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

Spatiotemporal Patterns of White Matter Maturation after Pre-Adolescence: A Diffusion Kurtosis Imaging Study

Diffusion tensor imaging (DTI) enables the assessment of changes in brain tissue microstructure during maturation and ageing. In general, patterns of cerebral maturation and decline render non-monotonic lifespan trajectories of DTI metrics with age, and, importantly, the rate of microstructural changes is heterochronous for various white matter fibres. Recent studies have demonstrated that diffusion kurtosis imaging (DKI) metrics are more sensitive to microstructural changes during ageing compared to those of DTI. In a previous work, we demonstrated that the Cohen's d of mean diffusional kurtosis (dMK) represents a useful biomarker for quantifying maturation heterochronicity. However, some inferences on the maturation grades of different fibre types, such as association, projection, and commissural, were of a preliminary nature due to the insufficient number of fibres considered. Hence, the purpose of this follow-up work was to further explore the heterochronicity of microstructural maturation between pre-adolescence and middle adulthood based on DTI and DKI metrics. Using the effect size of the between-group parametric changes and Cohen's d, we observed that all commissural fibres achieved the highest level of maturity, followed by the majority of projection fibres, while the majority of association fibres were the least matured. We also demonstrated that dMK strongly correlates with the maxima or minima of the lifespan curves of DTI metrics. Furthermore, our results provide substantial evidence for the existence of spatial gradients in the timing of white matter maturation. In conclusion, our data suggest that DKI provides useful biomarkers for the investigation of maturation spatial heterogeneity and heterochronicity.

Clinical and imaging markers for the prognosis of acute ischemic stroke

Background and purpose

Significant differences in the outcomes observed in patients with acute ischemic stroke (AIS) have led to research investigations for identifying the predictors. In this retrospective study, we aimed to investigate the relationship of different clinical and imaging factors with the prognosis of AIS.

Materials and methods

All clinical and imaging metrics were compared between the good and poor prognosis groups according to the modified Rankin Scale (mRS) score at 90 days after discharge. Clinical factors included gender, age, NIHSS scores at admission, and other medical history risk factors. Imaging markers included the lesion's size and location, diffusion, and perfusion metrics of infarction core and peripheral regions, and the state of collateral circulation. Spearman's correlations were analyzed for age and imaging markers between the different groups. The Chi-square test and Cramer's V coefficient analysis were performed for gender, collateral circulation status, NIHSS score, and other stroke risk factors.

Results

A total of 89 patients with AIS were divided into the good (mRS score ≤ 2) and poor prognosis groups (mRS score ≥ 3). There were differences in NIHSS score at the admission; relative MK (rMK), relative MD (rMD), relative CBF (rCBF) of the infarction core; relative mean transit time (rMTT), relative time to peak (rTTP), and relative CBF (rCBF) of peripheral regions; and collateral circulation status between the two groups (p < 0.05). Among them, the rMK of infarction lesions had the strongest correlation with the mRS score at 90 days after discharge (r = 0.545, p < 0.001).

Conclusion

Perfusion and diffusion metrics could reflect the microstructure and blood flow characteristics of the lesion, which were the key factors for the salvage ability and prognosis of the infarction tissue. The characteristics of the infarction core and peripheral regions have different effects on the outcomes. Diffusion of infarction core has strong relations with the prognosis, whereas the time metrics (MTT, TTP) were more important for peripheral regions. MK had a more significant association with prognosis than MD. These factors were the primary markers influencing the prognosis of cerebral infarction patients.

Higher order diffusion imaging as a putative index of human sleep-related microstructural changes and glymphatic clearance

The brain has a unique macroscopic waste clearance system, termed the glymphatic system which utilises perivascular tunnels surrounded by astroglia to promote cerebrospinal-interstitial fluid exchange. Rodent studies have demonstrated a marked increase in glymphatic clearance during sleep which has been linked to a sleep-induced expansion of the extracellular space and concomitant reduction in intracellular volume. However, despite being implicated in the pathophysiology of multiple human neurodegenerative disorders, non-invasive techniques for imaging glymphatic clearance in humans are currently limited. Here we acquired multi-shell diffusion weighted MRI (dwMRI) in twenty-one healthy young participants (6 female, 22.3 ± 3.2 years) each scanned twice, once during wakefulness and once during sleep induced by a combination of one night of sleep deprivation and 10 mg of the hypnotic zolpidem 30 min before scanning. To capture hypothesised sleep-associated changes in intra/extracellular space, dwMRI were analysed using higher order diffusion modelling with the prediction that sleep-associated increases in interstitial (extracellular) fluid volume would result in a decrease in diffusion kurtosis, particularly in areas associated with slow wave generation at the onset of sleep. In line with our hypothesis, we observed a global reduction in diffusion kurtosis (t15=2.82, p = 0.006) during sleep as well as regional reductions in brain areas associated with slow wave generation during early sleep and default mode network areas that are highly metabolically active during wakefulness. Analysis with a higher-order representation of diffusion (MAP-MRI) further indicated that changes within the intra/extracellular domain rather than membrane permeability likely underpin the observed sleep-associated decrease in kurtosis. These findings identify higher-order modelling of dwMRI as a potential new non-invasive method for imaging glymphatic clearance and extend rodent findings to suggest that sleep is also associated with an increase in interstitial fluid volume in humans.

Correlation Tensor MRI deciphers underlying kurtosis sources in stroke

Noninvasively detecting and characterizing modulations in cellular scale micro-architecture remains a desideratum for contemporary neuroimaging. Diffusion MRI (dMRI) has become the mainstay methodology for probing microstructure, and, in ischemia, its contrasts have revolutionized stroke management. Diffusion kurtosis imaging (DKI) has been shown to significantly enhance the sensitivity of stroke detection compared to its diffusion tensor imaging (DTI) counterparts. However, the interpretation of DKI remains ambiguous as its contrast may arise from competing kurtosis sources related to the anisotropy of tissue components, diffusivity variance across components, and microscopic kurtosis (e.g., arising from cross-sectional variance, structural disorder, and restriction). Resolving these sources may be fundamental for developing more specific imaging techniques for stroke management, prognosis, and understanding its pathophysiology. In this study, we apply Correlation Tensor MRI (CTI) - a double diffusion encoding (DDE) methodology recently introduced for deciphering kurtosis sources based on the unique information captured in DDE's diffusion correlation tensors - to investigate the underpinnings of kurtosis measurements in acute ischemic lesions. Simulations for the different kurtosis sources revealed specific signatures for cross-sectional variance (representing neurite beading), edema, and cell swelling. Ex vivo CTI experiments at 16.4 T were then performed in an experimental photothrombotic stroke model 3 h post-stroke (N = 10), and successfully separated anisotropic, isotropic, and microscopic non-Gaussian diffusion sources in the ischemic lesions. Each of these kurtosis sources provided unique contrasts in the stroked area. Particularly, microscopic kurtosis was shown to be a primary "driver" of total kurtosis upon ischemia; its large increases, coupled with decreases in anisotropic kurtosis, are consistent with the expected elevation in cross-sectional variance, likely linked to beading effects in small objects such as neurites. In vivo experiments at 9.4 T at the same time point (3 h post ischemia, N = 5) demonstrated the stability and relevance of the findings and showed that fixation is not a dominant confounder in our findings. In future studies, the different CTI contrasts may be useful to address current limitations of stroke imaging, e.g., penumbra characterization, distinguishing lesion progression form tissue recovery, and elucidating pathophysiological correlates.

Spatiotemporal characterisation of ischaemic lesions in transient stroke animal models using diffusion free water elimination and mapping MRI with echo time dependence

BACKGROUND AND PURPOSE

The excess fluid as a result of vasogenic oedema and the subsequent tissue cavitation obscure the microstructural characterisation of ischaemic tissue by conventional diffusion and relaxometry MRI. They lead to a pseudo-normalisation of the water diffusivity and transverse relaxation time maps in the subacute and chronic phases of stroke. Within the context of diffusion MRI, the free water elimination and mapping method (FWE) with echo time dependence has been proposed as a promising approach to measure the amount of free fluid in brain tissue robustly and to eliminate its biasing effect on other biomarkers. In this longitudinal study of transient middle cerebral artery occlusion (MCAo) in the rat brain, we investigated the use of FWE MRI with echo time dependence for the characterisation of the tissue microstructure and explored the potential of the free water fraction as a novel biomarker of ischaemic tissue condition.

METHODS

Adult rats received a transient MCAo. Diffusion- and transverse relaxation-weighted MRI experiments were performed longitudinally, pre-occlusion and on days 1, 3, 4, 5, 6, 7 and 10 after MCAo on four rats. Histology was performed for non-stroke and 1, 3 and 10 days after MCAo on three different rats at each time point.

RESULTS

The free water fraction was homogeneously increased in the ischaemic cortex one day after stroke. Between three and ten days after stroke, the core of the ischaemic tissue showed a progressive normalisation in the amount of free water, whereas the inner and outer border zones of the ischaemic cortex depicted a large, monotonous increase with time. The specific lesions in brain sections were verified by H&E and immunostaining. The tissue-specific diffusion and relaxometry MRI metrics in the ischaemic cortex were significantly different compared to their conventional counterpart.

CONCLUSIONS

Our results demonstrate that the free water fraction in FWE MRI with echo time dependence is a valuable biomarker, sensitive to the progressive degeneration in ischaemic tissue. We showed that part of the heterogeneity previously observed in conventional parameter maps can be accounted for by a heterogeneous distribution of free water in the tissue. Our results suggest that the temporal evolution of the free fluid fraction map at the core and inner border zone can be associated with the pathological changes linked to the evolution of vasogenic oedema. Namely, the homogeneous increase in free water one day after stroke and its tendency to normalise in the core of the ischaemic cortex starting three days after stroke, followed by a progressive increase in free water at the inner border zone from three to ten days after stroke. Finally, the monotonous increase in free fluid in the outer border zone of the cortex reflects the formation of fluid-filled cysts.

Advanced non-invasive MRI of neuroplasticity in ischemic stroke: Techniques and applications

Ischemic stroke represents a serious medical condition which could cause survivors suffer from long-term and even lifetime disabilities. After a stroke attack, the brain would undergo varying degrees of recovery, in which the central nervous system could be reorganized spontaneously or with the help of appropriate rehabilitation. Magnetic resonance imaging (MRI) is a non-invasive technique which can provide comprehensive information on structural, functional and metabolic features of brain tissue. In the last decade, there has been an increased technical advancement in MR techniques such as voxel-based morphological analysis (VBM), diffusion magnetic resonance imaging (dMRI), functional magnetic resonance imaging (fMRI), arterial spin-labeled perfusion imaging (ASL), magnetic sensitivity weighted imaging (SWI), quantitative sensitivity magnetization (QSM) and magnetic resonance spectroscopy (MRS) which have been proven to be a valuable tool to study the brain tissue reorganization. Due to MRI indices of neuroplasticity related to neurological outcome could be translated to the clinic. The ultimate goal of this review is to equip readers with a fundamental understanding of advanced MR techniques and their corresponding clinical application for improving the ability to predict neuroplasticity that are most suitable for stroke management.

Neuroanatomical underpinning of diffusion kurtosis measurements in the cerebral cortex of healthy macaque brains

PURPOSE

To investigate the neuroanatomical underpinning of healthy macaque brain cortical microstructure measured by diffusion kurtosis imaging (DKI), which characterizes non-Gaussian water diffusion.

METHODS

High-resolution DKI was acquired from 6 postmortem macaque brains. Neurofilament density (ND) was quantified based on structure tensor from neurofilament histological images of a different macaque brain sample. After alignment of DKI-derived mean kurtosis (MK) maps to the histological images, MK and histology-based ND were measured at corresponding regions of interests characterized by distinguished cortical MK values in the prefrontal/precentral-postcentral and temporal cortices. Pearson correlation was performed to test significant correlation between these cortical MK and ND measurements.

RESULTS

Heterogeneity of cortical MK across different cortical regions was revealed, with significantly and consistently higher MK measurements in the prefrontal/precentral-postcentral cortex compared to those in the temporal cortex across all six scanned macaque brains. Corresponding higher ND measurements in the prefrontal/precentral-postcentral cortex than in the temporal cortex were also found. The heterogeneity of cortical MK is associated with heterogeneity of histology-based ND measurements, with significant correlation between cortical MK and corresponding ND measurements (P < .005).

CONCLUSION

These findings suggested that DKI-derived MK can potentially be an effective noninvasive biomarker quantifying underlying neuroanatomical complexity inside the cerebral cortical mantle for clinical and neuroscientific research.

Diffusion kurtosis imaging and pathological comparison of early hypoxic-ischemic 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.

Effects of signal averaging, gradient encoding scheme, and spatial resolution on diffusion kurtosis imaging: An empirical study using 7T MRI

BACKGROUND

Although diffusion gradient directions and b-values have been optimized for diffusion kurtosis imaging (DKI), little is known about the effect of signal averaging on DKI reliability.

PURPOSE

To evaluate how signal averaging influences the reliability of DKI indices using two gradient encoding schemes with three spatial resolutions.

STUDY TYPE

Prospective.

ANIMAL MODEL

Fifteen naïve Sprague-Dawley rats.

FIELD STRENGTH/SEQUENCE

DKI was performed at 7T using two schemes (30 directions with three b-values [30d-3b] and six directions with 15 b-values [6d-15b]), three resolutions, and eight repetitions.

ASSESSMENT

DKI reliability was assessed using voxelwise relative error (σ) and test-retest error of fractional anisotropy (FA), mean diffusivity (MD), and mean kurtosis (MK) within gray matter (GM) and white matter (WM). The number of excitations (NEX) was optimized by considering DKI reliability. The influence of the partial volume effect (PVE) was also assessed.

STATISTICAL TEST

One-way analysis of variance.

RESULTS

The 30d-3b scheme, compared with the 6d-15b scheme, exhibited apparently smaller σ_FA and σ_MK (eg, at NEX 1, in GM, for three resolutions, σ_FA : 19.9-38.2% vs. 34.2-61.4%, σ_MK : 6.9-11.4% vs. 14.1-15.4%) and similar σ_MD (all differences between two schemes <1.6%). The optimal NEX was determined as 2 for enabling a reliable measurement of DKI-derived indices. The PVE at the lowest resolution apparently increased σ_FA for both schemes (19.9% for 30d-3b and 34.2% for 6d-15b) and σ_MK for the 6d-15b scheme (14.7%) in GM, and exerted lower effects on MK values for the 30d-3b scheme (P > 0.05).

DATA CONCLUSION

A higher number of diffusion directions would benefit FA and MK estimation. A higher spatial resolution helps to reduce PVE. By using the 30d-3b scheme, MK is considered a robust index to reflect microstructural changes in GM and WM. We propose a systematic approach to determine the optimal DKI protocols for appropriate preclinical settings.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:1593-1603.

Oscillating gradient diffusion kurtosis imaging of normal and injured mouse brains

Recent advances in diffusion MRI employ multiple diffusion encoding schemes with varying diffusion direction, weighting, and diffusion time to investigate specific microstructural properties in biological tissues. In this study, we examined time-dependent diffusion kurtosis contrast in adult mouse brains and in neonatal mouse brains after hypoxic-ischemic (HI) injury. In vivo diffusion kurtosis maps were acquired with a short diffusion time using an oscillating gradient spin echo (OGSE) sequence at 100 Hz and with a relatively long diffusion time (20 ms) using a pulsed gradient spin echo (PGSE) sequence. In the adult mouse brain, we found that the cortex and hippocampus showed larger differences between OGSE kurtosis and PGSE kurtosis than major white matter tracts. In neonatal mouse brains with unilateral HI injury, the OGSE kurtosis map overall provided stronger edema contrast than the PGSE kurtosis map, and the differences between OGSE and PGSE kurtosis measurements in the edema region reflected heterogeneity of injury. This is the first in vivo study that has demonstrated multi-direction OGSE kurtosis contrasts in the mouse brain. Comparing PGSE and OGSE kurtosis measures may provide additional information on microstructural changes after ischemic stroke.

Stroke infarct volume estimation in fixed tissue: Comparison of diffusion kurtosis imaging to diffusion weighted imaging and histology in a rodent MCAO model

Diffusion kurtosis imaging (DKI) is a new promising MRI technique with microstructural sensitivity superior to conventional diffusion tensor (DTI) based methods. In stroke, considerable mismatch exists between the infarct lesion outline obtained from the two methods, kurtosis and diffusion tensor derived metrics. We aim to investigate if this mismatch can be examined in fixed tissue. Our investigation is based on estimates of mean diffusivity (MD) and mean (of the) kurtosis tensor (MKT) obtained using recent fast DKI methods requiring only 19 images. At 24 hours post stroke, rat brains were fixed and prepared. The infarct was clearly visible in both MD and MKT maps. The MKT lesion volume was roughly 31% larger than the MD lesion volume. Subsequent histological analysis (hematoxylin) revealed similar lesion volumes to MD. Our study shows that structural components underlying the MD/MKT mismatch can be investigated in fixed tissue and therefore allows a more direct comparison between lesion volumes from MRI and histology. Additionally, the larger MKT infarct lesion indicates that MKT do provide increased sensitivity to microstructural changes in the lesion area compared to MD.

Susceptibility-weighted and diffusion kurtosis imaging to evaluate encephalomalacia with epilepsy after traumatic brain injury

Objective

Encephalomalacia after traumatic brain injury (TBI) is one of the factors leading to epilepsy. In this study, magnetic resonance imaging (MRI) was used to explore the brain image features of epilepsy after traumatic encephalomalacia, and to provide objective evidence for predicting the possible occurrence of epilepsy after traumatic encephalomalacia.

Methods

Two‐hundred‐fifty‐two patients with traumatic encephalomalacia were prospectively enrolled in the study. All patients underwent MRI after discharge from the hospital. At the 1‐year follow‐up, participants were divided into epilepsy and nonepilepsy groups. All participants underwent MRI including conventional imaging, susceptibility‐weighted imaging (SWI), and diffusion kurtosis imaging (DKI). The lesion volume, iron deposition, mean diffusion (MD), and mean kurtosis (MK) around the lesions were calculated for each group and compared using t‐tests. P values < 0.05 were considered statistically significant.

Results

Sixty patients with epilepsy and 91 without epilepsy were reported. There were no significant differences in Glasgow Coma Scale (GCS), lesion volume, encephalomalacia, or MD values between the two groups. Iron deposition was significantly higher in the epilepsy group (P < 0.05). The MK values were significantly different (P < 0.05).

Interpretation

Advanced MRI is an important means of evaluating risk of developing epilepsy at 1 year due to encephalomalacia in patients with TBI. SWI and DKI could be used to assess the microstructural changes around the encephalomalacia, and therefore be used to evaluate risk of developing epilepsy at 1 year.

JOURNAL CLUB: Evaluation of Diffusion Kurtosis Imaging of Stroke Lesion With Hemodynamic and Metabolic MRI in a Rodent Model of Acute Stroke

OBJECTIVE

Diffusion kurtosis imaging (DKI) has emerged as a new acute stroke imaging approach, augmenting routine DWI. Although it has been shown that a diffusion lesion without kurtosis abnormality is more likely to recover after reperfusion, whereas a kurtosis lesion shows poor response, little is known about the underlying pathophysiologic profile of the kurtosis lesion versus the kurtosis lesion-diffusion lesion mismatch.

MATERIALS AND METHODS

We performed multiparametric MRI, including arterial spin labeling, pH-sensitive amide proton transfer, and DKI, in a rodent model of acute stroke caused by embolic middle cerebral artery occlusion. Diffusion and kurtosis lesions were semiautomatically segmented, and multiparametric MRI indexes were compared among the kurtosis lesion, diffusion lesion, kurtosis lesion-diffusion lesion mismatch, and the contralateral normal tissue area.

RESULTS

We confirmed a significant difference between diffusion lesion and kurtosis lesion volumes (mean [± SD] volume, 151 ± 65 vs 125 ± 47 mm³; p < 0.05). Although ischemic lesions have significantly reduced cerebral blood flow compared with contralateral normal tissue, we did not find a significant difference in cerebral blood flow between the kurtosis lesion and the kurtosis lesion-diffusion lesion mismatch (mean cerebral blood flow, 0.53 ± 0.10 vs 0.47 ± 0.14 mL/g of tissue per minute; p > 0.05). Of importance, the pH of the kurtosis lesion was significantly lower than that of the lesion mismatch (mean pH, 6.81 ± 0.08 vs 6.89 ± 0.09; p < 0.01).

CONCLUSION

The present study confirms that DKI provides an expedient approach for refining the heterogeneous DWI lesion that is associated with graded metabolic derangement, which is promising for improving the infarction core definition and ultimately helping to guide stroke treatment.

Precision and accuracy of diffusion kurtosis estimation and the influence of b-value selection

Diffusion kurtosis imaging (DKI) is an extension of diffusion tensor imaging that accounts for leading non-Gaussian diffusion effects. In DKI studies, a wide range of different gradient strengths (b-values) is used, which is known to affect the estimated diffusivity and kurtosis parameters. Hence there is a need to assess the accuracy and precision of the estimated parameters as a function of b-value. This work examines the error in the estimation of mean of the kurtosis tensor (MKT) with respect to the ground truth, using simulations based on a biophysical model for both gray (GM) and white (WM) matter. Model parameters are derived from densely sampled experimental data acquired in ex vivo rat brain and in vivo human brain. Additionally, the variability of MKT is studied using the experimental data. Prevalent fitting protocols are implemented and investigated. The results show strong dependence on the maximum b-value of both net relative error and standard deviation of error for all of the employed fitting protocols. The choice of b-values with minimum MKT estimation error and standard deviation of error was found to depend on the protocol type and the tissue. Protocols that utilize two terms of the cumulant expansion (DKI) were found to achieve minimum error in GM at b-values less than 1 ms/μm² , whereas maximal b-values of about 2.5 ms/μm² were found to be optimal in WM. Protocols including additional higher order terms of the cumulant expansion were found to provide higher accuracy for the more commonly used b-value regime in GM, but were associated with higher error in WM. Averaged over multiple voxels, a net average error of around 15% for both WM and GM was observed for the optimal b-value choice. These results suggest caution when using DKI generated metrics for microstructural modeling and when comparing results obtained using different fitting techniques and b-values.

Diffusional Kurtosis Imaging and Motor Outcome in Acute Ischemic Stroke

BACKGROUND AND PURPOSE

Motor impairment is the most common deficit after stroke. Our aim was to evaluate whether diffusional kurtosis imaging can detect corticospinal tract microstructural changes in the acute phase for patients with first-ever ischemic stroke and motor impairment and to assess the correlations between diffusional kurtosis imaging-derived diffusion metrics for the corticospinal tract and motor impairment 3 months poststroke.

MATERIALS AND METHODS

We evaluated 17 patients with stroke who underwent brain MR imaging including diffusional kurtosis imaging within 4 days after the onset of symptoms. Neurologic evaluation included the Fugl-Meyer Upper Extremity Motor scale in the acute phase and 3 months poststroke. For the corticospinal tract in the lesioned and contralateral hemispheres, we estimated with diffusional kurtosis imaging both pure diffusion metrics, such as the mean diffusivity and mean kurtosis, and model-dependent quantities, such as the axonal water fraction. We evaluated the correlations between corticospinal tract diffusion metrics and the Fugl-Meyer Upper Extremity Motor scale at 3 months.

RESULTS

Among all the diffusion metrics, the largest percentage signal changes of the lesioned hemisphere corticospinal tract were observed with axial kurtosis, with an average 12% increase compared with the contralateral corticospinal tract. The strongest associations between the 3-month Fugl-Meyer Upper Extremity Motor scale score and diffusion metrics were found for the lesioned/contralateral hemisphere corticospinal tract mean kurtosis (ρ = -0.85) and axial kurtosis (ρ = -0.78) ratios.

CONCLUSIONS

This study was designed to be one of hypothesis generation. Diffusion metrics related to kurtosis were found to be more sensitive than conventional diffusivity metrics to early poststroke corticospinal tract microstructural changes and may have potential value in the prediction of motor impairment at 3 months.

Multidimensional diffusion MRI

Principles from multidimensional NMR spectroscopy, and in particular solid-state NMR, have recently been transferred to the field of diffusion MRI, offering non-invasive characterization of heterogeneous anisotropic materials, such as the human brain, at an unprecedented level of detail. Here we revisit the basic physics of solid-state NMR and diffusion MRI to pinpoint the origin of the somewhat unexpected analogy between the two fields, and provide an overview of current diffusion MRI acquisition protocols and data analysis methods to quantify the composition of heterogeneous materials in terms of diffusion tensor distributions with size, shape, and orientation dimensions. While the most advanced methods allow estimation of the complete multidimensional distributions, simpler methods focus on various projections onto lower-dimensional spaces as well as determination of means and variances rather than actual distributions. Even the less advanced methods provide simple and intuitive scalar parameters that are directly related to microstructural features that can be observed in optical microscopy images, e.g. average cell eccentricity, variance of cell density, and orientational order - properties that are inextricably entangled in conventional diffusion MRI. Key to disentangling all these microstructural features is MRI signal acquisition combining isotropic and directional dimensions, just as in the field of multidimensional solid-state NMR from which most of the ideas for the new methods are derived.

Evaluation of non-Gaussian diffusion in cardiac MRI

PURPOSE

The diffusion tensor model assumes Gaussian diffusion and is widely applied in cardiac diffusion MRI. However, diffusion in biological tissue deviates from a Gaussian profile as a result of hindrance and restriction from cell and tissue microstructure, and may be quantified better by non-Gaussian modeling. The aim of this study was to investigate non-Gaussian diffusion in healthy and hypertrophic hearts.

METHODS

Thirteen rat hearts (five healthy, four sham, four hypertrophic) were imaged ex vivo. Diffusion-weighted images were acquired at b-values up to 10,000 s/mm² . Models of diffusion were fit to the data and ranked based on the Akaike information criterion.

RESULTS

The diffusion tensor was ranked best at b-values up to 2000 s/mm² but reflected the signal poorly in the high b-value regime, in which the best model was a non-Gaussian "beta distribution" model. Although there was considerable overlap in apparent diffusivities between the healthy, sham, and hypertrophic hearts, diffusion kurtosis and skewness in the hypertrophic hearts were more than 20% higher in the sheetlet and sheetlet-normal directions.

CONCLUSION

Non-Gaussian diffusion models have a higher sensitivity for the detection of hypertrophy compared with the Gaussian model. In particular, diffusion kurtosis may serve as a useful biomarker for characterization of disease and remodeling in the heart. Magn Reson Med 78:1174-1186, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Data for evaluation of fast kurtosis strategies, b-value optimization and exploration of diffusion MRI contrast

Here we describe and provide diffusion magnetic resonance imaging (dMRI) data that was acquired in neural tissue and a physical phantom. Data acquired in biological tissue includes: fixed rat brain (acquired at 9.4 T) and spinal cord (acquired at 16.4 T) and in normal human brain (acquired at 3 T). This data was recently used for evaluation of diffusion kurtosis imaging (DKI) contrasts and for comparison to diffusion tensor imaging (DTI) parameter contrast. The data has also been used to optimize b-values for ex vivo and in vivo fast kurtosis imaging. The remaining data was obtained in a physical phantom with three orthogonal fiber orientations (fresh asparagus stems) for exploration of the kurtosis fractional anisotropy. However, the data may have broader interest and, collectively, may form the basis for image contrast exploration and simulations based on a wide range of dMRI analysis strategies.

Instantaneous signal attenuation method for analysis of PFG fractional diffusions

An instantaneous signal attenuation (ISA) method for analyzing pulsed field gradient (PFG) fractional diffusion (FD) has been developed, which is modified from the propagator approach developed in 2001 by Lin et al. for analyzing PFG normal diffusion. Both, the current ISA method and the propagator method have the same fundamental basis that the total signal attenuation (SA) is the accumulation of all the ISA, and the ISA is the average SA of the whole diffusion system at each moment. However, the manner of calculating ISA is different. Unlike the use of the instantaneous propagator in the propagator method, the current method directly calculates ISA as A(K(t'),t'+dt')/A(K(t'),t'), where A(K(t'),t'+dt') and A(K(t'),t') are the SA. This modification makes the current method applicable to PFG FD as the instantaneous propagator may not be obtainable in FD. The ISA method was applied to study PFG SA including the effect of finite gradient pulse widths (FGPW) for free FD, restricted FD and the FD affected by a non-homogeneous gradient field. The SA expressions were successfully obtained for all three types of free FDs while other current methods still have difficulty in obtaining all of them. The results from this method agree with reported results such as that obtained by the effective phase shift diffusion equation (EPSDE) method. The M-Wright phase distribution approximation was also used to derive an SA expression for time FD as a comparison, which agrees with ISA method. Additionally, the continuous-time random walk (CTRW) simulation was performed to simulate the SA of PFG FD, and the simulation results agree with the analytical results. Particularly, the CTRW simulation results give good support to the analytical results including FGPW effect for free FD and restricted time FD based on a fractional derivative model where there have been no corresponding theoretical reports to date. The theoretical SA expressions including FGPW obtained here such as [Formula: see text] may be applied to analyze PFG FD in polymer or biological systems with improved accuracy where SGP approximation cannot be satisfied. The method can perhaps provide new insight to FD MRI and hence benefit the development of diffusion biomarkers based on fractional derivative.

Mapping the Orientation of White Matter Fiber Bundles: A Comparative Study of Diffusion Tensor Imaging, Diffusional Kurtosis Imaging, and Diffusion Spectrum Imaging

BACKGROUND AND PURPOSE

White matter fiber tractography relies on fiber bundle orientation estimates from diffusion MR imaging. However, clinically feasible techniques such as DTI and diffusional kurtosis imaging use assumptions, which may introduce error into in vivo orientation estimates. In this study, fiber bundle orientations from DTI and diffusional kurtosis imaging are compared with diffusion spectrum imaging as a criterion standard to assess the performance of each technique.

MATERIALS AND METHODS

For each subject, full DTI, diffusional kurtosis imaging, and diffusion spectrum imaging datasets were acquired during 2 independent sessions, and fiber bundle orientations were estimated by using the specific theoretic assumptions of each technique. Angular variability and angular error measures were assessed by comparing the orientation estimates. Tractography generated with each of the 3 reconstructions was also examined and contrasted.

RESULTS

Orientation estimates from all 3 techniques had comparable angular reproducibility, but diffusional kurtosis imaging decreased angular error throughout the white matter compared with DTI. Diffusion spectrum imaging and diffusional kurtosis imaging enabled the detection of crossing-fiber bundles, which had pronounced effects on tractography relative to DTI. Diffusion spectrum imaging had the highest sensitivity for detecting crossing fibers; however, the diffusion spectrum imaging and diffusional kurtosis imaging tracts were qualitatively similar.

CONCLUSIONS

Fiber bundle orientation estimates from diffusional kurtosis imaging have less systematic error than those from DTI, which can noticeably affect tractography. Moreover, tractography obtained with diffusional kurtosis imaging is qualitatively comparable with that of diffusion spectrum imaging. Because diffusional kurtosis imaging has a shorter typical scan time than diffusion spectrum imaging, diffusional kurtosis imaging is potentially more suitable for a variety of clinical and research applications.

Comparison of image sensitivity between conventional tensor-based and fast diffusion kurtosis imaging protocols in a rodent model of acute ischemic stroke

Diffusion kurtosis imaging (DKI) can offer a useful complementary tool to routine diffusion MRI for improved stratification of heterogeneous tissue damage in acute ischemic stroke. However, its relatively long imaging time has hampered its clinical application in the emergency setting. A recently proposed fast DKI approach substantially shortens the imaging time, which may help to overcome the scan time limitation. However, to date, the sensitivity of the fast DKI protocol for the imaging of acute stroke has not been fully described. In this study, we performed routine and fast DKI scans in a rodent model of acute stroke, and compared the sensitivity of diffusivity and kurtosis indices (i.e. axial, radial and mean) in depicting acute ischemic lesions. In addition, we analyzed the contrast-to-noise ratio (CNR) between the ipsilateral ischemic and contralateral normal regions using both conventional and fast DKI methods. We found that the mean kurtosis shows a relative change of 47.1 ± 7.3% between the ischemic and contralateral normal regions, being the most sensitive parameter in revealing acute ischemic injury. The two DKI methods yielded highly correlated diffusivity and kurtosis measures and lesion volumes (R(2)  ⩾ 0.90, p < 0.01). Importantly, the fast DKI method exhibited significantly higher CNR of mean kurtosis (1.6 ± 0.2) compared with the routine tensor protocol (1.3 ± 0.2, p < 0.05), with its CNR per unit time (CNR efficiency) approximately doubled when the scan time was taken into account. In conclusion, the fast DKI method provides excellent sensitivity and efficiency to image acute ischemic tissue damage, which is essential for image-guided and individualized stroke treatment.

Apparent exchange rate for breast cancer characterization

Although diffusion MRI has shown promise for the characterization of breast cancer, it has low specificity to malignant subtypes. Higher specificity might be achieved if the effects of cell morphology and molecular exchange across cell membranes could be disentangled. The quantification of exchange might thus allow the differentiation of different types of breast cancer cells. Based on differences in diffusion rates between the intra- and extracellular compartments, filter exchange spectroscopy/imaging (FEXSY/FEXI) provides non-invasive quantification of the apparent exchange rate (AXR) of water between the two compartments. To test the feasibility of FEXSY for the differentiation of different breast cancer cells, we performed experiments on several breast epithelial cell lines in vitro. Furthermore, we performed the first in vivo FEXI measurement of water exchange in human breast. In cell suspensions, pulsed gradient spin-echo experiments with large b values and variable pulse duration allow the characterization of the intracellular compartment, whereas FEXSY provides a quantification of AXR. These experiments are very sensitive to the physiological state of cells and can be used to establish reliable protocols for the culture and harvesting of cells. Our results suggest that different breast cancer subtypes can be distinguished on the basis of their AXR values in cell suspensions. Time-resolved measurements allow the monitoring of the physiological state of cells in suspensions over the time-scale of hours, and reveal an abrupt disintegration of the intracellular compartment. In vivo, exchange can be detected in a tumor, whereas, in normal tissue, the exchange rate is outside the range experimentally accessible for FEXI. At present, low signal-to-noise ratio and limited scan time allows the quantification of AXR only in a region of interest of relatively large tumors.

Stroke assessment with intravoxel incoherent motion diffusion-weighted MRI

Intravoxel incoherent motion (IVIM) diffusion-weighted MRI can simultaneously measure diffusion and perfusion characteristics in a non-invasive way. This study aimed to determine the potential utility of IVIM in characterizing brain diffusion and perfusion properties for clinical stroke. The multi-b-value diffusion-weighted images of 101 patients diagnosed with acute/subacute ischemic stroke were retrospectively evaluated. The diffusion coefficient D, representing the water apparent diffusivity, was obtained by fitting the diffusion data with increasing high b-values to a simple mono-exponential model. The IVIM-derived perfusion parameters, pseudodiffusion coefficient D*, vascular volume fraction f and blood flow-related parameter fD*, were calculated with the bi-exponential model. Additionally, the apparent diffusion coefficient (ADC) was fitted according to the mono-exponential model using all b-values. The diffusion parameters for the ischemic lesion and normal contralateral region were measured in each patient. Statistical analysis was performed using the paired Student t-test and Pearson correlation test. Diffusion data in both the ischemic lesion and normal contralateral region followed the IVIM bi-exponential behavior, and the IVIM model showed better goodness of fit than the mono-exponential model with lower Akaike information criterion values. The paired Student t-test revealed significant differences for all diffusion parameters (all P < 0.001) except D* (P = 0.218) between ischemic and normal areas. For all patients in both ischemic and normal regions, ADC was significantly positively correlated with D (both r = 1, both P < 0.001) and f (r = 0.541, P < 0.001; r = 0.262, P = 0.008); significant correlation was also found between ADC and fD* in the ischemic region (r = 0.254, P = 0.010). For all pixels within the region of interest from a representative subject in both ischemic and normal regions, ADC was significantly positively correlated with D (both r = 1, both P < 0.001), f (r = 0.823, P < 0.001; r = 0.652, P < 0.001) and fD* (r = 0.294, P < 0.001; r = 0.340, P < 0.001). These findings may have clinical implications for the use of IVIM imaging in the assessment and management of acute/subacute stroke patients. Copyright © 2016 John Wiley & Sons, Ltd.

Experimental considerations for fast kurtosis imaging

PURPOSE

The clinical use of kurtosis imaging is impeded by long acquisitions and postprocessing. Recently, estimation of mean kurtosis tensor W¯ and mean diffusivity ( D¯) was made possible from 13 distinct diffusion weighted MRI acquisitions (the 1-3-9 protocol) with simple postprocessing. Here, we analyze the effects of noise and nonideal diffusion encoding, and propose a new correction strategy. We also present a 1-9-9 protocol with increased robustness to experimental imperfections and minimal additional scan time. This refinement does not affect computation time and also provides a fast estimate of fractional anisotropy (FA).

THEORY AND METHODS

1-3-9/1-9-9 data are acquired in rat and human brains, and estimates of D¯, FA, W¯ from human brains are compared with traditional estimates from an extensive diffusion kurtosis imaging data set. Simulations are used to evaluate the influence of noise and diffusion encodings deviating from the scheme, and the performance of the correction strategy. Optimal b-values are determined from simulations and data.

RESULTS

Accuracy and precision in D¯ and W¯ are comparable to nonlinear least squares estimation, and is improved with the 1-9-9 protocol. The compensation strategy vastly improves parameter estimation in nonideal data.

CONCLUSION

The framework offers a robust and compact method for estimating several diffusion metrics. The protocol is easily implemented. Magn Reson Med 76:1455-1468, 2016. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Accuracies and Contrasts of Models of the Diffusion-Weighted-Dependent Attenuation of the MRI Signal at Intermediate b-values

The diffusion-weighted-dependent attenuation of the MRI signal E(b) is extremely sensitive to microstructural features. The aim of this study was to determine which mathematical model of the E(b) signal most accurately describes it in the brain. The models compared were the monoexponential model, the stretched exponential model, the truncated cumulant expansion (TCE) model, the biexponential model, and the triexponential model. Acquisition was performed with nine b-values up to 2500 s/mm² in 12 healthy volunteers. The goodness-of-fit was studied with F-tests and with the Akaike information criterion. Tissue contrasts were differentiated with a multiple comparison corrected nonparametric analysis of variance. F-test showed that the TCE model was better than the biexponential model in gray and white matter. Corrected Akaike information criterion showed that the TCE model has the best accuracy and produced the most reliable contrasts in white matter among all models studied. In conclusion, the TCE model was found to be the best model to infer the microstructural properties of brain tissue.

Performances of diffusion kurtosis imaging and diffusion tensor imaging in detecting white matter abnormality in schizophrenia

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. However, little attention was paid to the performances of DKI and DTI in detecting white matter abnormality in schizophrenia. In this study, DKI and DTI were performed in 94 schizophrenia patients and 91 sex- and age-matched healthy controls. White matter integrity was assessed by fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), mean kurtosis (MK), axial kurtosis (AK) and radial kurtosis (RK) of DKI and FA, MD, AD and RD of DTI. Group differences in these parameters were compared using tract-based spatial statistics (TBSS) (P < 0.01, corrected). The sensitivities in detecting white matter abnormality in schizophrenia were MK (34%) > AK (20%) > RK (3%) and RD (37%) > FA (24%) > MD (21%) for DKI, and RD (43%) > FA (30%) > MD (21%) for DTI. DKI-derived diffusion parameters (RD, FA and MD) were sensitive to detect abnormality in white matter regions (the corpus callosum and anterior limb of internal capsule) with coherent fiber arrangement; however, the kurtosis parameters (MK and AK) were sensitive to reveal abnormality in white matter regions (the juxtacortical white matter and corona radiata) with complex fiber arrangement. In schizophrenia, the decreased AK suggests axonal damage; however, the increased RD indicates myelin impairment. These findings suggest that diffusion and kurtosis parameters could provide complementary information and they should be jointly used to reveal pathological changes in schizophrenia.

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Kurtosis parameters are suitable to assess WM regions with complex fiber arrangement.

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Diffusion parameters are suitable to assess WM regions with coherent fiber arrangement.

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Increased RD suggests myelin abnormalities in schizophrenia.

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Decreased AK indicates axonal abnormalities in schizophrenia.

Validation of fast diffusion kurtosis MRI for imaging acute ischemia in a rodent model of stroke

Diffusion-weighted imaging (DWI) captures ischemic tissue that is likely to infarct, and has become one of the most widely used acute stroke imaging techniques. Diffusion kurtosis imaging (DKI) has lately been postulated as a complementary MRI method to stratify the heterogeneously damaged DWI lesion. However, the conventional DKI acquisition time is relatively long, limiting its use in the acute stroke setting. Recently, a fast kurtosis mapping method has been demonstrated in fixed brains and control subjects. The fast DKI approach provides mean diffusion and kurtosis measurements under substantially reduced scan time, making it amenable to acute stroke imaging. Because it is not practical to obtain and compare different means of DKI to test whether the fast DKI method can reliably detect diffusion and kurtosis lesions in acute stroke patients, our study investigated its diagnostic value using an animal model of acute stroke, a critical step before fast DKI acquisition can be routinely applied in the acute stroke setting. We found significant correlation, per voxel, between the diffusion and kurtosis coefficients measured using the fast and conventional DKI protocols. In acute stroke rats, the two DKI methods yielded diffusion and kurtosis lesions that were in good agreement. Importantly, substantial kurtosis-diffusion lesion mismatch was observed using the conventional (26 ± 13%, P < 0.01) and fast DKI methods (23 ± 8%, P < 0.01). In addition, regression analysis showed that the kurtosis-diffusion lesion mismatches obtained using conventional and fast DKI methods were substantially correlated (R(2) = 0.57, P = 0.02). Our results confirmed that the recently proposed fast DKI method is capable of capturing heterogeneous diffusion and kurtosis lesions in acute ischemic stroke, and thus is suitable for translational applications in the acute stroke clinical setting.

Histological correlation of diffusional kurtosis and white matter modeling metrics in cuprizone-induced corpus callosum demyelination

The cuprizone mouse model is well established for studying the processes of both demyelination and remyelination in the corpus callosum, and it has been utilized together with diffusion tensor imaging (DTI) to investigate myelin and axonal pathology. Although some underlying morphological mechanisms contributing to the changes in diffusion tensor (DT) metrics have been identified, the understanding of specific associations between histology and diffusion measures remains limited. Diffusional kurtosis imaging (DKI) is an extension of DTI that provides metrics of diffusional non-Gaussianity, for which an associated white matter modeling (WMM) method has been developed. The main goal of the present study was to quantitatively assess the relationships between diffusion measures and histological measures in the mouse model of cuprizone-induced corpus callosum demyelination. The diffusional kurtosis (DK) and WMM metrics were found to provide additional information that enhances the sensitivity to detect the morphological heterogeneity in the chronic phase of the disease process in the rostral segment of the corpus callosum. Specifically, in the rostral segment, axonal water fraction (d = 2.6; p < 0.0001), radial kurtosis (d = 2.0; p = 0.001) and mean kurtosis (d = 1.5; p = 0.005) showed the most sensitivity between groups with respect to yielding statistically significant p values and high Cohen's d values. These results demonstrate the ability of DK and WMM metrics to detect white mater changes and inflammatory processes associated with cuprizone-induced demyelination. They also validate, in part, the application of these new WMM metrics for studying neurological diseases, as well as helping to elucidate their biophysical meaning.

A simple and robust test object for the assessment of isotropic diffusion kurtosis

PURPOSE

To create a robust test object for the assessment of isotropic diffusion kurtosis and to investigate the relationships between barrier concentration and kurtosis and diffusion coefficients.

THEORY AND METHODS

Diffusion kurtosis imaging is an extension of conventional diffusion-weighted magnetic resonance imaging which provides a means of assessing the degree to which diffusion processes of spin-bearing particles are non-Gaussian, a property that is quantified by the kurtosis. We present a set of test objects, each possessing a different concentration of colloidal dispersion, allowing barrier concentration of the dispersed colloidal particles to be related to the kurtosis of the water diffusion. Diffusion coefficients from the kurtosis model and the monoexponential model are compared.

RESULTS

A relationship between barrier concentration and kurtosis is found, demonstrating that the diffusion process becomes less Gaussian as the barrier concentration is increased. Differences in the two estimates for the diffusion coefficients are examined. The test object is robust, displaying long-term reproducibility of results.

CONCLUSIONS

Colloidal dispersions provide a suitable and stable test object for the assessment and reproducibility measurements of kurtosis.

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.

Influence of noise correction on intra- and inter-subject variability of quantitative metrics in diffusion kurtosis imaging

Diffusion kurtosis imaging (DKI) is a promising extension of diffusion tensor imaging, giving new insights into the white matter microstructure and providing new biomarkers. Given the rapidly increasing number of studies, DKI has a potential to establish itself as a valuable tool in brain diagnostics. However, to become a routine procedure, DKI still needs to be improved in terms of robustness, reliability, and reproducibility. As it requires acquisitions at higher diffusion weightings, results are more affected by noise than in diffusion tensor imaging. The lack of standard procedures for post-processing, especially for noise correction, might become a significant obstacle for the use of DKI in clinical routine limiting its application. We considered two noise correction schemes accounting for the noise properties of multichannel phased-array coils, in order to improve the data quality at signal-to-noise ratio (SNR) typical for DKI. The SNR dependence of estimated DKI metrics such as mean kurtosis (MK), mean diffusivity (MD) and fractional anisotropy (FA) is investigated for these noise correction approaches in Monte Carlo simulations and in in vivo human studies. The intra-subject reproducibility is investigated in a single subject study by varying the SNR level and SNR spatial distribution. Then the impact of the noise correction on inter-subject variability is evaluated in a homogeneous sample of 25 healthy volunteers. Results show a strong impact of noise correction on the MK estimate, while the estimation of FA and MD was affected to a lesser extent. Both intra- and inter-subject SNR-related variability of the MK estimate is considerably reduced after correction for the noise bias, providing more accurate and reproducible measures. In this work, we have proposed a straightforward method that improves accuracy of DKI metrics. This should contribute to standardization of DKI applications in clinical studies making valuable inferences in group analysis and longitudinal studies.

Non-Gaussian diffusion imaging for enhanced contrast of brain tissue affected by ischemic stroke

Recent diffusion MRI studies of stroke in humans and animals have shown that the quantitative parameters characterising the degree of non-Gaussianity of the diffusion process are much more sensitive to ischemic changes than the apparent diffusion coefficient (ADC) considered so far as the "gold standard". The observed changes exceeded that of the ADC by a remarkable factor of 2 to 3. These studies were based on the novel non-Gaussian methods, such as diffusion kurtosis imaging (DKI) and log-normal distribution function imaging (LNDFI). As shown in our previous work investigating the animal stroke model, a combined analysis using two methods, DKI and LNDFI provides valuable complimentary information. In the present work, we report the application of three non-Gaussian diffusion models to quantify the deviations from the Gaussian behaviour in stroke induced by transient middle cerebral artery occlusion in rat brains: the gamma-distribution function (GDF), the stretched exponential model (SEM), and the biexponential model. The main goal was to compare the sensitivity of various non-Gaussian metrics to ischemic changes and to investigate if a combined application of several models will provide added value in the assessment of stroke. We have shown that two models, GDF and SEM, exhibit a better performance than the conventional method and allow for a significantly enhanced visualization of lesions. Furthermore, we showed that valuable information regarding spatial properties of stroke lesions can be obtained. In particular, we observed a stratified cortex structure in the lesions that were well visible in the maps of the GDF and SEM metrics, but poorly distinguishable in the ADC-maps. Our results provided evidence that cortical layers tend to be differently affected by ischemic processes.

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.

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.

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.

Isotropic diffusion weighting in PGSE NMR by magic-angle spinning of the q-vector

When PGSE NMR is applied to water in microheterogeneous materials such as liquid crystals, foodstuffs, porous rocks, and biological tissues, the signal attenuation is often multi-exponential, indicating the presence of pores having a range of sizes or anisotropic domains having a spread of orientations. Here we modify the standard PGSE experiment by introducing low-amplitude harmonically modulated gradients, which effectively make the q-vector perform magic-angle spinning (MAS) about an axis fixed in the laboratory frame. With this new technique, denoted q-MAS PGSE, the signal attenuation depends on the isotropic average of the local diffusion tensor. The capability of q-MAS PGSE to distinguish between pore size and domain orientation dispersion is demonstrated by experiments on a yeast cell suspension and a polydomain anisotropic liquid crystal. In the latter case, the broad distribution of apparent diffusivities observed with PGSE is narrowed to its isotropic average with q-MAS PGSE in a manner that is analogous to the narrowing of chemical shift anisotropy powder patterns using magic-angle sample spinning in solid-state NMR. The new q-MAS PGSE technique could be useful for resolving size/orientation ambiguities in the interpretation of PGSE data from, e.g., water confined within the axons of human brain tissue.