Diffusional kurtosis imaging of normal-appearing white matter in multiple sclerosis: preliminary clinical experience

Diffusion kurtosis MRI tracks gray matter myelin content in the primate cerebral cortex

Diffusion magnetic resonance imaging (dMRI) has been widely employed to model the trajectory of myelinated fiber bundles in white matter. Increasingly, dMRI is also used to assess local tissue properties throughout the brain. In the cerebral cortex, myelin content is a critical indicator of the maturation, regional variation, and disease related degeneration of gray matter tissue. Gray matter myelination can be measured and mapped using several non-diffusion MRI strategies; however, first order diffusion statistics such as fractional anisotropy (FA) show only weak spatial correlation with cortical myelin content. Here we show that a simple higher order diffusion parameter, the mean diffusion kurtosis (MK), is strongly correlated with the laminar and regional variation of myelin in the primate cerebral cortex. We carried out ultra-high resolution, multi-shelled dMRI in ex vivo marmoset monkey brains and compared dMRI parameters from a number of higher order models (diffusion kurtosis, NODDI and MAP MRI) to the distribution of myelin obtained using histological staining, and via Magnetization Transfer Ratio MRI (MTR), a non-diffusion MRI method. In contrast to FA, MK closely matched the myelin content assessed by histology and by MTR in the same sample. The parameter maps from MAP-MRI and NODDI also showed good correspondence with cortical myelin content. The results demonstrate that dMRI can be used to assess the variation of local myelin content in the primate cortical cortex, which may be of great value for assessing tissue integrity and tracking disease in living human patients.

Increased cortical lesion load contributed to pathological changes beyond focal lesion in cortical gray matter of multiple sclerosis: a diffusion kurtosis imaging analysis

Biomarkers specific to cortical gray matter (cGM) pathological changes of multiple sclerosis (MS) are desperately needed to better understand the disease progression. The cGM damage occurs in cortical lesion (CL) and normal-appearing cGM (NAcGM) areas. While the association between CL load and cGM damage has been reported, little is known about how different CL types, i.e. intracortical lesion (ICL) and leukocortical lesion (LCL) would be associated with cGM damage. In our study, relapsing-remitting MS patients and healthy controls were divided into 4 groups according to CL load level. NAcGM diffusion kurtosis imaging (DKI)/diffusion tensor imaging (DTI) values and cGM volume (cGMV) were used to characterize the pathological changes in cGM. Univariate general linear model was used for group comparisons and stepwise regression analysis was used to assess the effects of ICL volume and LCL volume on NAcGM damage. We found peak values in DKI/DTI values, cGMV and neuropsychological scores in high CL load group. Kurtosis fractional anisotropy (KFA) was the most sensitive in characterizing NAcGM damage, and LCL volume related more to NAcGM damage. Our findings suggested KFA could become a surrogate biomarker to cGM damage, and LCL might be the main factor in whole brain NAcGM damage.

Cross-sectional analysis of whole-brain microstructural changes in adult patients with bipolar and unipolar depression by diffusion kurtosis imaging

RATIONALE AND OBJECTIVES

More than half of the bipolar depression (BD) subjects are misdiagnosed as unipolar depression (UD) due to lack of objective diagnostic criteria. We aimed to identify microstructural neuronal changes differentiating BD from UD groups using diffusion kurtosis imaging (DKI). The objective of the study is to identify an objective neuro-imaging marker to differentiate BD from UD.

MATERIALS AND METHODS

A prospective, cross-sectional study included total of 62 subjects with diagnosis of bipolar depression (n = 21), unipolar depression (n = 21), and healthy controls (n = 20). All subjects underwent diffusion-weighted imaging (b = 0,1000,2000) of the whole brain on 3-Tesla MR scanner. DKI data was analyzed using 189 region whole-brain atlas. Eight diffusion and kurtosis metrics including mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), fractional anisotropy (FA), mean kurtosis (MK), axial kurtosis (AK), radial kurtosis (RK), and kurtosis fractional anisotropy (FKA) were measured against these 189 regions. Principle component analysis (PCA) was utilized to identify the most significant regions of the brain. ANOVA with post hoc tests was used for analyzing these regions.

RESULTS

BD group showed increased MD, RD, decreased AK at the left amygdala and decreased MK and RK at the right hemi-cerebellum. UD group showed increased MK and RK at the right external capsule; and increased AK, MK, and RK at the right amygdala.

CONCLUSION

The right and left amygdala, right external capsule, and right hemi-cerebellum showed microstructural abnormalities capable of differentiating BD and UD groups. Diffusion imaging especially DKI can aid in management of depression patients.

Mapping early tumor response to radiotherapy using diffusion kurtosis imaging*

PURPOSE

In this pilot study, DKI measures of diffusivity and kurtosis were compared in active tumor regions and correlated to radiologic response to radiotherapy after completion of 2 weeks of treatment to derive potential early measures of tumor response.

METHODS

MRI and Magnetic Resonance Spectroscopic Imaging (MRSI) data were acquired before the beginning of RT (pre-RT) and 2 weeks after the initiation of treatment (during-RT) in 14 glioblastoma patients. The active tumor region was outlined as the union of the residual contrast-enhancing region and metabolically active tumor region. Average and standard deviation of mean, axial, and radial diffusivity (MD, AD, RD) and mean, axial, and radial kurtosis (MK, AK, RK) values were calculated for the active tumor VOI from images acquired pre-RT and during-RT and paired t-tests were executed to estimate pairwise differences. Receiver operating characteristic (ROC) curve analysis was conducted to evaluate the predictive capabilities of changes in diffusion metrics for progression-free survival (PFS).

RESULTS

Analysis showed significant pairwise differences for AD (p = 0.035; Cohen's d of 0.659) and AK (p = 0.019; Cohen's d of 0.753) in diffusion measures after 2 weeks of RT. ROC curve analysis showed that percentage change differences in AD and AK between pre-RT and during-RT scans provided an Area Under the Curve (AUC) of 0.524 and 0.762, respectively, in discriminating responders (PFS>180 days) and non-responders (PFS<180 days).

CONCLUSION

This pilot study, although preliminary in nature, showed significant changes in AD and AK maps, with kurtosis derived AK maps showing an increased sensitivity in mapping early changes in the active tumor regions.

Diffusion-derived parameters in lesions, peri-lesion and normal-appearing white matter in multiple sclerosis using tensor, kurtosis and fixel-based analysis

Neuronal damage is the primary cause of long-term disability of multiple sclerosis (MS) patients. Assessment of axonal integrity from diffusion MRI parameters might enable better disease characterisation. 16 diffusion derived measurements from diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), and fixel-based analysis (FBA) in lesions, peri-lesion and normal appearing white matter were investigated. Diffusion MRI scans of 11 MS patients were processed to generate DTI, DKI, and FBA images. Fractional anisotropy (FA) and fibre density (FD) were used to assess axonal integrity across brain regions. Subsequently, 359 lesions were identified, and lesion and peri-lesion segmentation was performed using structural T1w, T2w, T2w-FLAIR, and T1w post-contrast MRI. The segmentations were then used to extract 16 diffusion MRI parameters from lesion, peri-lesion, and contralateral normal appearing white matter (NAWM). The measurements for axonal integrity, DTI-FA, DKI-FA, FBA-FD, produced similar results. All diffusion MRI parameters were affected in lesions as compared to NAWM (p < 0.001), confirming loss of axonal integrity in lesions. In peri-lesions, most parameters, except FBA-FD, were also significantly different from NAWM, although the effect size was smaller than in lesions. The reduction in axonal integrity in peri-lesions, despite unaffected fibre density estimates, suggests an effect of Wallerian degeneration.

The Application of Diffusion Kurtosis Imaging on the Heterogeneous White Matter in Relapsing-Remitting Multiple Sclerosis

Objectives

To evaluate the microstructural damage in the heterogeneity of different white matter areas in relapsing-remitting multiple sclerosis (RRMS) patients by using diffusion kurtosis imaging (DKI) and its correlation with clinical and cognitive status.

Materials and Methods

Kurtosis fractional anisotropy (KFA), fractional anisotropy (FA), mean kurtosis (MK), and mean diffusivity (MD) in T1-hypointense lesions (T1Ls), pure T2-hyperintense lesions (pure-T2Ls), normal-appearing white matter (NAWM), and white matter in healthy controls (WM in HCs) were measured in 48 RRMS patients and 26 sex- and age-matched HCs. All the participants were assessed with the Mini-Mental State Examination (MMSE), the Montreal Cognitive Assessment (MoCA), and the Symbol Digit Modalities Test (SDMT) scores as the cognitive status. The Kurtzke Expanded Disability Status Scale (EDSS) scores were used to evaluate the clinical status in RRMS patients.

Results

The lowest KFA, FA, and MK values and the highest MD values were found in T1Ls, followed by pure-T2Ls, NAWM, and WM in HCs. The T1Ls and pure-T2Ls were significantly different in FA (p = 0.002) and MK (p = 0.013), while the NAWM and WM in HCs were significantly different in KFA, FA, and MK (p < 0.001; p < 0.001; p = 0.001). The KFA, FA, MK, and MD values in NAWM (r = 0.360, p = 0.014; r = 0.415, p = 0.004; r = 0.369, p = 0.012; r = −0.531, p < 0.001) were correlated with the MMSE scores and the FA, MK, and MD values in NAWM (r = 0.423, p = 0.003; r = 0.427, p = 0.003; r = −0.359, p = 0.014) were correlated with the SDMT scores.

Conclusion

Applying DKI to the imaging-based white matter classification has the potential to reflect the white matter damage and is correlated with cognitive impairment.

Altered Microstructural Changes Detected by Diffusion Kurtosis Imaging in Patients With Cognitive Impairment After Acute Cerebral Infarction

Objective

To detect the microstructural changes in patients with cognitive impairment after acute cerebral infarction using diffusion kurtosis imaging (DKI).

Materials and Methods

A total of 70 patients with acute cerebral infarction were divided into two groups: 35 patients with cognitive impairment (VCI group), and 35 patients without cognitive impairment (N-VCI group), according to mini-mental state examination (MMSE) score. Healthy individuals (n = 36) were selected as the normal control (NORM) group. DKI parameters from 28 different brain regions of interest (ROIs) were selected, measured, and compared.

Results

VCI group patients had significantly higher mean diffusion (MD) and significantly lower mean kurtosis (MK) values in most ROIs than those in the N-VCI and NORM groups. DKI parameters in some ROIs correlated significantly with MMSE score. The splenium of corpus callosum MD was most correlated with MMSE score, the correlation coefficient was −0.652, and this parameter had good ability to distinguish patients with VCI from healthy controls; at the optimal cut-off MD value (0.9915), sensitivity was 91.4%, specificity 100%, and the area under the curve value 0.964.

Conclusions

Pathological changes in some brain regions may underlie cognitive impairment after acute cerebral infarction, especially the splenium of corpus callosum. These preliminary results suggest that, in patients with VCI, DKI may be useful for assessing microstructural tissue damage.

Advanced Diffusion MR Imaging for Multiple Sclerosis in the Brain and Spinal Cord

Diffusion tensor imaging (DTI) has been established its usefulness in evaluating normal-appearing white matter (NAWM) and other lesions that are difficult to evaluate with routine clinical MRI in the evaluation of the brain and spinal cord lesions in multiple sclerosis (MS), a demyelinating disease. With the recent advances in the software and hardware of MRI systems, increasingly complex and sophisticated MRI and analysis methods, such as q-space imaging, diffusional kurtosis imaging, neurite orientation dispersion and density imaging, white matter tract integrity, and multiple diffusion encoding, referred to as advanced diffusion MRI, have been proposed. These are capable of capturing in vivo microstructural changes in the brain and spinal cord in normal and pathological states in greater detail than DTI.

This paper reviews the current status of recent advanced diffusion MRI for assessing MS in vivo as part of an issue celebrating two decades of magnetic resonance in medical sciences (MRMS), an official journal of the Japanese Society of Magnetic Resonance in Medicine.

Advanced Diffusion of the Pediatric Brain and Spine

This article discusses new diffusion-weighted imaging (DWI) sequences, diffusion tensor imaging (DTI), and fiber tractography (FT), as well as more advanced diffusion imaging in pediatric brain and spine. Underlying disorder and pathophysiology causing diffusion abnormalities are discussed. Multishot echo planar imaging (EPI) DWI and non-EPI DWI provide higher spatial resolution with less susceptibility artifact and distortion, which are replacing conventional single-shot EPI DWI. DTI and FT have established clinical significance in pediatric brain and spine. This article discusses advanced diffusion imaging, including diffusion kurtosis imaging, neurite orientation dispersion and density imaging, diffusion spectrum imaging, intravoxel incoherent motion, and oscillating-gradient spin-echo.

Diffusion-Weighted Imaging: Recent Advances and Applications

Quantitative diffusion imaging techniques enable the characterization of tissue microstructural properties of the human brain "in vivo", and are widely used in neuroscientific and clinical contexts. In this review, we present the basic physical principles behind diffusion imaging and provide an overview of the current diffusion techniques, including standard and advanced techniques as well as their main clinical applications. Standard diffusion tensor imaging (DTI) offers sensitivity to changes in microstructure due to diseases and enables the characterization of single fiber distributions within a voxel as well as diffusion anisotropy. Nonetheless, its inability to represent complex intravoxel fiber topologies and the limited biological specificity of its metrics motivated the development of several advanced diffusion MRI techniques. For example, high-angular resolution diffusion imaging (HARDI) techniques enabled the characterization of fiber crossing areas and other complex fiber topologies in a single voxel and supported the development of higher-order signal representations aiming to decompose the diffusion MRI signal into distinct microstructure compartments. Biophysical models, often known by their acronym (e.g., CHARMED, WMTI, NODDI, DBSI, DIAMOND) contributed to capture the diffusion properties from each of such tissue compartments, enabling the computation of voxel-wise maps of axonal density and/or morphology that hold promise as clinically viable biomarkers in several neurological and neuroscientific applications; for example, to quantify tissue alterations due to disease or healthy processes. Current challenges and limitations of state-of-the-art models are discussed, including validation efforts. Finally, novel diffusion encoding approaches (e.g., b-tensor or double diffusion encoding) may increase the biological specificity of diffusion metrics towards intra-voxel diffusion heterogeneity in clinical settings, holding promise in neurological applications.

Impact of the acquisition protocol on the sensitivity to demyelination and axonal loss of clinically feasible DWI techniques: a simulation study

OBJECTIVE

To evaluate: (a) the specific effect that the demyelination and axonal loss have on the DW signal, and (b) the impact of the sequence parameters on the sensitivity to damage of two clinically feasible DWI techniques, i.e. DKI and NODDI.

METHODS

We performed a Monte Carlo simulation of water diffusion inside a novel synthetic model of white matter in the presence of axonal loss and demyelination, with three compartments with permeable boundaries between them. We compared DKI and NODDI in their ability to detect and assess the damage, using several acquisition protocols. We used the F test statistic as an index of the sensitivity for each DWI parameter to axonal loss and demyelination, respectively.

RESULTS

DKI parameters significantly changed with increasing axonal loss, but, in most cases, not with demyelination; all the NODDI parameters showed sensitivity to both the damage processes (at p < 0.01). However, the acquisition protocol strongly affected the sensitivity to damage of both the DKI and NODDI parameters and, especially for NODDI, the parameter absolute values also.

DISCUSSION

This work is expected to impact future choices for investigating white matter microstructure in focusing on specific stages of the disease, and for selecting the appropriate experimental framework to obtain optimal data quality given the purpose of the experiment.

Diffusivity parameters of diffusion tensor imaging and apparent diffusion coefficient as imaging markers for predicting the treatment response of patients with trigeminal neuralgia

OBJECTIVE

Trigeminal neuralgia (TN) is facial pain that is usually caused by neurovascular compression syndrome and is characterized by suddenly intense and paroxysmal pain. Radiofrequency lesioning (RFL) is one of the major treatments for TN, but the treatment response for RFL is sometimes inconsistent, and the recurrence of TN is not uncommon. This study aimed to estimate the outcome predictors of TN treated with RFL by using the parameters of diffusion tensor imaging (DTI).

METHODS

Fifty-one patients with TN who were treated with RFL were enrolled in the study. MRI was performed in all patients within 1 week before surgery. The visual analog scale was used to evaluate symptom severity at three time points: before, 1 week after, and 3 months after RFL. The involved cisternal segment of the trigeminal nerves was manually selected, and the histograms of each of the diffusivity metrics-including the apparent diffusion coefficient (ADC), fractional anisotropy (FA), axial diffusivity (AD), and radial diffusivity (RD)-were measured. The differences in the means, as well as the kurtosis and skewness of each of the diffusivity metrics between the nonrecurrent and recurrent groups, were then analyzed using the Mann-Whitney U-test.

RESULTS

There were significantly lower kurtosis values (a broader peak of the distributional curves) for both FA and ADC in the recurrent group (p = 0.0004 and 0.015, respectively), compared to the nonrecurrent group. The kurtoses of AD and RD, as well as the mean and skewness of all other diffusivity metrics, did not show significant differences between the two groups.

CONCLUSIONS

The pretreatment diffusivity metrics of DTI and ADC may be feasible imaging biomarkers for predicting the outcome of TN after RFL. A clarification of the kurtosis value of FA and ADC is helpful for determining the prognosis of patients after RFL.

Diffusion Kurtosis Imaging maps neural damage in the EAE model of multiple sclerosis

Diffusion kurtosis imaging (DKI) is an imaging modality that yields novel disease biomarkers and in combination with nervous tissue modeling, provides access to microstructural parameters. Recently, DKI and subsequent estimation of microstructural model parameters has been used for assessment of tissue changes in neurodegenerative diseases and associated animal models. In this study, mouse spinal cords from the experimental autoimmune encephalomyelitis (EAE) model of multiple sclerosis (MS) were investigated for the first time using DKI in combination with biophysical modeling to study the relationship between microstructural metrics and degree of animal dysfunction. Thirteen spinal cords were extracted from animals with varied grades of disability and scanned in a high-field MRI scanner along with five control specimen. Diffusion weighted data were acquired together with high resolution T₂* images. Diffusion data were fit to estimate diffusion and kurtosis tensors and white matter modeling parameters, which were all used for subsequent statistical analysis using a linear mixed effects model. T₂* images were used to delineate focal demyelination/inflammation. Our results reveal a strong relationship between disability and measured microstructural parameters in normal appearing white matter and gray matter. Relationships between disability and mean of the kurtosis tensor, radial kurtosis, radial diffusivity were similar to what has been found in other hypomyelinating MS models, and in patients. However, the changes in biophysical modeling parameters and in particular in extra-axonal axial diffusivity were clearly different from previous studies employing other animal models of MS. In conclusion, our data suggest that DKI and microstructural modeling can provide a unique contrast capable of detecting EAE-specific changes correlating with clinical disability.

MR g-ratio-weighted connectome analysis in patients with multiple sclerosis

Multiple sclerosis (MS) is a brain network disconnection syndrome. Although the brain network topology in MS has been evaluated using diffusion MRI tractography, the mechanism underlying disconnection in the disorder remains unclear. In this study, we evaluated the brain network topology in MS using connectomes with connectivity strengths based on the ratio of the inner to outer myelinated axon diameter (i.e., g-ratio), thereby providing enhanced sensitivity to demyelination compared with the conventional measures of connectivity. We mapped g-ratio-based connectomes in 14 patients with MS and compared them with those of 14 age- and sex-matched healthy controls. For comparison, probabilistic tractography was also used to map connectomes based on the number of streamlines (NOS). We found that g-ratio- and NOS-based connectomes comprised significant connectivity reductions in patients with MS, predominantly in the motor, somatosensory, visual, and limbic regions. However, only the g-ratio-based connectome enabled detection of significant increases in nodal strength in patients with MS. Finally, we found that the g-ratio-weighted nodal strength in motor, visual, and limbic regions significantly correlated with inter-individual variation in measures of disease severity. The g-ratio-based connectome can serve as a sensitive biomarker for diagnosing and monitoring disease progression.

Development of a novel method for visualizing restricted diffusion using subtraction of apparent diffusion coefficient values

In order to visualize restricted diffusion, the present study developed a novel method called 'apparent diffusion coefficient (ADC) subtraction method (ASM)' and compared it with diffusion kurtosis imaging (DKI). The diffusion-weighted images of physiological saline, in addtion to bio-phatoms of low cell density and the highest cell density were obtained using two sequences with different effective diffusion times. Then, the calculated ADC values were subtracted. The mean values and standard deviations (SD) of the ADC values of physiological saline, low cell density and the highest cell density phantoms were 2.95±0.08x10‑3, 1.90±0.35x10‑3 and 0.79±0.05x10‑3 mm2/sec, respectively. The mean kurtosis values and SD of DKI were 0.04±0.01, 0.44±0.13 and 1.27±0.03, respectively. The ASM and SD values were 0.25±0.20x104, 0.51±0.41x104 and 4.80±4.51x104 (sec/mm2)2, respectively. Using bio‑phantoms, the present study demonstrated that DKI exhibits restricted diffusion in the extracellular space. Similarly, ASM may reflect the extent of restricted diffusion in the extracellular space.

Gray Matter Alterations in Early and Late Relapsing-Remitting Multiple Sclerosis Evaluated with Synthetic Quantitative Magnetic Resonance Imaging

Extensive gray matter (GM) involvement has been demonstrated in multiple sclerosis (MS) patients. This study was aimed to identify GM alterations in relapsing-remitting MS (RRMS) patients using synthetic quantitative MRI (qMRI). We assessed myelin volume fraction (MVF) in each voxel on the basis of R1 and R2 relaxation rates and proton density in 14 early and 28 late (disease duration ≤5 and >5 years, respectively) RRMS patients, and 15 healthy controls (HCs). The MVF and myelin volumes of GM (GM-MyVol) were compared between groups using GM-based spatial statistics (GBSS) and the Kruskal-Wallis test, respectively. Correlations between MVF or GM-MyVol and disease duration or expanded disability status scale were also evaluated. RRMS patients showed a lower MVF than HCs, predominantly in the limbic and para-limbic areas, with more extensive areas noted in late RRMS patients. Late-RRMS patients had the smallest GM-MyVol (20.44 mL; early RRMS, 22.77 mL; HCs, 23.36 mL). Furthermore, the GM-MyVol in the RRMS group was inversely correlated with disease duration (r = -0.43, p = 0.005). In conclusion, the MVF and MyVol obtained by synthetic qMRI can be used to evaluate GM differences in RRMS patients.

From micro- to macro-structures in multiple sclerosis: what is the added value of diffusion imaging

Diffusion imaging has been instrumental in understanding damage to the central nervous system as a result of its sensitivity to microstructural changes. Clinical applications of diffusion imaging have grown exponentially over the past couple of decades in many neurological and neurodegenerative diseases, such as multiple sclerosis (MS). For several reasons, MS has been extensively researched using advanced neuroimaging techniques, which makes it an 'example disease' to illustrate the potential of diffusion imaging for clinical applications. In addition, MS pathology is characterized by several key processes competing with each other, such as inflammation, demyelination, remyelination, gliosis and axonal loss, enabling the specificity of diffusion to be challenged. In this review, we describe how diffusion imaging can be exploited to investigate micro-, meso- and macro-scale properties of the brain structure and discuss how they are affected by different pathological substrates. Conclusions from the literature are that larger studies are needed to confirm the exciting results from initial investigations before current trends in diffusion imaging can be translated to the neurology clinic. Also, for a comprehensive understanding of pathological processes, it is essential to take a multiple-level approach, in which information at the micro-, meso- and macroscopic scales is fully integrated.

Evaluation of patients with relapsing-remitting multiple sclerosis using tract-based spatial statistics analysis: diffusion kurtosis imaging

Background

Diffusion kurtosis imaging (DKI) has the potential to provide microstructural insights into myelin and axonal pathology with additional kurtosis parameters. To our knowledge, few studies are available in the current literature using DKI by tract-based spatial statistics (TBSS) analysis in patients with multiple sclerosis (MS). The aim of this study is to assess the performance of commonly used parameters derived from DKI and diffusion tensor imaging (DTI) in detecting microstructural changes and associated pathology in relapsing remitting MS (RRMS).

Methods

Thirty-six patients with RRMS and 49 age and sex matched healthy controls underwent DKI. The brain tissue integrity was assessed by fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (Da), radial diffusivity (Dr), mean kurtosis (MK), axial kurtosis (Ka) and radial kurtosis (Kr) of DKI and FA, MD, Da and Dr of DTI. Group differences in these parameters were compared using TBSS (P < 0.01, corrected). To compare the sensitivity of these parameters in detecting white matter (WM) damage, the percentage of the abnormal voxels based on TBSS analysis, relative to the whole skeleton voxels for each parameter was calculated.

Results

The sensitivities in detecting WM abnormality in RRMS were MK (78.2%) > Kr (76.7%) > Ka (53.5%) and Dr (78.8%) > MD (76.7%) > FA (74.1%) > Da (28.3%) for DKI, and Dr (79.8%) > MD (79.5%) > FA (68.6%) > Da (40.1%) for DTI. DKI-derived diffusion parameters (FA, MD, and Dr) were sensitive for detecting abnormality in WM regions with coherent fiber arrangement; however, the kurtosis parameters (MK and Kr) were sensitive to discern abnormalities in WM regions with complex fiber arrangement.

Conclusions

The diffusion and kurtosis parameters could provide complementary information for revealing brain microstructural damage in RRMS. Dr and DKI_Kr may be regarded as useful surrogate markers for reflecting pathological changes in RRMS.

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.

Diffusion kurtosis imaging in the differential diagnosis of parotid gland disease and parotid adenolymphoma: preliminary results

OBJECTIVES

To study the value of diffusion kurtosis imaging (DKI) in diagnosis of parotid gland disease (PGD) with different pathological patterns and parotid adenolymphoma (PAL).

METHODS

57 patients with different kinds of PGD were enrolled and underwent DKI and conventional diffusion-weighted imaging (DWI). All patients were categorized into different groups according to their pathological patterns. The result of calculating the value of DKI-derived parameters (K_mean, K_rad, K_ax, D_mean, D_rad, D_ax, and FA) and apparent diffusion coefficient (ADC) of DWI were used to study their diagnostic accuracy in PGD with different pathological patterns. The binary logistic regression method was used to confirm clinical valuable diffusion parameters (obtained with DKI and DWI models) for diagnosing PAL. Using MedCalc 13.0, receiver operating characteristic (ROC) analysis was conducted to evaluate the diagnostic value of confirmed parameters based on the logistic regression equation.

RESULTS

Both DKI parameters and conventional ADC showed statistical significance in diagnosing PGD with different pathological patterns (p < .01). By using the DKI model, kurtosis coefficients showed higher diagnostic capability than diffusion coefficients ([K_mean+K_rad + K_ax] vs [D_mean +D_rad + D_ax]: 22 vs 15, p < .01) did in the differential diagnosis among different PGD groups. In the diagnosis of PAL among all PGD patterns, the ROC analysis demonstrated that the area under curve (AUC) FA +K_ax [0.881 ± 0.057 (0.824 to 0.938)] is higher than that when using FA [0.629 ± 0.095 (0.534 to 0.724)] and K_ax [0.800 ± 0.070 (0.730 to 0.870)] alone (p < .05), with sensitivity, specificity, accuracy, and both positive and negative predictive values of 71.43, 95.78, 91.77, 76.92, and 94.44%, respectively.

CONCLUSIONS

DKI showed higher diagnostic capacity in the differential diagnosis of PGD with different pathological patterns. Combined parameters of DKI can differentiate PAL from other PGD pathological patterns with a high degree of accuracy. This technique shows great potential for DKI in the differential diagnosis of PGD within a certain pathological category.

Repair strategies for multiple sclerosis: challenges, achievements and perspectives

PURPOSE OF REVIEW

Despite major progress in multiple sclerosis (MS) treatment, to date, accumulation of irreversible clinical disability is not sufficiently prevented with immunotherapies. In this context, repair strategies aimed at reducing axonal damage are becoming a very active field of preclinical and clinical research.

RECENT FINDINGS

Improved understanding of the cellular and molecular mechanisms of myelin repair, together with the emergence of new therapeutic candidates are paving the way for novel therapeutic strategies in MS. In parallel, there is a very active development of imaging methods to assess lesions ongoing remyelination that are crucially needed to evaluate therapeutic efficacy.

SUMMARY

The current development of a very dynamic and multidisciplinary research on remyelination should accelerate the development of myelin repair strategies in MS, to prevent disability progression.

The Relationship between Neurite Density Measured with Confocal Microscopy in a Cleared Mouse Brain and Metrics Obtained from Diffusion Tensor and Diffusion Kurtosis Imaging

Purpose:

Diffusional kurtosis imaging (DKI) enables sensitive measurement of tissue microstructure by quantifying the non-Gaussian diffusion of water. Although DKI is widely applied in many situations, histological correlation with DKI analysis is lacking. The purpose of this study was to determine the relationship between DKI metrics and neurite density measured using confocal microscopy of a cleared mouse brain.

Methods:

One thy-1 yellow fluorescent protein 16 mouse was deeply anesthetized and perfusion fixation was performed. The brain was carefully dissected out and whole-brain MRI was performed using a 7T animal MRI system. DKI and diffusion tensor imaging (DTI) data were obtained. After the MRI scan, brain sections were prepared and then cleared using aminoalcohols (CUBIC). Confocal microscopy was performed using a two-photon confocal microscope with a laser. Forty-eight ROIs were set on the caudate putamen, seven ROIs on the anterior commissure, and seven ROIs on the ventral hippocampal commissure on the confocal microscopic image and a corresponding MR image. In each ROI, histological neurite density and the metrics of DKI and DTI were calculated. The correlations between diffusion metrics and neurite density were analyzed using Pearson correlation coefficient analysis.

Results:

Mean kurtosis (MK) (P = 5.2 × 10⁻⁹, r = 0.73) and radial kurtosis (P = 2.3 × 10⁻⁹, r = 0.74) strongly correlated with neurite density in the caudate putamen. The correlation between fractional anisotropy (FA) and neurite density was moderate (P = 0.0030, r = 0.42). In the anterior commissure and the ventral hippocampal commissure, neurite density and FA are very strongly correlated (P = 1.3 × 10⁻⁵, r = 0.90). MK in these areas were very high value and showed no significant correlation (P = 0.48).

Conclusion:

DKI accurately reflected neurite density in the area with crossing fibers, potentially allowing evaluation of complex microstructures.

Analysis of White Matter Damage in Patients with Multiple Sclerosis via a Novel In Vivo MR Method for Measuring Myelin, Axons, and G-Ratio

BACKGROUND AND PURPOSE

Myelin and axon volume fractions can now be estimated via MR imaging in vivo, as can the g-ratio, which equals the ratio of the inner to the outer diameter of a nerve fiber. The purpose of this study was to evaluate WM damage in patients with MS via this novel MR imaging technique.

MATERIALS AND METHODS

Twenty patients with relapsing-remitting MS with a combined total of 149 chronic plaques were analyzed. Myelin volume fraction was calculated based on simultaneous tissue relaxometry. Intracellular and CSF compartment volume fractions were quantified via neurite orientation dispersion and density imaging. Axon volume fraction and g-ratio were calculated by combining these measurements. Myelin and axon volume fractions and g-ratio were measured in plaques, periplaque WM, and normal-appearing WM.

RESULTS

All metrics differed significantly across the 3 groups (P < .001, except P = .027 for g-ratio between periplaque WM and normal-appearing WM). Those in plaques differed most from those in normal-appearing WM. The percentage changes in plaque and periplaque WM metrics relative to normal-appearing WM were significantly larger in absolute value for myelin volume fraction than for axon volume fraction and g-ratio (P < .001, except P = .033 in periplaque WM relative to normal-appearing WM for comparison between myelin and axon volume fraction).

CONCLUSIONS

In this in vivo MR imaging study, the myelin of WM was more damaged than axons in plaques and periplaque WM of patients with MS. Myelin and axon volume fractions and g-ratio may potentially be useful for evaluating WM damage in patients with MS.

Quantifying the Susceptibility Variation of Normal-Appearing White Matter in Multiple Sclerosis by Quantitative Susceptibility Mapping

OBJECTIVE

The purpose of this study is to evaluate the magnetic susceptibility of normal-appearing white matter (NAWM) in patients with multiple sclerosis (MS) using quantitative susceptibility mapping.

MATERIALS AND METHODS

Ninety-four patients with relapse-remitting MS (RRMS) (37 with gadolinium-enhancing lesions and 57 with only gadolinium-nonenhancing lesions) and 55 healthy control subjects were included in this retrospective study. The susceptibility values of NAWM relative to CSF in patients with MS were compared with those of white matter (WM) in healthy control subjects and were correlated with the patient status of gadolinium-enhancing lesions, disease duration, and expanded disability status scale scores.

RESULTS

All 37 patients with RRMS and gadolinium-enhancing lesions also had gadolinium-nonenhancing lesions. Susceptibility values of NAWM in patients with MS and only gadolinium-nonenhancing lesions (-18.29 ± 8.03 parts per billion [ppb]) were higher than those for WM in healthy control subjects (-25.81 ± 6.02 ppb; p < 0.001) and NAWM in patients with gadolinium-enhancing lesions (-25.64 ± 6.55 ppb; p < 0.001). Susceptibility values of NAWM in patients with MS with gadolinium-enhancing lesions were similar to those for WM in healthy control subjects (p = 0.91). This trend was dependent on neither NAWM region nor disease duration when the data were controlled for age. NAWM susceptibility was not correlated with either disease duration or expanded disability status scale (p > 0.05).

CONCLUSION

In patients with RRMS and gadolinium-nonenhancing lesions, the susceptibility values of NAWM decrease when gadolinium-enhancing lesions appear, approaching values similar to those of WM in healthy control subjects, suggesting that NAWM may contribute to the iron accumulation observed in early active MS lesions.

Automated detection of pathologic white matter alterations in Alzheimer's disease using combined diffusivity and kurtosis method

Diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) are important diffusion MRI techniques for detecting microstructure abnormities in diseases such as Alzheimer's. The advantages of DKI over DTI have been reported generally; however, the indistinct relationship between diffusivity and kurtosis has not been clearly revealed in clinical settings. In this study, we hypothesize that the combination of diffusivity and kurtosis in DKI improves the capacity of DKI to detect Alzheimer's disease compared with diffusivity or kurtosis alone. Specifically, a support vector machine-based approach was applied to combine diffusivity and kurtosis and to compare different indices datasets. Strict assessments were conducted to ensure the reliability of all classifiers. Then, data from the optimized classifiers were used to detect abnormalities. With the combination, high accuracy performances of 96.23% were obtained in 53 subjects, including 27 Alzheimer's patients. More highly scored abnormal regions were selected by the combination than alone. The results revealed that more precise diffusivity and complementary kurtosis mainly contributed to the high performance of the combination in DKI. This study provides further understanding of DKI and the relationship between diffusivity and kurtosis in pathologic white matter alterations in Alzheimer's disease.

Diffusion magnetic resonance imaging: A molecular imaging tool caught between hope, hype and the real world of “personalized oncology”

“Personalized oncology” is a multi-disciplinary science, which requires inputs from various streams for optimal patient management. Humongous progress in the treatment modalities available and the increasing need to provide functional information in addition to the morphological data; has led to leaping progress in the field of imaging. Magnetic resonance imaging has undergone tremendous progress with various newer MR techniques providing vital functional information and is becoming the cornerstone of “radiomics/radiogenomics”. Diffusion-weighted imaging is one such technique which capitalizes on the tendency of water protons to diffuse randomly in a given system. This technique has revolutionized oncological imaging, by giving vital qualitative and quantitative information regarding tumor biology which helps in detection, characterization and post treatment surveillance of the lesions and challenging the notion that “one size fits all”. It has been applied at various sites with different clinical experience. We hereby present a brief review of this novel functional imaging tool, with its application in “personalized oncology”.

Diffusional Kurtosis Imaging of the Corticospinal Tract in Multiple Sclerosis: Association with Neurologic Disability

BACKGROUND AND PURPOSE

Multiple sclerosis is an autoimmune disorder resulting in progressive neurologic disability. Our aim was to evaluate the associations between diffusional kurtosis imaging-derived metrics for the corticospinal tract and disability in multiple sclerosis.

MATERIALS AND METHODS

Forty patients with MS underwent brain MR imaging including diffusional kurtosis imaging. After we masked out T2 hyperintense lesions, the fractional anisotropy, mean diffusivity, radial diffusivity, axial diffusivity, mean kurtosis, radial kurtosis, and axial kurtosis were estimated for the corticospinal tract. Disability was quantified by using the Expanded Disability Status Scale at the time of MR imaging and 12 months post-MR imaging. The Pearson correlation coefficient and linear regression analyses were conducted to evaluate the associations between diffusion metrics and disability.

RESULTS

Significant correlations were found between the Expanded Disability Status Scale scores during the baseline visit and age (r = 0.47), T2 lesion volume (r = 0.38), corticospinal tract mean diffusivity (r = 0.41), radial diffusivity (r = 0.41), axial diffusivity (r = 0.34), fractional anisotropy (r = -0.36), and radial kurtosis (r = -0.42). Significant correlations were also found between the Expanded Disability Status Scale scores at 12-month follow-up and age (r = 0.38), mean diffusivity (r = 0.45), radial diffusivity (r = 0.41), axial diffusivity (r = 0.45), mean kurtosis (r = -0.42), radial kurtosis (r = -0.56), and axial kurtosis (r = -0.36). Linear regression analyses demonstrated significant associations among radial kurtosis, age, and Expanded Disability Status Scale score during the baseline visit, while radial kurtosis was the only variable associated with Expanded Disability Status Scale score for the 12-month follow-up.

CONCLUSIONS

Radial kurtosis of the corticospinal tract may have an association with neurologic disability in MS.

Diffusion Kurtosis Imaging of Microstructural Alterations in the Brains of Paediatric Patients with Congenital Sensorineural Hearing Loss

Our aim was to assess microstructural alterations in the cerebrums of paediatric patients with congenital sensorineural hearing loss (SNHL) using diffusion kurtosis imaging (DKI). Seventy-two paediatric SNHL patients and 38 age-matched healthy volunteers were examined via DKI using a 3.0 T magnetic resonance (MR) imager. Fractional anisotropy (FA) and mean kurtosis (MK) values were computed for 12 cerebral regions in both the controls and the SNHL patients. Compared with patients below age 3, patients in the older age group were found to have more significant differences in MK than in FA, and these appeared in more major areas of the brain. In contrast, in 1- to 3-year-old children, a few major brain areas exhibited differences in FA, but none exhibited appreciable differences in MK. There were significant decreases in the FA or MK values (P < 0.05, all) in more areas of the brain in patients with lesions than in patients with normal-appearing brains. DKI offers comprehensive measurements for quantitative evaluation of age-related microstructural changes in both white and grey matter in SNHL patients. DKI scans of children with SNHL exhibiting significant decreases in MK might play an important role in evaluating the severity of developmental delay.

Empirical Comparison of Diffusion Kurtosis Imaging and Diffusion Basis Spectrum Imaging Using the Same Acquisition in Healthy Young Adults

As diffusion tensor imaging gains widespread use, many researchers have been motivated to go beyond the tensor model and fit more complex diffusion models, to gain a more complete description of white matter microstructure and associated pathology. Two such models are diffusion kurtosis imaging (DKI) and diffusion basis spectrum imaging (DBSI). It is not clear which DKI parameters are most closely related to DBSI parameters, so in the interest of enabling comparisons between DKI and DBSI studies, we conducted an empirical survey of the interrelation of these models in 12 healthy volunteers using the same diffusion acquisition. We found that mean kurtosis is positively associated with the DBSI fiber ratio and negatively associated with the hindered ratio. This was primarily driven by the radial component of kurtosis. The axial component of kurtosis was strongly and specifically correlated with the restricted ratio. The joint spatial distributions of DBSI and DKI parameters are tissue-dependent and stable across healthy individuals. Our contribution is a better understanding of the biological interpretability of the parameters generated by the two models in healthy individuals.

White matter microstructure and volitional motor activity in schizophrenia: A diffusion kurtosis imaging study

Avolition is a core feature of schizophrenia and may arise from altered brain connectivity. Here we used diffusion kurtosis imaging (DKI) to investigate the association between white matter (WM) microstructure and volitional motor activity. Multi-shell diffusion MRI and 24-h actigraphy data were obtained from 20 right-handed patients with schizophrenia and 16 right-handed age and gender matched healthy controls. We examined correlations between fractional anisotropy (FA), mean diffusivity (MD), mean kurtosis (MK), and motor activity level, as well as group differences in these measures. In the patient group, increasing motor activity level was positively correlated with MK in the inferior, medial and superior longitudinal fasciculus, the corpus callosum, the posterior fronto-occipital fasciculus and the posterior cingulum. This association was not found in control subjects or in DTI measures. These results show that a lack of volitional motor activity in schizophrenia is associated with potentially altered WM microstructure in posterior brain regions associated with cognitive function and motivation. This could reflect both illness related dysconnectivity which through altered cognition, manifests as reduced volitional motor activity, and/or the effects of reduced physical activity on brain WM.

Application of diffusional kurtosis imaging to detect occult brain damage in multiple sclerosis and neuromyelitis optica

Multiple sclerosis (MS) and neuromyelitis optica (NMO) are two common types of inflammatory demyelinating disease of the central nervous system. Early distinction of NMO from MS is crucial but quite challenging. In this study, 13 NMO spectrum disorder patients (Expanded Disability Status Scale (EDSS) of 3.0 ± 1.7, ranging from 2 to 6.5; disease duration of 5.3 ± 4.7 years), 17 relapsing-remitting MS patients (EDSS of 2.6 ± 1.4, ranging from 1 to 5.5; disease duration of 7.9 ± 7.8 years) and 18 healthy volunteers were recruited. Diffusional kurtosis imaging was employed to discriminate NMO and MS patients at the early or stable stage from each other, and from healthy volunteers. The presence of alterations in diffusion and diffusional kurtosis metrics in normal-appearing white matter (NAWM) and diffusely increased mean diffusivity (MD) in the cortical normal-appearing gray matter (NAGM) favors the diagnosis of MS rather than NMO. Meanwhile, normal diffusivities and kurtosis metrics in all NAWM as well as increases in MD in the frontal and temporal NAGM suggest NMO. Our results suggest that diffusion and diffusional kurtosis metrics may well aid in discriminating the two diseases.

Diffusion kurtosis imaging can efficiently assess the glioma grade and cellular proliferation

Conventional diffusion imaging techniques are not sufficiently accurate for evaluating glioma grade and cellular proliferation, which are critical for guiding glioma treatment. Diffusion kurtosis imaging (DKI), an advanced non-Gaussian diffusion imaging technique, has shown potential in grading glioma; however, its applications in this tumor have not been fully elucidated. In this study, DKI and diffusion weighted imaging (DWI) were performed on 74 consecutive patients with histopathologically confirmed glioma. The kurtosis and conventional diffusion metric values of the tumor were semi-automatically obtained. The relationships of these metrics with the glioma grade and Ki-67 expression were evaluated. The diagnostic efficiency of these metrics in grading was further compared. It was demonstrated that compared with the conventional diffusion metrics, the kurtosis metrics were more promising imaging markers in distinguishing high-grade from low-grade gliomas and distinguishing among grade II, III and IV gliomas; the kurtosis metrics also showed great potential in the prediction of Ki-67 expression. To our best knowledge, we are the first to reveal the ability of DKI to assess the cellular proliferation of gliomas, and to employ the semi-automatic method for the accurate measurement of gliomas. These results could have a significant impact on the diagnosis and subsequent therapy of glioma.

Application of q-Space Diffusion MRI for the Visualization of White Matter

White matter abnormalities in the CNS have been reported recently in various neurological and psychiatric disorders. Quantitation of non-Gaussianity for water diffusion by q-space diffusional MRI (QSI) renders biological diffusion barriers such as myelin sheaths; however, the time-consuming nature of this method hinders its clinical application. In the current study, we aimed to refine QSI protocols to enable their clinical application and to visualize myelin signals in a clinical setting. For this purpose, animal studies were first performed to optimize the acquisition protocol of a non-Gaussian QSI metric. The heat map of standardized kurtosis values derived from optimal QSI (myelin map) was then created. Histological validation of the myelin map was performed in myelin-deficient mice and in a nonhuman primate by monitoring its variation during demyelination and remyelination after chemical spinal cord injury. The results demonstrated that it was sensitive enough to depict dysmyelination, demyelination, and remyelination in animal models. Finally, its utility in clinical practice was assessed by a pilot clinical study in a selected group of patients with multiple sclerosis (MS). The human myelin map could be obtained within 10 min with a 3 T MR scanner. Use of the myelin map was practical for visualizing white matter and it sensitively detected reappearance of myelin signals after demyelination, possibly reflecting remyelination in MS patients. Our results together suggest that the myelin map, a kurtosis-related heat map obtainable with time-saving QSI, may be a novel and clinically useful means of visualizing myelin in the human CNS.

SIGNIFICANCE STATEMENT

Myelin abnormalities in the CNS have been gaining increasing attention in various neurological and psychiatric diseases. However, appropriate methods with which to monitor CNS myelin in daily clinical practice have been lacking. In the current study, we introduced a novel MRI modality that produces the "myelin map." The myelin map accurately depicted myelin status in mice and nonhuman primates and in a pilot clinical study of multiple sclerosis patients, suggesting that it is useful in detecting possibly remyelinated lesions. A myelin map of the human brain could be obtained in <10 min using a 3 T scanner and it therefore promises to be a powerful tool for researchers and clinicians examining myelin-related diseases.

Assessment of cochlear nerve deficiency and its effect on normal maturation of auditory tract by diffusion kurtosis imaging and diffusion tensor imaging: A correlational approach

OBJECTIVE

The use of diffusion kurtosis imaging (DKI) and diffusion tensor imaging (DTI) was evaluated in assessing cochlear nerve deficiency (CND) and its effect on normal maturation of auditory tract.

METHODS

25 CND patients and 25 controls (age matched: 2months to 17years, gender matched) were evaluated by mean kurtosis (MK), axial kurtosis, and radial kurtosis and compared against fractional anisotropy (FA), axial and radial diffusivities in internal auditory canal (IAC), lateral lemniscus (LL) and inferior colliculus (IC). The age related changes of auditory tract were studied through Pearson correlation between estimated indices and age of both CND and control populations.

RESULTS

Significant loss of MK (IAC: 10.71%, IC: 10.87%, LL: 15.63%) was observed in CND cases as against moderate reduction in FA (IAC: 8.57%, IC: 10%, LL: 7.69%) in all three anatomical locations. Similarly, substantial decline is observed in radial kurtosis (IAC: 27.03%, IC: 33.33%, LL: 31.43%) in comparison to moderate increase in radial diffusivity (IAC: 13.46%, IC: 24.39%, LL: 24%) in CND cases. No statistically significant change was seen in both axial kurtosis and diffusivities. In control populations, MK (r=0.473, p=0.011) and radial kurtosis (r=0.418, p=0.016) correlate positively with age and had no correlation in case of CND cases. FA (r=0.356, p=0.019) minimally correlated with age in control population but showed no statistically significant correlation in CND cases (r=0.198, p=0.036).

CONCLUSION

DKI metrics performed better than DTI in assessing microstructural changes of CND. In particular, MK and radial kurtosis are found to be more sensitive enough to differentiate the normal maturation of cochlear nerve from CND cases.

Multimodal imaging findings in normal-appearing white matter of leucoaraiosis: a review

Leucoaraiosis (LA), also referred to as white matter hyperintensities (WMHs), are usually seen as patchy or confluent hyperintense areas on T2-weighted or fluid-attenuated inversion recovery MRI in the elderly. It is often asymptomatic in its early stages, yet its persistent evolution to more advanced stages may lead to substantial neurological dysfunction including dementia, stroke and death. Despite its clinical significance, the pathogenic mechanisms underlying LA development are uncertain. In patients with LA, the pathophysiological changes in white matter (WM) are suggested to be continuous from WMHs to its neighbourhood ‘normal-appearing white matter (NAWM)’ on conventional MRI sequences. Multimodal imaging studies revealed that the so-called ‘NAWM’ was actually abnormal with regard to underlying haemodynamic and microstructural changes. On the basis of positron emission tomography CT, xenon-CT, perfusion MRI, etc, the cerebral blood flow of NAWM was found to be significantly reduced in patients with LA, compared with healthy controls. Meanwhile, the integrity of microstructures and blood–brain barrier in NAWM was also demonstrated to be impaired with diffusion tensor imaging and dynamic contrast-enhanced MRI studies, respectively. In addition,the integrity of NAWM correlated much stronger with cognitive performance than did WMHs load. It is reasonable to assume that the subtle injury of NAWM would be more reversible than WMHs themselves. Therefore, multimodal imaging modalities could be appropriately applied to future interventional studies targeting at early pathophysiological changes of NAWM. In this paper, we summarise current knowledge about NAWM of LA mainly acquired from multimodal imaging studies in vivo, and attempt to give options for future work.

Quantification of normal-appearing white matter tract integrity in multiple sclerosis: a diffusion kurtosis imaging study

Our aim was to characterize the nature and extent of pathological changes in the normal-appearing white matter (NAWM) of patients with multiple sclerosis (MS) using novel diffusion kurtosis imaging-derived white matter tract integrity (WMTI) metrics and to investigate the association between these WMTI metrics and clinical parameters. Thirty-two patients with relapsing-remitting MS and 19 age- and gender-matched healthy controls underwent MRI and neurological examination. Maps of mean diffusivity, fractional anisotropy and WMTI metrics (intra-axonal diffusivity, axonal water fraction, tortuosity and axial and radial extra-axonal diffusivity) were created. Tract-based spatial statistics analysis was performed to assess for differences in the NAWM between patients and controls. A region of interest analysis of the corpus callosum was also performed to assess for group differences and to evaluate correlations between WMTI metrics and measures of disease severity. Mean diffusivity and radial extra-axonal diffusivity were significantly increased while fractional anisotropy, axonal water fraction, intra-axonal diffusivity and tortuosity were decreased in MS patients compared with controls (p values ranging from <0.001 to <0.05). Axonal water fraction in the corpus callosum was significantly associated with the expanded disability status scale score (ρ = -0.39, p = 0.035). With the exception of the axial extra-axonal diffusivity, all metrics were correlated with the symbol digits modality test score (p values ranging from 0.001 to <0.05). WMTI metrics are thus sensitive to changes in the NAWM of MS patients and might provide a more pathologically specific, clinically meaningful and practical complement to standard diffusion tensor imaging-derived metrics.

Diffusional Kurtosis Imaging in Idiopathic Normal Pressure Hydrocephalus: Correlation with Severity of Cognitive Impairment

PURPOSE

Diffusional kurtosis imaging (DKI) is an emerging technique that describes diffusion of water molecules in terms of deviation from Gaussian distribution. This study investigated correlations between DKI metrics and cognitive function in patients with idiopathic normal pressure hydrocephalus (iNPH).

MATERIALS AND METHODS

DKI was performed in 29 iNPH patients and 14 age-matched controls. Mini-mental state examination (MMSE), frontal assessment battery (FAB), and trail making test A (TMT-A) were used as cognitive measures. Tract-based spatial statistics (TBSS) analyses were performed to investigate the between-group differences and correlations with the cognitive measures of the diffusion metrics, including mean kurtosis (MK), fractional anisotropy (FA), apparent diffusion coefficient (ADC), axial diffusivity (AD), and radial diffusivity (RD).

RESULTS

In iNPH patients, FA and MK identified positive correlations with cognitive function in similar regions, predominantly in the frontal lobes (P < 0.05, corrected for multiple comparisons). The frontoparietal subcortical white matter showed significant correlations with FAB and TMT-A across more extensive areas in MK analyses than in FA. ADC, AD, and RD analyses showed no significant correlations with MMSE and FAB, while negative correlation with TMT-A was observed in the limited portion of the frontal deep white matter.

CONCLUSION

Both FA and MK correlated well with cognitive impairment in iNPH. The observed differences between FA and MK results suggest DKI may play a complementary role to conventional FA and ADC analyses, especially for evaluation of the subcortical white matter.

Spatially selective 2D RF inner field of view (iFOV) diffusion kurtosis imaging (DKI) of the pediatric spinal cord

Magnetic resonance based diffusion imaging has been gaining more utility and clinical relevance over the past decade. Using conventional echo planar techniques, it is possible to acquire and characterize water diffusion within the central nervous system (CNS); namely in the form of Diffusion Weighted Imaging (DWI) and Diffusion Tensor Imaging (DTI). While each modality provides valuable clinical information in terms of the presence of diffusion and its directionality, both techniques are limited to assuming an ideal Gaussian distribution for water displacement with no intermolecular interactions. This assumption neglects pathological processes that are not Gaussian therefore reducing the amount of potentially clinically relevant information. Additions to the Gaussian distribution measured by the excess kurtosis, or peakedness, of the probabilistic model provide a better understanding of the underlying cellular structure. The objective of this work is to provide mathematical and experimental evidence that Diffusion Kurtosis Imaging (DKI) can offer additional information about the micromolecular environment of the pediatric spinal cord. This is accomplished by a more thorough characterization of the nature of random water displacement within the cord. A novel DKI imaging sequence based on a tilted 2D spatially selective radio frequency pulse providing reduced field of view (FOV) imaging was developed, implemented, and optimized on a 3 Tesla MRI scanner, and tested on pediatric subjects (healthy subjects: 15; patients with spinal cord injury (SCI):5). Software was developed and validated for post processing of the DKI images and estimation of the tensor parameters. The results show statistically significant differences in mean kurtosis (p < 0.01) and radial kurtosis (p < 0.01) between healthy subjects and subjects with SCI. DKI provides incremental and novel information over conventional diffusion acquisitions when coupled with higher order estimation algorithms.

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Diffusion Kurtosis Imaging (DKI) was performed on pediatric subjects using a tilted 2D RF reduced field of view sequence.

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Results show statistically significant differences in FA, MK, Krad, and Drad between healthy subjects and patients with SCI.

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DKI provides additional structural information that when paired with DTI metrics could be used as a novel imaging biomarker.

Diffusion kurtosis imaging probes cortical alterations and white matter pathology following cuprizone induced demyelination and spontaneous remyelination

Although MRI is the gold standard for the diagnosis and monitoring of multiple sclerosis (MS), current conventional MRI techniques often fail to detect cortical alterations and provide little information about gliosis, axonal damage and myelin status of lesioned areas. Diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) provide sensitive and complementary measures of the neural tissue microstructure. Additionally, specific white matter tract integrity (WMTI) metrics modelling the diffusion in white matter were recently derived. In the current study we used the well-characterized cuprizone mouse model of central nervous system demyelination to assess the temporal evolution of diffusion tensor (DT), diffusion kurtosis tensor (DK) and WMTI-derived metrics following acute inflammatory demyelination and spontaneous remyelination. While DT-derived metrics were unable to detect cuprizone induced cortical alterations, the mean kurtosis (MK) and radial kurtosis (RK) were found decreased under cuprizone administration, as compared to age-matched controls, in both the motor and somatosensory cortices. The MK remained decreased in the motor cortices at the end of the recovery period, reflecting long lasting impairment of myelination. In white matter, DT, DK and WMTI-derived metrics enabled the detection of cuprizone induced changes differentially according to the stage and the severity of the lesion. More specifically, the MK, the RK and the axonal water fraction (AWF) were the most sensitive for the detection of cuprizone induced changes in the genu of the corpus callosum, a region less affected by cuprizone administration. Additionally, microgliosis was associated with an increase of MK and RK during the acute inflammatory demyelination phase. In regions undergoing severe demyelination, namely the body and splenium of the corpus callosum, DT-derived metrics, notably the mean diffusion (MD) and radial diffusion (RD), were among the best discriminators between cuprizone and control groups, hence highlighting their ability to detect both acute and long lasting changes. Interestingly, WMTI-derived metrics showed the aptitude to distinguish between the different stages of the disease. Both the intra-axonal diffusivity (Da) and the AWF were found to be decreased in the cuprizone treated group, Da specifically decreased during the acute inflammatory demyelinating phase whereas the AWF decrease was associated to the spontaneous remyelination and the recovery period. Altogether our results demonstrate that DKI is sensitive to alterations of cortical areas and provides, along with WMTI metrics, information that is complementary to DT-derived metrics for the characterization of demyelination in both white and grey matter and subsequent inflammatory processes associated with a demyelinating event.

Diffusion-tensor-based method for robust and practical estimation of axial and radial diffusional kurtosis

Objectives

A new method that can estimate diffusional kurtosis image (DKI), estimated DKI (eDKI), parallel and perpendicular to neuronal fibres from greatly limited image data was designed to enable quick and practical assessment of DKI in clinics. The purpose of this study was to discuss the potential of this method for clinical use.

Methods

Fourteen healthy volunteers were examined with a 3-Tesla MRI. The diffusion-weighting parameters included five different b-values (0, 500, 1,500, 2,000 and 2,500 s/mm²) with 64 different encoding directions for each of the b-values. K values were calculated by both conventional DKI (convDKI) and eDKI from these complete data, and also from the data that the encoding directions were abstracted to 32, 21, 15, 12 and 6. Error-pixel ratio and the root mean square error (RMSE) compared with the standard were compared between the methods (Wilcoxon signed-rank test: P < 0.05 was considered significant).

Results

Error-pixel ratio was smaller in eDKI than in convDKI and the difference was significant. In addition, RMSE was significantly smaller in eDKI than in convDKI, or otherwise the differences were not significant when they were obtained from the same data set.

Conclusion

eDKI might be useful for assessing DKI in clinical settings.

Key Points

• A method to practically estimate axial/radial DKI from limited data was developed.

• The high robustness of the proposed method can greatly improve map images.

• The accuracy of the proposed method was high.

• Axial/radial K maps can be calculated from limited diffusion-encoding directions.

• The proposed method might be useful for assessing DKI in clinical settings.

Exploring the 3D geometry of the diffusion kurtosis tensor--impact on the development of robust tractography procedures and novel biomarkers

Diffusion kurtosis imaging (DKI) is a diffusion-weighted technique which overcomes limitations of the commonly used diffusion tensor imaging approach. This technique models non-Gaussian behaviour of water diffusion by the diffusion kurtosis tensor (KT), which can be used to provide indices of tissue heterogeneity and a better characterisation of the spatial architecture of tissue microstructure. In this study, the geometry of the KT is elucidated using synthetic data generated from multi-compartmental models, where diffusion heterogeneity between intra- and extra-cellular media is taken into account, as well as the sensitivity of the results to each model parameter and to synthetic noise. Furthermore, based on the assumption that the maxima of the KT are distributed perpendicularly to the direction of well-aligned fibres, a novel algorithm for estimating fibre direction directly from the KT is proposed and compared to the fibre directions extracted from DKI-based orientation distribution function (ODF) estimates previously proposed in the literature. Synthetic data results showed that, for fibres crossing at high intersection angles, direction estimates extracted directly from the KT have smaller errors than the DKI-based ODF estimation approaches (DKI-ODF). Nevertheless, the proposed method showed smaller angular resolution and lower stability to changes of the simulation parameters. On real data, tractography performed on these KT fibre estimates suggests a higher sensitivity than the DKI-based ODF in resolving lateral corpus callosum fibres reaching the pre-central cortex when diffusion acquisition is performed with five b-values. Using faster acquisition schemes, KT-based tractography did not show improved performance over the DKI-ODF procedures. Nevertheless, it is shown that direct KT fibre estimates are more adequate for computing a generalised version of radial kurtosis maps.

Analysis of normal-appearing white matter of multiple sclerosis by tensor-based two-compartment model of water diffusion

Objectives

To compare the significance of the two-compartment model, considering diffusional anisotropy with conventional diffusion analyzing methods regarding the detection of occult changes in normal-appearing white matter (NAWM) of multiple sclerosis (MS).

Methods

Diffusion-weighted images (nine b-values with six directions) were acquired from 12 healthy female volunteers (22–52 years old, median 33 years) and 13 female MS patients (24–48 years old, median 37 years). Diffusion parameters based on the two-compartment model of water diffusion considering diffusional anisotropy was calculated by a proposed method. Other parameters including diffusion tensor imaging and conventional apparent diffusion coefficient (ADC) were also obtained. They were compared statistically between the control and MS groups.

Results

Diffusion of the slow diffusion compartment in the radial direction of neuron fibers was elevated in MS patients (0.121 × 10⁻³ mm2/s) in comparison to control (0.100 × 10⁻³ mm²/s), the difference being significant (P = 0.001). The difference between the groups was not significant in other comparisons, including conventional ADC and fractional anisotropy (FA) of diffusion tensor imaging.

Conclusion

The proposed method was applicable to clinically acceptable small data. The parameters obtained by this method improved the detectability of occult changes in NAWM compared to the conventional methods.

Key Points

• Water diffusion was compared between the controls and multiple sclerosis patients.

• A two-compartment model, considering diffusional anisotropy was selected for water diffusion analysis.

• Axial and radial diffusion of fast and slow diffusion components were evaluated.

• A new method was developed to obtain the metrics stably.

• The metrics indicated high detectability of slight differences between the groups.

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.

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.