Feasibility of Diffusion Kurtosis Imaging in Evaluating Cervical Spinal Cord Injury in Multiple Sclerosis

Background：Quantitative evaluation of cervical spinal cord (CSC) injury in multiple sclerosis has always been a difficulty. The present study aimed to evaluate the lesion, normal-appearing gray matter (GM) and white matter (WM) damage, and therapeutic effect using diffusion kurtosis imaging (DKI) on CSC of patients with multiple sclerosis.Methods: A total of 48 patients with MS and 30 healthy adults, underwent routine MR scan and DKI of CSC. DKI-metrics were measured in the lesions and in the normal-appearing gray and white matter. MS patients were divided into those with and without T2-hyperintense lesions. Disability was assessed by the expanded disability status scale before and after therapy.Results：1) Significant differences were detected in MK, MD, and FA values between patients and healthy subjects (P < 0.05) and between patients with CSC T2-hyperintense and patients without T2-hyperintense (P < 0.05); 2) Compared to healthy, GM-MK and WM-FA were statistically reduced in patients without T2-hyperintense (P < 0.05). 3) Significant differences were observed in MK, MD, and FA between patients with T2-hyperintense after therapy (P < 0.05), as well as GM-MK and WM-FA in patients without T2-hyperintense (P < 0.05); 4) EDSS was correlated with MK values, as well as EDSS scores and MK values after therapy.Conclusions：1) DKI-metrics can detect and quantitatively evaluate the changes in cervical spinal cord micropathological structure; 2) MK values are sensitive metrics to detect the damage of gray matter; 3) MK values quantitatively evaluate the clinical disability progression and the therapeutic effect in MS patients.

Widespread White Matter Microstructure Alterations Based on Diffusion Tensor Imaging and Diffusion Kurtosis Imaging in Patients With Pontine Infarction

Neurological deficits after stroke are closely related to white matter microstructure damage. However, secondary changes in white matter microstructure after pontine infarction (PI) in the whole brain remain unclear. This study aimed to investigate the correlation of diffusion kurtosis imaging (DKI)-derived diffusion and kurtosis parameters of abnormal white matter tracts with behavioral function in patients with chronic PI. Overall, 60 patients with unilateral chronic PI (33 patients with left PI and 27 patients with right PI) and 30 normal subjects were recruited and underwent DKI scans. Diffusion parameters derived from diffusion tensor imaging (DTI) and DKI and kurtosis parameters derived from DKI were obtained. Between-group differences in multiple parameters were analyzed to assess the changes in abnormal white matter microstructure. Moreover, we also calculated the sensitivities of different diffusion and kurtosis parameters of DTI and DKI for identifying abnormal white matter tracts. Correlations between the DKI-derived parameters in secondary microstructure changes and behavioral scores in the PI were analyzed. Compared with the NC group, both left PI and right PI groups showed more extensive perilesional and remote white matter microstructure changes. The DKI-derived diffusion parameters showed higher sensitivities than did the DTI-derived parameters. Further, DKI-derived diffusion and kurtosis parameters in abnormal white matter regions were correlated with impaired motor and cognitive function in patients with PI. In conclusion, PI could lead to extensive white matter tracts impairment in perilesional and remote regions. Further, the diffusion and kurtosis parameters could be complementary for identifying comprehensive tissue microstructural damage after PI.

The Value of Diffusion Kurtosis Imaging in Detecting Delayed Brain Development of Premature Infants

Objective: Preterm infants are at high risk of the adverse neurodevelopmental outcomes. Our aim is to explore the value of diffusion kurtosis imaging (DKI) in diagnosing brain developmental disorders in premature infants.Materials and Methods: A total of 52 subjects were included in this study, including 26 premature infants as the preterm group, and 26 full-term infants as the control group. Routine MRI and DKI examinations were performed. Mean kurtosis (MK), radial kurtosis (RK), fractional anisotropy (FA), and mean diffusivity (MD) values were measured in the brain regions including posterior limbs of the internal capsule (PLIC), anterior limb of internal capsule (ALIC), parietal white matter (PWM), frontal white matter (FWM), thalamus (TH), caudate nucleus (CN), and genu of the corpus callosum (GCC). The chi-squared test, t-test, Spearman's correlation analysis, and receiver operating characteristic curve were used for data analyses.Results: In the premature infant group, the MK and RK values of PLIA, ALIC, and PWM were lower than those in the control group (p &lt; 0.05). The FA values of PWM, FWM, and TH were also lower than those of the control group (p &lt; 0.05). The area under curves of MK in PLIC and ALIC, MD in PWM, and FA in FWM were 0.813, 0.802, 0.842, and 0.867 (p &lt; 0.05). In the thalamus and CN, the correlations between MK, RK values, and postmenstrual age (PMA) were higher than those between FA, MD values, and PMA.Conclusion: Diffusion kurtosis imaging can be used as an effective tool in detecting brain developmental disorders in premature infants.

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

Background and purpose Microstructure imaging with advanced diffusion MRI (dMRI) techniques have shown increased sensitivity and specificity to microstructural changes in various disease and injury models. Oscillating gradient spin echo (OGSE) dMRI, implemented by varying the oscillating gradient frequency, and microscopic anisotropy (μA) dMRI, implemented via tensor valued diffusion encoding, may provide additional insight by increasing sensitivity to smaller spatial scales and disentangling fiber orientation dispersion from true microstructural changes, respectively. The aims of this study were to characterize the test-retest reproducibility of in vivo OGSE and μA dMRI metrics in the mouse brain at 9.4 Tesla and provide estimates of required sample sizes for future investigations. Methods Twelve adult C57Bl/6 mice were scanned twice (5 days apart). Each imaging session consisted of multifrequency OGSE and μA dMRI protocols. Metrics investigated included μA, linear diffusion kurtosis, isotropic diffusion kurtosis, and the diffusion dispersion rate (Λ), which explores the power-law frequency dependence of mean diffusivity. The dMRI metric maps were analyzed with mean region-of-interest (ROI) and whole brain voxel-wise analysis. Bland-Altman plots and coefficients of variation (CV) were used to assess the reproducibility of OGSE and μA metrics. Furthermore, we estimated sample sizes required to detect a variety of effect sizes. Results Bland-Altman plots showed negligible biases between test and retest sessions. ROI-based CVs revealed high reproducibility for most metrics (CVs < 15%). Voxel-wise CV maps revealed high reproducibility for μA (CVs ~ 10%), but low reproducibility for OGSE metrics (CVs ~ 50%). Conclusion Most of the μA dMRI metrics are reproducible in both ROI-based and voxel-wise analysis, while the OGSE dMRI metrics are only reproducible in ROI-based analysis. Given feasible sample sizes (10–15), μA metrics and OGSE metrics may provide sensitivity to subtle microstructural changes (4–8%) and moderate changes (> 6%), respectively.