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Clinical research using restricted diffusion-weighted imaging, especially diffusion kurtosis (DK) imaging, has been progressing, with reports on its effectiveness in the diagnostic imaging of cerebral infarctions, neurodegenerative diseases, and tumors, among others. However, the application of DK imaging in daily clinical practice has not spread because of the long imaging time required and the use of specific software for image creation. Herein, with the aim of promoting clinical research using DK imaging at any medical facility, we evaluated fast DK imaging using a new software program. We developed a new macro program that produces DK images using general-purpose, inexpensive software (Microsoft Excel and ImageJ), and we evaluated fast DK imaging using bio-phantoms and a healthy volunteer in clinical trials. The DK images created by the new software with diffusion-weighted images captured with short-time imaging sequences were similar to the original DK images captured with long-time imaging sequences. The DK images using three b-values, which can reduce the imaging time by 43%, were equivalent to the DK images using five b-values. The DK imaging technique developed herein might allow any medical facility to increase its daily clinical use of DK imaging and easily conduct clinical research., Competing Interests: No potential conflict of interest relevant to this article was reported.

Purpose: The current study aimed to investigate the associations between diffusion dynamics of ischemic lesions and clinical functional outcome of acute and early subacute stroke., Material and Methods: A total of 80 patients with first ever infarcts in the territory of the middle cerebral artery underwent multi-b-values diffusion-weighted imaging and diffusion kurtosis imaging. Multiple diffusion parameters were generated in postprocessing using different diffusion models. Long-term functional outcome was evaluated with modified Rankin scale (mRS) at 6 months post-stroke. Good functional outcome was defined as mRS score ≤ 2 and poor functional outcome was defined as mRS score ≥ 3. Univariate analysis was used to compare the diffusion parameters and clinical features between patients with poor and good functional outcome. Significant parameters were further analyzed for correlations with functional outcome using partial correlation., Results: In univariate analyses, standard-b-values apparent diffusion coefficient (ADC st ) ratio and fractional anisotropy (FA) ratio of acute stroke, ADC st ratio and mean kurtosis (MK) ratio of early subacute stroke were statistically different between patients with poor outcome and good outcome (P < 0.05). When the potential confounding factor of lesion volume was controlled, only FA ratio of acute stroke, ADC st ratio and MK ratio of early subacute stroke remained correlated with the functional outcome (P < 0.05)., Conclusion: Diffusion dynamics are correlated with the clinical functional outcome of ischemic stroke. This correlation is independent of the effect of lesion volume and is specific to the time period between symptom onset and imaging. More effort is needed to further investigate the predictive value of diffusion-weighted imaging.

Purpose: The purpose of this study was to explore the usefulness of diffusion kurtosis imaging (DKI) and molecular markers in predicting the prognosis of glioma patients., Method: Fifty-one patients with gliomas were examined by conventional MRI and DKI at 3.0 T before operation. The mean kurtosis (MK), mean diffusivity (MD), axial kurtosis (AK), and radial kurtosis (RK) values of tumors were measured and normalized to the contralateral normal-appearing white matter. The molecular markers of gliomas, including isocitrate dehydrogenase-1 (IDH1), α thalassemia/mental retardation syndrome x-linked (ATRX) and O6-methylguanine-DNA methyltransferase (MGMT), were immunohistochemically stained on the resected tumor tissues. Statistical methods, including the chi-square test, independent sample t-test, receiver operating characteristic curve analysis, Kaplan-Meier curve analysis, and Cox regression analysis were performed., Results: The patients with lower MK, AK, RK, and higher MD values showed significantly better prognosis (P < 0.001). Survival time was better in glioma patients with IDH1 mutation (P < 0.01), ATRX loss of expression (P < 0.05), and MGMT negative expression (P < 0.05). However, among the groups of gliomas with IDH1 wild type, ATRX retention and those with MGMT positive expression, the patients with lower MK showed better outcome (P < 0.01). Cox multivariate regression analysis demonstrated that MK, RK values and ATRX retention could be used as independent prognostic risk factors, and high MK values had the highest risk for prognosis (HR = 65.288)., Conclusions: Molecular markers and DKI parameters, especially MK values, can be used to effectively evaluate the prognosis of glioma patients., Competing Interests: Declaration of Competing Interest The authors declared that they have no conflicts of interest to this work.We declare that we do not have any commercial or associative interest that represents a conflict of interest in connection with the work submitted., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Purpose: To explore the value of Diffusion kurtosis imaging (DKI) metrics in the differential diagnosis of meningioma., Methods: For this study, we retrospectively enrolled 35 patients of cerebral meningioma with DKI which included axial diffusion coefficient (AD), radial diffusion coefficient (RD), mean diffusion coefficient (MD), fractional anisotropy (FA), axial kurtosis (AK), radial kurtosis (RK) and mean kurtosis (MK). All of these metrics were normalized according to contralateral normal-appearing white matter (NAWMc). Patients were divided into two groups (benign and malignant meningioma) and were further analyzed using the independent sample t-test and receiver operating characteristic (ROC) curve. A one-way ANOVA analysis was used to analyze four groups divided according to pathological subtypes., Results: The metrics of AD, normalized AD, normalized MD, MK and normalized MK showed a significant difference between benign and malignant group, and MK showed relatively higher diagnostic ability with its cut-off value, area under the curve (AUC), sensitivity and specificity of 0.875, 0.780, 70% and 89%, respectively. The metrics of normalized MD, RD and normalized RD, FA and normalized FA, AK and normalized AK, and RK showed significant difference among four subtypes. MK and RK in meningioma were found to correlate positively with the Ki-67 labeling index (Ki-67 LI)., Conclusions: DKI metrics may be used to differentiate benign from malignant meningioma, and also to distinguish some histological subtypes of meningioma. Moreover, DKI metrics may potentially reflect cellular proliferation., (Copyright © 2017. Published by Elsevier B.V.)

Diffusion kurtosis imaging (DKI) can offer a useful complementary tool to routine diffusion MRI for improved stratification of heterogeneous tissue damage in acute ischemic stroke. However, its relatively long imaging time has hampered its clinical application in the emergency setting. A recently proposed fast DKI approach substantially shortens the imaging time, which may help to overcome the scan time limitation. However, to date, the sensitivity of the fast DKI protocol for the imaging of acute stroke has not been fully described. In this study, we performed routine and fast DKI scans in a rodent model of acute stroke, and compared the sensitivity of diffusivity and kurtosis indices (i.e. axial, radial and mean) in depicting acute ischemic lesions. In addition, we analyzed the contrast-to-noise ratio (CNR) between the ipsilateral ischemic and contralateral normal regions using both conventional and fast DKI methods. We found that the mean kurtosis shows a relative change of 47.1 ± 7.3% between the ischemic and contralateral normal regions, being the most sensitive parameter in revealing acute ischemic injury. The two DKI methods yielded highly correlated diffusivity and kurtosis measures and lesion volumes (R(2)  ⩾ 0.90, p < 0.01). Importantly, the fast DKI method exhibited significantly higher CNR of mean kurtosis (1.6 ± 0.2) compared with the routine tensor protocol (1.3 ± 0.2, p < 0.05), with its CNR per unit time (CNR efficiency) approximately doubled when the scan time was taken into account. In conclusion, the fast DKI method provides excellent sensitivity and efficiency to image acute ischemic tissue damage, which is essential for image-guided and individualized stroke treatment., (Copyright © 2016 John Wiley & Sons, Ltd.)

Background: Diffusion magnetic resonance imaging (dMRI) has revealed microstructural changes in white matter (WM) in Huntington's disease (HD). Objective: To compare the validities of different dMRI, i.e., diffusion kurtosis imaging (DKI) and diffusion tensor imaging (DTI) in HD. Methods: 22 mutant huntingtin (mHTT) carriers and 14 controls were enrolled. Clinical assessments and dMRI were conducted. Based on CAG-Age Product (CAP) score, mHTT carriers were categorized into high CAP (hCAP) and medium and low CAP (m& lCAP) groups. Spearman analyses were used to explore correlations between imaging parameters in brain regions and clinical assessments. Receiver operating characteristic (ROC) was used to distinguish mHTT carriers from control, and define the HD patients at advanced stage. Results: Compared to controls, mHTT carriers exhibited WM changes in DKI and DTI. There were 22 more regions showing significant differences in HD detected by MK than FA. Only MK in five brain regions showed significantly difference between any two group, and negatively correlated with the disease burden (r = –0.80 to –0.71). ROC analysis revealed that MK was more sensitive and FA was more specific, while Youden index showed that the integration of FA and MK gave rise to higher authenticities, in distinguishing m& lCAP from controls (Youden Index = 0.786), and discerning different phase of HD (Youden Index = 0.804). Conclusions: Microstructural changes in WM occur at early stage of HD and deteriorate over the disease progression. Integrating DKI and DTI would provide the best accuracies for differentiating early HD from control and identifying advanced HD. [ABSTRACT FROM AUTHOR]

Background: Our initial clinical study using simple diffusion kurtosis imaging (SDI), which simultaneously produces a diffusion kurtosis image (DKI) and an apparent diffusion coefficient map, confirmed the usefulness of SDI for tumor diagnosis. However, the obtained DKI had noticeable variability in the mean kurtosis (MK) values, which is inherent to SDI. We aimed to improve this variability in SDI by preprocessing with three different filters (Gaussian [G], median [M], and nonlocal mean) of the diffusion-weighted images used for SDI. Methods: The usefulness of filter parameters for diagnosis was examined in basic and clinical studies involving 13 patients with head and neck tumors. Results: The filter parameters, which did not change the median MK value, but reduced the variability and significantly homogenized the MK values in tumor and normal tissues in both basic and clinical studies, were identified. In the receiver operating characteristic curve analysis for distinguishing tumors from normal tissues using MK values, the area under curve values significantly improved from 0.627 without filters to 0.641 with G (σ = 0.5) and 0.638 with M (radius = 0.5). Conclusions: Thus, image pretreatment with G and M for SDI was shown to be useful for improving tumor diagnosis in clinical practice. [ABSTRACT FROM AUTHOR]

We evaluated the usefulness of simple diffusion kurtosis (SD) imaging, which was developed to generate diffusion kurtosis images simultaneously with an apparent diffusion coefficient (ADC) map for 27 cystic disease lesions in the head and neck region. The mean kurtosis (MK) and ADC values were calculated for the cystic space. The MK values were dentigerous cyst (DC): 0.74, odontogenic keratocyst (OKC): 0.86, ranula (R): 0.13, and mucous cyst (M): 0, and the ADC values were DC: 1364 × 10−6 mm2/s, OKC: 925 × 10−6 mm2/s, R: 2718 × 10−6 mm2/s, and M: 2686 × 10−6 mm2/s. The MK values of DC and OKC were significantly higher than those of R and M, whereas their ADC values were significantly lower. One reason for the characteristic signal values in diffusion-weighted images of DC may be related to content components such as fibrous tissue and exudate cells. When imaging cystic disease in the head and neck region using SD imaging, the maximum b-value setting at the time of imaging should be limited to approximately 1200 s/mm2 for accurate MK value calculation. This study is the first to show that the MK values of DC are characteristically higher than those of other cysts. [ABSTRACT FROM AUTHOR]

Abstract: Diffusional kurtosis imaging (DKI), which measures the non-Gaussianity of water diffusion, has been demonstrated to be a sensitive biomarker in many neuropathologies. The goal of this study was to longitudinally examine the spatiotemporal dynamics of DKI in cerebral ischemia in an animal model of permanent and transient (45 min) middle cerebral artery occlusion (MCAO) during the hyperacute, acute and chronic phases. Diffusional kurtosis showed different spatiotemporal dynamics. In particular, mean kurtosis (MK) was sensitive to hyperacute and acute stroke changes, and exhibited different contrast than mean diffusivity (MD) and higher contrast than fractional anisotropy (FA) and T2. MK contrast persisted 1 to 7days post-occlusion, whereas MD showed renormalization at day 1–2 and reversed contrast at day 7. The current study showed that DKI has the potential to complement existing stroke imaging techniques, particularly in the assessment of subacute to early chronic stroke evolution. [Copyright &y& Elsevier]