Joseph A. Helpern

Diffusional kurtosis imaging: The quantification of non‐gaussian water diffusion by means of magnetic resonance imaging

A magnetic resonance imaging method is presented for quantifying the degree to which water diffusion in biologic tissues is non‐Gaussian. Since tissue structure is responsible for the deviation of water diffusion from the Gaussian behavior typically observed in homogeneous solutions, this method provides a specific measure of tissue structure, such as cellular compartments and membranes. The method is an extension of conventional diffusion‐weighted imaging that requires the use of somewhat higher b values and a modified image postprocessing procedure. In addition to the diffusion coefficient, the method provides an estimate for the excess kurtosis of the diffusion displacement probability distribution, which is a dimensionless metric of the departure from a Gaussian form. From the study of six healthy adult subjects, the excess diffusional kurtosis is found to be significantly higher in white matter than in gray matter, reflecting the structural differences between these two types of cerebral tissues. Diffusional kurtosis imaging is related to q‐space imaging methods, but is less demanding in terms of imaging time, hardware requirements, and postprocessing effort. It may be useful for assessing tissue structure abnormalities associated with a variety of neuropathologies. Magn Reson Med 53:1432–1440, 2005.

MRI quantification of non-Gaussian water diffusion by kurtosis analysis†

Quantification of non‐Gaussianity for water diffusion in brain by means of diffusional kurtosis imaging (DKI) is reviewed. Diffusional non‐Gaussianity is a consequence of tissue structure that creates diffusion barriers and compartments. The degree of non‐Gaussianity is conveniently quantified by the diffusional kurtosis and derivative metrics, such as the mean, axial, and radial kurtoses. DKI is a diffusion‐weighted MRI technique that allows the diffusional kurtosis to be estimated with clinical scanners using standard diffusion‐weighted pulse sequences and relatively modest acquisition times. DKI is an extension of the widely used diffusion tensor imaging method, but requires the use of at least 3 b‐values and 15 diffusion directions. This review discusses the underlying theory of DKI as well as practical considerations related to data acquisition and post‐processing. It is argued that the diffusional kurtosis is sensitive to diffusional heterogeneity and suggested that DKI may be useful for investigating ischemic stroke and neuropathologies, such as Alzheimers disease and schizophrenia. Copyright

The Metabolic Effects of Mild Hypothermia on Global Cerebral Ischemia and Recirculation in the Cat: Comparison to Normothermia and Hyperthermia

The metabolic effects of graded whole body hypothermia on complete global cerebral ischemia and recirculation was investigated in the cat. Hypothermia was induced to one of three levels prior to ischemia; T = 26.8° ± 0.5° (n = 4), T = 32.1° ± 0.2°C (n = 5), and T = 34.6° ± 0.3°C (n = 6), and maintained constant throughout 16 min of ischemia and 1.5–2 h of recirculation. Intracellular cerebral pH and relative concentrations of high-energy phosphate metabolites were continuously monitored, using in vivo 31P nuclear magnetic resonance (NMR) spectroscopy. Except for the first 4 min of ischemia, no significant differences were detected in the response of adenylate intensities and intracellular pH to ischemia and recirculation between the hypothermic groups. The three hypothermic groups were then pooled into one group, and the data compared to previously published data from a normothermic group, T = 38.4° ± 0.6°C (n = 14), and a hyperthermic group, T = 40.6° ± 0.2°C (n = 9), subjected to the identical ischemic and NMR measurement protocols. The hypothermic animals exhibited a statistically significant reduction of cerebral intracellular acidosis, both during ischemia and recirculation, as well as a more rapid return of adenylate intensities during recirculation, compared to the normothermic or hyperthermic groups. The data thus suggest that mild hypothermia has an ameliorative affect on brain energy metabolism and intracellular pH under conditions of complete global cerebral ischemia and recirculation.

White matter characterization with diffusional kurtosis imaging.

Diffusional kurtosis imaging (DKI) is a clinically feasible extension of diffusion tensor imaging that probes restricted water diffusion in biological tissues using magnetic resonance imaging. Here we provide a physically meaningful interpretation of DKI metrics in white matter regions consisting of more or less parallel aligned fiber bundles by modeling the tissue as two non-exchanging compartments, the intra-axonal space and extra-axonal space. For the b-values typically used in DKI, the diffusion in each compartment is assumed to be anisotropic Gaussian and characterized by a diffusion tensor. The principal parameters of interest for the model include the intra- and extra-axonal diffusion tensors, the axonal water fraction and the tortuosity of the extra-axonal space. A key feature is that these can be determined directly from the diffusion metrics conventionally obtained with DKI. For three healthy young adults, the model parameters are estimated from the DKI metrics and shown to be consistent with literature values. In addition, as a partial validation of this DKI-based approach, we demonstrate good agreement between the DKI-derived axonal water fraction and the slow diffusion water fraction obtained from standard biexponential fitting to high b-value diffusion data. Combining the proposed WM model with DKI provides a convenient method for the clinical assessment of white matter in health and disease and could potentially provide important information on neurodegenerative disorders.

Estimation of tensors and tensor-derived measures in diffusional kurtosis imaging.

This article presents two related advancements to the diffusional kurtosis imaging estimation framework to increase its robustness to noise, motion, and imaging artifacts. The first advancement substantially improves the estimation of diffusion and kurtosis tensors parameterizing the diffusional kurtosis imaging model. Rather than utilizing conventional unconstrained least squares methods, the tensor estimation problem is formulated as linearly constrained linear least squares, where the constraints ensure physically and/or biologically plausible tensor estimates. The exact solution to the constrained problem is found via convex quadratic programming methods or, alternatively, an approximate solution is determined through a fast heuristic algorithm. The computationally more demanding quadratic programming‐based method is more flexible, allowing for an arbitrary number of diffusion weightings and different gradient sets for each diffusion weighting. The heuristic algorithm is suitable for real‐time settings such as on clinical scanners, where run time is crucial. The advantage offered by the proposed constrained algorithms is demonstrated using in vivo human brain images. The proposed constrained methods allow for shorter scan times and/or higher spatial resolution for a given fidelity of the diffusional kurtosis imaging parametric maps. The second advancement increases the efficiency and accuracy of the estimation of mean and radial kurtoses by applying exact closed‐form formulae. Magn Reson Med, 2011.

Does diffusion kurtosis imaging lead to better neural tissue characterization? A rodent brain maturation study

Diffusion kurtosis imaging (DKI) can be used to estimate excess kurtosis, which is a dimensionless measure for the deviation of water diffusion profile from Gaussian distribution. Several recent studies have applied DKI to probe the restricted water diffusion in biological tissues. The directional analysis has also been developed to obtain the directionally specific kurtosis. However, these studies could not directly evaluate the sensitivity of DKI in detecting subtle neural tissue alterations. Brain maturation is known to involve various biological events that can affect water diffusion properties, thus providing a sensitive platform to evaluate the efficacy of DKI. In this study, in vivo DKI experiments were performed in normal Sprague-Dawley rats of 3 different ages: postnatal days 13, 31 and 120 (N=6 for each group). Regional analysis was then performed for 4 white matter (WM) and 3 gray matter (GM) structures. Diffusivity and kurtosis estimates derived from DKI were shown to be highly sensitive to the developmental changes in these chosen structures. Conventional diffusion tensor imaging (DTI) parameters were also computed using monoexponential model, yielding reduced sensitivity and directional specificity in monitoring the brain maturation changes. These results demonstrated that, by measuring directionally specific diffusivity and kurtosis, DKI offers a more comprehensive and sensitive detection of tissue microstructural changes. Such imaging advance can provide a better MR diffusion characterization of neural tissues, both WM and GM, in normal, developmental and pathological states.

Age‐related non‐Gaussian diffusion patterns in the prefrontal brain

To characterize age‐related MR diffusion patterns of the prefrontal brain cortex microstructure using a new method for investigating the non‐Gaussian behavior of water diffusion called diffusional kurtosis imaging (DKI).

Functional magnetic resonance imaging of brain activity in the visual oddball task.

Abnormalities in the P300 ERP, elicited by the oddball task and measured using EEG, have been found in a number of central nervous system disorders including schizophrenia, Alzheimers disease, and alcohol dependence. While electrophysiological studies provide high temporal resolution, localizing the P300 deficit has been particularly difficult because the measurements are collected from the scalp. Knowing which brain regions are involved in this process would elucidate the behavioral correlates of P300. The aim of this study was to determine the brain regions involved in a visual oddball task using fMRI. In this study, functional and high-resolution anatomical MR images were collected from seven normal volunteers. The data were analyzed using a randomization-based statistical method that accounts for multiple comparisons, requires no assumptions about the noise structure of the data, and does not require spatial or temporal smoothing. Activations were detected (P<0.01) bilaterally in the supramarginal gyrus (SMG; BA 40), superior parietal lobule (BA 7), the posterior cingulate gyrus, thalamus, inferior occipitotemporal cortex (BA 19/37), insula, dorsolateral prefrontal cortex (BA 9), anterior cingulate cortex (ACC), medial frontal gyrus (BA 6), premotor area, and cuneus (BA 17). Our results are consistent with previous studies that have observed activation in ACC and SMG. Activation of thalamus, insula, and the occipitotemporal cortex has been reported less consistently. The present study lends further support to the involvement of these structures in visual target detection.

Quantitative Assessment of Iron Accumulation in the Deep Gray Matter of Multiple Sclerosis by Magnetic Field Correlation Imaging

BACKGROUND AND PURPOSE: Deposition of iron has been recognized recently as an important factor of pathophysiologic change including neurodegenerative processes in multiple sclerosis (MS). We propose that there is an excess accumulation of iron in the deep gray matter in patients with MS that can be measured with a newly developed quantitative MR technique—magnetic field correlation (MFC) imaging. MATERIALS AND METHODS: With a 3T MR system, we studied 17 patients with relapsing-remitting MS and 14 age-matched healthy control subjects. We acquired MFC imaging using an asymmetric single-shot echo-planar imaging sequence. Regions of interest were selected in both deep gray matter and white matter regions, and the mean MFC values were compared between patients and controls. We also correlated the MFC data with lesion load and neuropsychologic tests in the patients. RESULTS: MFC measured in the deep gray matter in patients with MS was significantly higher than that in the healthy controls (P ≤ .03), with an average increase of 24% in the globus pallidus, 39.5% in the putamen, and 30.6% in the thalamus. The increased iron deposition measured with MFC in the deep gray matter in the patients correlated positively with the total number of MS lesions (thalamus: r = 0.61, P = .01; globus pallidus: r = 0.52, P = .02). A moderate but significant correlation between the MFC value in the deep gray matter and the neuropsychologic tests was also found. CONCLUSION: Quantitative measurements of iron content with MFC demonstrate increased accumulation of iron in the deep gray matter in patients with MS, which may be associated with the disrupted iron outflow pathway by lesions. Such abnormal accumulation of iron may contribute to neuropsychologic impairment and have implications for neurodegenerative processes in MS.

Stroke Assessment With Diffusional Kurtosis Imaging

Background and Purpose— Despite being the gold standard technique for stroke assessment, conventional diffusion MRI provides only partial information about tissue microstructure. Diffusional kurtosis imaging is an advanced diffusion MRI method that yields, in addition to conventional diffusion information, the diffusional kurtosis, which may help improve characterization of tissue microstructure. In particular, this additional information permits the description of white matter (WM) in terms of WM-specific diffusion metrics. The goal of this study is to elucidate possible biophysical mechanisms underlying ischemia using these new WM metrics. Methods— We performed a retrospective review of clinical and diffusional kurtosis imaging data of 44 patients with acute/subacute ischemic stroke. Patients with a history of brain neoplasm or intracranial hemorrhages were excluded from this study. Region of interest analysis was performed to measure percent change of diffusion metrics in ischemic WM lesions compared with the contralateral hemisphere. Results— Kurtosis maps exhibit distinct ischemic lesion heterogeneity that is not apparent on apparent diffusion coefficient maps. Kurtosis metrics also have significantly higher absolute percent change than complementary conventional diffusion metrics. Our WM metrics reveal an increase in axonal density and a larger decrease in the intra-axonal (Da) compared with extra-axonal diffusion microenvironment of the ischemic WM lesion. Conclusions— The well-known decrease in the apparent diffusion coefficient of WM after ischemia is found to be mainly driven by a significant drop in the intra-axonal diffusion microenvironment. Our results suggest that ischemia preferentially alters intra-axonal environment, consistent with a proposed mechanism of focal enlargement of axons known as axonal swelling or beading.