Regional values of diffusional kurtosis estimates in the healthy brain

Investigating apparent differences between standard DKI and axisymmetric DKI and its consequences for biophysical parameter estimates

PURPOSE

The purpose of the study is to identify differences between axisymmetric diffusion kurtosis imaging (DKI) and standard DKI, their consequences for biophysical parameter estimates, and the protocol choice influence on parameter estimation.

METHODS

Noise-free and noisy, synthetic diffusion MRI human brain data is simulated using standard DKI for a standard and the fast "199" acquisition protocol. First the noise-free "baseline" difference between both DKI models is estimated and the influence of fiber complexity is investigated. Noisy data is used to establish the signal-to-noise ratio at which the baseline difference exceeds noise variability. The influence of protocol choices and denoising is investigated. The five axisymmetric DKI tensor metrics (AxTM), the parallel and perpendicular diffusivity and kurtosis and mean of the kurtosis tensor are used to compare both DKI models. Additionally, the baseline difference is also estimated for the five parameters of the WMTI-Watson model.

RESULTS

The parallel and perpendicular kurtosis and all of the WMTI-Watson parameters had large baseline differences. Using a Westin or FA mask reduced the number of voxels with large baseline difference, that is, by selecting voxels with less complex fibers. For the noisy data, precision was worsened by the fast "199" protocol but adaptive denoising can help counteract these effects.

CONCLUSION

For the diffusivities and mean of the kurtosis tensor, axisymmetric DKI with a standard protocol delivers similar results as standard DKI. Fiber complexity is one main driver of the baseline differences. Using the "199" protocol worsens precision in noisy data but adaptive denoising mitigates these effects.

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.

Common Relationship Between Causality Orientation and the Prefrontal Region in Psychiatric Disorders as Revealed by Diffusional Kurtosis Imaging

Background Motivation dysregulation is common in several psychiatric disorders. However, little is known about the relationships between motivation and the regional brain areas involved. We evaluated the relationships between brain microstructural features and causality orientation in patients with schizophrenia, major depressive disorder (MDD), and bipolar disorder (BD) using diffusional kurtosis imaging (DKI) techniques. Methods Forty patients with MDD, 36 with BD, and 30 with schizophrenia underwent DKI and assessment using the General Causality Orientation Scale (GCOS). We analyzed the DKI index and the GCOS subscales. Results The psychiatric patients showed significant positive correlations between the GCOS-autonomy orientation score and the mean kurtosis (MK) values in the prefrontal regions, orbitofrontal regions, and posterior cingulate cortex. When the analyses were performed separately by disease and gender, a positive correlation was found between the GCOS-autonomy orientation score and the MK values in the left prefrontal regions transdiagnostically, especially among female patients with MDD, BD, and schizophrenia. Conclusions A similar association between intrinsic motivation and MK value in the left prefrontal cortex was suggested in patients with schizophrenia, MDD, and BD. The commonality of this association among these disorders might lead to the discovery of a new biomarker for psychiatric clinical research.

Purpose in life as a resilience factor for brain health: diffusion MRI findings from the Midlife in the U.S. study

Introduction

A greater sense of purpose in life is associated with several health benefits relevant for active aging, but the mechanisms remain unclear. We evaluated if purpose in life was associated with indices of brain health.

Methods

We examined data from the Midlife in the United States (MIDUS) Neuroscience Project. Diffusion weighted magnetic resonance imaging data (n=138; mean age 65.2 years, age range 48-95; 80 females; 37 black, indigenous, and people of color) were used to estimate microstructural indices of brain health such as axonal density, and axonal orientation. The seven-item purpose in life scale was used. Permutation analysis of linear models was used to examine associations between purpose in life scores and the diffusion metrics in white matter and in the bilateral hippocampus, adjusting for age, sex, education, and race.

Results and discussion

Greater sense of purpose in life was associated with brain microstructural features consistent with better brain health. Positive associations were found in both white matter and the right hippocampus, where multiple convergent associations were detected. The hippocampus is a brain structure involved in learning and memory that is vulnerable to stress but retains the capacity to grow and adapt through old age. Our findings suggest pathways through which an enhanced sense of purpose in life may contribute to better brain health and promote healthy aging. Since purpose in life is known to decline with age, interventions and policy changes that facilitate a greater sense of purpose may extend and improve the brain health of individuals and thus improve public health.

Comparison of three magnetic resonance imaging measures of brain iron in healthy and cocaine use disorder participants

Several magnetic resonance imaging (MRI) measures for quantifying endogenous nonheme brain iron have been proposed. These correspond to distinct physical properties with varying sensitivities and specificities to iron. Moreover, they may depend not only on tissue iron concentration, but also on the intravoxel spatial pattern of iron deposition, which is complex in many brain regions. Here, the three MRI brain iron measures of R 2 * , magnetic field correlation (MFC), and magnetic susceptibility are compared in several deep gray matter regions for both healthy participants (HPs) and individuals with cocaine use disorder (CUD). Their concordance is assessed from their correlations with each other and their relative dependencies on age. In addition, associations between the iron measures and microstructure in adjacent white matter regions are investigated by calculating their correlations with diffusion MRI measures from the internal capsule, and associations with cognition are determined by using results from a battery of standardized tests relevant to CUD. It is found that all three iron measures are strongly correlated with each other for the considered gray matter regions, but with correlation coefficients substantially less than one indicating important differences. The age dependencies of all three measures are qualitatively similar in most regions, except for the red nucleus, where the susceptibility has a significantly stronger correlation with age than R 2 * . Weak to moderate correlations are seen for the iron measures with several of the diffusion and cognitive measures, with the strongest correlations being obtained for R 2 * . The iron measures differ little between the HP and CUD groups, although susceptibility is significantly lower in the red nucleus for the CUD group. For the comparisons made, the iron measures behave similarly in most respects, but with notable quantitative differences. It is suggested that these differences may be, in part, attributable to a higher sensitivity to the spatial pattern of iron deposition for R 2 * and MFC than for susceptibility. This is supported most strongly by a sharp contrast between the values of the iron measures in the globus pallidus relative to those in the red nucleus. The observed correlations of the iron measures with diffusion and cognitive scores point to possible connections between gray matter iron, white matter microstructure, and cognition.

Microstructural changes of peripheral nerves in early multiple sclerosis: A prospective magnetic resonance neurography study

BACKGROUND AND PURPOSE

Multiple sclerosis (MS) is a demyelinating disorder of the central nervous system (CNS). However, there is increasing evidence of peripheral nerve involvement. This study aims to characterize the pattern of peripheral nerve changes in patients with newly diagnosed MS using quantitative magnetic resonance (MR) neurography.

METHODS

In this prospective study, 25 patients first diagnosed with MS according to the revised McDonald criteria (16 female, mean age = 32.8 ± 10.6 years) and 14 healthy controls were examined with high-resolution 3-T MR neurography of the sciatic nerve using diffusion kurtosis imaging (DKI; 20 diffusional directions, b = 0, 700, 1200 s/mm2 ) and magnetization transfer imaging (MTI). In total, 15 quantitative MR biomarkers were analyzed and correlated with clinical symptoms, intrathecal immunoglobulin synthesis, electrophysiology, and lesion load on brain and spine MR imaging.

RESULTS

Patients showed decreased fractional anisotropy (mean = 0.51 ± 0.04 vs. 0.56 ± 0.03, p < 0.001), extra-axonal tortuosity (mean = 2.32 ± 0.17 vs. 2.49 ± 0.17, p = 0.008), and radial kurtosis (mean = 1.40 ± 0.23 vs. 1.62 ± 0.23, p = 0.014) and higher radial diffusivity (mean = 1.09 ∙ 10-3  mm2 /s ± 0.16 vs. 0.98 ± 0.11 ∙ 10-3  mm2 /s, p = 0.036) than controls. Groups did not differ in MTI. No significant association was found between MR neurography markers and clinical/laboratory parameters or CNS lesion load.

CONCLUSIONS

This study provides further evidence of peripheral nerve involvement in MS already at initial diagnosis. The characteristic pattern of DKI parameters indicates predominant demyelination and suggests a primary coaffection of the peripheral nervous system in MS. This first human study using DKI for peripheral nerves shows its potential and clinical feasibility in providing novel biomarkers.

White matter microstructural integrity pre- and post-treatment in individuals with chronic post-stroke aphasia

While previous studies have found that white matter damage relates to impairment severity in individuals with aphasia, further study is required to understand the relationship between white matter integrity and treatment response. In this study, 34 individuals with chronic post-stroke aphasia underwent behavioral testing and structural magnetic resonance imaging at two timepoints. Thirty participants within this sample completed typicality-based semantic feature treatment for anomia. Tractography of bi-hemispheric white matter tracts was completed via Automated Fiber Quantification. Associations between microstructural integrity metrics and behavioral measures were evaluated at the tract level and in nodes along the tract. Diffusion measures of the left inferior longitudinal, superior longitudinal, and arcuate fasciculi were related to aphasia severity and diffusion measures of the left inferior longitudinal fasciculus were related to naming and treatment response. This study also found preliminary evidence of left inferior longitudinal fasciculus microstructural changes following treatment.

DKI enhances the sensitivity and interpretability of age-related DTI patterns in the white matter of UK biobank participants

Studies of healthy brain aging traditionally report diffusivity patterns associated with white matter degeneration using diffusion tensor imaging (DTI), which assumes that diffusion measured at typical b-values (approximately 1000 s/mm²) is Gaussian. Diffusion kurtosis imaging (DKI) is an extension of DTI that measures non-Gaussian diffusion (kurtosis) to better capture microenvironmental processes by incorporating additional data at a higher b-value. In this study, using diffusion data (b-values of 1000 and 2000 s/mm²) from 700 UK Biobank participants aged 46-80, we investigate (1) the extent of novel information gained from adding diffusional kurtosis to diffusivity observations in aging, and (2) how conventional DTI metrics in aging compare with diffusivity metrics derived from DKI, which are corrected for kurtosis. We establish a pattern of lower kurtosis alongside higher diffusivity among older adults, with kurtosis generally being more sensitive to age than diffusivity. We also find discrepancies between diffusivity metrics derived from DTI and DKI, emphasizing the importance of accounting for non-Gaussian diffusion when interpreting age-related diffusivity patterns.

[Evaluation of Diffusional Kurtosis Inference Using Synthetic q-space Learning and Bias Correction]

PURPOSE

In synthetic q-space learning (synQSL), which uses deep learning to infer the diffusional kurtosis (K), a bias that depends on the noise level added to the synthetic training data occurs. The purpose of this study was to evaluate K inference using synQSL and bias correction.

METHODS

Using the synthetic test data and the real image data, K was inferred by synQSL, and bias correction was performed. Then, those results were compared with K inferred by fitting by the least-squares fitting (LSF) method. At this time, the noise level of the training data was set to 3 types, the noise level of the synthesis test data was set to 5 types, and the number of excitation (NEX) of the real image data was set to 4 types. Robustness of inference was evaluated by the outlier rate, which is the ratio of K outliers to the whole brain. We also evaluated the root mean square error (RMSE) of the inferred K.

RESULTS

The outlier rate inferred by synQSL without correction was significantly lower in the test data of each noise level than that by the LSF method and was further reduced by correction. In addition, the RMSE of NEX 1 with NEX 4 as the correct answer based on the real image data had the smallest correction result of K by synQSL.

CONCLUSION

Inferring K using synQSL and bias correction is a robust and small error method compared to that using the LSF method.

Sensitivity of Diffusion MRI to White Matter Pathology: Influence of Diffusion Protocol, Magnetic Field Strength, and Processing Pipeline in Systemic Lupus Erythematosus

There are many ways to acquire and process diffusion MRI (dMRI) data for group studies, but it is unknown which maximizes the sensitivity to white matter (WM) pathology. Inspired by this question, we analyzed data acquired for diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) at 3T (3T-DTI and 3T-DKI) and DTI at 7T in patients with systemic lupus erythematosus (SLE) and healthy controls (HC). Parameter estimates in 72 WM tracts were obtained using TractSeg. The impact on the sensitivity to WM pathology was evaluated for the diffusion protocol, the magnetic field strength, and the processing pipeline. Sensitivity was quantified in terms of Cohen's d for group comparison. Results showed that the choice of diffusion protocol had the largest impact on the effect size. The effect size in fractional anisotropy (FA) across all WM tracts was 0.26 higher when derived by DTI than by DKI and 0.20 higher in 3T compared with 7T. The difference due to the diffusion protocol was larger than the difference due to magnetic field strength for the majority of diffusion parameters. In contrast, the difference between including or excluding different processing steps was near negligible, except for the correction of distortions from eddy currents and motion which had a clearly positive impact. For example, effect sizes increased on average by 0.07 by including motion and eddy correction for FA derived from 3T-DTI. Effect sizes were slightly reduced by the incorporation of denoising and Gibbs-ringing removal (on average by 0.011 and 0.005, respectively). Smoothing prior to diffusion model fitting generally reduced effect sizes. In summary, 3T-DTI in combination with eddy current and motion correction yielded the highest sensitivity to WM pathology in patients with SLE. However, our results also indicated that the 3T-DKI and 7T-DTI protocols used here may be adjusted to increase effect sizes.

Improved diffusion parameter estimation by incorporating T2 relaxation properties into the DKI-FWE model

The free water elimination (FWE) model and its kurtosis variant (DKI-FWE) can separate tissue and free water signal contributions, thus providing tissue-specific diffusional information. However, a downside of these models is that the associated parameter estimation problem is ill-conditioned, necessitating the use of advanced estimation techniques that can potentially bias the parameter estimates. In this work, we propose the T₂-DKI-FWE model that exploits the T₂ relaxation properties of both compartments, thereby better conditioning the parameter estimation problem and providing, at the same time, an additional potential biomarker (the T₂ of tissue). In our approach, the T₂ of tissue is estimated as an unknown parameter, whereas the T₂ of free water is assumed known a priori and fixed to a literature value (1573 ms). First, the error propagation of an erroneous assumption on the T₂ of free water is studied. Next, the improved conditioning of T₂-DKI-FWE compared to DKI-FWE is illustrated using the Cramér-Rao lower bound matrix. Finally, the performance of the T₂-DKI-FWE model is compared to that of the DKI-FWE and T₂-DKI models on both simulated and real datasets. The error due to a biased approximation of the T₂ of free water was found to be relatively small in various diffusion metrics and for a broad range of erroneous assumptions on its underlying ground truth value. Compared to DKI-FWE, using the T₂-DKI-FWE model is beneficial for the identifiability of the model parameters. Our results suggest that the T₂-DKI-FWE model can achieve precise and accurate diffusion parameter estimates, through effective reduction of free water partial volume effects and by using a standard nonlinear least squares approach. In conclusion, incorporating T₂ relaxation properties into the DKI-FWE model improves the conditioning of the model fitting, while only requiring an acquisition scheme with at least two different echo times.

The diagnostic value of diffusion kurtosis imaging in Parkinson's disease: a systematic review and meta-analysis

Background

Under the background that diffusion kurtosis imaging (DKI) has become a research hotspot of central nervous system diseases, there are no studies with large sample size evaluating the value of DKI in diagnosing Parkinson's disease (PD). Moreover, the diagnostic efficacy of DKI in PD is not consistent. Therefore, the main purpose of this study is to use the method of meta-analysis, to summarize and evaluate the diagnostic efficacy of DKI in the identification of PD, and to explore the value of its clinical application.

Methods

We use PICOS principles for project design. The included patients were PD patients, and the control group were healthy volunteers. We hope to use DKI to make a differential diagnosis between the two, and this study is a diagnostic test. We performed a literature search of English (PubMed, Embase, Cochrane Library, etc.) and Chinese (China knowledge Network, Wanfang Data Knowledge Service platform, China Science and Technology Journal Database, China Biomedical Literature Service system) databases for related literatures on the efficacy of DKI in the differential diagnosis of PD published before March 29, 2022. We used Revman 5.3 software to assess the quality of the literature, Meta-Disc 1.4 software for summarizing sensitivity (Sen), specificity (Spe), diagnostic odds ratios, and heterogeneity tests, and for subgrouping, and Stata 16.0 software for publication bias analysis.

Results

Fourteen articles were included through the literature search. The 14 studies included 535 patients with PD and 486 patients without PD. Most of the included literature had good clinical applicability and relatively low risk. By merging statistics, the results obtained were as follows: Sen =0.78 [95% confidence interval (CI): 0.74-0.81], Spe =0.83 (95% CI: 0.79-0.86), and the area under the summary receiver operating characteristic (SROC) curve was 0.8870.

Discussion

The results of the meta-analysis showed that magnetic resonance DKI has comparable diagnostic accuracy in the diagnosis of PD. However, this study also has limitations, and the use of different diagnostic gold standards in the included studies may have some impact on the case selection in the study.

Combined Application of Quantitative Susceptibility Mapping and Diffusion Kurtosis Imaging Techniques to Investigate the Effect of Iron Deposition on Microstructural Changes in the Brain in Parkinson's Disease

OBJECTIVES

Brain iron deposition and microstructural changes in brain tissue are associated with Parkinson's disease (PD). However, the correlation between these factors in Parkinson's disease has been little studied. This study aimed to use quantitative susceptibility mapping combined with diffusion kurtosis imaging to investigate the effects of iron deposition on microstructural tissue alterations in the brain.

METHODS

Quantitative susceptibility mapping and diffusion kurtosis imaging were performed on 24 patients with early PD, 13 patients with advanced PD, and 25 healthy controls. The mean values of magnetic susceptibility and diffusion kurtosis were calculated for the bilateral substantia nigra, red nucleus, putamen, globus pallidus, and caudate nucleus, and compared between the groups. Correlation analyses between the diffusion kurtosis of each nucleus and its magnetic susceptibility parameters in PD patients and healthy controls were performed.

RESULTS

The study found a significant increase in iron deposition in the substantia nigra, red nucleus, putamen and globus pallidus, bilaterally, in patients with PD. Mean kurtosis values were increased in the substantia nigra but decreased in the globus pallidus; axial kurtosis values were decreased in both the substantia nigra and red nucleus; radial kurtosis values were increased in the substantia nigra but showed an opposite trend in the globus pallidus and caudate nucleus. In the substantia nigra of patients with PD, magnetic susceptibility was positively correlated with mean and radial kurtosis values, and negatively correlated with axial kurtosis. None of these correlations were significantly different in the control group. In the putamen, magnetic susceptibility was positively correlated with mean, axial, and radial kurtosis only in patients with advanced-stage PD.

CONCLUSION

Our study provides new evidence for brain iron content and microstructural alterations in patients with PD. Iron deposition may be a common mechanism for microstructural alterations in the substantia nigra and putamen of patients with PD. Tracking the dynamic changes in iron content and microstructure throughout the course of PD will help us to better understand the dynamics of iron metabolism and microstructural alterations in the pathogenesis of PD and to develop new approaches to monitor and treat PD.

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.

Diffusion kurtosis imaging: An efficient tool for evaluating age-related changes in rat brains

PURPOSE

To evaluate and determine age-related changes in rat brains by studying the diffusion kurtosis imaging results among different age groups of rats.

METHODS

Sprague-Dawley (SD) rats underwent conventional magnetic resonance imaging (MRI) and diffusion Kurtosis Imaging (DKI). Two diffusion values of mean kurtosis (MK) and kurtosis (K⊥ ) were measured and analyzed based on laterality, brain regions and age groups. The MK and K⊥ data were plotted against different age groups.

RESULTS

No laterality was found for the MK or K⊥ values in the cerebral cortex (CT), external capsule (EC), or caudate putamen (CPu) regions. In contrast, significant changes in these values were observed among different age groups. Changes of the MK and K⊥ values were significant in both hemispheres in the EC, the CT, and the CPu brain regions. The changes in the MK and K⊥ values showed a parabolic relationship with ages in all the brain regions.

CONCLUSION

No laterality in the MK and K⊥ values was observed for the EC, CT, or CPu regions of the rat brain. Significant changes in MK and K⊥ values were both observed among different age groups, thus suggesting diffusion kurtosis imaging as an efficient tool for studying brain aging in rats.

A Fast Protocol for Multiparametric Characterisation of Diffusion in the Brain and Brain Tumours

Multi-parametric tissue characterisation is demonstrated using a 4-minute protocol based on diffusion trace acquisitions. Three diffusion regimes are covered simultaneously: pseudo-perfusion, Gaussian, and non-Gaussian diffusion. The clinical utility of this method for fast multi-parametric mapping for brain tumours is explored. A cohort of 17 brain tumour patients was measured on a 3T hybrid MR-PET scanner with a standard clinical MRI protocol, to which the proposed multi-parametric diffusion protocol was subsequently added. For comparison purposes, standard perfusion and a full diffusion kurtosis protocol were acquired. Simultaneous amino-acid (¹⁸F-FET) PET enabled the identification of active tumour tissue. The metrics derived from the proposed protocol included perfusion fraction, pseudo-diffusivity, apparent diffusivity, and apparent kurtosis. These metrics were compared to the corresponding metrics from the dedicated acquisitions: cerebral blood volume and flow, mean diffusivity and mean kurtosis. Simulations were carried out to assess the influence of fitting methods and noise levels on the estimation of the parameters. The diffusion and kurtosis metrics obtained from the proposed protocol show strong to very strong correlations with those derived from the conventional protocol. However, a bias towards lower values was observed. The pseudo-perfusion parameters showed very weak to weak correlations compared to their perfusion counterparts. In conclusion, we introduce a clinically applicable protocol for measuring multiple parameters and demonstrate its relevance to pathological tissue characterisation.

Cortical and white matter correlates of language-learning aptitudes

People learn new languages with varying degrees of success but what are the neuroanatomical correlates of the difference in language‐learning aptitude? In this study, we set out to investigate how differences in cortical morphology and white matter microstructure correlate with aptitudes for vocabulary learning, phonetic memory, and grammatical inferencing as measured by the first‐language neutral LLAMA test battery. We used ultra‐high field (7T) magnetic resonance imaging to estimate the cortical thickness and surface area from sub‐millimeter resolved image volumes. Further, diffusion kurtosis imaging was used to map diffusion properties related to the tissue microstructure from known language‐related white matter tracts. We found a correlation between cortical surface area in the left posterior‐inferior precuneus and vocabulary learning aptitude, possibly indicating a greater predisposition for storing word‐figure associations. Moreover, we report negative correlations between scores for phonetic memory and axial kurtosis in left arcuate fasciculus as well as mean kurtosis, axial kurtosis, and radial kurtosis of the left superior longitudinal fasciculus III, which are tracts connecting cortical areas important for phonological working memory.

Rapid microstructural plasticity in the cortical semantic network following a short language learning session

Despite the clear importance of language in our life, our vital ability to quickly and effectively learn new words and meanings is neurobiologically poorly understood. Conventional knowledge maintains that language learning—especially in adulthood—is slow and laborious. Furthermore, its structural basis remains unclear. Even though behavioural manifestations of learning are evident near instantly, previous neuroimaging work across a range of semantic categories has largely studied neural changes associated with months or years of practice. Here, we address rapid neuroanatomical plasticity accompanying new lexicon acquisition, specifically focussing on the learning of action-related language, which has been linked to the brain’s motor systems. Our results show that it is possible to measure and to externally modulate (using transcranial magnetic stimulation (TMS) of motor cortex) cortical microanatomic reorganisation after mere minutes of new word learning. Learning-induced microstructural changes, as measured by diffusion kurtosis imaging (DKI) and machine learning-based analysis, were evident in prefrontal, temporal, and parietal neocortical sites, likely reflecting integrative lexico-semantic processing and formation of new memory circuits immediately during the learning tasks. These results suggest a structural basis for the rapid neocortical word encoding mechanism and reveal the causally interactive relationship of modal and associative brain regions in supporting learning and word acquisition.

This combined neuroimaging and brain stimulation study reveals rapid and distributed microstructural plasticity after a single immersive language learning session, demonstrating the causal relevance of the motor cortex in encoding the meaning of novel action words.

The association between White matter microstructure alterations detected by Diffusional kurtosis imaging in Neural circuit and post-stroke depression

AIM

In order to study the mechanism of post-stroke depression (PSD), we used diffusion kurtosis imaging (DKI) to describe the changes in white matter (WM) microstructure in PSD patients, to investigate the association between WM damage in limbic-cortical-striatal-pallidal-thalamic (LCSPT) circuit and PSD, and the utility of DKI in the diagnosis of PSD.

METHODS

Fifty-eight participants were divided into different groups: control group (n=20), stroke patients without depression (Non-PSD, n=21) and PSD group (n=17). All were taken DKI scans. The WM of bilateral superior frontal gyrus, middle frontal gyrus, inferior frontal gyrus, temporal lobe, parietal lobe, occipital lobe, the anterior and posterior limb of internal capsule, the genu and splenium of corpus callosum were selected as the regions of interest (ROI) and selected mean kurtosis (MK), radial kurtosis (RK), axial kurtosis (AK) as the DKI parameters.

RESULTS

Compared with control and Non-PSD, MK of PSD group in bilateral superior frontal gyrus, middle frontal gyrus, temporal lobe and the genu of corpus callosum were decreased significantly, as well as the RK in left superior frontal gyrus, bilateral middle frontal gyrus and temporal lobe. But there was no significant difference in AK. Besides, the decrease in MK and RK in frontal and temporal lobe was negatively associated with the severity of PSD.

CONCLUSION

Our research indicated that the damage to WM microstructure in the frontal lobe, temporal lobe and the genu of corpus callosum may be related toPSD. DKI explores the microstructural changes of WM in PSD patients and may be an auxiliary diagnostic method for PSD.

Non-local means based Rician noise filtering for diffusion tensor and kurtosis imaging in human brain and spinal cord

BACKGROUND

To investigate the effect of using a Rician nonlocal means (NLM) filter on quantification of diffusion tensor (DT)- and diffusion kurtosis (DK)-derived metrics in various anatomical regions of the human brain and the spinal cord, when combined with a constrained linear least squares (CLLS) approach.

METHODS

Prospective brain data from 9 healthy subjects and retrospective spinal cord data from 5 healthy subjects from a 3 T MRI scanner were included in the study. Prior to tensor estimation, registered diffusion weighted images were denoised by an optimized blockwise NLM filter with CLLS. Mean kurtosis (MK), radial kurtosis (RK), axial kurtosis (AK), mean diffusivity (MD), radial diffusivity (RD), axial diffusivity (AD) and fractional anisotropy (FA), were determined in anatomical structures of the brain and the spinal cord. DTI and DKI metrics, signal-to-noise ratio (SNR) and Chi-square values were quantified in distinct anatomical regions for all subjects, with and without Rician denoising.

RESULTS

The averaged SNR significantly increased with Rician denoising by a factor of 2 while the averaged Chi-square values significantly decreased up to 61% in the brain and up to 43% in the spinal cord after Rician NLM filtering. In the brain, the mean MK varied from 0.70 (putamen) to 1.27 (internal capsule) while AK and RK varied from 0.58 (corpus callosum) to 0.92 (cingulum) and from 0.70 (putamen) to 1.98 (corpus callosum), respectively. In the spinal cord, FA varied from 0.78 in lateral column to 0.81 in dorsal column while MD varied from 0.91 × 10^-3 mm²/s (lateral) to 0.93 × 10^-3 mm²/s (dorsal). RD varied from 0.34 × 10^-3 mm²/s (dorsal) to 0.38 × 10^-3 mm²/s (lateral) and AD varied from 1.96 × 10^-3 mm²/s (lateral) to 2.11 × 10^-3 mm²/s (dorsal).

CONCLUSIONS

Our results show a Rician denoising NLM filter incorporated with CLLS significantly increases SNR and reduces estimation errors of DT- and KT-derived metrics, providing the reliable metrics estimation with adequate SNR levels.

Diffusion Kurtosis Imaging of Microstructural Changes in Gray Matter Nucleus in Parkinson Disease

Objective: To explore the microstructural damage of extrapyramidal system gray matter nuclei in Parkinson disease (PD) using diffusion kurtosis imaging (DKI). Materials and Methods: We enrolled 35 clinically confirmed PD patients and 23 healthy volunteers. All patients underwent MR examination with conventional MRI scan sequences and an additional DKI sequence. We subsequently reconstructed the DKI raw images and analyzed the data. A radiologist in our hospital collected the Mini-Mental State Examination (MMSE) score of all subjects. Results: In the PD group, the mean kurtosis and axial kurtosis level decreased in the red nucleus (RN) and thalamus; the radial kurtosis increased in the substantia nigra (SN) and globus pallidus (GP). Fractional anisotropy decreased in the putamen. The largest area under the ROC curve of mean diffusion in GP was 0.811. Most kurtosis parameters demonstrated a positive correlation with the MMSE score, while several diffusion parameters showed a negative correlation with the same. Conclusion: DKI can qualitatively distinguish PD from healthy controls; furthermore, DKI-derived parameters can quantitatively evaluate the modifications of microstructures in extrapyramidal system gray matter nucleus in PD.

A quick test of cognitive speed can predict development of dementia in Parkinson's disease

Parkinson’s disease (PD) patients frequently develop cognitive impairment. There is a need for brief clinical assessments identifying PD patients at high risk of progressing to dementia. In this study, we look into predicting dementia in PD and underlying structural and functional correlates to cognitive decline in PD. We included 175 patients with PD, 30 with PD dementia, 51 neurologically healthy controls and 121 patients with Alzheimer’s disease (AD) from Skane University Hospital, BIOFINDER cohorts. All underwent cognitive tests, including MMSE, 10-word list delayed recall (ADAS-cog), A Quick Test of cognitive speed (AQT), Letter S fluency, Clock Drawing Test (CDT) and pentagon copying. In non-demented patients with PD, abnormal AQT and CDT results predicted an increased risk of subsequent development of dementia (hazard ratio 2.2 for both). When comparing the cognitive profile between PD and AD, decreased performance on AQT, which measures attention and processing speed, was more typical in PD. Lastly, we investigated the underlying structural and functional correlates for the PD-specific test AQT with magnetic resonance imaging. In PD patients, decreased performance on AQT was associated with i) cortical thinning in temporoparietal regions, ii) changes in diffusion MRI, especially in the cingulum tract, and iii) decreased functional connectivity in posterior brain networks.

Detecting normal pediatric brain development with diffusional kurtosis imaging

PURPOSE

To characterise the pattern of change of diffusional kurtosis imaging (DKI) parameters (including kurtosis and diffusion parameters) in both white matter and gray matter in normal brain development with a large sample of subjects from term-born neonates to 14-years old children.

METHODS

Two hundred and eighteen normal children (136 male, 82 female) underwent conventional magnetic resonance imaging and DKI. Regions of interest (ROIs) were placed in 7 white matter areas and 4 gray matter areas. Then the DKI-derived parameters were automatically calculated, including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (Da), radial diffusivity (Dr), mean kurtosis (MK), axial kurtosis (Ka) and radial kurtosis (Kr). The correlation between the DKI parameters and ages were analyzed using nonlinear fit, and the rate of parameter change was computed compared to the baseline value of the neonates.

RESULTS

For all ROIs in the white matter and gray matter, the FA, MK, Kr, Ka values increased with age, while the MD and Dr values decreased with age. The correlations were good to excellent, which changed rapidly within the first 2 years and relatively slowly after 2 years. The Da values in peripheral white matters and some gray matter structures (caudate nucleus and putamen) decreased with age. The amplitude of kurtosis parameters variation was greater than that of the diffusion parameters in both white matter and gray matter.

CONCLUSIONS

The DKI parameters correlated well with age, and kurtosis parameters showed a potential advantage in detecting the normal brain development of children.

Microstructural white matter alterations associated to neurocognitive deficits in childhood leukemia survivors treated with cranial radiotherapy - a diffusional kurtosis study

Background: Cranial radiotherapy (CRT) is a known risk factor for neurocognitive impairment in survivors of childhood acute lymphoblastic leukemia (ALL). Diffusion tensor imaging (DTI) and diffusional kurtosis imaging (DKI) are MRI techniques that quantify microstructural changes in brain white matter (WM) and DKI is regarded as the more sensitive of them. Our aim was to more thoroughly understand the nature of cognitive deficits after cranial radiotherapy (CRT) in adulthood after childhood ALL. Material and methods: Thirty-eight (21 women) ALL survivors, median age 38 (27-46) years, were investigated at median 34 years after diagnosis. All had been treated with a CRT dose of 24 Gy and with 11 years of complete hormone supplementation. DTI and DKI parameters were determined and neurocognitive tests were performed in ALL survivors and 29 matched controls. Results: ALL survivors scored lower than controls in neurocognitive tests of vocabulary, memory, learning capacity, spatial ability, executive functions, and attention (p < .001). The survivors had altered DTI parameters in the fornix, uncinate fasciculus, and ventral cingulum (all p < .05) and altered DKI parameters in the fornix, uncinate fasciculus, and dorsal and ventral cingulum (p < .05). Altered DTI parameters in the fornix were associated with impaired episodic verbal memory (r = -0.40, p < .04). The left and right uncinate fasciculus (r = 0.6, p < .001), (r = -0.5, p < .02) as well as the right ventral cingulum (r = 0.5, p < .007) were associated with impaired episodic visual memory. Altered DKI parameters in the fornix, right uncinate fasciculus (r = 0.3, r = 0.05, p = .02), and ventral cingulum (r = 0.3, p = .02) were associated with impaired results of episodic visual memory. Conclusion: ALL survivors with cognitive deficits demonstrated microstructural damage in several WM tracts that were more extensive with DKI as compared to DTI; this might be a marker of radiation and chemotherapy neurotoxicity underlying cognitive dysfunction.

Development of anisotropic phantoms using wood and fiber materials for diffusion tensor imaging and diffusion kurtosis imaging

Objective

Several studies have demonstrated that anisotropic phantoms can be utilized for diffusion magnetic resonance imaging. The purpose of our study was to examine whether wood is suitable as an anisotropic phantom material from the viewpoints of affordability and availability. In the current study, wood was used for restricted diffusion, and fibers were used for hindered diffusion.

Materials and methods

Wood and fiber phantoms were made. Diffusion kurtosis images were acquired with three magnetic resonance scanners. Fractional anisotropy, radial diffusivity, axial diffusivity, radial kurtosis and axial kurtosis values were measured. The wood phantom was imaged, and its durability was confirmed. The phantoms were imaged in varying orientations within the magnetic field. The wood was observed using an optical microscope.

Results

Ten kinds of wood and the fiber had a diffusion metrics. The wood diffusion metrics suggested low variation over a period of 9 months. Changing the orientation of the phantoms within the magnetic field resulted in changes in diffusion metrics. Observation of wood vessels and fibers was conducted.

Discussion

Wood and fibers have anisotropy and are promising as phantom materials. The development of anisotropic phantoms that anyone can use is useful for diffusion magnetic resonance imaging research and clinical applications.

Altered white matter microstructure in patients with post-stroke depression detected by diffusion kurtosis imaging

The aim of our study is to determine the pathological changes of white matter microstructure in patients with early post-stroke depression (PSD), and to investigate the association between white matter integrity examined by diffusion kurtosis imaging (DKI) and early PSD. Thirty-eight patients with acute cerebral infarction were selected, including 17 patients with depression (PSD group), and 21 patients without depression (N-PSD group). In addition, 20 normal healthy controls (NORM group) were selected. All were taken DKI scans. The white matter of the frontal lobe, temporal lobe, parietal lobe, occipital lobe, anterior limb of internal capsule, and posterior limb of internal capsule, in addition to the genu of corpus callosum and splenium of corpus callosum was selected as a region of interest (ROI). Selected parameters include fractional anisotropy (FA) and mean kurtosis (MK). Compared with N-PSD group and NORM group, FA value of the left frontal lobe and MK value of the bilateral frontal lobe, bilateral temporal lobe, and genu of corpus callosum in PSD group were decreased (P < 0.05). Our results indicated that the early PSD patients had white matter microstructure abnormalities in the frontal lobe, temporal lobe, and genu of corpus callosum. DKI provides a comprehensive brain imaging reference for detecting early microstructural damage of white matter in PSD patients, which can be used as an imaging biomarker to detect early PSD and its progression potentially.

Age-related microstructural and physiological changes in normal brain measured by MRI γ-metrics derived from anomalous diffusion signal representation

Nowadays, increasing longevity associated with declining cerebral nervous system functions, suggests the need for continued development of new imaging contrast mechanisms to support the differential diagnosis of age-related decline. In our previous papers, we developed a new imaging contrast metrics derived from anomalous diffusion signal representation and obtained from diffusion-weighted (DW) data collected by varying diffusion gradient strengths. Recently, we highlighted that the new metrics, named γ-metrics, depended on the local inhomogeneity due to differences in magnetic susceptibility between tissues and diffusion compartments in young healthy subjects, thus providing information about myelin orientation and iron content within cerebral regions. The major structural modifications occurring in brain aging are myelinated fibers damage in nerve fibers and iron accumulation in gray matter nuclei. Therefore, we investigated the potential of γ-metrics in relation to other conventional diffusion metrics such as DTI, DKI and NODDI in detecting age-related structural changes in white matter (WM) and subcortical gray matter (scGM). DW-images were acquired in 32 healthy subjects, adults and elderly (age range 20-77 years) using 3.0T and 12 b-values up to 5000 s/mm². Association between diffusion metrics and subjects' age was assessed using linear regression. A decline in mean γ (Mγ) in the scGM and a complementary increase in radial γ (γ_⊥) in frontal WM, genu of corpus callosum and anterior corona radiata with advancing age were found. We suggested that the increase in γ⊥ might reflect declined myelin density, and Mγ decrease might mirror iron accumulation. An increase in D_// and a decrease in the orientation dispersion index (ODI) were associated with axonal loss in the pyramidal tracts, while their inverted trends within the thalamus were thought to be linked to reduced architectural complexity of nerve fibers. γ-metrics together with conventional diffusion-metrics can more comprehensively characterize the complex mechanisms underlining age-related changes than conventional diffusion techniques alone.

DIFFUSION-KURTOSIS IMAGING IN ASSESMENT OF BRAIN MICROSTRUCTURE. HEALTHY VOLUNTEERS MEASURMENTS

Aim:discover quantitative and qualitative variance of diffusion parameters in white and gray matter of healthyvolunteers brain. Discover correlation between diffusion and kurtosis parameters, find out if there is correlation between the parameters and aging microstructural changes.Materials and methods.14 healthy volunteers were investigated (9 men, 5 women; age from 21 to 55 years, mean 34). The volunteers were classified into two groups by age: 7 subjects who younger 35 (6 men and 1 woman, mean age 25) and 7 subjects who older 35 years (3 men and 4 women, mean age 44). We used 3.0 Tesla MRI (3.0T SignaHDxt, General Electric, USA) with 8 channel head coil, gradient strength 50 mT/m, slew rate 150 T/m/s. Diffusion imaging was based on echo planar “spin echo” sequence (SE EPI), TR = 10000 ms, TEmin = 102 ms, FOV = 240 mm, voxel size 3 × 3 × 3 mm3, 60 non-coplanar diffusion directions and three b-values: 0, 1000, 2500 s/mm2. Acquisition time of diffusion kurtosis imaging was 22 minutes. We excluded extracerebral areas on diffusion and kurtosis parametric maps using semi-automatic approach. After that, brain images were transformed to MNI152 space using affine method. Masks of 9 anatomical structures were applied to the transformed images. Diffusion and kurtosis values were measured in these structures.Results.Fractional anisotropy (FA) changed from 0.06 in lateral occipital cortex to 0.25 in cerebral white matter, kurtosis anisotropy (KA) changed from 0.03 to 0.14 in the same cerebral structures. Axial (AK), radial (RK) and mean kurtosis (MK) were minimal in superior frontal gyrus and maximal in cerebral white matter. AK changed from 0.55 to 0.72, RK changed from 0.62 to 1.05, MK from 0.59 to 0.88. Axial(AxEAD) and radial extra axonal water diffusion (RadEAD) were minimal in putamen and maximal in superior frontal gyrus. AxEAD was changing from 1.38 • 10–3 to 2.57 • 10–3, RadEAD from 1.03 • 10–3 to 2.34 • 10–3. Axonal water fraction (AWF) had minimal value 0,18 in superior frontal gyrus and maximal value 0.29 in cerebral white matter. Tortuosity (TORT) changed from 1.06 in lateral occipital cortex to 1.43 in cerebral white matter. There was significant difference between age groups in AWF, RK, RadEAD in putamen and in KA in superior temporal gyrus. Maximal correlation with age was in MK in superior temporal gyrus, anterior division. It was equal to 0.562.Conclusions:Diffusion kurtosis imaging is highly sensitive method of brain tissue microstructure assessment, which detects age-related changes.

Value of diffusion kurtosis imaging in assessing low-grade gliomas

BACKGROUND

Diffusion kurtosis imaging (DKI) measures have been shown to provide increased sensitivity relative to diffusion tensor imaging (DTI) in detecting pathologies.

PURPOSE

To compare the sensitivity of DKI-derived kurtosis and diffusion maps for assessment of low-grade gliomas (LGG).

STUDY TYPE

Prospective study.

POPULATION

In all, 19 LGG patients and 26 healthy control subjects were recruited.

FIELD STRENGTH/SEQUENCE

Echo-planar-imaging diffusion-weighted MR images (b-values = 0, 1000, and 2000 with 30 diffusion gradient directions) were acquired on a 3T scanner.

ASSESSMENT

Maps for mean, axial, and radial diffusivity (MD, AD, and RD) and kurtosis (MK, AK, and RK), and fractional anisotropy (FA) were evaluated in the tumor, perilesional white matter, and contralateral normal-appearing white matter regions.

STATISTICAL TESTING

General linear models (GLM), Cohen's d for effect size estimates, false discovery rate (FDR) for multiple corrections, Cochran Q-test.

RESULTS

Pairwise differences were observed for all diffusion and kurtosis measures between the studied regions (FDR P < 0.001), except an FA map that failed to show significant differences between the lesion and perilesional white matter (FDR P = 0.373). Effect size analysis showed that kurtosis metrics were found to be 18.8% (RK, P = 0.144) to 29.1% (AK, P < 0.05) more sensitive in discriminating perilesional regions from the lesion than corresponding diffusion metrics, whereas AK provided a 25.0% (P < 0.05) increase in sensitivity in discriminating perilesional and contralateral white matter. RK was found to be the most sensitive to contralateral white matter differences between low-grade gliomas and controls, with MK and RK providing a significantly greater sensitivity of 587.2% (P < 0.001) and 320.7% (P < 0.001) than MD and RD, respectively.

DATA CONCLUSION

Kurtosis maps showed increased sensitivity, as compared to counterpart diffusion maps, for evaluation of microstructural changes in gliomas with a 3-6-fold increment in assessing changes in contralateral white matter.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;48:1551-1558.

Alteration of putaminal fractional anisotropy in Parkinson's disease: a longitudinal diffusion kurtosis imaging study

Purpose

In Parkinson’s disease (PD), pathological microstructural changes occur that may be detected using diffusion magnetic resonance imaging (dMRI). However, there are few longitudinal studies that explore the effect of disease progression on diffusion indices.

Methods

We prospectively included 76 patients with PD and 38 healthy controls (HC), all of whom underwent diffusion kurtosis imaging (DKI) as part of the prospective Swedish BioFINDER study at baseline and 2 years later. Annualized rates of change in DKI parameters, including fractional anisotropy (FA), mean diffusivity (MD), and mean kurtosis (MK), were estimated in the gray matter (GM) by placing regions of interest (ROIs) in the basal ganglia and the thalamus, and in the white matter (WM) by tract-based spatial statistics (TBSS) analysis.

Results

When adjusting for potential confounding factors (age, gender, baseline-follow-up interval, and software upgrade of MRI scanner), only a decrease in FA in the putamen of PD patients (β = − 0.248, P < .01) over 2 years was significantly different from the changes observed in HC over the same time period. This 2-year decrease in FA in the putamen in PD correlated with higher l-dopa equivalent dose at baseline (Spearman’s rho = .399, P < .0001).

Conclusion

The study indicates that in PD microstructural changes in the putamen occur selectively over a 2-year period and can be detected with DKI.

Electronic supplementary material

The online version of this article (10.1007/s00234-017-1971-3) contains supplementary material, which is available to authorized users.

Comparison of cumulant expansion and q-space imaging estimates for diffusional kurtosis in brain

PURPOSE

To compare estimates for the diffusional kurtosis in brain as obtained from a cumulant expansion (CE) of the diffusion MRI (dMRI) signal and from q-space (QS) imaging.

THEORY AND METHODS

For the CE estimates of the kurtosis, the CE was truncated to quadratic order in the b-value and fit to the dMRI signal for b-values from 0 up to 2000s/mm². For the QS estimates, b-values ranging from 0 up to 10,000s/mm² were used to determine the diffusion displacement probability density function (dPDF) via Stejskal's formula. The kurtosis was then calculated directly from the second and fourth order moments of the dPDF. These two approximations were studied for in vivo human data obtained on a 3T MRI scanner using three orthogonal diffusion encoding directions.

RESULTS

The whole brain mean values for the CE and QS kurtosis estimates differed by 16% or less in each of the considered diffusion encoding directions, and the Pearson correlation coefficients all exceeded 0.85. Nonetheless, there were large discrepancies in many voxels, particularly those with either very high or very low kurtoses relative to the mean values.

CONCLUSION

Estimates of the diffusional kurtosis in brain obtained using CE and QS approximations are strongly correlated, suggesting that they encode similar information. However, for the choice of b-values employed here, there may be substantial differences, depending on the properties of the diffusion microenvironment in each voxel.

No differences in brain microstructure between young KIBRA-C carriers and non-carriers

KIBRA rs17070145 polymorphism is associated with variations in memory function and the microstructure of related brain areas. Diffusion kurtosis imaging (DKI) as an extension of diffusion tensor imaging that can provide more information about changes in microstructure, based on the idea that water diffusion in biological tissues is heterogeneous due to structural hindrance and restriction. We used DKI to explore the relationship between KIBRA gene polymorphism and brain microstructure in young adults. We recruited 100 healthy young volunteers, including 53 TT carriers and 47 C allele carriers. No differences were detected between the TT homozygotes and C-allele carriers for any diffusion and kurtosis parameter. These results indicate KIBRA rs17070145 polymorphism likely has little or no effect on brain microstructure in young adults.

NODDI-DTI: Estimating Neurite Orientation and Dispersion Parameters from a Diffusion Tensor in Healthy White Matter

The NODDI-DTI signal model is a modification of the NODDI signal model that formally allows interpretation of standard single-shell DTI data in terms of biophysical parameters in healthy human white matter (WM). The NODDI-DTI signal model contains no CSF compartment, restricting application to voxels without CSF partial-volume contamination. This modification allowed derivation of analytical relations between parameters representing axon density and dispersion, and DTI invariants (MD and FA) from the NODDI-DTI signal model. These relations formally allow extraction of biophysical parameters from DTI data. NODDI-DTI parameters were estimated by applying the proposed analytical relations to DTI parameters estimated from the first shell of data, and compared to parameters estimated by fitting the NODDI-DTI model to both shells of data (reference dataset) in the WM of 14 in vivo diffusion datasets recorded with two different protocols, and in simulated data. The first two datasets were also fit to the NODDI-DTI model using only the first shell (as for DTI) of data. NODDI-DTI parameters estimated from DTI, and NODDI-DTI parameters estimated by fitting the model to the first shell of data gave similar errors compared to two-shell NODDI-DTI estimates. The simulations showed the NODDI-DTI method to be more noise-robust than the two-shell fitting procedure. The NODDI-DTI method gave unphysical parameter estimates in a small percentage of voxels, reflecting voxelwise DTI estimation error or NODDI-DTI model invalidity. In the course of evaluating the NODDI-DTI model, it was found that diffusional kurtosis strongly biased DTI-based MD values, and so, making assumptions based on healthy WM, a novel heuristic correction requiring only DTI data was derived and used to mitigate this bias. Since validations were only performed on healthy WM, application to grey matter or pathological WM would require further validation. Our results demonstrate NODDI-DTI to be a promising model and technique to interpret restricted datasets acquired for DTI analysis in healthy white matter with greater biophysical specificity, though its limitations must be borne in mind.

Structural plasticity of the ventral stream and aphasia recovery

Restrengthening of the residual language network is likely to be crucial for speech recovery in poststroke aphasia. Eight participants with chronic aphasia received intensive speech therapy for 3 weeks, with standardized naming tests and brain magnetic resonance imaging before and after therapy. Kurtosis-based diffusion tensor tractography was used to measure mean kurtosis (MK) along a segment of the inferior longitudinal fasciculus (ILF). Therapy-related reduction in the number of semantic but not phonemic errors was associated with strengthening (renormalization) of ILF MK (r = -0.90, p < 0.05 corrected), suggesting that speech recovery is related to structural plasticity of language-specific components of the residual language network. Ann Neurol 2017;82:147-151.

Whole brain analyses of age-related microstructural changes quantified using different diffusional magnetic resonance imaging methods

PURPOSE

The new diffusional magnetic resonance imaging (dMRI) techniques, diffusional kurtosis imaging (DKI) and neurite orientation dispersion and density imaging (NODDI) have been developed to clarify the microstructural changes. To our knowledge, however, there is little information on the similarities and differences of these metrics evaluated by the image-by-image paired t test.

MATERIALS AND METHODS

Twenty-three healthy subjects underwent dMRI. We estimated the relationships of these metrics evaluated by the image-by-image paired t-test and compared aging effects on each metric.

RESULTS

We found that fractional anisotropy (FA), mean kurtosis (MK) derived from DKI and neurite density index (NDI) values derived from NODDI correlated with each other positively, and mean diffusivity (MD) and orientation dispersion index (ODI) values from NODDI correlated negatively with the FA value. There were no significant relationships of age with FA or MD values, while MK, ODI and NDI values showed significant correlations with age.

CONCLUSION

These results may indicate not only the similar tendency among the metrics, but also the higher sensitivity of NODDI and DKI to the changes in microstructural tissue organization with advancing age. These techniques could shed light on both normal and degenerated brain changes.

Evaluating kurtosis-based diffusion MRI tissue models for white matter with fiber ball imaging

In order to quantify well-defined microstructural properties of brain tissue from diffusion MRI (dMRI) data, tissue models are typically employed that relate biological features, such as cell morphology and cell membrane permeability, to the diffusion dynamics. A variety of such models have been proposed for white matter, and their validation is a topic of active interest. In this paper, three different tissue models are tested by comparing their predictions for a specific microstructural parameter to a value measured independently with a recently proposed dMRI method known as fiber ball imaging (FBI). The three tissue models are all constructed with the diffusion and kurtosis tensors, and they are hence compatible with diffusional kurtosis imaging. Nevertheless, the models differ significantly in their details and predictions. For voxels with fractional anisotropies (FAs) exceeding 0.5, all three are reasonably consistent with FBI. However, for lower FA values, one of these, called the white matter tract integrity (WMTI) model, is found to be in much better accord with FBI than the other two, suggesting that the WMTI model has a broader range of applicability.

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.

Parameters of diffusional kurtosis imaging for the diagnosis of acute cerebral infarction in different brain regions

Diffusional kurtosis imaging (DKI) is a new type diffusion-weighted sequence which measures the non-Gaussianity of water diffusion. The present study aimed to investigate whether the parameters of DKI could distinguish between differences in water molecule diffusion in various brain regions under the conditions of acute infarction and to identify the optimal DKI parameter for locating ischemic lesions in each brain region. A total of 28 patients with acute ischemic stroke in different brain regions were recruited for the present study. The relative values of DKI parameters were selected as major assessment indices, and the homogeneity of background image and contrast of adjacent structures were used as minor assessment indices. According to the brain region involved in three DKI parametric maps, including mean kurtosis (MK), axial kurtosis (Ka) and radial kurtosis (Kr), 112 groups of regions of interest were outlined in the following regions: Corpus callosum (n=17); corona radiata (n=26); thalamus (n=21); subcortical white matter (n=24); and cerebral cortex (n=24). For ischemic lesions in the corpus callosum and corona radiata, significant increases in relative Ka were detected, as compared with the other parameters (P<0.05). For ischemic lesions in the thalamus, subcortical white matter and cerebral cortices, an increase in the three parameters was detected, however this difference was not significant. Minor assessment indices demonstrated that Ka lacked tissue contrast and the background of Kr was heterogeneous; thus, MK was the superior assessment parameter for ischemic lesions in these regions. In conclusion, Ka is better suited for the diagnosis of acute ischemic lesions in highly anisotropic brain regions, such as the corpus callosum and corona radiate. MK may be appropriate for the lesions in low anisotropic or isotropic brain regions, such as the thalamus, subcortical white matter and cerebral cortices.

Evaluation of mean diffusion and kurtosis MRI mismatch in subacute ischemic stroke: Comparison with NIHSS score

Neurological deterioration (ND) is a devastating complication following ischemic stroke. This study aimed to identify the differences in lesion characteristics in subacute ischemic stroke patients with and without ND using diffusional kurtosis imaging (DKI), as well as to confirm the responsible lesions that may lead to ND, as assessed by the National Institutes of Health Stroke Scale (NIHSS) score. Seventy-nine patients with subacute cerebral infarction were allocated to the ND (-) and ND (+) groups according to the NIHSS score and lesion number. The mean diffusion (MD) lesions were significantly larger than the mean kurtosis (MK) deficits in the ND (+) group (P<0.05); however, there was no significant difference in the ND (-) group (P>0.05). The MD and MK in the lesion recovered to normal levels over time; however, the recovery trends in the ND (+) group were substantially slower than the ND (-) group. The differences between the two groups were only significant regarding the MK (p<0.05). Furthermore, multiple infarction lesions exhibited good consistency in the ND (-) group, but were non-homogeneous in the ND (+) group. To the best of our knowledge, this is the first study to demonstrate that a significant MD/MK mismatch and heterogeneity of multiple ischemic lesions on MK in subacute ischemic stroke may represent a new expansion of an ischemic lesion or acute reinfarction, which is closely related to ND.

Q-space trajectory imaging for multidimensional diffusion MRI of the human brain

This work describes a new diffusion MR framework for imaging and modeling of microstructure that we call q-space trajectory imaging (QTI). The QTI framework consists of two parts: encoding and modeling. First we propose q-space trajectory encoding, which uses time-varying gradients to probe a trajectory in q-space, in contrast to traditional pulsed field gradient sequences that attempt to probe a point in q-space. Then we propose a microstructure model, the diffusion tensor distribution (DTD) model, which takes advantage of additional information provided by QTI to estimate a distributional model over diffusion tensors. We show that the QTI framework enables microstructure modeling that is not possible with the traditional pulsed gradient encoding as introduced by Stejskal and Tanner. In our analysis of QTI, we find that the well-known scalar b-value naturally extends to a tensor-valued entity, i.e., a diffusion measurement tensor, which we call the b-tensor. We show that b-tensors of rank 2 or 3 enable estimation of the mean and covariance of the DTD model in terms of a second order tensor (the diffusion tensor) and a fourth order tensor. The QTI framework has been designed to improve discrimination of the sizes, shapes, and orientations of diffusion microenvironments within tissue. We derive rotationally invariant scalar quantities describing intuitive microstructural features including size, shape, and orientation coherence measures. To demonstrate the feasibility of QTI on a clinical scanner, we performed a small pilot study comparing a group of five healthy controls with five patients with schizophrenia. The parameter maps derived from QTI were compared between the groups, and 9 out of the 14 parameters investigated showed differences between groups. The ability to measure and model the distribution of diffusion tensors, rather than a quantity that has already been averaged within a voxel, has the potential to provide a powerful paradigm for the study of complex tissue architecture.

Alterations of Diffusion Kurtosis and Neurite Density Measures in Deep Grey Matter and White Matter in Parkinson's Disease

In Parkinson’s disease (PD), pathological microstructural changes occur and such changes might be detected using diffusion magnetic resonance imaging (dMRI). However, it is unclear whether dMRI improves PD diagnosis or helps differentiating between phenotypes, such as postural instability gait difficulty (PIGD) and tremor dominant (TD) PD. We included 105 patients with PD and 44 healthy controls (HC), all of whom underwent dMRI as part of the prospective Swedish BioFINDER study. Diffusion kurtosis imaging (DKI) and neurite density imaging (NDI) analyses were performed using regions of interest in the basal ganglia, the thalamus, the pons and the midbrain as well as tractography of selected white matter tracts. In the putamen, the PD group showed increased mean diffusivity (MD) (p = .003), decreased fractional anisotropy (FA) (p = .001) and decreased mean kurtosis (MK), compared to HC (p = .024). High MD and a low MK in the putamen were associated with more severe motor and cognitive symptomatology (p < .05). Also, patients with PIGD exhibited increased MD in the putamen compared to the TD patients (p = .009). In the thalamus, MD was increased (p = .001) and FA was decreased (p = .032) in PD compared to HC. Increased MD and decreased FA correlated negatively with motor speed and balance (p < .05). In the superior longitudinal fasciculus (SLF), MD (p = .019) and f_iso were increased in PD compared to HC (p = .03). These changes correlated negatively with motor speed (p < .002) and balance (p < .037). However, most of the observed changes in PD were also present in cases with either multiple system atrophy (n = 11) or progressive supranuclear palsy (n = 10). In conclusion, PD patients exhibit microstructural changes in the putamen, the thalamus, and the SLF, which are associated with worse disease severity. However, the dMRI changes are not sufficiently specific to improve the diagnostic work-up of PD. Longitudinal studies should evaluate whether dMRI measures can be used to track disease progression.

[A correlation between diffusion kurtosis imaging and the proliferative activity of brain glioma]

The aim of the study was to assess the capabilities of diffusion kurtosis imaging (DKI) in diagnosis of the glioma proliferative activity and to evaluate a relationship between the glioma proliferative activity index and diffusion parameters of the contralateral normal appearing white matter (CNAWM).

MATERIAL AND METHODS

The study included 47 patients with newly diagnosed brain gliomas (23 low grade, 13 grade III, and 11 grade IV gliomas). We determined a relationship between absolute and normalized parameters of the diffusion tensor (mean (MD), axial (AD), and radial (RD) diffusivities; fractional (FA) and relative (RA) anisotropies) and diffusion kurtosis (mean (MK), axial (AK), and radial (RK) kurtosis; kurtosis anisotropy (KA)) and the proliferative activity index in the most malignant glioma parts (p<0.05). We also established a relationship between the tensor and kurtosis parameters of CNAWM and the glioma proliferative activity index (p<0.05).

RESULTS

The correlation between all the absolute and normalized diffusion parameters and the glioma proliferative activity index, except absolute and normalized FA and RA values, was found to be statistically significant (p<0.05). Kurtosis (MK, AK, and RK) and anisotropy (KA, FA, RA) values increased, and diffusivity (MD, AD, RD) values decreased as the glioma proliferative activity index increased. A strong correlation between the proliferative activity index and absolute RK (r=0,71; p=0.000001) and normalized values of MK (r=0.8; p=0.000001), AK (r=0.71; p=0.000001), RK (r=0.81; p=0.000001), and RD (r=-0.71; p=0.000001) was found. A weak, but statistically significant correlation between the glioma proliferative activity index and diffusion values RK (r=-0.36; p=0.014), KA (r=-0.39; p=0.007), RD (r=0.35; p=0.017), FA (r=-0.42; p=0.003), and RA (r=-0.41; p=0.004) of CNAWM was found.

CONCLUSION

DKI has good capabilities to detect immunohistochemical changes in gliomas. DKI demonstrated a high sensitivity in detection of microstructural changes in the contralateral normal appearing white matter in patients with brain gliomas.

Assessment of severity of leukoaraiosis: a diffusional kurtosis imaging study

OBJECTIVE

The objective was to investigate the capabilities of diffusional kurtosis imaging (DKI) in detection of age-related white matter (WM) changes in elderly patients with leukoaraiosis.

MATERIAL AND METHODS

Fractional anisotropy (FA), kurtosis, and diffusion parameters in the frontal lobe and parietal lobe were compared between 14 patients at Fazekas scale 0 and 1, and 15 patients at Fazekas scale 2 and 3.

RESULTS

FA and DKI parameters were significantly altered in the ischemic lesions vs normal regions of WM in the severe patients.

CONCLUSION

DKI can provide sensitive imaging biomarkers for assessing the severity of leukoaraiosis in reference to Fazekas score.