Key result
Thirty-direction cDTI reduces RMSD by ~41% vs six directions.
Why the study?
Cardiac diffusion tensor imaging is sensitive to imaging parameters including diffusion encoding directions and repetitions, but clear clinical guidance for optimising these parameters is lacking.
Does prioritizing the number of diffusion encoding directions over repetitions improve the accuracy and precision of cardiac diffusion tensor imaging in healthy volunteers?
Does prioritizing the number of diffusion encoding directions over repetitions improve the accuracy and precision of cardiac diffusion tensor imaging in healthy volunteers?
In cardiac diffusion tensor imaging, prioritizing the number of diffusion encoding directions over repetitions and acquiring sufficient low b-value data improves the accuracy and precision of imaging parameters.
Answers are grounded in this paper and cite their sources.
Optimizing diffusion directions may enhance cardiac DTI accuracy in volunteers; hypothesis-generating for protocol refinement pending patient validation.
Background Cardiac diffusion tensor imaging (cDTI) is sensitive to imaging parameters including the number of unique diffusion encoding directions (ND) and number of repetitions (NR; analogous to number of signal averages or NSA). However, there is no clear guidance for optimising these parameters in the clinical setting. Methods Spin echo cDTI data with 2 nd order motion compensated diffusion encoding gradients were acquired in ten healthy volunteers on a 3T MRI scanner with different diffusion encoding schemes in pseudo-randomised order. The data were subsampled to yield 96 acquisition schemes with 6 ≤ ND ≤ 30 and 33 ≤ total number of acquisitions (NA all ) ≤ 180. Stratified bootstrapping with robust fitting was performed to assess the precision and accuracy of each acquisition scheme. This was quantified across a mid-ventricular short-axis slice in terms of root mean squared difference (RMSD) with respect to the full reference dataset, and standard deviation (SD) across bootstrap samples respectively. Results For the same acquisition time, the ND = 30 schemes had on average 48%, 40%, 34% and 34% lower RMSD and 6.2%, 7.4%, 10% and 5.6% lower SD in MD, FA, HA and E2A compared to the ND = 6 schemes. Given a fixed number of high b-value acquisitions, there was a trend towards lower RMSD and SD of MD and FA with increasing numbers of low b-value acquisitions. Higher NA all with longer acquisition times led to improved accuracy in all metrics whereby quadrupling NA all from 40 to 160 volumes led to a 21%, 40%, 13% and 4.5% reduction in RMSD of MD, FA, HA and E2A, averaged across six diffusion encoding schemes. Precision was also improved with a corresponding 53%, 50%, 52% and 36% reduction in SD. Conclusions We observed that accuracy and precision were enhanced by (i) prioritising number of diffusion encoding directions over number of repetitions given a fixed acquisition time, (ii) acquiring sufficient low b-value data, (iii) using longer protocols where feasible. For clinically relevant protocols, our findings support the use of ND = 30 and NA b50 :NA b500 ≥ 1/3 for better accuracy and precision in cDTI parameters. These findings are intended to help guide protocol optimisation for harmonisation of cDTI.
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Coveney et al. (2025) studied Healthy volunteers (n=10). 30 diffusion encoding directions (ND = 30) vs. 6 diffusion encoding directions (ND = 6) was evaluated on Root mean squared difference (RMSD) and standard deviation (SD) in cDTI parameters. Using 30 diffusion encoding directions for cardiac diffusion tensor imaging compared to 6 directions reduced root mean squared difference by 34-48% and standard deviation by 5.6-10%.
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