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Background: Diffusion kurtosis imaging is an advanced magnetic resonance imaging technique that reveals additional information on the microstructure and micro-dynamics of different brain masses without the need for contrast agents. The aim of this study was to provide a comprehensive analysis of the role of MRI diffusion kurtosis and to compare it with magnetic resonance spectroscopy (MRS) and dynamic susceptibility contrast perfusion (DSC) in characterizing different brain masses, including gliomas, recurrent tumors, radiation necrosis, abscesses, and infarctions. Sixty-six patients with intracranial brain masses were enrolled in this prospective study. All patients were examined by conventional MRI sequences, DSC perfusion, MRS, and diffusion kurtosis imaging, with implemented b values which were 200, 500, 1000, 1500 and 2000s/mm2. Results: Mean kurtosis (MK) was higher (P < 0.001) in recurrent brain tumors than in radiation-induced necrosis; the optimal MK cutoff value for differentiation between them was 642 with 91.3% sensitivity and 85.7% specificity. Mean kurtosis was also higher (P < 0.001) in high-grade gliomas than in low-grade gliomas; the optimal MK cutoff value for differentiation between them was 639 with 91.6% sensitivity and 85.71% specificity. There was a good level of agreement between ADC and MD within the studied cases, with a correlation coefficient r = 0.815. MK had more sensitivity and specificity in differentiation between high- and low-grade gliomas, as well as RIN and tumoral recurrence, than MRS and DSC. Conclusions: Diffusion kurtosis imaging stands as an integral, noninvasive, and noncontrast tool for the characterization of various brain masses. It augments the capabilities of traditional and advanced MRI techniques, providing a deeper understanding of the microstructural changes in brain tissues. [ABSTRACT FROM AUTHOR]

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: Both fractional anisotropy (FA) and mean kurtosis (MK) in diffusion kurtosis imaging (DKI) have value in the diagnosis of Parkinson's disease (PD). We here investigated the sensitivity and specificity of FA and MK to explore which of these methods were more efficient in the early diagnosis of the PD rat model. Materials and Methods: Twenty male SD rats were injected with 6-OHDA into the right substantia nigra (SN) for modeling, and other 20 rats were included in control group. DKI was performed 5 weeks after modeling. The FA and MK values of the right SN were measured and analyzed. Receiver operating characteristic curve was used to evaluate the sensitivity and specificity of the above two value in the identifying PD. Immunohistochemistry of tyrosine hydroxylase (TH), Tunel assay, and Nissl staining in the SN was performed. Results: The FA, MK and FA+MK values in the PD group obtained on the 5th week were statistically significantly different from those of the control group (P < 0.01). The optimal cut-off FA+MK value (with respective area under the curve, sensitivity, specificity) was 1.404 (0.925, 95%, 75%), the Youden's index of FA+MK was higher than of either of the two alone. The FA, MK and FA+MK values correlated positively with the Tunel staining, while they correlated negatively with the TH and Nissl staining. Conclusions: At the 5th week, the diagnostic efficiency of the combined FA and MK values was better than of either of the two alone in diagnosing PD. [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]

Objectives: To explore the diagnostic performance of diffusion kurtosis imaging (DKI) in evaluating the clinical and pathological characteristics of patients with immunoglobulin A nephropathy (IgAN) compared with conventional DWI. Materials and methods: A total of 28 IgAN patients and 14 healthy volunteers prospectively underwent MRI examinations including coronal T2WI, axial T1WI, T2WI, and DWI sequences from September 2020 to August 2021. We measured mean kurtosis (MK), mean diffusivity (MD), and apparent diffusion coefficient (ADC) by using MR Body Diffusion Toolbox v1.4.0 (Siemens Healthcare). Patients were divided into three groups according to their estimated glomerular filtration rate (eGFR) (Group1, healthy volunteers without kidney disease or other diseases that affect renal function; Group2, IgAN patients with eGFR > 60 mL/min/1.73 m2; Group3, IgAN patients with eGFR < 60 mL/min/1.73 m2). One-way analysis of variance, Pearson or Spearman correlation, and receiver operating characteristic curves were applied in our statistical analysis. Results: MKCortex and ADCCortex showed significant differences between the Group1 and Group2. MKCortex, MDCortex, ADCCortex, MKMedulla, and ADCMedulla showed significant differences between Group2 and Group3. MKCortex had the highest correlation with CKD stages (r = 0.749, p < 0.001), and tubulointerstitial lesion score (r = 0.656, p < 0.001). MDCortex had the highest correlation with glomerular lesion score (r = − 0.475, p = 0.011). MKCortex had the highest AUC (AUC = 0.923) for differentiating Group1 from Group2, and MDCortex had the highest AUC (AUC = 0.924) for differentiating Group2 from Group3, followed by MKMedulla (AUC = 0.923). Conclusions: DKI is a feasible and reliable technique that can assess the clinical and pathological characteristics of IgAN patients and can provide more valuable information than conventional DWI, especially MKCortex. [ABSTRACT FROM AUTHOR]

This study proposed to detect changes in brain microstructure in patients with Parkinson's disease (PD) using diffusion kurtosis imaging (DKI) to quantitatively diagnose early-stage PD. Conventional magnetic resonance imaging and DKI scanning were performed in 24 patients with PD and in 12 age- and sex-matched healthy participants. Hoehn and Yahr (H–Y) stage and Unified Parkinson's Disease Rating Scale-III (UPDRS-III) scores were obtained from both groups. The mean kurtosis (MK), axial kurtosis, and radial kurtosis of the bilateral substantia nigra on DKI were measured and compared between the two groups. The correlations between MK, H–Y stage, and UPDRS-III scores were determined. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic efficacy of MK for PD in the substantia nigra. The MK value in the PD group was 0.971. The area under the ROC curve of the substantia nigra was 0.905; the sensitivity and specificity were 0.917 and 0.875, respectively, and the cutoff value was 1.046. The MK of the substantia nigra in the PD group had no significant correlation with the H–Y stages but was negatively correlated with the UPDRS-III scores (r = − 0. 5 0 6 ; p = 0. 0 1 2). Our research identified DKI as a novel tool for the qualitative diagnosis of PD. The optimal MK value for PD diagnosis could be determined with ROC analysis. [ABSTRACT FROM AUTHOR]

Purpose: The aim of the study was to assess the predictive value of preoperatively assessed diffusion kurtosis imaging (DKI) metrics as prognostic factors in the 2016 World Health Organization Classification of Tumors of the Central Nervous System integrated glioma groups.Material and Methods: Seventy-seven patients with histopathologically confirmed treatment-naïve glioma were retrospectively assessed between 08/2013 and 10/2017 using mean kurtosis (MK) and mean diffusivity (MD) histogram parameters from DKI, overall and progression-free survival, and relevant prognostic molecular data (isocitrate dehydrogenase, [IDH]; alpha-thalassemia/mental retardation syndrome X-linked, [ATRX]; chromosome 1p/19q loss of heterozygosity). Receiver operating characteristic (ROC) analysis was performed on metric variables to determine the optimal cutoff-values. The Kaplan-Meier method was used to assess univariate survival data. A multivariate Cox proportional hazards model was performed on significant results from the univariate analysis.Results: There were significant differences in overall and progression-free survival between patient age (p = 0.001), resection statuses (p = 0.002), WHO glioma grades (p < 0.0001), and integrated molecular profiles (p < 0.0001). Survival was significantly better in patients with lower MK and higher MD values globally (p = 0.009), in gliomas without chromosome 1p/19q LOH (p < 0.0001), and those with retained ATRX expression (p = 0.008).Conclusions: Patient age and MK from DKI from DKI are relevant factors for preoperatively predicting overall and progression-free survival. Regarding the molecular subgroups, they seem to be predictive in gliomas with ATRX retention, representing a feature of IDH wild-type gliomas. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]