MR diffusion kurtosis imaging for neural tissue characterization

Axon diameter and intra-axonal volume fraction of the corticospinal tract in idiopathic normal pressure hydrocephalus measured by q-space imaging

Purpose

Previous studies suggest that compression and stretching of the corticospinal tract (CST) potentially cause treatable gait disturbance in patients with idiopathic normal pressure hydrocephalus (iNPH). Measurement of axon diameter with diffusion MRI has recently been used to investigate microstructural alterations in neurological diseases. In this study, we investigated alterations in the axon diameter and intra-axonal fraction of the CST in iNPH by q-space imaging (QSI) analysis.

Methods

Nineteen patients with iNPH and 10 age-matched controls were recruited. QSI data were obtained with a 3-T system by using a single-shot echo planar imaging sequence with the diffusion gradient applied parallel to the antero-posterior axis. By using a two-component low-q fit model, the root mean square displacements of intra-axonal space ( =  axon diameter) and intra-axonal volume fraction of the CST were calculated at the levels of the internal capsule and body of the lateral ventricle, respectively.

Results

Wilcoxon's rank-sum test revealed a significant increase in CST intra-axonal volume fraction at the paraventricular level in patients (p<0.001), whereas no significant difference was observed in the axon diameter. At the level of the internal capsule, neither axon diameter nor intra-axonal volume fraction differed significantly between the two groups.

Conclusion

Our results suggest that in patients with iNPH, the CST does not undergo irreversible axonal damage but is rather compressed and/or stretched owing to pressure from the enlarged ventricle. These analyses of axon diameter and intra-axonal fraction yield insights into microstructural alterations of the CST in iNPH.

Diffusion tensor imaging for anatomical localization of cranial nerves and cranial nerve nuclei in pontine lesions: initial experiences with 3T-MRI

With continuous refinement of neurosurgical techniques and higher resolution in neuroimaging, the management of pontine lesions is constantly improving. Among pontine structures with vital functions that are at risk of being damaged by surgical manipulation, cranial nerves (CN) and cranial nerve nuclei (CNN) such as CN V, VI, and VII are critical. Pre-operative localization of the intrapontine course of CN and CNN should be beneficial for surgical outcomes. Our objective was to accurately localize CN and CNN in patients with intra-axial lesions in the pons using diffusion tensor imaging (DTI) and estimate its input in surgical planning for avoiding unintended loss of their function during surgery. DTI of the pons obtained pre-operatively on a 3Tesla MR scanner was analyzed prospectively for the accurate localization of CN and CNN V, VI and VII in seven patients with intra-axial lesions in the pons. Anatomical sections in the pons were used to estimate abnormalities on color-coded fractional anisotropy maps. Imaging abnormalities were correlated with CN symptoms before and after surgery. The course of CN and the area of CNN were identified using DTI pre- and post-operatively. Clinical associations between post-operative improvements and the corresponding CN area of the pons were demonstrated. Our results suggest that pre- and post-operative DTI allows identification of key anatomical structures in the pons and enables estimation of their involvement by pathology. It may predict clinical outcome and help us to better understand the involvement of the intrinsic anatomy by pathological processes.

A fast schema for parameter estimation in diffusion kurtosis imaging

Diffusion kurtosis imaging (DKI) is a new model in magnetic resonance imaging (MRI) characterizing restricted diffusion of water molecules in living tissues. We propose a method for fast estimation of the DKI parameters. These parameters - apparent diffusion coefficient (ADC) and apparent kurtosis coefficient (AKC) - are evaluated using an alternative iteration schema (AIS). This schema first roughly estimates a pair of ADC and AKC values from a subset of the DKI data acquired at 3 b-values. It then iteratively and alternately updates the ADC and AKC until they are converged. This approach employs the technique of linear least square fitting to minimize estimation error in each iteration. In addition to the common physical and biological constrains that set the upper and lower boundaries of the ADC and AKC values, we use a smoothing procedure to ensure that estimation is robust. Quantitative comparisons between our AIS methods and the conventional methods of unconstrained nonlinear least square (UNLS) using both synthetic and real data showed that our unconstrained AIS method can significantly accelerate the estimation procedure without compromising its accuracy, with the computational time for a DKI dataset successfully reduced to only 1 or 2min. Moreover, the incorporation of the smoothing procedure using one of our AIS methods can significantly enhance the contrast of AKC maps and greatly improve the visibility of details in fine structures.

Interimager variability in ADC measurement of the human brain

PURPOSE

Routine clinical practice involves the application of diverse scanning parameters that can affect apparent diffusion coefficient (ADC) values. We evaluated interimager variability in ADC values with respect to their potential effect in clinical applications.

METHODS

In 7 healthy volunteers, we obtained diffusion-weighted (DW) images using routine clinical parameters and 1.5- (n = 9) and 3-tesla (n = 3) magnetic resonance (MR) imagers from 5 different vendors, performing 84 MR imaging studies. To evaluate the differences in ADC values among the imagers, vendors, and magnetic field strengths, we measured the mean pixel values of the frontal white matter and thalamus (gray matter) in both cerebral hemispheres of the 7 volunteers and used repeated-measures analysis of variance for multiple comparisons.

RESULTS

The laterality of ADC values in the bilateral structures ranged from one to 3% for the 12 imagers. Although the relative difference in ADC values of white matter was 7% for scanners yielding the highest and lowest mean ADC values (P < 0.01), it was within 2 to 4% for instruments from the same vendors. For gray matter, the interimager difference was 4 to 12%, even among the same vendors (P < 0.05). Among the 3T imagers, the difference for white and gray matter was approximately 3%.

CONCLUSIONS

There were significant interimager differences in ADC values, especially with respect to gray matter. Taking into consideration the existing laterality, however, the differences among our 3T imagers may be acceptable despite the use of diverse scanning parameters. In routine clinical practice, the existing variability must be considered imager by imager.

Diffusion kurtosis imaging and high-resolution MRI demonstrate structural aberrations of caudate putamen and amygdala after chronic mild stress

The pathophysiology of major depressive disorder (MDD) and other stress related disorders has been associated with aberrations in the hippocampus and the frontal brain areas. More recently, other brain regions, such as the caudate nucleus, the putamen and the amygdala have also been suggested to play a role in the development of mood disorders. By exposing rats to a variety of stressors over a period of eight weeks, different phenotypes, i.e. stress susceptible (anhedonic-like) and stress resilient animals, can be discriminated based on the sucrose consumption test. The anhedonic-like animals are a well validated model for MDD. Previously, we reported that in vivo diffusion kurtosis imaging (DKI) of the hippocampus shows altered diffusion properties in chronically stressed rats independent of the hedonic state and that the shape of the right hippocampus is differing among the three groups, including unchallenged controls. In this study we evaluated diffusion properties in the prefrontal cortex, caudate putamen (CPu) and amygdala of anhedonic-like and resilient phenotypes and found that mean kurtosis in the CPu was significantly different between the anhedonic-like and resilient animals. In addition, axial diffusion and radial diffusion were increased in the stressed animal groups in the CPu and the amygdala, respectively. Furthermore, we found that the CPu/brain volume ratio was increased significantly in anhedonic-like animals as compared with control animals. Concurrently, our results indicate that the effects of chronic stress on the brain are not lateralized in these regions. These findings confirm the involvement of the CPu and the amygdala in stress related disorders and MDD. Additionally, we also show that DKI is a potentially important tool to promote the objective assessment of psychiatric disorders.

Can diffusion kurtosis imaging improve the sensitivity and specificity of detecting microstructural alterations in brain tissue chronically after experimental stroke? Comparisons with diffusion tensor imaging and histology

Imaging techniques that provide detailed insights into structural tissue changes after stroke can vitalize development of treatment strategies and diagnosis of disease. Diffusion-weighted MRI has been playing an important role in this regard. 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. In this study we sought to discern the microstructural alterations characterized by changes in diffusion tensor imaging (DTI) and DKI parameters at a chronic time point after experimental stroke. Of particular interest was the question of whether DKI parameters provide additional information in comparison to DTI parameters in understanding structural tissue changes, and if so, what their histological origins could be. Region-of-interest analysis and a data-driven approach to identify tissue abnormality were adopted to compare DTI- and DKI-based parameters in post mortem rat brain tissue, which were compared against immunohistochemistry of various cellular characteristics. The unilateral infarcted area encompassed the ventrolateral cortex and the lateral striatum. Results from region-of-interest analysis in the lesion borderzone and contralateral tissue revealed significant differences in DTI and DKI parameters between ipsi- and contralateral sensorimotor cortex, corpus callosum, internal capsule and striatum. This was reflected by a significant reduction in ipsilateral mean diffusivity (MD) and fractional anisotropy (FA) values, accompanied by significant increases in kurtosis parameters in these regions. Data-driven analysis to identify tissue abnormality revealed that the use of kurtosis-based parameters improved the detection of tissue changes in comparison with FA and MD, both in terms of dynamic range and in being able to detect changes to which DTI parameters were insensitive. This was observed in gray as well as white matter. Comparison against immunohistochemical stainings divulged no straightforward correlation between diffusion-based parameters and individual neuronal, glial or inflammatory tissue features. Our study demonstrates that DKI allows sensitive detection of structural tissue changes that reflect post-stroke tissue remodeling. However, our data also highlights the generic difficulty in unambiguously asserting specific causal relationships between tissue status and MR diffusion parameters.

A robust post-processing workflow for datasets with motion artifacts in diffusion kurtosis imaging

PURPOSE

The aim of this study was to develop a robust post-processing workflow for motion-corrupted datasets in diffusion kurtosis imaging (DKI).

MATERIALS AND METHODS

The proposed workflow consisted of brain extraction, rigid registration, distortion correction, artifacts rejection, spatial smoothing and tensor estimation. Rigid registration was utilized to correct misalignments. Motion artifacts were rejected by using local Pearson correlation coefficient (LPCC). The performance of LPCC in characterizing relative differences between artifacts and artifact-free images was compared with that of the conventional correlation coefficient in 10 randomly selected DKI datasets. The influence of rejected artifacts with information of gradient directions and b values for the parameter estimation was investigated by using mean square error (MSE). The variance of noise was used as the criterion for MSEs. The clinical practicality of the proposed workflow was evaluated by the image quality and measurements in regions of interest on 36 DKI datasets, including 18 artifact-free (18 pediatric subjects) and 18 motion-corrupted datasets (15 pediatric subjects and 3 essential tremor patients).

RESULTS

The relative difference between artifacts and artifact-free images calculated by LPCC was larger than that of the conventional correlation coefficient (p<0.05). It indicated that LPCC was more sensitive in detecting motion artifacts. MSEs of all derived parameters from the reserved data after the artifacts rejection were smaller than the variance of the noise. It suggested that influence of rejected artifacts was less than influence of noise on the precision of derived parameters. The proposed workflow improved the image quality and reduced the measurement biases significantly on motion-corrupted datasets (p<0.05).

CONCLUSION

The proposed post-processing workflow was reliable to improve the image quality and the measurement precision of the derived parameters on motion-corrupted DKI datasets. The workflow provided an effective post-processing method for clinical applications of DKI in subjects with involuntary movements.

Diffusion kurtosis imaging: an emerging technique for evaluating the microstructural environment of the brain

OBJECTIVE

Diffusion kurtosis imaging is an emerging technique based on the non-gaussian diffusion of water in biologic systems. The purpose of this article is to introduce and discuss the ongoing research and potential clinical applications of this technique.

CONCLUSION

Diffusion kurtosis imaging provides independent and complementary information to that acquired with traditional diffusion techniques. The additional information is thought to indicate the complexity of the microstructural environment of the imaged tissue and may lead to broad-reaching applications in all aspects of neuroradiology.

Double-pulsed diffusional kurtosis imaging

Diffusional kurtosis imaging (DKI) is extended to double-pulsed-field-gradient (d-PFG) diffusion MRI sequences. This gives a practical approach for acquiring and analyzing d-PFG data. In particular, the leading d-PFG effects, beyond what conventional single-pulsed field gradient (s-PFG) provides, are interpreted in terms of the kurtosis for a diffusion displacement probability density function (dPDF) in a six-dimensional (6D) space. The 6D diffusional kurtosis encodes the unique information provided by d-PFG sequences up to second order in the b-value. This observation leads to a compact expression for the signal magnitude, and it suggests novel data acquisition and analysis methods. Double-pulsed DKI (DP-DKI) is demonstrated for in vivo mouse brain with d-PFG data obtained at 7 T. Copyright © 2014 John Wiley & Sons, Ltd.

Leading non-Gaussian corrections for diffusion orientation distribution function

An analytical representation of the leading non-Gaussian corrections for a class of diffusion orientation distribution functions (dODFs) is presented. This formula is constructed from the diffusion and diffusional kurtosis tensors, both of which may be estimated with diffusional kurtosis imaging (DKI). By incorporating model-independent non-Gaussian diffusion effects, it improves on the Gaussian approximation used in diffusion tensor imaging (DTI). This analytical representation therefore provides a natural foundation for DKI-based white matter fiber tractography, which has potential advantages over conventional DTI-based fiber tractography in generating more accurate predictions for the orientations of fiber bundles and in being able to directly resolve intra-voxel fiber crossings. The formula is illustrated with numerical simulations for a two-compartment model of fiber crossings and for human brain data. These results indicate that the inclusion of the leading non-Gaussian corrections can significantly affect fiber tractography in white matter regions, such as the centrum semiovale, where fiber crossings are common.

Non-Gaussian diffusion-weighted imaging for assessing diurnal changes in intervertebral disc microstructure

PURPOSE

To investigate the use of non-Gaussian diffusion-weighted imaging (q-space imaging [QSI]) to estimate diurnal changes in intervertebral disc (IVD) microstructure.

MATERIALS AND METHODS

IVDs of 15 male subjects (mean age, 27.3 years; mean body mass index, 22.50 kg/m(2) ) were investigated once in the morning, less than 30 min after rising, and a second time in the evening after at least 10 h of normal physical activity, using 3 Tesla (T) MR imaging. T2 mapping and QSI data values (apparent diffusion coefficient [ADC], root mean square displacement [RMSD], and apparent kurtosis coefficient [AKC]) were calculated and compared between the morning and evening imaging sessions.

RESULTS

The T2, ADC, and RMSD values showed a significant decrease in the evening (175.8 ± 49.5 ms, 1.56 ± 0.32 10(-3) mm(2) /s and 40.0 ± 3.0 μm, respectively; P < 0.05 for all values; paired t-test), when compared with the morning values (226.5 ± 83.8 ms, 1.69 ± 0.29 10(-3) mm(2) /s and 45.2 ± 2.9 μm, respectively). The AKC value showed a significant increase in the evening (0.67 ± 0.08), when compared with the morning value (0.58 ± 0.04; P < 0.05).

CONCLUSION

The RMSD and AKC values obtained from QSI analysis may be biomarkers for IVD diurnal microstructural changes.

A better characterization of spinal cord damage in multiple sclerosis: a diffusional kurtosis imaging study

BACKGROUND AND PURPOSE

The spinal cord is a site of predilection for MS lesions. While diffusion tensor imaging is useful for the study of anisotropic systems such as WM tracts, it is of more limited utility in tissues with more isotropic microstructures (on the length scales studied with diffusion MR imaging) such as gray matter. In contrast, diffusional kurtosis imaging, which measures both Gaussian and non-Gaussian properties of water diffusion, provides more biomarkers of both anisotropic and isotropic structural changes. The aim of this study was to investigate the cervical spinal cord of patients with MS and to characterize lesional and normal-appearing gray matter and WM damage by using diffusional kurtosis imaging.

MATERIALS AND METHODS

Nineteen patients (13 women, mean age = 41.1 ± 10.7 years) and 16 controls (7 women, mean age = 35.6 ± 11.2-years) underwent MR imaging of the cervical spinal cord on a 3T scanner (T2 TSE, T1 magnetization-prepared rapid acquisition of gradient echo, diffusional kurtosis imaging, T2 fast low-angle shot). Fractional anisotropy, mean diffusivity, and mean kurtosis were measured on the whole cord and in normal-appearing gray matter and WM.

RESULTS

Spinal cord T2-hyperintense lesions were identified in 18 patients. Whole spinal cord fractional anisotropy and mean kurtosis (P = .0009, P = .003), WM fractional anisotropy (P = .01), and gray matter mean kurtosis (P = .006) were significantly decreased, and whole spinal cord mean diffusivity (P = .009) was increased in patients compared with controls. Mean spinal cord area was significantly lower in patients (P = .04).

CONCLUSIONS

Diffusional kurtosis imaging of the spinal cord can provide a more comprehensive characterization of lesions and normal-appearing WM and gray matter damage in patients with MS. Diffusional kurtosis imaging can provide additional and complementary information to DTI on spinal cord pathology.

Attention-deficit/hyperactivity disorder without comorbidity is associated with distinct atypical patterns of cerebral microstructural development

Differential core symptoms and treatment responses are associated with the pure versus comorbid forms of attention-deficit/hyperactivity disorder (ADHD). However, comorbidity has largely been unaccounted for in neuroimaging studies of ADHD. We used diffusional kurtosis imaging to investigate gray matter (GM) and white matter (WM) microstructure of children and adolescents with ADHD (n = 22) compared to typically developing controls (TDC, n = 27) and examined whether differing developmental patterns are related to comorbidity. The ADHD group (ADHD-mixed) consisted of subgroups with and without comorbidity (ADHD-comorbid, n = 11; ADHD-pure, n = 11, respectively). Age-related changes and group differences in cerebral microstructure of the ADHD-mixed group and each ADHD subgroup were compared to TDC. Whole-brain voxel-based analyses with mean kurtosis (MK) and mean diffusivity (MD) metrics were conducted to probe GM and WM. Tract-based spatial statistics analyses of WM were performed with MK, MD, fractional anisotropy, and directional (axial, radial) kurtosis and diffusivity metrics. ADHD-pure patients lacked significant age-related changes in GM and WM microstructure that were observed globally in TDC and had significantly greater WM microstructural complexity than TDC in bilateral frontal and parietal lobes, insula, corpus callosum, and right external and internal capsules. Including ADHD patients with diverse comorbidities in analyses masked these findings. A distinct atypical age-related trajectory and aberrant regional differences in brain microstructure were detected in ADHD without comorbidity. Our results suggest that different phenotypic manifestations of ADHD, defined by the presence or absence of comorbidity, differ in cerebral microstructural markers.

Diffusion kurtosis imaging with tract-based spatial statistics reveals white matter alterations in preschool children

Diffusion kurtosis imaging (DKI), an extension of diffusion tensor imaging (DTI), provides a practical method to describe non-Gaussian water diffusion in neural tissues. The sensitivity of DKI to detect the subtle changes in several chosen brain structures has been studied. However, intuitive and holistic methods to validate the merits of DKI remain to be explored. In this paper, tract-based spatial statistics (TBSS) was used to demonstrate white matter alterations in both DKI and DTI parameters in preschool children (1-6 years; n=10). Correlation analysis was also performed in multiple regions of interest (ROIs). Fractional anisotropy, mean kurtosis, axial kurtosis and radial kurtosis increased with age, while mean diffusivity and radial diffusivity decreased significantly with age. Fractional anisotropy of kurtosis and axial diffusivity were found to be less sensitive to the changes with age. These preliminary findings indicated that TBSS could be used to detect subtle changes of DKI parameters on the white matter tract. Kurtosis parameters, except fractional anisotropy of kurtosis, demonstrated higher sensitivity than DTI parameters. TBSS may be a convenient method to yield higher sensitivity of DKI.

Evaluation of optimized b-value sampling schemas for diffusion kurtosis imaging with an application to stroke patient data

Diffusion kurtosis imaging (DKI) is a new method of magnetic resonance imaging (MRI) that provides non-Gaussian information that is not available in conventional diffusion tensor imaging (DTI). DKI requires data acquisition at multiple b-values for parameter estimation; this process is usually time-consuming. Therefore, fewer b-values are preferable to expedite acquisition. In this study, we carefully evaluated various acquisition schemas using different numbers and combinations of b-values. Acquisition schemas that sampled b-values that were distributed to two ends were optimized. Compared to conventional schemas using equally spaced b-values (ESB), optimized schemas require fewer b-values to minimize fitting errors in parameter estimation and may thus significantly reduce scanning time. Following a ranked list of optimized schemas resulted from the evaluation, we recommend the 3b schema based on its estimation accuracy and time efficiency, which needs data from only 3 b-values at 0, around 800 and around 2600 s/mm2, respectively. Analyses using voxel-based analysis (VBA) and region-of-interest (ROI) analysis with human DKI datasets support the use of the optimized 3b (0, 1000, 2500 s/mm2) DKI schema in practical clinical applications.

A preliminary study of epilepsy in children using diffusional kurtosis imaging

OBJECTIVE

To study brain abnormalities, in terms of non-Gaussian water diffusion properties using diffusional kurtosis imaging (DKI) in children with electroencephalography (EEG) confirmed epilepsy lateralized to both hemispheres.

METHODS

A total of 15 children with epileptiform waves on EEG in both hemispheres and 18 children as normal controls (NC) matched for age and sex were recruited. Data from DKI for all children were used to characterize non-Gaussian properties. Fractional anisotropy (FA), mean diffusivity (MD), and mean kurtosis (MK) maps were estimated from the DKI datasets. Voxel-based analyses (VBA) based on these measures were performed and compared between the epilepsy and NC groups.

RESULTS

The VBA showed abnormal regions in both white matter (WM) and gray matter (GM) in those with epilepsy. Analysis of FA values revealed that the abnormal regions were significant mainly in the left frontal and temporal lobes of the WM. Analysis of MD values revealed that differences were significant mainly in the right hemisphere of the limbic lobe, uncus, parahippocampal region, both in GM and WM of frontal and temporal lobes, and GM of the rectus of the left cerebrum. Finally, analysis of MK values revealed significant differences mainly in WM of the frontal lobes of both cerebrum, and GM and WM of the parietal lobe of the right cerebrum.

CONCLUSIONS

These preliminary results suggest that DKI is sensitive for the characterization of diffusion abnormalities in both WM and GM of children with epilepsy.

Brain connectivity plasticity in the motor network after ischemic stroke

The motor function is controlled by the motor system that comprises a series of cortical and subcortical areas interacting via anatomical connections. The motor function will be disturbed when the stroke lesion impairs either any of these areas or their connections. More and more evidence indicates that the reorganization of the motor network including both areas and their anatomical and functional connectivity might contribute to the motor recovery after stroke. Here, we review recent studies employing models of anatomical, functional, and effective connectivity on neuroimaging data to investigate how ischemic stroke influences the connectivity of motor areas and how changes in connectivity relate to impaired function and functional recovery. We suggest that connectivity changes constitute an important pathophysiological aspect of motor impairment after stroke and important mechanisms of motor recovery. We also demonstrate that therapeutic interventions may facilitate motor recovery after stroke by modulating the connectivity among the motor areas. In conclusion, connectivity analyses improved our understanding of the mechanisms of motor recovery after stroke and may help to design hypothesis-driven treatment strategies and sensitive measures for outcome prediction in stroke patients.

Diffusion/perfusion MR imaging of the liver: practice, challenges, and future

Diffusion-weighted (DWI) magnetic resonance (MR) imaging is useful in diagnosing various pathologic conditions in the liver, such as malignant tumors or hepatic fibrosis, and is now part of routine MR imaging protocols for the liver following the development of a parallel encoding technique that has markedly improved image quality. DWI is not very sensitive for detecting hepatocellular carcinomas (HCC) and is useless for characterizing border-line hepatocellular nodules in cirrhosis, but it complements gadolinium-enhanced MR imaging in detecting regional tumor recurrence or intrahepatic metastases of HCC following treatment. DWI is more useful for detecting hepatic metastasis, because histopathologic architecture of metastases does not resemble that of liver tissue and T(2) relaxation time of hepatic metasitasis is fairly longer than that of liver parenchyma. DWI is also useful for detecting moderate and advanced hepatic fibrosis. In cirrhosis, however, decreased blood flow in fibrotic liver is thought to lower apparent diffusion coefficient of the liver. For MR perfusion analysis, a dual-input one-compartment model is used to correlate various hepatic blood flow parameters that represent hepatic arterial/portal blood flow or fraction, mean transit time, and distribution volume with the severity of cirrhosis and portal hypertension. Conventional multisectional imaging and perfusion study can be combined using a 3-dimensional sequence with high temporal resolution, but spatial resolution is not sufficiently high to diagnose tiny hepatic lesions. The advent of liver-specific contrast agents, such as gadoxetic acid, may spur the development of a new analysis model that incorporates extracellular perfusion and hepatocyte function.

MR diffusion tensor imaging detects rapid microstructural changes in amygdala and hippocampus following fear conditioning in mice

BACKGROUND

Following fear conditioning (FC), ex vivo evidence suggests that early dynamics of cellular and molecular plasticity in amygdala and hippocampal circuits mediate responses to fear. Such altered dynamics in fear circuits are thought to be etiologically related to anxiety disorders including posttraumatic stress disorder (PTSD). Consistent with this, neuroimaging studies of individuals with established PTSD in the months after trauma have revealed changes in brain regions responsible for processing fear. However, whether early changes in fear circuits can be captured in vivo is not known.

METHODS

We hypothesized that in vivo magnetic resonance diffusion tensor imaging (DTI) would be sensitive to rapid microstructural changes elicited by FC in an experimental mouse PTSD model. We employed a repeated measures paired design to compare in vivo DTI measurements before, one hour after, and one day after FC-exposed mice (n=18).

RESULTS

Using voxel-wise repeated measures analysis, fractional anisotropy (FA) significantly increased then decreased in amygdala, decreased then increased in hippocampus, and was increasing in cingulum and adjacent gray matter one hour and one day post-FC respectively. These findings demonstrate that DTI is sensitive to early changes in brain microstructure following FC, and that FC elicits distinct, rapid in vivo responses in amygdala and hippocampus.

CONCLUSIONS

Our results indicate that DTI can detect rapid microstructural changes in brain regions known to mediate fear conditioning in vivo. DTI indices could be explored as a translational tool to capture potential early biological changes in individuals at risk for developing PTSD.

Diffusion MR imaging: How to get the maximum from the experimental time

Diffusion-based MR imaging is the only non-invasive method for characterising the microstructural organization of brain tissue in vivo. Diffusion tensor MRI (DT-MRI) is currently routinely used in both research and clinical practice. However, other diffusion approaches are gaining more and more popularity and an increasing number of researchers express interest in using them concomitantly with DT-MRI. While non tensor-based methods hold great promises for increasing the specificity of diffusion MR imaging, including them in the experimental routine inevitably leads to longer experimental times. In most cases, this may preclude the translation of the full protocol to clinical practice, especially when these methods are to be used with subjects that are not compatible with long scanning sessions (e.g., with elderly and pediatric subjects who have difficulties in maintaining a fixed head position during a long imaging session).

The aim of this review is to guide the end-users on obtaining the maximum from the experimental time allocated to collecting diffusion MRI data. This is done by: (i) briefly reviewing non tensor-based approaches; (ii) reviewing the optimal protocols for both tensor and non tensor-based imaging; and (iii) drawing the conclusions for different experimental times.

Cognitive impairment in mild traumatic brain injury: a longitudinal diffusional kurtosis and perfusion imaging study

BACKGROUND AND PURPOSE

Cognitive impairment is frequent among patients with mild traumatic brain injury despite the absence of detectable damage on conventional MR imaging. In this study, the quantitative MR imaging techniques DTI, DKI, and ASL were used to measure changes in the structure and function in the thalamus and WM of patients with MTBI during a short follow-up period, to determine whether these techniques can be used to investigate relationships with cognitive performance and to predict outcome.

MATERIALS AND METHODS

Twenty patients with MTBI and 16 controls underwent MR imaging at 3T and a neuropsychological battery designed to yield measures for attention, concentration, executive functioning, memory, learning, and information processing. MK, FA, MD, and CBF were measured in the thalamus by using region-of-interest analysis and in WM by using tract-based spatial statistics. Analyses were performed comparing regional imaging measures of subject groups and the results of testing of their associations with neuropsychological performance.

RESULTS

Patients with MTBI exhibited significant differences from controls for DTI, DKI, and ASL measures in the thalamus and various WM regions both within 1 month after injury and >9 months after injury. At baseline, DTI and DKI measures in the thalamus and various WM regions were significantly associated with performance in different neuropsychological domains, and cognitive impairment was significantly associated with MK in the thalamus and FA in optic radiations.

CONCLUSIONS

Combined application of DTI, DKI, and ASL to study MTBI might be useful for investigating dynamic changes in the thalamus and WM as well as cognitive impairment during a short follow-up period, though the small number of patients examined did not predict outcome.

Diffusion kurtosis imaging and log-normal distribution function imaging enhance the visualisation of lesions in animal stroke models

In this work, we report a case study of a stroke model in animals using two methods of quantification of the deviations from Gaussian behaviour: diffusion kurtosis imaging (DKI) and log-normal distribution function imaging (LNDFI). The affected regions were predominantly in grey rather than in white matter. The parameter maps were constructed for metrics quantifying the apparent diffusivity (evaluated from conventional diffusion tensor imaging, DKI and LNDFI) and for those quantifying the degree of deviations (mean kurtosis and a parameter σ characterising the width of the distribution). We showed that both DKI and LNDFI were able to dramatically enhance the visualisation of ischaemic lesions in comparison with conventional methods. The largest relative change in the affected versus healthy regions was observed in the mean kurtosis values. The average changes in the mean kurtosis and σ values in the lesions were a factor of two to three larger than the relative changes observed in the mean diffusivity. In conclusion, the applied methods promise valuable perspectives in the assessment of stroke.

Effect of cerebral spinal fluid suppression for diffusional kurtosis imaging

PURPOSE

To evaluate the cerebral spinal fluid (CSF) partial volume effect on diffusional kurtosis imaging (DKI) metrics in white matter and cortical gray matter.

MATERIALS AND METHODS

Four healthy volunteers participated in this study. Standard DKI and fluid-attenuated inversion recovery (FLAIR) DKI experiments were performed using a twice-refocused-spin-echo diffusion sequence. The conventional diffusion tensor imaging (DTI) metrics of fractional anisotropy (FA), mean, axial, and radial diffusivity (MD, D[symbol in text], D[symbol in text] together with DKI metrics of mean, axial, and radial kurtosis (MK, K[symbol in text], K[symbol in text], were measured and compared. Single image slices located above the lateral ventricles, with similar anatomical features for each subject, were selected to minimize the effect of CSF from the ventricles.

RESULTS

In white matter, differences of less than 10% were observed between diffusion metrics measured with standard DKI and FLAIR-DKI sequences, suggesting minimal CSF contamination. For gray matter, conventional DTI metrics differed by 19% to 52%, reflecting significant CSF partial volume effects. Kurtosis metrics, however, changed by 11% or less, indicating greater robustness with respect to CSF contamination.

CONCLUSION

Kurtosis metrics are less sensitive to CSF partial voluming in cortical gray matter than conventional diffusion metrics. The kurtosis metrics may then be more specific indicators of changes in tissue microstructure, provided the effect sizes for the changes are comparable.

Parametric mapping of brain tissues from diffusion kurtosis tensor

Diffusion kurtosis imaging (DKI) is a new diffusion magnetic resonance imaging (MRI) technique to go beyond the shortages of conventional diffusion tensor imaging (DTI) from the assumption that water diffuse in biological tissue is Gaussian. Kurtosis is used to measure the deviation of water diffusion from Gaussian model, which is called non-Gaussian, in DKI. However, the high-order kurtosis tensor in the model brings great difficulties in feature extraction. In this study, parameters like fractional anisotropy of kurtosis eigenvalues (FAek) and mean values of kurtosis eigenvalues (Mek) were proposed, and regional analysis was performed for 4 different tissues: corpus callosum, crossing fibers, thalamus, and cerebral cortex, compared with other parameters. Scatterplot analysis and Gaussian mixture decomposition of different parametric maps are used for tissues identification. Diffusion kurtosis information extracted from kurtosis tensor presented a more detailed classification of tissues actually as well as clinical significance, and the FAek of D-eigenvalues showed good sensitivity of tissues complexity which is important for further study of DKI.

Stratification of heterogeneous diffusion MRI ischemic lesion with kurtosis imaging: evaluation of mean diffusion and kurtosis MRI mismatch in an animal model of transient focal ischemia

BACKGROUND AND PURPOSE

Ischemic tissue damage is heterogeneous, resulting in complex patterns in the widely used diffusion-weighted MRI. Our study examined the spatiotemporal characteristics of diffusion kurtosis imaging in an animal model of transient middle cerebral artery occlusion.

METHODS

Adult male Wistar rats (N=18) were subjected to 90 minutes middle cerebral artery occlusion. Multiparametric MR images were obtained during middle cerebral artery occlusion and 20 minutes after reperfusion with diffusion-weighted MRI obtained using 8 b-values from 250 to 3000 s/mm(2) in 6 diffusion gradient directions. Diffusion and kurtosis lesions were outlined in shuffled images by 2 investigators independently. T(2) MRI was obtained 24 hours after middle cerebral artery occlusion to evaluate stroke outcome.

RESULTS

Mean diffusion lesion (23.5%±8.1%, percentage of the brain slice) was significantly larger than mean kurtosis lesion (13.2%±2.0%) during middle cerebral artery occlusion. Mean diffusion lesion decreased significantly after reperfusion (13.8%±4.3%), whereas mean kurtosis lesion showed little change (13.0%±2.5%) with their lesion size difference being insignificant.

CONCLUSIONS

We demonstrated that mean diffusion/mean kurtosis mismatch recovered reasonably well on reperfusion, whereas regions with concurrent mean diffusion and mean kurtosis deficits showed poor recovery. Diffusion kurtosis imaging may help stratify heterogeneous diffusion-weighted MRI lesions for enhanced characterization of ischemic tissue injury.

Identification and characterization of Huntington related pathology: an in vivo DKI imaging study

An important focus of Huntington Disease (HD) research is the identification of symptom-independent biomarkers of HD neuropathology. There is an urgent need for reproducible, sensitive and specific outcome measures, which can be used to track disease onset as well as progression. Neuroimaging studies, in particular diffusion-based MRI methods, are powerful probes for characterizing the effects of disease and aging on tissue microstructure. We report novel diffusional kurtosis imaging (DKI) findings in aged transgenic HD rats. We demonstrate altered diffusion metrics in the (pre)frontal cerebral cortex, external capsule and striatum. Presence of increased diffusion complexity and restriction in the striatum is confirmed by an increased fiber dispersion in this region. Immunostaining of the same specimens reveals decreased number of microglia in the (pre)frontal cortex, and increased numbers of oligodendrocytes in the striatum. We conclude that DKI allows sensitive and specific characterization of altered tissue integrity in this HD rat model, indicating a promising potential for diagnostic imaging of gray and white matter pathology.

Altered diffusion tensor imaging measurements in aged transgenic Huntington disease rats

Rodent models of Huntington disease (HD) are valuable tools for investigating HD pathophysiology and evaluating new therapeutic approaches. Non-invasive characterization of HD-related phenotype changes is important for monitoring progression of pathological processes and possible effects of interventions. The first transgenic rat model for HD exhibits progressive late-onset affective, cognitive, and motor impairments, as well as neuropathological features reflecting observations from HD patients. In this report, we contribute to the anatomical phenotyping of this model by comparing high-resolution ex vivo DTI measurements obtained in aged transgenic HD rats and wild-type controls. By region of interest analysis supplemented by voxel-based statistics, we find little evidence of atrophy in basal ganglia regions, but demonstrate altered DTI measurements in the dorsal and ventral striatum, globus pallidus, entopeduncular nucleus, substantia nigra, and hippocampus. These changes are largely compatible with DTI findings in preclinical and clinical HD patients. We confirm earlier reports that HD rats express a moderate neuropathological phenotype, and provide evidence of altered DTI measures in specific HD-related brain regions, in the absence of pronounced morphometric changes.

Oscillating and pulsed gradient diffusion magnetic resonance microscopy over an extended b-value range: implications for the characterization of tissue microstructure

Oscillating gradient spin-echo (OGSE) pulse sequences have been proposed for acquiring diffusion data with very short diffusion times, which probe tissue structure at the subcellular scale. OGSE sequences are an alternative to pulsed gradient spin echo measurements, which typically probe longer diffusion times due to gradient limitations. In this investigation, a high-strength (6600 G/cm) gradient designed for small-sample microscopy was used to acquire OGSE and pulsed gradient spin echo data in a rat hippocampal specimen at microscopic resolution. Measurements covered a broad range of diffusion times (TDeff = 1.2-15.0 ms), frequencies (ω = 67-1000 Hz), and b-values (b = 0-3.2 ms/μm2). Variations in apparent diffusion coefficient with frequency and diffusion time provided microstructural information at a scale much smaller than the imaging resolution. For a more direct comparison of the techniques, OGSE and pulsed gradient spin echo data were acquired with similar effective diffusion times. Measurements with similar TDeff were consistent at low b-value (b < 1 ms/μm(2) ), but diverged at higher b-values. Experimental observations suggest that the effective diffusion time can be helpful in the interpretation of low b-value OGSE data. However, caution is required at higher b, where enhanced sensitivity to restriction and exchange render the effective diffusion time an unsuitable representation. Oscillating and pulsed gradient diffusion techniques offer unique, complementary information. In combination, the two methods provide a powerful tool for characterizing complex diffusion within biological tissues.

New diffusion metrics for spondylotic myelopathy at an early clinical stage

OBJECTIVES

To investigate the use of root mean square displacement (RMSD) and mean diffusional kurtosis (DK) metrics of q-space imaging data to estimate spinal cord compression in patients with early cervical spondylosis.

METHODS

We studied 50 consecutive patients at our institution (22 male, 28 female; mean age 58 years; age range 20-86 years) who had clinical signs and symptoms suggestive of early clinical stage cervical myelopathy. After conventional magnetic resonance (MR) imaging, diffusion tensor and q-space image data were acquired using 3-T MR imaging. Fractional anisotropy (FA), apparent diffusion coefficient (ADC), RMSD and mean DK values were calculated and compared between compressed and uncompressed spinal cords.

RESULTS

FA and mean DK values were significantly lower and RMSD was significantly higher (P = 0.0060, 0.0020 and 0.0062, respectively; Mann-Whitney U test with the Bonferroni correction) in compressed spinal cords than in uncompressed cords. ADC was also higher in compressed cords, but this difference was not statistically significant.

CONCLUSIONS

In the evaluation of spinal cord damage in early cervical spondylosis, mean DK and RMSD values in the spinal cord may be highly sensitive indicators of microstructural change and damage.

KEY POINTS

• Absolute surgical indications for cervical spondylosis with myelopathy remain to be established. • Diffusion tensor MRI shows abnormalities in normal-appearing but compressed spinal cord. • Non-Gaussian diffusion analysis is highly sensitive in revealing spinal cord damage.

Functional MRI and diffusion tensor imaging of brain reorganization after experimental stroke

The potential of the adult brain to reorganize after ischemic injury is critical for functional recovery and provides a significant target for therapeutic strategies to promote brain repair. Despite the accumulating evidence of brain plasticity, the interaction and significance of morphological and physiological modifications in post-stroke brain tissue remain mostly unclear. Neuroimaging techniques such as functional MRI (fMRI) and diffusion tensor imaging (DTI) enable in vivo assessment of the spatial and temporal pattern of functional and structural changes inside and outside ischemic lesion areas. This can contribute to the elucidation of critical aspects in post-stroke brain remodeling. Task/stimulus-related fMRI, resting-state fMRI, or pharmacological MRI enables direct or indirect measurement of neuronal activation, functional connectivity, or neurotransmitter system responses, respectively. DTI allows estimation of the structural integrity and connectivity of white matter tracts. Together, these MRI methods provide an unprecedented means to (a) measure longitudinal changes in tissue structure and function close by and remote from ischemic lesion areas, (b) evaluate the organizational profile of neural networks after stroke, and (c) identify degenerative and restorative processes that affect post-stroke functional outcome. Besides, the availability of MRI in clinical institutions as well as research laboratories provides an optimal basis for translational research on stroke recovery. This review gives an overview of the current status and perspectives of fMRI and DTI applications to study brain reorganization in experimental stroke models.

Diffusion kurtosis as an in vivo imaging marker for reactive astrogliosis in traumatic brain injury

Diffusion Kurtosis Imaging (DKI) provides quantifiable information on the non-Gaussian behavior of water diffusion in biological tissue. Changes in water diffusion tensor imaging (DTI) parameters and DKI parameters in several white and gray matter regions were investigated in a mild controlled cortical impact (CCI) injury rat model at both the acute (2 h) and the sub-acute (7 days) stages following injury. Mixed model ANOVA analysis revealed significant changes in temporal patterns of both DTI and DKI parameters in the cortex, hippocampus, external capsule and corpus callosum. Post-hoc tests indicated acute changes in mean diffusivity (MD) in the bilateral cortex and hippocampus (p<0.0005) and fractional anisotropy (FA) in ipsilateral cortex (p<0.0005), hippocampus (p=0.014), corpus callosum (p=0.031) and contralateral external capsule (p=0.011). These changes returned to baseline by the sub-acute stage. However, mean kurtosis (MK) was significantly elevated at the sub-acute stages in all ipsilateral regions and scaled inversely with the distance from the impacted site (cortex and corpus callosum: p<0.0005; external capsule: p=0.003; hippocampus: p=0.011). Further, at the sub-acute stage increased MK was also observed in the contralateral regions compared to baseline (cortex: p=0.032; hippocampus: p=0.039) while no change was observed with MD and FA. An increase in mean kurtosis was associated with increased reactive astrogliosis from immunohistochemistry analysis. Our results suggest that DKI is sensitive to microstructural changes associated with reactive astrogliosis which may be missed by standard DTI parameters alone. Monitoring changes in MK allows the investigation of molecular and morphological changes in vivo due to reactive astrogliosis and may complement information available from standard DTI parameters. To date the use of diffusion tensor imaging has been limited to study changes in white matter integrity following traumatic insults. Given the sensitivity of DKI to detect microstructural changes even in the gray matter in vivo, allows the extension of the technique to understand patho-morphological changes in the whole brain following a traumatic insult.

Diffusion imaging with balanced steady state free precession

Balanced steady state free precession (bSSFP) offers high signal efficiency and relative motion insensitivity. In this study, diffusion weighted bSSFP (DW-bSSFP) was introduced by modifying standard bSSFP sequence with two pairs of balanced bipolar diffusion gradients. The diffusion effect was analyzed and described in closed forms. It was found to be coupled to the transverse and longitudinal relaxation, flip angle and spin phase advance per TR. Such coupling was demonstrated in phantom experiment at 7T. Preliminary DW-bSSFP imaging experiment was performed in rat brain in vivo for diffusion tensor imaging, yielding parametric maps qualitatively similar to those obtained with an 8-shot DW-EPI protocol. The proposed DW-bSSFP approach can provide a new means of diffusion imaging with high resolution, relative motion insensitivity and short diffusion time. Such approach may lead to improved and new diffusion characterization of neural tissues, abdominal organs, myocardium and musculoskeletal tissues.

A simple isotropic phantom for diffusional kurtosis imaging

Dairy cream is shown to be a simple, inexpensive, isotropic phantom useful for testing diffusional kurtosis imaging data acquisition and postprocessing. The MR-visible protons of cream exhibit slow and fast diffusion components, attributed to the fat and water protons, respectively, which give rise to a diffusion coefficient of 1.1 μm(2)/ms and a diffusional kurtosis of 1.2. These parameter values are similar to those observed in vivo for human brain. Heating the cream is found to increase the T(2)-relaxation time of the fat protons, which facilitates the evaluation of typical diffusional kurtosis imaging protocols used in clinical settings. The diffusion coefficient and diffusional kurtosis can both be measured directly and predicted based on the corresponding diffusion parameters of the individual water and fat components, which are independently measurable due to chemical shift misregistration, thus providing an important consistency check. This phantom is proposed as a convenient calibration standard for multicenter diffusional kurtosis imaging studies.

Thalamus and cognitive impairment in mild traumatic brain injury: a diffusional kurtosis imaging study

Conventional imaging is unable to detect damage that accounts for permanent cognitive impairment in patients with mild traumatic brain injury (mTBI). While diffusion tensor imaging (DTI) can help to detect diffuse axonal injury (DAI), it is a limited indicator of tissue complexity. It has also been suggested that the thalamus may play an important role in the development of clinical sequelae in mTBI. The purpose of this study was to determine if diffusional kurtosis imaging (DKI), a novel quantitative magnetic resonance imaging (MRI) technique, can provide early detection of damage in the thalamus and white matter (WM) of mTBI patients, and can help ascertain if thalamic injury is associated with cognitive impairment. Twenty-two mTBI patients and 14 controls underwent MRI and neuropsychological testing. Mean kurtosis (MK), fractional anisotropy (FA), and mean diffusivity (MD) were measured in the thalamus and several WM regions classically identified with DAI. Compared to controls, patients examined within 1 year after injury exhibited variously altered DTI- and DKI-derived measures in the thalamus and the internal capsule, while in addition to these regions, patients examined more than 1 year after injury also showed similar differences in the splenium of the corpus callosum and the centrum semiovale. Cognitive impairment was correlated with MK in the thalamus and the internal capsule. These findings suggest that combined use of DTI and DKI provides a more sensitive tool for identifying brain injury. In addition, MK in the thalamus might be useful for early prediction of permanent brain damage and cognitive outcome.

Parkinson disease: diagnostic utility of diffusion kurtosis imaging

PURPOSE

To examine the usefulness of diffusion kurtosis imaging for the diagnosis of Parkinson disease (PD).

MATERIALS AND METHODS

Examinations were performed with the understanding and written consent of each subject, with local ethics committee approval, and in compliance with national legislation and Declaration of Helsinki guidelines. Diffusion-weighted magnetic resonance imaging was performed in 30 patients with idiopathic PD (mean age, 64.5 years ± 3.4 [standard deviation]) and 30 healthy subjects (mean age, 65.0 years ± 5.1). Mean kurtosis, fractional anisotropy, and mean, axial, and radial diffusivity of the basal ganglia were compared between the groups. Disease severity was assessed by using Hoehn and Yahr staging and the motor section of the Unified Parkinson's Disease Rating Scale (mean scores, 2.0 and 33.6, respectively). Receiver operating characteristic (ROC) analysis was used to compare the diagnostic accuracies of the indexes of interest. Pearson correlation coefficient analysis was used to correlate imaging findings with disease severity.

RESULTS

Mean kurtosis in the putamen was higher in the PD group (0.93 ± 0.15) than in the control group (0.71 ± 0.09) (P < .000416). The area under the ROC curve (AUC) was 0.95 for both the ipsilateral putamen and the ipsilateral substantia nigra. The mean kurtosis for the ipsilateral substantia nigra had the best diagnostic performance (mean cutoff, 1.10; sensitivity, 0.92; specificity, 0.87). In contrast, AUCs for the tensor-derived indexes ranged between 0.43 (axial and radial diffusivity in substantia nigra) and 0.65 (fractional anisotropy in substantia nigra).

CONCLUSION

Diffusion kurtosis imaging in the basal ganglia, as compared with conventional diffusion-tensor imaging, can improve the diagnosis of PD.

Effect of gradient pulse duration on MRI estimation of the diffusional kurtosis for a two-compartment exchange model

Hardware constraints typically require the use of extended gradient pulse durations for clinical applications of diffusion-weighted magnetic resonance imaging (DW-MRI), which can potentially influence the estimation of diffusion metrics. Prior studies have examined this effect for the apparent diffusion coefficient. This study employs a two-compartment exchange model in order to assess the gradient pulse duration sensitivity of the apparent diffusional kurtosis (ADK), a quantitative index of diffusional non-Gaussianity. An analytic expression is derived and numerically evaluated for parameter ranges relevant to DW-MRI of brain. It is found that the ADK differs from the true diffusional kurtosis by at most a few percent. This suggests that ADK estimates for brain may be robust with respect to changes in pulse gradient duration.

Non-Gaussian diffusion imaging: a brief practical review

The departure from purely mono-exponential decay of the signal, as observed from brain tissue following a diffusion-sensitized sequence, has prompted the search for alternative models to characterize these unconventional water diffusion dynamics. Several approaches have been proposed in the last few years. While multi-exponential models have been applied to characterize brain tissue, several unresolved controversies about the interpretations of the results have motivated the search for alternative models that do not rely on the Gaussian diffusion hypothesis. In this brief review, diffusional kurtosis imaging (DKI) and anomalous diffusion imaging (ADI) techniques are addressed and compared with diffusion tensor imaging. Theoretical and experimental issues are briefly described to allow readers to understand similarities, differences and limitations of these two non-Gaussian models. However, since the ultimate goal is to improve specificity, sensitivity and spatial localization of diffusion MRI for the detection of brain diseases, special attention will be paid on the clinical feasibility of the proposed techniques as well as on the context of brain pathology investigations.

An introduction to diffusion tensor image analysis

Diffusion tensor magnetic resonance imaging (DTI) is a relatively new technology that is popular for imaging the white matter of the brain. This article provides a basic and broad overview of DTI to enable the reader to develop an intuitive understanding of these types of data, and an awareness of their strengths and weaknesses.