Conventional Diffusion Kurtosis Imaging Research Articles

Robust, fast and accurate mapping of diffusional mean kurtosis

Diffusional kurtosis imaging (DKI) is a methodology for measuring the extent of non-Gaussian diffusion in biological tissue, which has shown great promise in clinical diagnosis, treatment planning, and monitoring of many neurological diseases and disorders. However, robust, fast, and accurate estimation of kurtosis from clinically feasible data acquisitions remains a challenge. In this study, we first outline a new accurate approach of estimating mean kurtosis via the sub-diffusion mathematical framework. Crucially, this extension of the conventional DKI overcomes the limitation on the maximum b-value of the latter. Kurtosis and diffusivity can now be simply computed as functions of the sub-diffusion model parameters. Second, we propose a new fast and robust fitting procedure to estimate the sub-diffusion model parameters using two diffusion times without increasing acquisition time as for the conventional DKI. Third, our sub-diffusion-based kurtosis mapping method is evaluated using both simulations and the Connectome 1.0 human brain data. Exquisite tissue contrast is achieved even when the diffusion encoded data is collected in only minutes. In summary, our findings suggest robust, fast, and accurate estimation of mean kurtosis can be realised within a clinically feasible diffusion-weighted magnetic resonance imaging data acquisition time.

Robust, fast and accurate mapping of diffusional mean kurtosis.

Diffusional kurtosis imaging (DKI) is a methodology for measuring the extent of non-Gaussian diffusion in biological tissue, which has shown great promise in clinical diagnosis, treatment planning, and monitoring of many neurological diseases and disorders. However, robust, fast, and accurate estimation of kurtosis from clinically feasible data acquisitions remains a challenge. In this study, we first outline a new accurate approach of estimating mean kurtosis via the sub-diffusion mathematical framework. Crucially, this extension of the conventional DKI overcomes the limitation on the maximum b-value of the latter. Kurtosis and diffusivity can now be simply computed as functions of the sub-diffusion model parameters. Second, we propose a new fast and robust fitting procedure to estimate the sub-diffusion model parameters using two diffusion times without increasing acquisition time as for the conventional DKI. Third, our sub-diffusion-based kurtosis mapping method is evaluated using both simulations and the Connectome 1.0 human brain data. Exquisite tissue contrast is achieved even when the diffusion encoded data is collected in only minutes. In summary, our findings suggest robust, fast, and accurate estimation of mean kurtosis can be realised within a clinically feasible diffusion-weighted magnetic resonance imaging data acquisition time.

Added value of histogram analysis of intravoxel incoherent motion and diffusion kurtosis imaging for the evaluation of complete response to neoadjuvant therapy in locally advanced rectal cancer

Abstract Objective To evaluate how intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) histogram analysis contribute to assessing complete response (CR) to neoadjuvant therapy (NAT) in locally advanced rectal cancer (LARC). Material and methods In this prospective study, participants with LARC, who underwent NAT and subsequent surgery, with adequate MR image quality, were enrolled from November 2021 to March 2023. Conventional MRI (T2WI and DWI), IVIM, and DKI were performed before NAT (pre-NAT) and within two weeks before surgery (post-NAT). Image evaluation was independently performed by two experienced radiologists. Pathological complete response (pCR) was used as the reference standard. An IVIM–DKI-added model (a combination of IVIM and DKI histogram parameters with T2WI and DWI) was constructed. Receiver operating characteristic (ROC) curves were generated to evaluate the diagnostic performance of conventional MRI and the IVIM–DKI-added model. Results A total of 59 participants (median age: 58.00 years [IQR: 52.00, 62.00]; 38 [64%] men) were evaluated, including 21 pCR and 38 non-pCR cases. The histogram parameters of DKI, including skewness of kurtosis post-NAT (post-KSkewness) and root mean squared of change ratio of diffusivity (Δ%DDKI-root mean squared), were entered into the IVIM–DKI-added model. The area under the ROC curve (AUC) of the IVIM–DKI-added model for assessing CR to NAT was significantly higher than that of conventional MRI (0.855 [95% CI: 0.749–0.960] vs 0.685 [95% CI: 0.565–0.806], p < 0.001). Conclusion IVIM and DKI provide added value in the evaluation of CR to NAT in LARC. Key Points QuestionThe current conventional imaging evaluation system lacks adequacy for assessing CR to NAT in LARC. FindingsSignificantly improved diagnostic performance was observed with the histogram analysis of IVIM and DKI in conjunction with conventional MRI. Clinical relevanceIVIM and DKI provide significant value in evaluating CR to NAT in LARC, which bears significant implications for reducing surgical complications and facilitating organ preservation.

Application of diffusion kurtosis imaging in neonatal brain development.

Deviations from the regular pattern of growth and development could lead to early childhood diseases, suggesting the importance of evaluating early brain development. Through this study, we aimed to explore the changing patterns of white matter and gray matter during neonatal brain development using diffusion kurtosis imaging (DKI). In total, 42 full-term neonates (within 28 days of birth) underwent conventional brain magnetic resonance imaging (MRI) and DKI. The DKI metrics (including kurtosis parameters and diffusion parameters) of white matter and deep gray matter were measured. DKI metrics from the different regions of interest (ROIs) were evaluated using the Kruskal-Wallis test and Bonferroni method. Spearman rank correlation analysis of the DKI metrics was conducted, and the age at the time of brain MRI acquisition was calculated. The subjects were divided into three groups according to their age at the time of brain MRI acquisition: the first group, neonates aged ≤7 days; the second group, neonates aged 8-14 days; and the third group, neonates aged 15-28 days. The rate of change in DKI metrics relative to the first group was computed. The mean kurtosis (MK), axial kurtosis (Ka), radial kurtosis (Kr), and fractional anisotropy (FA) values showed positive correlations, whereas mean diffusion (MD), axial diffusion (Da), and radial diffusion (Dr) values showed negative correlations with the age at the time of brain MRI acquisition. The absolute correlation coefficients between MK values of almost all ROIs (except genu of the corpus callosum and frontal white matter) and the age at the time of brain MRI acquisition were greater than other metrics. The kurtosis parameters and FA values of central white matter were significantly higher than that of peripheral white matter, whereas the MD and Dr values were significantly lower than that of peripheral white matter. The MK value of the posterior limb of the internal capsule was the highest among the white matter areas. The FA value of the splenium of the corpus callosum was significantly higher than that of the other white matter areas. The kurtosis parameters and FA values of globus pallidus and thalamus were significantly higher than those of the caudate nucleus and putamen, whereas the Da and Dr values of globus pallidus and thalamus were significantly lower than those of the caudate nucleus and putamen. The relative change rates of kurtosis parameters and FA values of all ROIs were greater than those of MD, Da, and Dr values. The amplitude of MK values of almost all ROIs (except for the genu of the corpus callosum and central white matter of the centrum semiovale level) was greater than that of other metrics. The relative change rates of the Kr values of most ROIs were greater than those of the Ka value, and the relative change rates of the Dr values of most ROIs were greater than those of the Da value. DKI parameters showed potential advantages in detecting the changes in brain microstructure during neonatal brain development.

Diffusion Kurtosis Imaging in Evaluating the Mild Cognitive Impairment of Occupational Aluminum Workers

To investigate whether diffusion kurtosis imaging (DKI) can distinguish mild cognitive impairment (MCI) from normal controls (NC) in aluminum (Al)-exposed workers, and to explore the association of DKI with cognitive performance and plasma Al concentration. 28 patients with MCI and 25 NC at Al factory were enrolled in this study. All subjects underwent conventional MRI and DKI scans. The mean kurtosis (MK), axial kurtosis (Ka), radial kurtosis (Kr), mean diffusivity (MD) and fractional anisotropy (FA) parameters of the hippocampus, substantia nigra, red nucleus, thalamus, anterior cingulate gyrus, genu and crus of the corpus callosum, frontal, parietal and temporal lobe were measured. To compare the parameters between the two groups, the Mann-Whitney rank sum test was used. The correlation of parameter values with cognitive performance and plasma Al concentration was analyzed using Spearman correlation analysis. The receiver operating characteristic (ROC) curve and the Z-scores were used to evaluate the diagnostic efficacy of each parameter. Compared with the NC group, the MK, Ka, Kr, and FA values in the MCI group were significantly decreased, and the MD values were significantly increased (p<0.05). For the diagnosis of MCI, MK in the right hippocampus showed the largest AUC (0.924). The MK, Kr, MD and FA values were correlated with the Montreal Cognitive Assessment (MoCA) scores, and MK values in the right hippocampus showed the greatest correlation with MoCA scores (r=0.744, p <0.001). Plasma Al in the MCI group was higher than that in the NC group, although there was no significant difference in plasma Al between the two groups (p=0.057). There was no correlation between DKI parameters and plasma Al. The DKI method might be a sensitive imaging biomarker to discriminate MCI from NC, and could preliminarily assess the severity of cognitive impairment in Al-exposed workers. MK in the right hippocampus appeared to be the best independent predictor. The mechanism of cognitive decline is an important content of aluminum exposure research. This study indicates that the DKI technique could provide valuable information for the diagnosis of MCI.

CHANGES IN THE MICROSTRUCTURE AND FUNCTION OF BRAIN TISSUE IN PD BY DIFFUSION KURTOSIS IMAGING

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 ([Formula: see text]; [Formula: see text]). 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.

Diffusion Kurtosis-Based Brain Image Segmentation for the Structural Remodeling of White Matter in Patients with Hypoxic-Ischemic Encephalopathy

The aim was to explore the application value of brain image segmentation algorithm based on diffusion kurtosis imaging (DKI) in the structural remodeling of white matter (WM) in patients with hypoxic-ischemic encephalopathy (HIE). 120 patients with leukoencephalopathy and hypoxic-ischemic encephalopathy were selected as the research objects. Their heads were scanned by conventional magnetic resonance imaging (MRI) and DKI sequence. Besides, DKI based on the image segmentation algorithm was applied to process DKI images, DKE software was employed to obtain the values of fractional anisotropy (FA) and mean kurtosis (MK), and the differences in FA and MK were compared between acute and chronic phases. The results showed that the proposed algorithm could realize the best values of Jaccard similarity (JS) and Dice similarity coefficient (DSC) in WM, gray matter (GM), and cerebrospinal fluid (CSF), and the segmentation accuracy was better than other algorithms. FA values at the acute and chronic phases were compared in the area around lesions (0.421 ± 0.065 vs. 0.454 ± 0.052), the posterior limb of internal capsule on the affected side (0.498 ± 0.027 vs. 0.504 ± 0.046), and the pedunculus cerebri on the affected side (0.558 ± 0.038 vs. 0.568 ± 0.042), and the differences were statistically substantial ( P &lt; 0.05 ). Moreover, MK values at the acute and chronic phases were also compared in the area around lesions (1.362 ± 0.098 vs. 1.407 ± 0.077), the centrum semiovale on the affected side (1.305 ± 0.102 vs. 1.343 ± 0.076), the posterior limb of internal capsule on the affected side (1.338 ± 0.543 vs. 1.382 ± 0.076), and the pedunculus cerebri on the affected side (1.329 ± 0.089 vs. 1.398 ± 0.099), showing a statistical meaning ( P &lt; 0.05 ). The results indicated that the changes of FA and MK were related to the structural remodeling of WM. The DKI image segmentation algorithm could be applied in the diagnosis of leukoencephalopathy in patients with hypoxic-ischemic encephalopathy, and DKI technology was of great significance for the research of structural remodeling of WM.

Magnetic Resonance Image of Neonatal Acute Bilirubin Encephalopathy: A Diffusion Kurtosis Imaging Study.

Background and Objective: The abnormal T1-weighted imaging of MRI can be used to characterize neonatal acute bilirubin encephalopathy (ABE) in newborns, but has limited use in evaluating the severity and prognosis of ABE. This study aims to assess the value of diffusion kurtosis imaging (DKI) in detecting ABE and understanding its pathogenesis.Method: Seventy-six newborns with hyperbilirubinemia were grouped into three groups (mild group, moderate group, and severe group) based on serum bilirubin levels. All the patients underwent conventional MRI and DKI serial, as well as 40 healthy full-term infants (control group). The regions of interest (ROIs) were the bilateral globus pallidus, dorsal thalamus, frontal lobe, auditory radiation, superior temporal gyrus, substantia nigra, hippocampus, putamen, and inferior olivary nucleus. The values of mean diffusivity (MD), axial kurtosis (AK), radial kurtosis (RK), and mean kurtosis (MK), and fractional anisotropy (FA), radial diffusivity (RD), and axis diffusivity (AD) of the ROIs were evaluated. All newborns were followed up and evaluated using the Denver Development Screening Test (DDST). According to the follow-up results, the patients were divided into the normal group, the suspicious abnormal group, and the abnormal group.Result: Compared with the control group, significant differences were observed with the increased MK of dorsal thalamus, AD of globus pallidus in the moderate group, and increased RD, MK, AK, and RK value of globus pallidus, dorsal thalamus, auditory radiation, superior temporal gyrus, and hippocampus in the severe group. The peak value of total serum bilirubin was moderately correlated with the MK of globus pallidus, dorsal thalamus, and auditory radiation and was positively correlated with the other kurtosis value. Out of 76 patients, 40 finished the DDST, and only 9 patients showed an abnormality. Compared with the normal group, the AK value of inferior olivary nucleus showed significant differences (p < 0.05) in the suspicious abnormal group, and the MK of globus pallidus, temporal gyrus, and auditory radiation; RK of globus pallidus, dorsal thalamus, and auditory radiation; and MD of globus pallidus showed significant differences (p < 0.05) in the abnormal group.Conclusion: DKI can reflect the subtle structural changes of neonatal ABE, and MK is a sensitive indicator to indicate the severity of brain damage.

The diagnostic accuracy of intravoxel incoherent motion and diffusion kurtosis imaging in the differentiation of malignant and benign soft-tissue masses: which is better?

It is difficult for conventional magnetic resonance imaging (MRI) to distinguish benign soft-tissue masses (STMs) from malignant masses. To quantitatively compare the diagnostic value of intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) in STMs. The data from 58 patients with STMs were retrospectively analyzed. The GE Discovery 3.0-T MRI scanner was used to acquire conventional MRI sequences, IVIM, and DKI images. The chi-square test, independent sample t-test, and Mann-Whitney U tests were used to compare the differences between conventional MRI features, IVIM, and DKI parameters (Dslow, Dfast, f, mean kurtosis [MK], and mean diffusivity [MD]) between the benign and malignant groups. Receiver-operating characteristic (ROC) curve analysis was also performed. Tumor size and depth are statistically different in STTs. Dslow, MK, and MD values in the malignant groups are significantly lower than the benign groups (P < 0.05). However, Dfast and f values are not statistically different between the two groups. The area under the curve (AUC) of Dslow value (0.859) is higher than MD (0.765) and MK (0.676) values for identifying benign and malignant STMs. The Dslow value showed the best specificity (82.93%). The sensitivity and specificity of IVIM and DKI parameters are higher than that of conventional MRI sequences. IVIM and DKI can be used to distinguish between benign and malignant STMs, with Dslow as the most meaningful parameter.

Differentiation of microinfiltration and simple-edema areas in VX2 bone tumors by diffusion kurtosis imaging in animal experiments: a preliminary study.

Dual-energy computed tomography, diffusion-weighted imaging (DWI), and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can be used to distinguish microinvasion areas of malignant bone tumors. However, reports of diffusion kurtosis imaging (DKI) to determine the extent of intramedullary infiltration are relatively rare. To assess the application value of MR-DKI in differentiating areas of microinfiltration and simple edema in rabbit bone VX2 tumor models. Conventional MRI and DKI were performed on 25 successfully constructed rabbit VX2 bone tumor models. We acquired a midline sagittal section of the tumor for hematoxylin and eosin staining. Using pathological findings as the gold standard and combining them with MRI data, strict point-to-point control was performed to delineate regions of interest (ROIs) in the microinfiltration and simple-edema areas of bone tumors for quantitative measurement of mean diffusivity (MD) and mean kurtosis (MK). MD and MK values between microinfiltration and simple-edema areas were compared using an independent sample t-test, and the diagnostic values were evaluated by receiver operating characteristic (ROC) curve analysis. In comparison with the simple-edema area, the micro-infiltration area demonstrated significantly smaller MD values and larger MK values (P < 0.05), and MD showed a better area under the curve (AUC) than MK (AUC = 0.884 vs. AUC = 0.690) for distinguishing the microinfiltration area from the simple-edema area. The optimal cutoff MD value was 1108.5 mm2/s with a sensitivity of 84% and specificity of 84%. DKI can distinguish the microinfiltration and simple-edema areas of malignant bone tumors in animal experiments.

The diagnostic value of T2 map, diffusion tensor imaging, and diffusion kurtosis imaging in differentiating dermatomyositis from muscular dystrophy.

Dermatomyositis (DM) and muscular dystrophy are clinically difficult to differentiate. To confirm the feasibility and assess the accuracy of conventional magnetic resonance imaging (MRI), T2 map, diffusion tensor imaging (DTI), and diffusion kurtosis imaging (DKI) in the differentiation of DM from muscular dystrophy. Forty-two patients with DM proven by diagnostic criteria were enrolled in the study along with 23 patients with muscular dystrophy. Conventional MR, T2 map, DTI, and DKI images were obtained in the thigh musculature for all patients. Intramuscular T2 value, apparent diffusion coefficient (ADC), fractional anisotropy (FA), mean diffusivity (MD), and mean kurtosis (MK) values were compared between the patients with DM and muscular dystrophy. Student's t-tests and receiver operating characteristic (ROC) curve analyses were performed for all parameters. P values < 0.05 were considered statistically significant. The intramuscular T2, ADC, FA, MD, and MK values within muscles were statistically significantly different between the DM and muscular dystrophy groups (P<0.01). The MK value was statistically significantly different between the groups in comparison with T2 and FA value. As a supplement to conventional MRI, the parameters of MD and MK differentiated DM and muscular dystrophy may be valuable. The optimal cut-off value of ADC and MD values (with respective AUC, sensitivity, and specificity) between DM and muscular dystrophy were 1.698 ×10-3mm2/s (0.723, 54.1%, and 78.1%) and 1.80 ×10-3mm2/s (61.9% and 70.2%), respectively. Thigh muscle ADC and MD parameters may be useful in differentiating patients with DM from those with muscular dystrophy.

Prediction of muscle invasion of bladder cancer: A comparison between DKI and conventional DWI

ObjectivesTo prospectively compare the diagnostic efficacy of conventional diffusion-weighted imaging (DWI) and diffusion kurtosis imaging (DKI) in differentiating between muscle-invasive bladder cancer (MIBC) and non-muscle-invasive bladder cancer (NMIBC). MethodsMultiple b value DWIs were performed using a 3-T magnetic resonance (MR) imaging unit in fifty-one patients with bladder cancer including MIBC and NMIBC confirmed by histopathological findings. DWI data were postprocessed using mono-exponential and DKI models to calculate the apparent diffusion coefficient (ADC), apparent diffusional kurtosis (Kapp), and kurtosis-corrected diffusion coefficient (Dapp). Receiver-operating characteristic (ROC) analysis was performed to compare the diagnostic efficacy of all diffusion parameters. ResultsAll parameters differed significantly between MIBC and NIMBC including increased Kapp, decreased Dapp and ADC (all p < 0.001). Only the combination of Dapp and Kapp was significantly higher than ADC (p < 0.05), whilst Dapp and Kapp were not statistically different from ADC. ConclusionsBoth conventional DWI and DKI models are beneficial in differentiating between MIBC and NMIBC, whilst the combination of Dapp and Kapp can produce a more robust value than conventional ADC value in evaluating aggressiveness of bladder cancer.

Diffusion kurtosis imaging and pathological comparison of early hypoxic\u2013ischemic brain damage in newborn piglets

To investigate the application value of magnetic resonance diffusion kurtosis imaging (DKI) in hypoxic–ischemic brain damage (HIBD) in newborn piglets and to compare imaging and pathological results. Of 36 piglets investigated, 18 were in the experimental group and 18 in the control group. The HIBD model was established in newborn piglets by ligating the bilateral common carotid arteries and placing them into hypoxic chamber. All piglets underwent conventional MRI and DKI scans at 3, 6, 9, 12, 16, and 24 h postoperatively. Mean kurtosis (MK) and mean diffusivity (MD) maps were constructed. Then, the lesions were examined using light and electron microscopy and compared with DKI images. The MD value of the lesion area gradually decreased and the MK value gradually increased in the experimental group with time. The lesion areas gradually expanded with time; MK lesions were smaller than MD lesions. Light microscopy revealed neuronal swelling in the MK- and MD-matched and mismatched regions. Electron microscopy demonstrated obvious mitochondrial swelling and autophagosomes in the MK- and MD-matched region but normal mitochondrial morphology or mild swelling in the mismatched region. DKI can accurately evaluate early ischemic–hypoxic brain injury in newborn piglets.

Diffusion kurtosis imaging combined with molecular markers as a comprehensive approach to predict overall survival in patients with gliomas

PurposeThe purpose of this study was to explore the usefulness of diffusion kurtosis imaging (DKI) and molecular markers in predicting the prognosis of glioma patients. MethodFifty-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. ResultsThe 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). ConclusionsMolecular markers and DKI parameters, especially MK values, can be used to effectively evaluate the prognosis of glioma patients.

Diffusion kurtosis imaging characteristics of brain gray matter nucleus microstructure in Parkinson's disease with different movement disorder subtypes

Objective To investigate the difference in the microstructure of gray matter nucleus in different movement subtypes of Parkinson’s disease (PD) by diffusion kurtosis imaging (DKI) technique, and to analyze the correlation with clinical manifestations. Methods Ninety-seven patients with PD and 83 healthy controls performed conventional MRI sequence and DKI sequence scan. The PD patients were classified into gait disorder subtype (PIGD, n=57) and tremor dominant subtype (TD, n=40)subtypes according to motor symptoms. Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (Da), radial diffusivity(Dr), mean kurtosis (MK), axial kurtosis (Ka) and radial kurtosis (Dr) maps and data were generated by software after processing. DKI was performed for all subjects and data was collected from different brain regions in both hemispheres, including red nucleus(RN), substantia nigra pars reticulate(SNr), substantia nigra pars compacta(SNc), putamen(PUT), globus pallidus(GP), head of caudate nucleus (CN)and thalamus(THA). Results TD showed a higher MMSE score(P=0.019), but lower modified Hoehn-Yahr score than that in PIGD (P 0.05). Moreover, there was no significant correlation between DKI value and disease duration, MMSE score or Hoehn-Yahr scale (P>0.05) in TD and PIGD. Conclusion There is heterogeneity of clinical symptoms between these two subgroups of PD. DKI can quantify the microstructural changes of grey matter nucleus in different type PD patient. Key words: Parkinson's disease; Movement disorder subtypes; Diffusion kurtosis imaging; Heterogeneity

Detecting normal pediatric brain development with diffusional kurtosis imaging

PurposeTo characterise the pattern of change of diffusional kurtosis imaging (DKI) parameters (including kurtosis and diffusion parameters) in both white matter and gray matter in normal brain development with a large sample of subjects from term-born neonates to 14-years old children. MethodsTwo hundred and eighteen normal children (136 male, 82 female) underwent conventional magnetic resonance imaging and DKI. Regions of interest (ROIs) were placed in 7 white matter areas and 4 gray matter areas. Then the DKI-derived parameters were automatically calculated, including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (Da), radial diffusivity (Dr), mean kurtosis (MK), axial kurtosis (Ka) and radial kurtosis (Kr). The correlation between the DKI parameters and ages were analyzed using nonlinear fit, and the rate of parameter change was computed compared to the baseline value of the neonates. ResultsFor all ROIs in the white matter and gray matter, the FA, MK, Kr, Ka values increased with age, while the MD and Dr values decreased with age. The correlations were good to excellent, which changed rapidly within the first 2 years and relatively slowly after 2 years. The Da values in peripheral white matters and some gray matter structures (caudate nucleus and putamen) decreased with age. The amplitude of kurtosis parameters variation was greater than that of the diffusion parameters in both white matter and gray matter. ConclusionsThe DKI parameters correlated well with age, and kurtosis parameters showed a potential advantage in detecting the normal brain development of children.

Histogram analysis of diffusion kurtosis imaging in the differentiation of malignant from benign breast lesions

ObjectiveTo assess the diagnostic accuracy of histogram analysis of diffusion kurtosis imaging (DKI) in breast lesions. Materials and methodsOur institutional review board approved this retrospective study. Seventy-two breast lesions (30 benign and 42 malignant) in 71 patients were histopathologically confirmed. All breast lesions were evaluated by 3.0-T diffusion-weighted imaging (DWI) with 4 b-values of 0, 500, 800, and 2000s/mm2 and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Histogram analyses of conventional DWI and DKI were performed using FireVoxel software for whole lesions. The parameters included apparent diffusion coefficient (ADC), diffusivity (D), and kurtosis (K). The metrics of ADC and DKI parameters (D and K) for benign lesions were compared with those for malignant lesions. The effectiveness of the ADC and DKI parameters (D and K) for diagnosing breast lesions was analysed using receiver operating characteristic (ROC) regression models. ResultsFor the malignant breast lesions, the mean, median, and 10th/25th/75th percentile values of ADC and D were significantly lower, while the skewness of ADC and D were significantly higher in comparison of the benign lesions(all p < 0.05). The malignant lesions had significantly higher mean, median, and 10th/25th/75th/90th percentile K values than did the benign lesions (all p < 0.05). Within each set of parameters, the 10th percentile ADC (Az = 0.752) and D, (Az = 0.834) coupled with the 75th percentile K (Az = 0.904) were the best metrics for differentiating benign from malignant breast lesions. After comparing the parameters in pairs, the Az for the 75th percentile K was significantly higher than that for the 10th percentile ADC (p = 0.0321) in differentiating benign from malignant breast lesions. When comparing the combination of the 75th percentile K and the 10th percentile D (Az = 0.937) with the 10th percentile D, 75th percentile K and the mean K, a significantly higher Az was observed for the combination than that for the 10th percentile D and the mean K (p = 0.0097 and p = 0.0431, respectively). The diagnostic sensitivity and specificity of the combination of the 75th percentile K and the 10th percentile D were 85.71% and 93.33%, respectively. ConclusionHistogram analysis of DKI can accurately reflect the histologic characteristics and heterogeneity and is a reliable method for diagnosing breast lesions.

Characterizing Non-Gaussian Diffusion in Heterogeneously Oriented Tissue Microenvironments.

Complex tissue microstructure involving various types of cells and their membranes can deviate the movement of water molecules from the typical Gaussian diffusion. This deviation can be quantified using excess kurtosis to characterize tissue structural complexity. However, true kurtosis measurements can be obscured by complex white matter configurations such as fiber crossing, bending, and branching, which are ubiquitous in the brain. In this paper, we extend diffusion kurtosis imaging (DKI) to allow characterization of diffusional kurtosis in microstructural environments that are oriented heterogeneously. Our method, called microscopic DKI (μDKI), fits a cylindrically symmetric kurtosis model to the spherical mean of the diffusion signal as a function of diffusion weighting. The spherical mean, computed for each b-shell, is invariant to the fiber orientation distribution and is a function of per-axon microstructural properties. Experimental results indicate that μDKI yields significantly higher consistency in quantifying microstructure than the conventional DKI in the presence of orientation heterogeneity.

Characterization of Alzheimer's Disease Using Ultra-high b-values Apparent Diffusion Coefficient and Diffusion Kurtosis Imaging.

The aim of the study is to investigate the diffusion characteristics of Alzheimer’s disease (AD) patients using an ultra-high b-values apparent diffusion coefficient (ADC_uh) and diffusion kurtosis imaging (DKI). A total of 31 AD patients and 20 healthy controls (HC) who underwent both MRI examination and clinical assessment were included in this study. Diffusion weighted imaging (DWI) was acquired with 14 b-values in the range of 0 and 5000 s/mm2. Diffusivity was analyzed in selected regions, including the amygdala (AMY), hippocampus (HIP), thalamus (THA), caudate (CAU), globus pallidus (GPA), lateral ventricles (LVe), white matter (WM) of the frontal lobe (FL), WM of the temporal lobe (TL), WM of the parietal lobe (PL) and centrum semiovale (CS). The mean, median, skewness and kurtosis of the conventional apparent diffusion coefficient (ADC), DKI (including two variables, Dapp and Kapp) and ADC_uh values were calculated for these selected regions. Compared to the HC group, the ADC values of AD group were significantly higher in the right HIP and right PL (WM), while the ADC_uh values of the AD group increased significantly in the WM of the bilateral TL and right CS. In the AD group, the Kapp values in the bilateral LVe, bilateral PL/left TL (WM) and right CS were lower than those in the HC group, while the Dapp value of the right PL (WM) increased. The ADC_uh value of the right TL was negatively correlated with MMSE (mean, r=-0.420, p=0.019). The ADC value and Dapp value have the same regions correlated with MMSE. Compared with the ADC_uh, combining ADC_uh and ADC parameters will result in a higher AUC (0.894, 95%CI=0.803-0.984, p=0.022). Comparing to ADC or DKI, ADC_uh has no significant difference in the detectability of AD, but ADC_uh can better reflect characteristic alternation in unconventional brain regions of AD patients.

In Vivo Imaging Markers for Prediction of Radiotherapy Response in Patients with Nasopharyngeal Carcinoma: RESOLVE DWI versus DKI

In this prospective study, we compared the performance of readout segmentation of long variable echo trains of diffusion-weighted imaging (RESOLVE DWI) and diffusion kurtosis imaging (DKI) for the prediction of radiotherapy response in patients with nasopharyngeal carcinoma (NPC). Forty-one patients with NPC were evaluated. All patients underwent conventional MRI, RESOLVE DWI and DKI, before and after radiotherapy. All patients underwent conventional MRI every 3 months until 1 year after radiotherapy. The patients were divided into response group (RG; 36/41 patients) and no-response group (NRG; 5/41 patients) based on follow-up results. DKI (the mean of kurtosis coefficient, Kmean and the mean of diffusion coefficient, Dmean) and RESOLVE DWI (the minimum apparent diffusion coefficient, ADCmin) parameters were calculated. Parameter values at the pre-treatment period, post-treatment period, and the percentage change between these 2 periods were obtained. All parameters differed between the RG and NRG groups except for the pretreatment Dmean and ADCmin. Kmean-post was considered as an independent predictor of local control, with 87.5% sensitivity and 91.3% specificity (optimal threshold = 0.30, AUC: 0.924; 95% CI, 0.83–1.00). Kmean-post values of DKI have the potential to be used as imaging biomarkers for the early evaluation of treatment effects of radiotherapy on NPC.