
Background: Although diffusion gradient directions and b-values have been optimized for diffusion kurtosis imaging (DKI), little is known about the effect of signal averaging on DKI reliability.
Purpose: To evaluate how signal averaging influences the reliability of DKI indices using two gradient encoding schemes with three spatial resolutions.
Study Type: Prospective.
Animal Model: Fifteen naïve Sprague-Dawley rats.
Field Strength/sequence: DKI was performed at 7T using two schemes (30 directions with three b-values [30d-3b] and six directions with 15 b-values [6d-15b]), three resolutions, and eight repetitions.
Assessment: DKI reliability was assessed using voxelwise relative error (σ) and test-retest error of fractional anisotropy (FA), mean diffusivity (MD), and mean kurtosis (MK) within gray matter (GM) and white matter (WM). The number of excitations (NEX) was optimized by considering DKI reliability. The influence of the partial volume effect (PVE) was also assessed.
Statistical Test: One-way analysis of variance.
Results: The 30d-3b scheme, compared with the 6d-15b scheme, exhibited apparently smaller σ and σ (eg, at NEX 1, in GM, for three resolutions, σ : 19.9-38.2% vs. 34.2-61.4%, σ : 6.9-11.4% vs. 14.1-15.4%) and similar σ (all differences between two schemes <1.6%). The optimal NEX was determined as 2 for enabling a reliable measurement of DKI-derived indices. The PVE at the lowest resolution apparently increased σ for both schemes (19.9% for 30d-3b and 34.2% for 6d-15b) and σ for the 6d-15b scheme (14.7%) in GM, and exerted lower effects on MK values for the 30d-3b scheme (P > 0.05).
Data Conclusion: A higher number of diffusion directions would benefit FA and MK estimation. A higher spatial resolution helps to reduce PVE. By using the 30d-3b scheme, MK is considered a robust index to reflect microstructural changes in GM and WM. We propose a systematic approach to determine the optimal DKI protocols for appropriate preclinical settings.
Level Of Evidence: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:1593-1603.
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