Evaluating High Spatial Resolution Diffusion Kurtosis Imaging at 3T: Reproducibility and Quality of Fit

Abstract

Background Diffusion kurtosis imaging (DKI) quantifies the microstructure non-Gaussian diffusion properties. However, it has increased fitting parameters and requires higher b-values. Evaluation of DKI reproducibility is important for clinical purposes. Purpose To assess reproducibility in whole-brain high resolution DKI at varying b-values. Study Type Prospective. Subjects and Phantoms Forty-four individuals from the test-retest Human Connectome Project (HCP) database and twelve 3D-printed tissue mimicking phantoms. Field Strength/Sequence Multiband echo-planar imaging for in vivo and phantom diffusion-weighted imaging at 3T and 9.4T respectively. MPRAGE at 3T for in vivo structural data. Assessment From HCP data with b-value =1000,2000,3000 s/mm2 (dataset A), two additional datasets with b-values=1000, 3000 s/mm2 (dataset B) and b-values=1000, 2000 s/mm2 (dataset C) were extracted. Estimated DKI metrics from each dataset were used for evaluating reproducibility and fitting quality in whole-brain white matter (WM), region of interest (ROI) and gray matter (GM). Statistical Tests DKI reproducibility was assessed using the within-subject coefficient of variation (CoV), fitting residuals to evaluate DKI fitting accuracy and Pearson's correlation to investigate presence of systematic biases. Results Compared to dataset C, the CoV from DKI parameters from datasets A and B were comparable, with WM and GM CoVs <20%, while differences between datasets were smaller for the DKI-derived DTI parameters. Slightly higher fitting residuals were observed in dataset C compared to A and B, but lower residuals in dataset B were detected for the WM ROIs. A similar trend was observed for the phantom data with comparable CoVs at varying fiber orientations for datasets A and B. In addition, dataset C was characterized by higher residuals across the different fiber crossings. Data Conclusion The comparable reproducibility of DKI maps between datasets A and B observed in the in vivo and phantom data indicates that high reproducibility can still be achieved within a reasonable scan time, supporting DKI for clinical purposes.

Optimization of quasi‐diffusion magnetic resonance imaging for quantitative accuracy and time‐efficient acquisition

“…Each optimal b ‐value combination included unequally spaced b ‐values, a result consistent with similar DKI experiments 27,28 . A reproducibility study also concluded that DKI fits to b ‐values of 1000 and 3000 s mm −2 showed lower coefficients of variation than to 1000 and 2000 s mm −2 43 . These previous studies used maximum b ‐values within the range commonly used for DKI, whereas we showed that a larger b ‐value range is well‐fitted by the MLF.…”

Mean kurtosis‐Curve (MK‐Curve) correction improves the test–retest reproducibility of diffusion kurtosis imaging at 3 T

“…The scan time is mainly determined by the number of b‐values and it should be kept in mind that b‐values above 3000 s/mm 2 result in poorer fit quality 34 . Kasa et al 10 demonstrated that comparable reproducibility can be obtained by using either a three or a two multishell protocol with lower b‐values; the latter is the study protocol we opted for in this study. Technologies such as multiband might enable doubling the number of directions acquired in the same time, which will probably further reduce the CV.…”

“…However, only a few studies have investigated the test–retest reliability of DKI in the brain in healthy individuals 10–12 : of these, one study was conducted in three patients with traumatic brain injury and four healthy controls (HCs), 13 and one study in small vessel disease, 14 reporting good to excellent test–retest reproducibility. Of all these studies, only two included gray matter (GM) regions in their test–retest assessment 10,11 …”

Test-retest reproducibility of in vivo oscillating gradient and microscopic anisotropy diffusion MRI in mice at 9.4 Tesla

“…As dMRI has reached the forefront of tissue microstructure imaging [40], there is a need to establish the reproducibility of these emerging methods. While the reproducibility of DTI and DKI has been investigated extensively [41][42][43][44], to the best of our knowledge, no test-retest assessment of OGSE and µA dMRI has been done at an ultra-high field strength. The aim of this work was to assess test-retest reproducibility of in vivo OGSE and µA dMRI in mice at 9.4 Tesla and provide estimates of required sample sizes, which is essential in planning future preclinical neuroimaging studies involving models of disease/injury.…”