Diffusional kurtosis time dependence and the water exchange rate for the multi-compartment Kärger model.

PURPOSE: To demonstrate an analytic formula giving the time dependence of the diffusional kurtosis for the Kärger model (KM) with an arbitrary number of exchanging compartments and its application in estimating the mean KM water exchange rate. THEORY AND METHODS: The general formula for the kurtosis is derived from a power series solution for the multi-compartment KM. A lower bound on the exchange rate is established from the observation that the kurtosis is always a logarithmically convex function of time. Both the kurtosis time dependence and the lower bound are illustrated with numerical calculations. The lower bound is also applied to previously published data for the time dependence of the kurtosis in both brain and tumors. RESULTS: The kurtosis for the multi-compartment KM is given by a sum in which each term is associated with an eigenvector of the exchange rate matrix. The lower bound is determined from the most negative value for the logarithmic derivative of the kurtosis with respect to time. In the cerebral cortex, the lower bound is found to vary from 15 to 76 s-1 , depending on the experimental details, while for the tumors considered, it varies from 2 to 4 s-1 . CONCLUSION: The time dependence of the kurtosis for the multi-compartment KM has a simple analytic solution that allows a lower bound for the mean KM water exchange rate to be determined directly from experiment. This may be useful in tissues with complex microstructure that is difficult to model explicitly.

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.

Language Recovery after Brain Injury: A Structural Network Control Theory Study.

Aphasia recovery after stroke depends on the condition of the remaining, extralesional brain network. Network control theory (NCT) provides a unique, quantitative approach to assess the interaction between brain networks. In this longitudinal, large-scale, whole-brain connectome study, we evaluated whether controllability measures of language-related regions are associated with treated aphasia recovery. Using probabilistic tractography and controlling for the effects of structural lesions, we reconstructed whole-brain diffusion tensor imaging (DTI) connectomes from 68 individuals (20 female, 48 male) with chronic poststroke aphasia who completed a three-week language therapy. Applying principles of NCT, we computed regional (1) average and (2) modal controllability, which decode the ability of a region to (1) spread control input through the brain network and (2) to facilitate brain state transitions. We tested the relationship between pretreatment controllability measures of 20 language-related left hemisphere regions and improvements in naming six months after language therapy using multiple linear regressions and a parsimonious elastic net regression model with cross-validation. Regional controllability of the inferior frontal gyrus (IFG) pars opercularis, pars orbitalis, and the anterior insula were associated with treatment outcomes independently of baseline aphasia severity, lesion volume, age, education, and network size. Modal controllability of the IFG pars opercularis was the strongest predictor of treated aphasia recovery with cross-validation and outperformed traditional graph theory, lesion load, and demographic measures. Regional NCT measures can reflect the status of the residual language network and its interaction with the remaining brain network, being able to predict language recovery after aphasia treatment.SIGNIFICANCE STATEMENT Predicting and understanding language recovery after brain injury remains a challenging, albeit a fundamental aspect of human neurology and neuroscience. In this study, we applied network control theory (NCT) to fully harness the concept of brain networks as dynamic systems and to evaluate their interaction. We studied 68 stroke survivors with aphasia who underwent imaging and longitudinal behavioral assessments coupled with language therapy. We found that the controllability of the inferior frontal regional network significantly predicted recovery in language production six months after treatment. Importantly, controllability outperformed traditional demographic, lesion, and graph-theoretical measures. Our findings shed light on the neurobiological basis of human language and can be translated into personalized rehabilitation approaches.

Higher Dose Noninvasive Transcutaneous Auricular Vagus Nerve Stimulation Increases Feeding Volumes and White Matter Microstructural Complexity in Open-Label Study of Infants Slated for Gastrostomy Tube.

OBJECTIVE: To determine whether transcutaneous auricular vagus nerve stimulation (taVNS) paired with twice daily bottle feeding increases the volume of oral feeds and white matter neuroplasticity in term-age-equivalent infants failing oral feeds and determined to need a gastrostomy tube. STUDY DESIGN: In this prospective, open-label study, 21 infants received taVNS paired with 2 bottle feeds for 2 - 3 weeks (2x). We compared 1) increase oral feeding volumes with 2x taVNS and previously reported once daily taVNS (1x) to determine a dose response, 2) number of infants who attained full oral feeding volumes, and 3) diffusional kurtosis imaging and magnetic resonance spectroscopy before and after treatment by paired t tests. RESULTS: All 2x taVNS treated infants significantly increased their feeding volumes compared with 10 days before treatment. Over 50% of 2x taVNS infants achieved full oral feeds but in a shorter time than 1x cohort (median 7 days [2x], 12.5 days [1x], P < .05). Infants attaining full oral feeds showed greater increase in radial kurtosis in the right corticospinal tract at the cerebellar peduncle and external capsule. Notably, 75% of infants of diabetic mothers failed full oral feeds, and their glutathione concentrations in the basal ganglia, a measure of central nervous system oxidative stress, were significantly associated with feeding outcome. CONCLUSIONS: In infants with feeding difficulty, increasing the number of daily taVNS-paired feeding sessions to twice-daily significantly accelerates response time but not the overall response rate of treatment. taVNS was associated with white matter motor tract plasticity in infants able to attain full oral feeds. TRIAL REGISTRATION: Clinicaltrials.gov (NCT04643808).

Greater Diffusion Restriction in White Matter in Preclinical Alzheimer Disease.

OBJECTIVE: The Alzheimer's continuum is biologically defined by beta-amyloid deposition, which at the earliest stages is superimposed upon white matter degeneration in aging. However, the extent to which these co-occurring changes is characterized is relatively underexplored. The goal of this study was to use diffusional kurtosis imaging (DKI) and biophysical modeling to detect and describe amyloid-related white matter changes in preclinical Alzheimer disease. METHODS: Cognitively unimpaired participants ages 45 to 85 years completed brain magnetic resonance imaging, amyloid positron emission tomography (florbetapir), neuropsychological testing, and other clinical measures at baseline in a cohort study. We tested whether beta-amyloid-negative (AB-) and -positive (AB+) participants differed on DKI-based conventional (ie, fractional anisotropy [FA], mean diffusivity [MD], mean kurtosis) and modeling (ie, axonal water fraction [AWF], extra-axonal radial diffusivity [De,⊥ ]) metrics, and whether these metrics were associated with other biomarkers. RESULTS: We found significantly greater diffusion restriction (higher FA/AWF, lower MD/De,⊥ ) in white matter in AB+ than AB- (partial η2 =0.08-0.19), more notably in the extra-axonal space within primarily late myelinating tracts. Diffusion metrics predicted amyloid status incrementally over age (area under the curve = 0.84) with modest yet selective associations, where AWF (a marker of axonal density) correlated with speed/executive functions and neurodegeneration, whereas De,⊥ (a marker of gliosis/myelin repair) correlated with amyloid deposition and white matter hyperintensity volume. INTERPRETATION: These results support prior evidence of a nonmonotonic change in diffusion behavior, where an early increase in diffusion restriction is hypothesized to reflect inflammation and myelin repair prior to an ensuing decrease in diffusion restriction, indicating glial and neuronal degeneration. ANN NEUROL 2022;91:864-877.

Comparison of two types of microscopic diffusion anisotropy in mouse brain.

Two distinct types of microscopic diffusion anisotropy (MA) are compared in brain for both normal control and transgenic (3xTg-AD) mice, which develop Alzheimer's disease pathology. The first type of MA is the commonly used microscopic fractional anisotropy (µFA), and the second is a new MA measure referred to as µFA'. These two MA parameters have different symmetry properties that are central to their physical interpretations. Specifically, µFA is invariant with respect to local rotations of compartmental diffusion tensors while µFA' is invariant with respect to global diffusion tensor deformations. A key distinction between µFA and µFA' is that µFA is affected by the same type of orientationally coherent diffusion anisotropy as the conventional fractional anisotropy (FA) while µFA' is not. Furthermore, µFA can be viewed as having independent contributions from FA and µFA', as is quantified by an equation relating all three anisotropies. The normal control and transgenic mice are studied at ages ranging from 2 to 15 months, with double diffusion encoding MRI being used to estimate µFA and µFA'. µFA and µFA' are nearly identical in low FA brain regions, but they show notable differences when FA is large. In particular, µFA and FA are found to be strongly correlated in the fimbria, but µFA' and FA are not. In addition, both µFA and µFA' are seen to increase with age in the corpus callosum and external capsule, and modest differences between normal control and transgenic mice are observed for µFA and µFA' in the corpus callosum and for µFA in the fimbria. The triad of FA, µFA, and µFA' is proposed as a useful combination of parameters for assessing diffusion anisotropy in brain.

High b-value diffusion tractography: Abnormal axonal network organization associated with medication-refractory epilepsy.

Diffusion magnetic resonance imaging (dMRI) tractography has played a critical role in characterizing patterns of aberrant brain network reorganization among patients with epilepsy. However, the accuracy of dMRI tractography is hampered by the complex biophysical properties of white matter tissue. High b-value diffusion imaging overcomes this limitation by better isolating axonal pathways. In this study, we introduce tractography derived from fiber ball imaging (FBI), a high b-value approach which excludes non-axonal signals, to identify atypical neuronal networks in patients with epilepsy. Specifically, we compared network properties obtained from multiple diffusion tractography approaches (diffusion tensor imaging, diffusion kurtosis imaging, FBI) in order to assess the pathophysiological relevance of network rearrangement in medication-responsive vs. medication-refractory adults with focal epilepsy. We show that drug-resistant epilepsy is associated with increased global network segregation detected by FBI-based tractography. We propose exploring FBI as a clinically feasible alternative to quantify topological changes that could be used to track disease progression and inform on clinical outcomes.

Impact of intra-axonal kurtosis on fiber orientation density functions estimated with fiber ball imaging.

PURPOSE: To determine the impact of an intra-axonal kurtosis on estimates of the fiber orientation density function (fODF) obtained with fiber ball imaging (FBI). THEORY AND METHODS: Standard FBI assumes Gaussian diffusion within individual axons and estimates the fODF by applying an inverse generalized Funk transform to diffusion MRI data for b-values of 4000 s/mm2 or higher. However, recent work based on numeric simulations shows that diffusion inside axons is non-Gaussian with an intra-axonal kurtosis of ∼ 0.4. Here, the theory underlying FBI is extended to incorporate an intra-axonal kurtosis. This is done to first order in the intra-axonal kurtosis without making assumptions about the details of the diffusion dynamics and to all orders for a specific model based on a gamma distribution of diffusivities. The first order approximation is used to assess the effect of an intra-axonal kurtosis on FBI estimates for the fODF and axonal water fraction. The gamma distribution model is used to test the validity of the approximation. RESULTS: The first order approximation indicates the estimated fODF is altered by a few percent for an intra-axonal kurtosis of 0.4 in comparison to predictions of standard FBI. If one neglects the intra-axonal kurtosis, the angular resolution of the point spread function for the fODF is changed by <1°, whereas the axonal water fraction is overestimated by ∼ 5%. The gamma distribution model shows that the first order approximation is accurate to within a few percent. CONCLUSION: The intra-axonal kurtosis has a small impact on fODFs estimated with FBI.

High fidelity fiber orientation density functions from fiber ball imaging.

The fiber orientation density function (fODF) in white matter is a primary physical quantity that can be estimated with diffusion MRI. It has often been employed for fiber tracking and microstructural modeling. Requirements for the construction of high fidelity fODFs, in the sense of having good angular resolution, adequate data to avoid sampling errors, and minimal noise artifacts, are described for fODFs calculated with fiber ball imaging. A criterion is formulated for the number of diffusion encoding directions needed to achieve a given angular resolution. The advantages of using large b-values (≥6000 s/mm2 ) are also discussed. For the direct comparison of different fODFs, a method is developed for defining a local frame of reference tied to each voxel's individual axonal structure. The Matusita anisotropy axonal is proposed as a scalar fODF measure for quantifying angular variability. Experimental results, obtained at 3 T from human volunteers, are used as illustrations.

Fiber ball white matter modeling in focal epilepsy.

Multicompartment diffusion magnetic resonance imaging (MRI) approaches are increasingly being applied to estimate intra-axonal and extra-axonal diffusion characteristics in the human brain. Fiber ball imaging (FBI) and its extension fiber ball white matter modeling (FBWM) are such recently described multicompartment approaches. However, these particular approaches have yet to be applied in clinical cohorts. The modeling of several diffusion parameters with interpretable biological meaning may offer the development of new, noninvasive biomarkers of pharmacoresistance in epilepsy. In the present study, we used FBI and FBWM to evaluate intra-axonal and extra-axonal diffusion properties of white matter tracts in patients with longstanding focal epilepsy. FBI/FBWM diffusion parameters were calculated along the length of 50 white matter tract bundles and statistically compared between patients with refractory epilepsy, nonrefractory epilepsy and controls. We report that patients with chronic epilepsy had a widespread distribution of extra-axonal diffusivity relative to controls, particularly in circumscribed regions along white matter tracts projecting to cerebral cortex from thalamic, striatal, brainstem, and peduncular regions. Patients with refractory epilepsy had significantly greater markers of extra-axonal diffusivity compared to those with nonrefractory epilepsy. The extra-axonal diffusivity alterations in patients with epilepsy observed in the present study could be markers of neuroinflammatory processes or a reflection of reduced axonal density, both of which have been histologically demonstrated in focal epilepsy. FBI is a clinically feasible MRI approach that provides the basis for more interpretive conclusions about the microstructural environment of the brain and may represent a unique biomarker of pharmacoresistance in epilepsy.

Optimized rectification of fiber orientation density function.

PURPOSE: To demonstrate an optimized rectification strategy for fiber orientation density functions (fODFs). THEORY AND METHODS: In white matter, fODFs can be estimated with diffusion MRI. However, because of signal noise, imaging artifacts and other factors, experimentally determined fODFs may take on unphysical negative values in some directions. Here, we show how to rectify such fODFs to eliminate all negative values while minimizing the mean square difference between the original and rectified fODFs. The method is demonstrated for a mathematical model and for fODFs estimated from experimental human data using both constrained spherical deconvolution and fiber ball imaging. Comparison with an alternative nonoptimized rectification approach is also provided. RESULTS: For the mathematical model, it is found that the optimized rectification procedure removes negative fODF values while at the same time reducing the mean square error. Relative to the alternative rectification approach, the optimized fODFs are substantially more accurate. For the experimental data, the optimized fODFs have a lower average fractional anisotropy axonal and often fewer small peaks than the original, unrectified fODFs. The calculation of optimized fODFs is straightforward where the main step is the finding of the root to an equation in one variable, as may be efficiently accomplished with the bisection method. CONCLUSION: Unphysical negative fODF values can be easily eliminated in a manner that minimizes the mean square difference between the original and rectified fODFs. Optimized fODF rectification may be useful in applications for which negative values are problematic.

The impact of edema and fiber crossing on diffusion MRI metrics assessed in an ex vivo nerve phantom: Multi-tensor model vs. diffusion orientation distribution function.

Diffusion tensor imaging (DTI) has been employed for over 2 decades to noninvasively quantify central nervous system diseases/injuries. However, DTI is an inadequate simplification of diffusion modeling in the presence of coexisting inflammation, edema and crossing nerve fibers. We employed a tissue phantom using fixed mouse trigeminal nerves coated with various amounts of agarose gel to mimic crossing fibers in the presence of vasogenic edema. Diffusivity measures derived by DTI and diffusion basis spectrum imaging (DBSI) were compared at increasing levels of simulated edema and degrees of fiber crossing. Furthermore, we assessed the ability of DBSI, diffusion kurtosis imaging (DKI), generalized q-sampling imaging (GQI), q-ball imaging (QBI) and neurite orientation dispersion and density imaging to resolve fiber crossing, in reference to the gold standard angles measured from structural images. DTI-computed diffusivities and fractional anisotropy were significantly confounded by gel-mimicked edema and crossing fibers. Conversely, DBSI calculated accurate diffusivities of individual fibers regardless of the extent of simulated edema and degrees of fiber crossing angles. Additionally, DBSI accurately and consistently estimated crossing angles in various conditions of gel-mimicked edema when compared with the gold standard (r2 = 0.92, P = 1.9 × 10-9 , bias = 3.9°). Small crossing angles and edema significantly impact the diffusion orientation distribution function, making DKI, GQI and QBI less accurate in detecting and estimating fiber crossing angles. Lastly, we used diffusion tensor ellipsoids to demonstrate that DBSI resolves the confounds of edema and crossing fibers in the peritumoral edema region from a patient with lung cancer metastasis, while DTI failed. In summary, DBSI is able to separate two crossing fibers and accurately recover their diffusivities in a complex environment characterized by increasing crossing angles and amounts of gel-mimicked edema. DBSI also indicated better angular resolution compared with DKI, QBI and GQI.

Brain Reserve in a Case of Cognitive Resilience to Severe Leukoaraiosis.

OBJECTIVE: Leukoaraiosis, or white matter rarefaction, is a common imaging finding in aging and is presumed to reflect vascular disease. When severe in presentation, potential congenital or acquired etiologies are investigated, prompting referral for neuropsychological evaluation in addition to neuroimaging. T2-weighted imaging is the most common magnetic resonance imaging (MRI) approach to identifying white matter disease. However, more advanced diffusion MRI techniques may provide additional insight into mechanisms that influence the abnormal T2 signal, especially when clinical presentations are discrepant with imaging findings. METHOD: We present a case of a 74-year-old woman with severe leukoaraoisis. She was examined by a neurologist, neuropsychologist, and rheumatologist, and completed conventional (T1, T2-FLAIR) MRI, diffusion tensor imaging (DTI), and advanced single-shell, high b-value diffusion MRI (i.e., fiber ball imaging [FBI]). RESULTS: The patient was found to have few neurological signs, no significant cognitive impairment, a negative workup for leukoencephalopathy, and a positive antibody for Sjogren's disease for which her degree of leukoaraiosis would be highly atypical. Tractography results indicate intact axonal architecture that was better resolved using FBI rather than DTI. CONCLUSIONS: This case illustrates exceptional cognitive resilience in the face of severe leukoaraiosis and the potential for advanced diffusion MRI to identify brain reserve.

Intra- and interhemispheric white matter tract associations with auditory spatial processing: Distinct normative and aging effects.

Declining auditory spatial processing is hypothesized to contribute to the difficulty older adults have detecting, locating, and selecting a talker from among others in noisy listening environments. Though auditory spatial processing has been associated with several cortical structures, little is known regarding the underlying white matter architecture or how age-related changes in white matter microstructure may affect it. The arcuate fasciculus is a target for understanding age-related differences in auditory spatial attention based on normative spatial attention findings in humans. Similarly, animal and human clinical studies suggest that the corpus callosum plays a role in the cross-hemispheric integration of auditory spatial information important for spatial localization and attention. The current investigation used diffusion imaging to examine the extent to which age-group differences in the identification of spatially cued speech were accounted for by individual differences in the white matter microstructure of the right arcuate fasciculus and the corpus callosum. Higher right arcuate and callosal fractional anisotropy (FA) predicted better segregation and identification of spatially cued speech across younger and older listeners. Further, individual differences in callosal microstructure mediated age-group differences in auditory spatial processing. Follow-up analyses suggested that callosal tracts connecting left and right pre-frontal and posterior parietal cortex are particularly important for auditory spatial processing. The results are consistent with previous work in animals and clinical human samples and provide a cortical mechanism to account for age-related deficits in auditory spatial processing. Further, the results suggest that both intrahemispheric and interhemispheric mechanisms are involved in auditory spatial processing.

Triple diffusion encoding MRI predicts intra-axonal and extra-axonal diffusion tensors in white matter.

PURPOSE: To demonstrate how triple diffusion encoding (TDE) MRI can be applied to separately estimate the intra-axonal and extra-axonal diffusion tensors in white matter (WM). METHODS: Using a TDE pulse sequence with an axially symmetric b-matrix, diffusion MRI data were acquired at 3T for 3 healthy adults with an axial b-value of 4000 s/mm2 , a radial b-value of 307 s/mm2 , and 64 diffusion encoding directions. This acquisition was then repeated with the radial b-value set to 0. A previously proposed theory was applied to these data in order to estimate the intra-axonal diffusivity and axonal water fraction for each WM voxel. Conventional single diffusion encoding data were also obtained with b-values of 1000 and 2000 s/mm2 , which provided additional information sufficient for determining both the intra-axonal and extra-axonal diffusion tensors. RESULTS: From the TDE data, the average intra-axonal diffusivity in WM was found to be 2.24 ± 0.18 µm2 /ms, and the average axonal water fraction was found to be 0.60 ± 0.11. From the 2 diffusion tensors, average WM values were estimated for several compartment-specific diffusion parameters. In particular, the extra-axonal mean diffusivity was 1.09 ± 0.19 µm2 /ms, the intra-axonal fractional anisotropy was 0.50 ± 0.14, and the extra-axonal fractional anisotropy was 0.23 ± 0.13. CONCLUSION: By using a simple TDE pulse sequence with an axially symmetric b-matrix, the diffusion tensors for the intra-axonal and extra-axonal spaces can be separately estimated in adult WM. This allows one to determine compartment-specific diffusion properties for these 2 water pools.

Diffusion MRI detects early brain microstructure abnormalities in 2-month-old 3×Tg-AD mice.

The 3×Tg-AD mouse is one of the most studied animal models of Alzheimer's disease (AD), and develops both amyloid beta deposits and neurofibrillary tangles in a temporal and spatial pattern that is similar to human AD pathology. Additionally, abnormal myelination patterns with changes in oligodendrocyte and myelin marker expression are reported to be an early pathological feature in this model. Only few diffusion MRI (dMRI) studies have investigated white matter abnormalities in 3×Tg-AD mice, with inconsistent results. Thus, the goal of this study was to investigate the sensitivity of dMRI to capture brain microstructural alterations in 2-month-old 3×Tg-AD mice. In the fimbria, the fractional anisotropy (FA), kurtosis fractional anisotropy (KFA), and radial kurtosis (K┴ ) were found to be significantly lower in 3×Tg-AD mice than in controls, while the mean diffusivity (MD) and radial diffusivity (D┴ ) were found to be elevated. In the fornix, K┴ was lower for 3×Tg-AD mice; in the dorsal hippocampus MD and D┴ were elevated, as were FA, MD, and D┴ in the ventral hippocampus. These results indicate, for the first time, dMRI changes associated with myelin abnormalities in young 3×Tg-AD mice, before they develop AD pathology. Morphological quantification of myelin basic protein immunoreactivity in the fimbria was significantly lower in the 3×Tg-AD mice compared with the age-matched controls. Our results demonstrate that dMRI is able to detect widespread, significant early brain morphological abnormalities in 2-month-old 3×Tg-AD mice.

Optimization of data acquisition and analysis for fiber ball imaging.

The inverse Funk transform of high angular resolution diffusion imaging (HARDI) data provides an estimate for the fiber orientation density function (fODF) in white matter (WM). Since the inverse Funk transform is a straightforward linear transformation, this technique, referred to as fiber ball imaging (FBI), offers a practical means of calculating the fODF that avoids the need for a response function or nonlinear numerical fitting. Nevertheless, the accuracy of FBI depends on both the choice of b-value and the number of diffusion-encoding directions used to acquire the HARDI data. To inform the design of optimal scan protocols for its implementation, FBI predictions are investigated here with in vivo data from healthy adult volunteers acquired at 3 T for b-values spanning 1000 to 10,000 s/mm2, for diffusion-encoding directions varying in number from 30 to 256 and for TE ranging from 90 to 120 ms. Our results suggest b-values above 4000 s/mm2 with at least 64 diffusion-encoding directions are adequate to achieve reasonable accuracy with FBI for calculating axon-specific diffusion measures and for performing WM fiber tractography (WMFT).

Measuring intra-axonal T2 in white matter with direction-averaged diffusion MRI.

PURPOSE: To demonstrate how the T2 relaxation time of intra-axonal water (T2a ) in white matter can be measured with direction-averaged diffusion MRI. METHODS: For b-values larger than about 4000 s/mm2 , the direction-averaged diffusion MRI signal from white matter is dominated by the contribution from water within axons, which enables T2a to be estimated by acquiring data for multiple TE values and fitting a mono-exponential decay curve. If given a value of the intra-axonal diffusivity, an extension of the method allows the extra-axonal relaxation time (T2e ) to be calculated also. This approach was applied to estimate T2a in white matter for 3 healthy subjects at 3 T, as well as T2e for a selected set of assumed intra-axonal diffusivities. RESULTS: The estimated T2a values ranged from about 50 ms to 110 ms, with considerable variation among white matter regions. For white matter tracts with primarily collinear fibers, T2a was found to depend on the angle of the tract relative to the main magnetic field, which is consistent with T2a being affected by magnetic field inhomogeneities arising from spatial differences in magnetic susceptibility. The T2e values were significantly smaller than the T2a values across white matter regions for several plausible choices of the intra-axonal diffusivity. CONCLUSION: The relaxation time for intra-axonal water in white matter can be determined in a straightforward manner by measuring the direction-averaged diffusion MRI signal with a large b-value for multiple TEs. In healthy brain, T2a is greater than T2e and varies considerably with anatomical region.

Modeling white matter microstructure with fiber ball imaging.

Fiber ball imaging (FBI) provides a means of calculating the fiber orientation density function (fODF) in white matter from diffusion MRI (dMRI) data obtained over a spherical shell with a b-value of about 4000 s/mm2 or higher. By supplementing this FBI-derived fODF with dMRI data acquired for two lower b-value shells, it is shown that several microstructural parameters may be estimated, including the axonal water fraction (AWF) and the intrinsic intra-axonal diffusivity. This fiber ball white matter (FBWM) modeling method is demonstrated for dMRI data acquired from healthy volunteers, and the results are compared with those of the white matter tract integrity (WMTI) method. Both the AWF and the intra-axonal diffusivity obtained with FBWM are found to be significantly larger than for WMTI, with the FBWM values for the intra-axonal diffusivity being more consistent with recent results obtained using isotropic diffusion weighting. An important practical advantage of FBWM is that the only nonlinear fitting required is the minimization of a cost function with just a single free parameter, which facilitates the implementation of efficient and robust numerical routines.

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.