Optimization of Scan Parameters to Reduce Acquisition Time for Diffusion Kurtosis Imaging at 1.5T

Abstract

Purpose: To shorten acquisition of diffusion kurtosis imaging (DKI) in 1.5-tesla magnetic resonance (MR) imaging, we investigated the effects of the number of b-values, diffusion direction, and number of signal averages (NSA) on the accuracy of DKI metrics.Methods: We obtained 2 image datasets with 30 gradient directions, 6 b-values up to 2500 s/mm 2 , and 2 signal averages from 5 healthy volunteers and generated DKI metrics, i.e., mean, axial, and radial kurtosis (MK, K ¬ , and K ¦ ) maps, from various combinations of the datasets. These maps were estimated by using the intraclass correlation coefficient (ICC) with those from the full datasets.Results: The MK and K ¦ maps generated from the datasets including only the b-value of 2500 s/mm 2 showed excellent agreement (ICC, 0.96 to 0.99). Under the same acquisition time and diffusion directions, agreement was better of MK, K ¬ , and K ¦ maps obtained with 3 b-values (0, 1000, and 2500 s/mm 2 ) and 4 signal averages than maps obtained with any other combination of numbers of b-value and varied NSA. Good agreement (ICC > 0.6) required at least 20 diffusion directions in all the metrics.Conclusion: MK and K ¦ maps with ICC greater than 0.95 can be obtained at 1.5T within 10 min (b-value = 0, 1000, and 2500 s/mm 2 ; 20 diffusion directions; 4 signal averages; slice thickness, 6 mm with no interslice gap; number of slices, 12).

Toward quantitative fast diffusion kurtosis imaging with b‐values chosen in consideration of signal‐to‐noise ratio and model fidelity

“…Instead, we analyzed data based on two different average numbers to represent low and high signal‐to‐noise ratios, respectively. Second, the number and interval of b‐values were not numerically optimized . Note that the optimization is also dependent on signal‐to‐noise ratio which varies from study to study.…”

Effects of signal averaging, gradient encoding scheme, and spatial resolution on diffusion kurtosis imaging: An empirical study using 7T MRI

“…Yan et al 19 reported that an optimized sampling scheme with three b-values (0, 1000, 2500 s/mm 2 ) achieved similar accuracy with time efficiency in stroke patients compared with the scheme with six equally spaced b-values (from 0 to 2500 s/mm 2 ). Yokosawa et al 20 reported that MK and RK estimations obtained from a dataset of 20 directions and three b-values highly agreed with those obtained from a dataset of 30 directions and six b-values. On clinical systems, Fukunaga et al 21 investigated the use of different b-values and diffusion directions combined with varied diffusion times for optimizing the DKI protocol and suggested the use of 20 directions, three b-values, and a longer diffusion time with a clinically relevant spatial resolution.…”

“…12,13 With this protocol, DKI has a longer scan time than does DTI, and this has considerably limited the clinical usability of DKI. For reducing the scan time, previous studies 11,12,[19][20][21][22][23][24][25] have explored the effects of the number of b-values, b-value sampling schemes, and number of diffusion directions on DKI indices. Jensen and Helpern 13 suggested the use of 30 directions and three b-values (0, 1000, 2000 s/mm 2 ) as a standard DKI protocol for the brain in order to efficiently achieve accurate DKI estimation.…”

Detection of changes in the periaqueductal gray matter of patients with episodic migraine using quantitative diffusion kurtosis imaging: preliminary findings

“…Diffusion metric maps, such as mean kurtosis (MK), FA, and mean diffusivity (MD), were calculated using an in-house software program that was developed by one of the authors (S.Y.) and 6 was used in previous studies [13,14]. These maps were then non-linearly registered to the Johns Hopkins University Eve (JHU-Eve) atlas template of DiffeoMap Ver.…”

“…DKI source images were obtained using a single-shot spin-echo echo-planar imaging (EPI) technique with the following scanning parameters, which were optimized by a previous study [13] …”