Evaluation of optimized b-value sampling schemas for diffusion kurtosis imaging with an application to stroke patient data

Abstract

Diffusion kurtosis imaging (DKI) is a new method of magnetic resonance imaging (MRI) that provides non-Gaussian information that is not available in conventional diffusion tensor imaging (DTI). DKI requires data acquisition at multiple b-values for parameter estimation; this process is usually time-consuming. Therefore, fewer b-values are preferable to expedite acquisition. In this study, we carefully evaluated various acquisition schemas using different numbers and combinations of b-values. Acquisition schemas that sampled b-values that were distributed to two ends were optimized. Compared to conventional schemas using equally spaced b-values (ESB), optimized schemas require fewer b-values to minimize fitting errors in parameter estimation and may thus significantly reduce scanning time. Following a ranked list of optimized schemas resulted from the evaluation, we recommend the 3b schema based on its estimation accuracy and time efficiency, which needs data from only 3 b-values at 0, around 800 and around 2600 s/mm2, respectively. Analyses using voxel-based analysis (VBA) and region-of-interest (ROI) analysis with human DKI datasets support the use of the optimized 3b (0, 1000, 2500 s/mm2) DKI schema in practical clinical applications.

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

“…In this study, the accuracy was substantially higher of DKI maps obtained from the dataset with the bvalue combination of 0, 1000, and 2500 s/mm 2 than with the combination of 0, 1000, and 2000 s/mm 2 , indicating that uneven intervals will satisfy the requirement for both high accuracy and short acquisition time. Our findings agreed with the previous study 20 that demonstrated that b-values at uneven intervals are optimal for the accuracy of the MK map. Our results further confirmed that those bvalues are also optimal for the accuracy of K ¬ and K ¦ maps.…”

State-of-the-art MRI techniques in neuroradiology: principles, pitfalls, and clinical applications

“…For comparison between DWI, DTI, and DKI, see Table 1. Several recent studies demonstrate that DKI in general has even higher accuracy as compared to DTI in various diseases including brain neoplasm [20,21], stroke [3,22,23], or neurodegenerative disorders [24][25][26][27][28]. This added diagnostic accuracy however has the price of longer acquisition times, which may among other problems increase head motion artifacts in patients.…”

Effects ofSYN1Q555Xmutation on cortical gray matter microstructure

“…DKI metrics were computed using the Diffusion Kurtosis Imaging software (https://github.com/NYU-DiffusionMRI/Diffusion-Kurtosis-Imaging), and the following metrics were used in the group comparison: mean kurtosis (MK), fractional anisotropy (FA) and mean diffusivity (MD). We should note that metrics common to DTI and DKI (e.g., FA and MD) are not quantitatively the same if computed using one model or the other (Lanzafame et al, ; Yan et al, ).…”