Both diffusion and kurtosis values have shown to be useful in the diagnosis of stroke and to investigate white matter pathologies. Our group is committed on contributing developed software to the scientific community by making it freely available on github, and the open source proiect mrtrix artifact correction. Diffusion kurtosis imaging dki extends conventional diffusion tensor imaging dti by estimating the kurtosis of the water diffusion probability distribution function 1 to 4. Metrics include mean kurtosis, radial, and axial kurtosis, and the methods are described in hansen, shemesh, and jespersen neuroimage 2016 in press. Diffusional kurtosis imaging college of medicine musc. Effects of diffusional kurtosis imaging parameters on. Introduction diffusionweighted imaging dwi detects severely damaged ischemic tissue that is likely to infarct and has been widely used in stroke imaging. Estimation of diffusion kurtosis dki from a given diffusion weighted mri dataset. Diffusion kurtosis imaging dki is an attempt to account for this variation and in a more refined approach overcomes this problem by quantifying.
Extending the series expansion to the fourth order of q diffusion kurtosis imaging 14 dki would reveal the kurtosis of the displacement pdf. Our aim was to evaluate the associations between diffusional kurtosis imaging derived metrics for the corticospinal tract and disability in multiple sclerosis. Forty patients with ms underwent brain mr imaging including diffusional kurtosis imaging. Stroke assessment with diffusional kurtosis imaging stroke. Stratification of heterogeneous diffusion mri ischemic. Diffusion kurtosis imaging questions and answers in mri. A new diffusion metric, diffusion kurtosis imaging, used in the serial examination of a patient with stroke. Kurtosis, denoted by the dimensionless parameter k, is a long recognized statistical metric for quantifying the shape of a probability distribution. The aim of this preliminary study was to compare how dki and dti. It should be compatible with any matlab version after 2014, and it can. Application of magnetic resonance diffusion kurtosis imaging for. Diffusion tensor magnetic resonance imaging dti is the currently unique invivo mri technique for probing the distribution of neural pathways and microstructures of biological tissues, thus promising for neurology and neuroanatomy research. Our purpose was to use diffusional kurtosis imaging to measure agerelated microstructural changes in both the wm and gm of the developing human brain. Diffusion kurtosis imaging dki was first proposed by jensen et al to account for the nongaussian diffusion property resulting from the microstructural complexity of tissues, and it provides kurtosis and diffusivity parameters.
We employed diffusional kurtosis imaging dki metrics to characterize white matter properties within five discrete segments of the corpus callosum in 17 typically developing td adults and 16 agematched. Diffusional kurtosis imaging and motor outcome in acute. However, the complexity of normal and pathologic tissue leads to hindered diffusion of water molecules and, therefore, should follow a nongaussian distribution. To retrospectively explore the utilization of mr diffusion kurtosis imaging dki in predicting prognosis of the patients with highgrade gliomas.
Mri in a patient with an oligodendroglioma grade ii in the right frontal lobe, nonsmoothed images. Diffusion kurtosis imaging dki allows for assessment of diffusion influenced by microcellular structures. The corpus callosum is implicated in the pathophysiology of autism spectrum disorder asd. For example, if x is a 2by3by4 array, then kurtosis x,1,1 2 returns a 1by1by4 array. Software downloads available on this page are provided free of charge and come without any warranty.
Whereas diffusion tensor imaging dti models the diffusion as a 3d gaussian function, dki takes it one step further by additionally quantifying the degree of nongaussian diffusion. A preliminary diffusional kurtosis imaging study of. Diffusion kurtosis imaging study of rectal adenocarcinoma. We aimed to find suitable b value, mpg direction, and diffusion time settings for faster dki. However, specific structural deficits and underlying mechanisms are yet to be well defined. In particular, it quantifies the microstructural integrity of white matter, even in the presence of crossing fibers. It provides a high order diffusion of water distribution and analyzes and also quantifies the diffusion restriction. Diffusional kurtosis imaging of the corpus callosum in. Diffusion weighted mri has been playing an important role in this regard. Proceedings of the 17th annual meeting of ismrm, honolulu, usa, 2009. Diffusion kurtosis tensor estimation in matlab download. Region of interest roi was delineated as white matter wm in controls and ms plaques and wm in patients. The recent introduction of advanced magnetic resonance mr imaging techniques to characterize focal and global degeneration in multiple sclerosis ms, like the composite hindered and restricted model of diffusion, or charmed, diffusional kurtosis imaging dki and neurite orientation dispersion and density imaging noddi made available new tools to image axonal pathology noninvasively in vivo. Distributions that are more peaked and with less weight on their shoulders typically have a positive kurtosis k0.
This directional variation is summarized in the scalar kurtosis fractional anisotropy kfa. Since the apparent diffusion tensor has 6 independent elements and the kurtosis tensor has 15 elements, there is a total of 21 parameters to be estimated. Motor impairment is the most common deficit after stroke. Diffusion kurtosis imaging dki, a recent addition to this repertoire, has opened up further possibilities in extending our knowledge about structural tissue changes related to injury as well as plasticity. Diffusion kurtosis imaging is an advanced dwi model that quantifies nongaussian behavior of diffusion, yielding additional parameters, apparent kurtosis coefficient k app, reflecting the deviation degree from the ideal gaussian curve, and the corrected adc value, which quantifies the nongaussian behavior of water molecular diffusion. Mr diffusion kurtosis imaging has been recently proposed as a means of quantifying nongaussian water diffusion 18 21. Materials and methods thirtythree consecutive patients with cerebral gliomas underwent pretreatment dki and diffusionweighted imaging examination on a. Evaluating the inflammatory activity in crohns disease. However, the original dki protocol six b values and 30 motionprobing gradient mpg directions requires more than 10 min of scanning time, which is too long for daily clinical use. The kurtosis is a general, dimensionless statistic for quantifying the nongaussianity of any distribution 5.
Can diffusion kurtosis imaging improve the sensitivity and. To evaluate the diagnostic performance of diffusion kurtosis imaging. Estimation of diffusion and kurtosis model parameters, including the white matter tract integrity metrics, using diffusion kurtosis imaging. Diffusion kurtosis imaging of the healthy human brain core. Note that dke requires the installation of the matlab compiler runtime 2012a mcr. Diffusion kurtosis imaging radiology reference article. Multiple sclerosis is an autoimmune disorder resulting in progressive neurologic disability. As an additional degree of freedom is associated with the noise free nondiffusionweighted signal at least 22. Texture analysis and support vector machineassisted. However, little attention was paid to the performances of dki and dti in detecting white matter abnormality in schizophrenia. The kurtosis k is a dimensionless statistical metric that quantifies the deviation from gaussianity of an arbitrary distribution.
Diffusional kurtosis imaging dki is a more sensitive technique than conventional diffusion tensor imaging dti for assessing tissue microstructure. Diffusivity axial, mean, radial and fractional anisotropy maps using either dki or diffusion tensor imaging signal models are also calculated in the processing. To assess the efficacy of diffusion kurtosis imaging dki and compare dkiderived parameters with conventional diffusionweighted imaging dwi for distinguishing hepatocellular carcinoma hcc from benign hepatic nodules including focal nodular hyperplasia fnh, hemangioma, and hepatocellular adenoma hca. Diffusion kurtosis imaging dki extends conventional diffusion tensor imaging. Kurtosis reflects the deviation of diffusion property from gaussian behavior, whereas diffusivity is the diffusion. The following matlab project contains the source code and matlab examples used for diffusion kurtosis tensor estimation. Diffusion kurtosis imaging estimator file exchange matlab. Diffusion kurtosis imaging dki is an extension of diffusion tensor imaging dti, exhibiting improved sensitivity and specificity in detecting developmental and pathological changes in neural tissues. The diffusion kurtosis observed with diffusion magnetic resonance imaging dmri may vary with direction. Frontiers correlations between the microstructural. Diffusional kurtosis estimator dke users guide contents nitrc. Diffusion kurtosis imaging for detection of early brain changes in parkinsons disease. Diffusion kurtosis imaging of gliomas grades ii and iii. Cureus white matter evaluation in multiple sclerosis.
Pdf diffusion kurtosis imaging for detection of early. The correction of the different types of artifacts gibbs ringing, epi distortion, eddy current distortion, motion, etc as well as noise is necessary for an accurate, precise and robust estimation of diffusion. One can observe that the kurtosis is a measure of peakedness or. To investigate diffusional changes in multiple sclerosis ms plaques and nongaussian behavior of water diffusion by using diffusional kurtosis imaging dki. Diffusion kurtosis imaging is an emerging technique based on the nongaussian diffusion of water in biologic systems.
Diffusion kurtosis imaging as an imaging biomarker for. Contribute to sunenjfastdiffusion kurtosisimagingdki development by creating an account. Precision and accuracy of diffusion kurtosis estimation. However, the 3dimensional dti tractography dtt suffers from the overwhelmingly dense resulting fiber tracts in its visualizations which substantially. Matlab scripts to compute kurtosis metrics from reduced diffusion kurtosis imaging data sets mri. Diffusion time dependent kurtosis maps visualize ischemic lesions in stroke patients. Diffusion weighted magnetic resonance imagesdwmri such as diffusion tensor imagingdti and diffusion kurtosis imagingdki are widely used in understanding the complex cellular microstructures noninvasively. Diffusion parameter estimation with gibbs and noise removal designer is an imageprocessing pipeline for diffusion mri data that has been developed to identify and correct various specific artifacts and confounding factors for an improved accuracy, precision, and robustness in diffusion mri analysis.
Diffusional kurtosis imaging dki is a new technique based on nongaussian water diffusion analysis. As an additional degree of freedom is associated with the noise free nondiffusionweighted signal at least 22 diffusion weighted images must be acquired for dki. Diffusional kurtosis imaging is an extension of dti but includes nongaussian diffusion effects, allowing more comprehensive characterization of microstructural changes during brain development. Our aim was to evaluate whether diffusional kurtosis imaging can detect corticospinal tract microstructural changes in the acute phase for patients with firstever ischemic stroke and motor impairment and to assess the correlations between diffusional kurtosis imagingderived diffusion. Dke requires the installation of the matlab compiler runtime 2012a mcr.
Hence there is a need to assess the accuracy and precision of the estimated parameters as a function of b. Jensen jh1, helpern ja, ramani a, lu h, kaczynski k. Diffusion kurtosis tensor estimation file exchange matlab. For example, if x is a 2by3by4 array, then kurtosisx,1,1 2 returns a 1by1by4 array.
Diffusion kurtosis imaging and conventional diffusion weighted imaging to assess electrochemotherapy response in locally advanced pancreatic cancer vincenza granata v. Diffusion in pure fluids is gaussian, but biological tissues are characterized. Evaluation of intratumoral heterogeneity by using diffusion kurtosis imaging and stretched exponential diffusionweighted imaging in an orthotopic hepatocellular carcinoma xenograft model ran guo1,2. These functions are a simple implementation of the algorithm presented by tabesh et al. A positive kurtosis means the distribution is more strongly peaked and has heavier tails than a gaussian. Each element of the output array is the biased kurtosis of the elements on the corresponding page of x. Comparative analysis of diffusional kurtosis imaging. This script shows how to compute the diffusion kurtosis dki coefficients from a given diffusionweighted mri dataset. In dki studies, a wide range of different gradient strengths bvalues is used, which is known to affect the estimated diffusivity and kurtosis parameters. Diffusion kurtosis imaging provides independent and complementary.
Apparent diffusion d app, in mm 2 s and apparent kurtosis k app, unitless were calculated with inhouse software written in matlab r2018a the mathworks inc. The purpose of this article is to introduce and discuss the ongoing research and potential clinical applications of this technique. Diffusional kurtosis imaging of the developing brain. Performances of diffusion kurtosis imaging and diffusion. Diffusion kurtosis imaging dki is an advanced neuroimaging modality which is an extension of diffusion tensor imaging by estimating the kurtosis skewed distribution of water diffusion based on a probability distribution function. Characterizing microstructural tissue properties in. Kurtosis is a dimensionless measure of the degree of diffusion hindrance or restriction and reflects the changes in structural complexity. Diffusion kurtosis imaging may help stratify heterogeneous diffusionweighted mri lesions for enhanced characterization of ischemic tissue injury. Diffusional kurtosis estimator dke is a software tool for postprocessing diffusional kurtosis imaging dki datasets that includes a suite of commandline programs along with a graphical user interface gui. Diffusion kurtosis imaging dki is an extension of diffusion tensor imaging that accounts for leading nongaussian diffusion effects. Diffusion kurtosis imaging dki is a recent imaging method that probes the diffusion of water molecules. It should be compatible with any matlab version after 2014, and it can be easily adapted to at least 2012 by uncommenting a line. The purpose of our study was to investigate the microstructural changes of the medial temporal cortex in mild cognitive impairment mci patients with cerebral small vascular disease csvd using diffusion kurtosis imaging dki and to examine whether dki parameters are correlated with mci. Diffusion kurtosis imaging and conventional diffusion.
426 1239 103 575 1152 372 442 986 1071 1484 1410 393 221 799 551 2 1004 24 1483 793 679 388 1111 47 1362 447 1502 404 313 1403 587 282 633 136 1039 42 129 1465 946 1040 892 31