Search

Objective Multiple sclerosis (MS) lesions are heterogeneous with regard to inflammation, demyelination, axonal injury, and neuronal loss. We previously developed a diffusion basis spectrum imaging (DBSI) technique to better address MS lesion heterogeneity. We hypothesized that the profiles of multiple DBSI metrics can identify lesion‐defining patterns. Here we test this hypothesis by combining a deep learning algorithm using deep neural network (DNN) with DBSI and other imaging methods. Methods Thirty‐eight MS patients were scanned with diffusion‐weighted imaging, magnetization transfer imaging, and standard conventional MRI sequences (cMRI). A total of 499 regions of interest were identified on standard MRI and labeled as persistent black holes (PBH), persistent gray holes (PGH), acute black holes (ABH), acute gray holes (AGH), nonblack or gray holes (NBH), and normal appearing white matter (NAWM). DBSI, diffusion tensor imaging (DTI), and magnetization transfer ratio (MTR) were applied to the 43,261 imaging voxels extracted from these ROIs. The optimized DNN with 10 fully connected hidden layers was trained using the imaging metrics of the lesion subtypes and NAWM. Results Concordance, sensitivity, specificity, and accuracy were determined for the different imaging methods. DBSI‐DNN derived lesion classification achieved 93.4% overall concordance with predetermined lesion types, compared with 80.2% for DTI‐DNN model, 78.3% for MTR‐DNN model, and 74.2% for cMRI‐DNN model. DBSI‐DNN also produced the highest specificity, sensitivity, and accuracy. Conclusions DBSI‐DNN improves the classification of different MS lesion subtypes, which could aid clinical decision making. The efficacy and efficiency of DBSI‐DNN shows great promise for clinical applications in automatic MS lesion detection and classification.

Background and ObjectivesThe neurologic deficits of neonatal post-hemorrhagic hydrocephalus (PHH) have been linked to periventricular white matter injury. To improve understanding of PHH-related injury, diffusion basis spectrum imaging (DBSI) was applied in neonates, modeling axonal and myelin integrity, fiber density, and extrafiber pathologies. Objectives included characterizing DBSI measures in periventricular tracts, associating measures with ventricular size, and examining MRI findings in the context of postmortem white matter histology from similar cases.MethodsA prospective cohort of infants born very preterm underwent term equivalent MRI, including infants with PHH, high-grade intraventricular hemorrhage without hydrocephalus (IVH), and controls (very preterm [VPT]). DBSI metrics extracted from the corpus callosum, corticospinal tracts, and optic radiations included fiber axial diffusivity, fiber radial diffusivity, fiber fractional anisotropy, fiber fraction (fiber density), restricted fractions (cellular infiltration), and nonrestricted fractions (vasogenic edema). Measures were compared across groups and correlated with ventricular size. Corpus callosum postmortem immunohistochemistry in infants with and without PHH assessed intra- and extrafiber pathologies.ResultsNinety-five infants born very preterm were assessed (68 VPT, 15 IVH, 12 PHH). Infants with PHH had the most severe white matter abnormalities and there were no consistent differences in measures between IVH and VPT groups. Key tract-specific white matter injury patterns in PHH included reduced fiber fraction in the setting of axonal or myelin injury, increased cellular infiltration, vasogenic edema, and inflammation. Specifically, measures of axonal injury were highest in the corpus callosum; both axonal and myelin injury were observed in the corticospinal tracts; and axonal and myelin integrity were preserved in the setting of increased extrafiber cellular infiltration and edema in the optic radiations. Increasing ventricular size correlated with worse DBSI metrics across groups. On histology, infants with PHH had high cellularity, variable cytoplasmic vacuolation, and low synaptophysin marker intensity.DiscussionPHH was associated with diffuse white matter injury, including tract-specific patterns of axonal and myelin injury, fiber loss, cellular infiltration, and inflammation. Larger ventricular size was associated with greater disruption. Postmortem immunohistochemistry confirmed MRI findings. These results demonstrate DBSI provides an innovative approach extending beyond conventional diffusion MRI for investigating neuropathologic effects of PHH on neonatal brain development.

Background: Advanced magnetic resonance imaging (MRI) methods can provide more specific information about various microstructural tissue changes in multiple sclerosis (MS) brain. Quantitative measurement of T1 and T2 relaxation, and diffusion basis spectrum imaging (DBSI) yield metrics related to the pathology of neuroinflammation and neurodegeneration that occurs across the spectrum of MS. Objective: To use relaxation and DBSI MRI metrics to describe measures of neuroinflammation, myelin and axons in different MS subtypes. Methods: 103 participants (20 clinically isolated syndrome (CIS), 33 relapsing-remitting MS (RRMS), 30 secondary progressive MS and 20 primary progressive MS) underwent quantitative T1, T2, DBSI and conventional 3T MRI. Whole brain, normal-appearing white matter, lesion and corpus callosum MRI metrics were compared across MS subtypes. Results: A gradation of MRI metric values was seen from CIS to RRMS to progressive MS. RRMS demonstrated large oedema-related differences, while progressive MS had the most extensive abnormalities in myelin and axonal measures. Conclusion: Relaxation and DBSI-derived MRI measures show differences between MS subtypes related to the severity and composition of underlying tissue damage. RRMS showed oedema, demyelination and axonal loss compared with CIS. Progressive MS had even more evidence of increased oedema, demyelination and axonal loss compared with CIS and RRMS.

Neuroimaging plays an important role in assessing axonal pathology after traumatic spinal cord injury. However, coexisting inflammation confounds imaging assessment of the severity of axonal injury. Herein, we applied diffusion basis spectrum imaging (DBSI) to quantitatively differentiate and quantify underlying pathologies in traumatic spinal cord injury at 3 days post-injury. Results reveal that DBSI was capable of detecting and differentiating axonal injury, demyelination, and inflammation-associated edema and cell infiltration in contusion-injured spinal cords. DBSI was able to detect and quantify axonal loss in the presence of white matter tract swelling. The DBSI-defined apparent axonal volume correlated with the corresponding histological markers. DBSI-derived pathological metrics could serve as neuroimaging biomarkers to differentiate and quantify coexisting white matter pathologies in spinal cord injury, providing potential surrogate outcome measures to assess spinal cord injury progression and response to therapies.

ObjectiveThe debilitating neurological deficits of neonatal post-hemorrhagic hydrocephalus (PHH) have been linked to periventricular white matter injury. To improve understanding of the deleterious mechanisms underlying PHH-related brain injury, this study applied diffusion basis spectrum imaging (DBSI) for the first time in neonates, modeling white matter fibers to assess axonal and myelin integrity, fiber density, and extra-fiber pathologies including cellularity, edema, and inflammation. The objectives of the study were to characterize DBSI measures in key periventricular white matter tracts of PHH infants, associate those diffusion measures with ventricular size, and utilize postmortem white matter histology to compare with the MRI findings.MethodA prospective cohort of very preterm infants (n=95) underwent MRI at term equivalent age, of which 68 were controls (VPT group), 15 had high-grade intraventricular hemorrhage without hydrocephalus (IVH group), and 12 had PHH (PHH group). DBSI metrics extracted from manually segmented corpus callosum (CC), corticospinal tracts (CST), and optic radiations (OPRA) included fiber level axial diffusivity (FAD), fiber radial diffusivity (FRD), fiber fractional anisotropy (FFA), fiber fraction (FF), restricted fractions (RF), and non-restricted fractions (NRF). All measures were contrasted across groups and correlated with frontal occipital horn ratio (FOHR), a measure of ventricular size. Postmortem immunohistochemistry was performed on the CC of 10 preterm infants (five VPT, three IVH, and two PHH) and two full-term infants who died from non-neurologic causes assessing white matter intra- and extra-fiber pathologies, as well as the integrity of the adjoining ventricular and subventricular zones.ResultsExcept for FF in the CC, there were no differences in all measures between IVH and VPT infants. In the unmyelinated CC, PHH had the lowest FF, FAD, and FFA and the highest RF. In the CC, FOHR related negatively with FAD, FFA, and FF and positively with RF. In the myelinated CST, PHH had the lowest FAD, FFA, and FF and the highest FRD and RF. FOHR related negatively to FAD and FFA and positively with NRF and FRD. In the OPRA, PHH was associated with the lowest FF and the highest RF, NRF, and FAD. FOHR related positively with FAD and NRF and negatively with FF. On postmortem tissues, PHH was associated with the highest white matter cellularity counts, variable amounts of cytoplasmic vacuolation, and the lowest synaptophysin marker intensity. The adjoining ventricular and subventricular zones in PHH had poor cytoarchitecture on H&E staining and relatively increased expression of GFAP and IBA1.ConclusionsThis initial utilization of DBSI to investigate neonatal brain development and injury demonstrated that PHH was associated with diffuse periventricular white matter injury, with tract-specific microstructural patterns and severity of axonal injury, myelin injury, white matter fiber loss, hypercellularity, and inflammation. While axonal injury was present in the CST and unmyelinated CC, myelin injury occurred only in the CST. The OPRA predominantly showed inflammation with myelin preservation. White matter cellular infiltration occurred in all tracts. Postmortem immunohistochemistry confirmed the imaging findings of decreased axonal fiber density, sparser fiber architecture, and increased cellular infiltration. Larger ventricular size was associated with greater white matter disruption. Building upon these results, DBSI provides an innovative approach for investigating the complex neuropathological effects of PHH on periventricular white matter microstructure.

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.

Background: High-grade pediatric brain tumors exhibit the highest cancer mortality rates in children. While conventional MRI has been widely adopted for examining pediatric high-grade brain tumors clinically, accurate neuroimaging detection and differentiation of tumor histopathology for improved diagnosis, surgical planning, and treatment evaluation, remains an unmet need in their clinical management. Methods: We employed a novel Diffusion Histology Imaging (DHI) approach employing diffusion basis spectrum imaging (DBSI) derived metrics as the input classifiers for deep neural network analysis. DHI aims to detect, differentiate, and quantify heterogeneous areas in pediatric high-grade brain tumors, which include normal white matter (WM), densely cellular tumor, less densely cellular tumor, infiltrating edge, necrosis, and hemorrhage. Distinct diffusion metric combination would thus indicate the unique distributions of each distinct tumor histology features. Results: DHI, by incorporating DBSI metrics and the deep neural network algorithm, classified pediatric tumor histology with an overall accuracy of 83.3%. Receiver operating analysis (ROC) analysis suggested DHI’s great capability in distinguishing individual tumor histology with AUC values (95%CI) of 0.983 (0.985 - 0.989), 0.961 (0.957 - 0.964), 0.993 (0.992 - 0.994), 0.953 (0.947 - 0.958), 0.974 (0.970 - 0.978) and 0.980 (0.977 - 0.983) for normal WM, densely cellular tumor, less densely cellular tumor, infiltrating edge, necrosis and hemorrhage, respectively. Conclusions: Our results suggest that DBSI-DNN, or DHI, accurately characterized and classified multiple tumor histologic features in pediatric high-grade brain tumors. If these results could be further validated in patients, the novel DHI might emerge as a favorable alternative to the current neuroimaging techniques to better guide biopsy and resection as well as monitor therapeutic response in patients with high-grade brain tumors.

High-grade pediatric brain tumors constitute the highest mortality of cancer-death in children. While conventional MRI has been widely adopted for examining pediatric high-grade brain tumor clinically, accurate neuroimaging detection and differentiation of tumor histopathology for improved diagnosis, surgical planning, and treatment evaluation, remains an unmet need in the clinical management of pediatric brain tumor. We employed a novel Diffusion Histology Imaging (DHI) approach that incorporates diffusion basis spectrum imaging (DBSI) and deep neural network. DHI aims to detect, differentiate, and quantify heterogenous areas in pediatric high-grade brain tumors, which include normal white matter (WM), densely cellular tumor (DC tumor), less densely cellular tumor (LDC tumor), infiltrating edge, necrosis, and hemorrhage. Distinct diffusion metric combination would thus indicate the unique distributions of each distinct tumor histology features. DHI, by incorporating DBSI metrics and the deep neural network algorithm, classified pediatric tumor histology with an overall accuracy of 83.3%. Receiver operating analysis (ROC) analysis suggested DHI’s great capability in distinguishing individual tumor histology with AUC values (95%CI) of 0.983 (0.985-0.989), 0.961 (0.957-0.964), 0.993 (0.992-0.994), 0.953 (0.947-0.958), 0.974 (0.970-0.978) and 0.980 (0.977-0.983) for normal WM, DC tumor, LDC tumor, infiltrating edge, necrosis and hemorrhage, respectively. Our results suggest that DBSI-DNN, or DHI, accurately characterized and classified multiple tumor histologic features in pediatric high-grade brain tumors. If further validated in patients, the novel DHI might emerge as a favorable alternative to the current neuroimaging techniques to better guide biopsy and resection as well as monitor therapeutic response in patients with high-grade brain tumors.

The aim of this study was to determine the feasibility of diffusion basis spectrum imaging in multiple sclerosis at 7 T and to investigate the pathological substrates of tissue damage in lesions and normal-appearing white matter. To this end, 43 patients with multiple sclerosis (24 relapsing-remitting, 19 progressive), and 21 healthy control subjects were enrolled. White matter lesions were classified in T1-isointense, T1-hypointense and black holes. Mean values of diffusion basis spectrum imaging metrics (fibres, restricted and non-restricted fractions, axial and radial diffusivities and fractional anisotropy) were measured from whole brain white matter lesions and from both lesions and normal appearing white matter of the corpus callosum. Significant differences were found between T1-isointense and black holes (P ranging from 0.005 to

Diffusion basis spectrum imaging (DBSI) models diffusion-weighted magnetic resonance imaging (MRI) signals as a combination of discrete anisotropic diffusion tensors and a spectrum of isotropic diffusion tensors. Here, we report the histopathological correlates of DBSI in the biopsied brain tissue of a patient with an inflammatory demyelinating lesion typical of multiple sclerosis (MS). Increased radial diffusivity (marker of demyelination), decreased fiber fraction (apparent axonal density), elevated nonrestricted isotropic fraction (marker of vasogenic edema), but unchanged axial diffusivity (marker of integrity of residual axons) seen in the lesion appeared consistent with histopathological findings of inflammatory demyelination with relative axonal sparing. Our report supports the application of DBSI as a biomarker in human studies of MS.

We describe a novel imaging method to assess central nervous system pathology called “Diffusion Basis Spectrum Imaging” (DBSI). Diffusion tensor imaging (DTI) has been widely used to estimate axonpathology and demyelination. However, in the settings of acute inflammation and chronic tissue loss asare common in multiple sclerosis, DTI signals can lead to false interpretations. DBSI is a computationallynovel method that separates isotropic from anisotropic components in imaging voxels. Isotropicdiffusion is believed to reflect inflammatory components (cells, edema), as well as intrinsic cells andextracellular space. DBSI enables the measurement of axial and radial diffusivities within the anisotropiccomponents of imaging voxels, which reflect the integrity of axon fibers and myelin, respectively.

PurposeDiffusion tensor imaging (DTI) has been employed for over two decades to noninvasively quantify central nervous system (CNS) diseases/injuries. However, DTI is an inadequate simplification of diffusion modeling in the presence of co-existing inflammation, edema, and crossing nerve fibers.MethodsWe 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. Further, 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 (NODDI) to resolve fiber crossing, in reference to the gold standard angles measured from structural images.ResultsDTI-computed diffusivities and fractional anisotropy (FA) were significantly confounded by gelmimicked 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. Additionaly, DBSI accurately and consistently estimated crossing angles in various conditions of gel-mimicked edema when comparing with gold standard (r2=0.92, p=1.9×10−9, bias=3.9°). Small crossing angles and edema sinficantly impact dODF, making DKI, GQI and QBI less accurate in detecting and estimating fibers corrsing angles. Lastly, we demonstrate DBSI’s superiority over DTI for recovering and delineating white matter tracts in peritumoral edema for preoperative planning of surgical resection.ConclusionsDBSI 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 capability compared with DKI, QBI and GQI.

BackgroundDiagnosing MS through magnetic resonance imaging (MRI) requires extensive clinical experience and tedious work. Furthermore, MRI-indicated MS lesion locations rarely align with the patients’ symptoms and often contradict with pathology studies. Our lab has developed and modified a novel diffusion basis spectrum imaging (DBSI) technique to address the shortcomings of MRI-based MS diagnoses. Although primary DBSI metrics have been demonstrated to be associated with axonal injury/loss, demyelination and inflammation, a more detailed analysis using multiple DBSI-structural metrics to improve the accuracy of MS lesion detection and differentiation is still needed. Here we report that Diffusion Histology Imaging (DHI), an improved approach that combines a deep neural network (DNN) algorithm with improved DBSI analyses, accurately detected and classified various MS lesion types.MethodsThirty-eight multiple sclerosis patients were scanned with T2-weighted imaging (T2WI) using fluid attenuated inversion recovery (FLAIR), T1-weighted imaging (T1WI) using magnetization-prepared rapid acquisition with gradient echo (MPRAGE), magnetization transfer contrast (MTR) imaging and diffusion-weighted imaging. The imaging results identified 43,261 voxels from 91 persistent black hole (PBH) lesions, 89 persistent gray hole (PGH) lesions, 16 acute gray hole (AGH) lesions, 189 non-black hole (NBH) lesions and 113 normal-appearing white matter (NAWM) areas. Data extracted from these lesions were randomly split into training, validation, and testing groups with an 8:1:1 ratio. The DNN was constructed with 10 fully-connected hidden layers using TensorFlow 2.0 in Python. Batch normalization and dropout regularization were used for model optimization.ResultsEach MS lesion type had unique DBSI derived diffusion metric profiles. Based on these DBSI diffusion metric profiles, DHI achieved a 93.6% overall concordance with neurologist determinations of all five MS lesions, compared with 74.3% from conventional MRI (cMRI)-DNN model, 78.2% from MTR-DNN model, and 80% from DTI-DNN model. DHI also achieved greater performances on detecting individual MS lesion types compared to other models. Specifically, DHI showed great performances on prediction of PBH (AUC: 0.991; F1-score: 0.923), PGH (AUC: 0.977; F1-score: 0.823) and AGH (AUC: 0.987; F1-score: 0.887), which significantly outperformed other models.ConclusionsDHI significantly improves the detection and classification accuracy for various MS lesion types, which could greatly aid the clinical decisions of neurologists and neuroradiologists. The efficacy and efficiency of this DNN model shows great promise for clinical application.

ObjectiveTo use diffusion basis spectrum imaging (DBSI) to assess how damage to normal-appearing white matter (NAWM) in the corpus callosum (CC) influences neurologic impairment in people with MS (pwMS).MethodsUsing standard MRI, the primary pathologies in MS of axonal injury/loss, demyelination, and inflammation are not differentiated well. DBSI has been shown in animal models, phantoms, and in biopsied and autopsied human CNS tissues to distinguish these pathologies. Fifty-five pwMS (22 relapsing-remitting, 17 primary progressive, and 16 secondary progressive) and 13 healthy subjects underwent DBSI analyses of NAWM of the CC, the main WM tract connecting the cerebral hemispheres. Tract-based spatial statistics were used to minimize misalignment. Results were correlated with scores from a battery of clinical tests focused on deficits typical of MS.ResultsNormal-appearing CC in pwMS showed reduced fiber fraction and increased nonrestricted isotropic fraction, with the most extensive abnormalities in secondary progressive MS (SPMS). Reduced DBSI-derived fiber fraction and increased DBSI-derived nonrestricted isotropic fraction of the CC correlated with worse cognitive scores in pwMS. Increased nonrestricted isotropic fraction in the body of the CC correlated with impaired hand function in the SPMS cohort.ConclusionsDBSI fiber fraction and nonrestricted isotropic fraction were the most useful markers of injury in the NAWM CC. These 2 DBSI measures reflect axon loss in animal models. Because of its ability to reveal axonal loss, as well as demyelination, DBSI may be a useful outcome measure for trials of CNS reparative treatments.

Repetitive electrical activity produces microstructural alteration in myelinated axons, which may afford the opportunity to noninvasively monitor function of myelinated fibers in peripheral nervous system (PNS)/CNS pathways. Microstructural changes were assessed via two different magnetic-resonance-based approaches: diffusion fMRI and dynamic T(2) spectroscopy in the ex vivo perfused bullfrog sciatic nerves. Using this robust, classical model as a platform for testing, we demonstrate that noninvasive diffusion fMRI, based on standard diffusion tensor imaging (DTI), can clearly localize the sites of axonal conduction blockage as might be encountered in neurotrauma or other lesion types. It is also shown that the diffusion fMRI response is graded in proportion to the total number of electrical impulses carried through a given locus. Dynamic T(2) spectroscopy of the perfused frog nerves point to an electrical-activity-induced redistribution of tissue water and myelin structural changes. Diffusion basis spectrum imaging (DBSI) reveals a reversible shift of tissue water into a restricted isotropic diffusion signal component. Submyelinic vacuoles are observed in electron-microscopy images of tissue fixed during electrical stimulation. A slowing of the compound action potential conduction velocity accompanies repetitive electrical activity. Correlations between electrophysiology and MRI parameters during and immediately after stimulation are presented. Potential mechanisms and interpretations of these results are discussed.

Purpose To assess the capability of signal-to-noise ratio enhancing reconstruction (SER) to reduce the acquisition time for quantitative white matter injury assessment. Methods Four single-average diffusion tensor imaging (DTI) datasets were acquired for each animal from four mouse cohorts: two models of spinal cord injury and two control groups. Quantitative parameters (apparent diffusion coefficient, relative anisotropy, axial and radial diffusivities) were computed from (I) single-average data with traditional reconstruction; (II) single-average data with SER; (III) four-average data with traditional reconstruction; and (IV) single-average data with optimized multicomponent nonlocal means (OMNLM) denoising. These approaches were compared based on coefficients of variation (COVs) and whether estimated diffusion parameters were sensitive to injury. Results SER yielded better COVs for diffusivity and anisotropy than traditional reconstruction of single-average data, and yielded comparable COVs to that achieved with four-average data. In addition, diffusion parameters obtained using SER with single-average data had comparable injury sensitivity to those obtained from four-average data, while diffusion parameters obtained from OMNLM and traditional reconstruction of single-average data had limited sensitivity. Conclusion A four-fold reduction in the number of averages for quantitative diffusion imaging of small animal white matter injury is feasible using SER. Our results also underscore the need to validate nonlinear methods using task-based measures on an application-by-application basis. Magn Reson Med, 2015. © 2015 Wiley Periodicals, Inc.

Axon injury/loss, demyelination and inflammation are the primary pathologies in multiple sclerosis lesions. Despite the prevailing notion that axon/neuron loss is the substrate of clinical progression of multiple sclerosis, the roles that these individual pathological processes play in multiple sclerosis progression remain to be defined. An imaging modality capable to effectively detect, differentiate and individually quantify axon injury/loss, demyelination and inflammation, would not only facilitate the understanding of the pathophysiology underlying multiple sclerosis progression, but also the assessment of treatments at the clinical trial and individual patient levels. In this report, the newly developed diffusion basis spectrum imaging was used to discriminate and quantify the underlying pathological components in multiple sclerosis white matter. Through the multiple-tensor modelling of diffusion weighted magnetic resonance imaging signals, diffusion basis spectrum imaging resolves inflammation-associated cellularity and vasogenic oedema in addition to accounting for partial volume effects resulting from cerebrospinal fluid contamination, and crossing fibres. Quantitative histological analysis of autopsied multiple sclerosis spinal cord specimens supported that diffusion basis spectrum imaging-determined cellularity, axon and myelin injury metrics closely correlated with those pathologies identified and quantified by conventional histological staining. We demonstrated in healthy control subjects that diffusion basis spectrum imaging rectified inaccurate assessments of diffusion properties of white matter tracts by diffusion tensor imaging in the presence of cerebrospinal fluid contamination and/or crossing fibres. In multiple sclerosis patients, we report that diffusion basis spectrum imaging quantitatively characterized the distinct pathologies underlying gadolinium-enhanced lesions, persistent black holes, non-enhanced lesions and non-black hole lesions, a task yet to be demonstrated by other neuroimaging approaches. Diffusion basis spectrum imaging-derived radial diffusivity (myelin integrity marker) and non-restricted isotropic diffusion fraction (oedema marker) correlated with magnetization transfer ratio, supporting previous reports that magnetization transfer ratio is sensitive not only to myelin integrity, but also to inflammation-associated oedema. Our results suggested that diffusion basis spectrum imaging-derived quantitative biomarkers are highly consistent with histology findings and hold promise to accurately characterize the heterogeneous white matter pathology in multiple sclerosis patients. Thus, diffusion basis spectrum imaging can potentially serve as a non-invasive outcome measure to assess treatment effects on the specific components of underlying pathology targeted by new multiple sclerosis therapies.

Inflammation occurs after HIV infection and persists despite highly active antiretroviral therapy (HAART). Diffusion tensor imaging (DTI), measures HIV associated white matter changes, but can be confounded by inflammation. Currently, the influence of inflammation on white matter integrity in well-controlled HIV+ patients remains unknown. We used diffusion basis Spectrum imaging (DBSI) derived cellularity to isolate restricted water diffusion associated with inflammation separated from the anisotropic diffusion associated with axonal integrity. Ninety-two virologically suppressed HIV+ patients on HAART and 66 HIV uninfected (HIV-) controls underwent neuropsychological performance (NP) testing and neuroimaging. NP tests assessed multiple domains (memory, psychomotor speed, and executive functioning). DTI and DBSI derived fractional anisotropy (FA) maps were processed with tract based spatial statistics for comparison between both groups. Cellularity was assessed with regards to age, HIV status, and NP. Within the HIV+ cohort, cellularity was compared to clinical (HAART duration) and laboratory measures of disease (e.g. CD4 cell current and nadir). NP was similar for both groups. DTI derived FA was lower in HIV+ compared to HIV- individuals. In contrast, DBSI derived FA was similar for both groups. Instead, diffuse increases in cellularity were present in HIV+ individuals. Observed changes in cellularity were significantly associated with age, but not NP, in HIV+ individuals. A trend level association was seen between cellularity and HAART duration. Elevated inflammation, measured by cellularity, persists in virologically well-controlled HIV+ individuals. Widespread cellularity changes occur in younger HIV+ individuals and diminish with aging and duration of HAART.

Background Magnetic resonance imaging markers have been widely used to detect and quantify white matter pathologies in multiple sclerosis. We have recently developed a diffusion basis spectrum imaging (DBSI) to distinguish and quantify co-existing axonal injury, demyelination, and inflammation in multiple sclerosis patients and animal models. It could serve as a longitudinal marker for axonal loss, a primary cause of permanent neurological impairments and disease progression. Methods Eight 10-week-old female C57BL/6 mice underwent optic nerve DBSI, followed by a week-long recuperation prior to active immunization for experimental autoimmune encephalomyelitis (EAE). Visual acuity of all mice was assessed daily. Longitudinal DBSI was performed in mouse optic nerves at baseline (naïve, before immunization), before, during, and after the onset of optic neuritis. Tissues were perfusion fixed after final in vivo scans. The correlation between DBSI detected pathologies and corresponding immunohistochemistry markers was quantitatively assessed. Results In this cohort of EAE mice, monocular vision impairment occurred in all animals. In vivo DBSI detected, differentiated, and quantified optic nerve inflammation, demyelination, and axonal injury/loss, correlating nerve pathologies with visual acuity at different time points of acute optic neuritis. DBSI quantified, in the presence of optic nerve swelling, ~15% axonal loss at the onset of optic neuritis in EAE mice. Conclusions Our findings support the notion that axonal loss could occur early in EAE mice. DBSI detected pathologies in the posterior visual pathway unreachable by optical coherence tomography and without confounding inflammation induced optic nerve swelling. DBSI could thus decipher the interrelationship among various pathological components and the role each plays in disease progression. Quantification of the rate of axonal loss could potentially serve as the biomarker to predict treatment outcome and to determine when progressive disease starts.

Clinicopathological paradox has hampered significantly the effective assessment of the efficacy of therapeutic intervention for multiple sclerosis. Neuroimaging biomarkers of tissue injury could guide more effective treatment by accurately reflecting the underlying subclinical pathologies. Diffusion tensor imaging-derived directional diffusivity and anisotropy indices have been applied to characterize white matter disorders. However, these biomarkers are sometimes confounded by the complex pathologies seen in multiple sclerosis and its animal models. Recently, a novel technique of diffusion basis spectrum imaging has been developed to quantitatively assess axonal injury, demyelination and inflammation in a mouse model of inflammatory demyelination. Lenaldekar, which inhibits T-cell expansion in a non-cytolytic manner, has been shown to suppress relapses and preserve white matter integrity in mice with experimental autoimmune encephalomyelitis. In this study, relapsing-remitting experimental autoimmune encephalomyelitis was induced through active immunization of SJL/J mice with a myelin proteolipid protein peptide. The therapeutic efficacy of Lenaldekar treatment was evaluated via daily clinical score, cross-sectional ex vivo diffusion basis spectrum imaging examination and histological analysis. Lenaldekar greatly reduced relapse severity and protected white matter integrity in these experimental autoimmune encephalomyelitis mice. Diffusion basis spectrum imaging-derived axial diffusivity, radial diffusivity and restricted diffusion tensor fraction accurately reflected axonal injury, myelin integrity and inflammation-associated cellularity change, respectively. These results support the potential use of diffusion basis spectrum imaging as an effective outcome measure for preclinical drug evaluation.

The dysmyelinated axons of shiverer mice exhibit impaired conduction characteristics similar to early postnatal axons before myelination, while the patterns of neuronal activity and connectivity are relatively comparable to those of wild-type myelinated axons. This unique dysmyelination pattern is exploited in the present study to determine the role of compact myelin on the loss and recovery of function following traumatic spinal cord injury (SCI). We applied in vivo diffusion tensor imaging (DTI) and post-mortem immunohistochemistry analysis to examine changes in myelin and axonal integrity and evaluated these changes in concert with analysis of locomotor function from 1 to 4 weeks following a mid-thoracic contusion injury in homozygous shiverer and heterozygous littermate mice. The DTI biomarkers, axial and radial diffusivities, are noninvasive indicators of axon and myelin integrity in response to SCI of both myelinated and dysmyelinated spinal cord. We show that myelin is critical for normal hind limb function in open field locomotion. However, when the functional outcome is limited during chronic SCI, the extent of recovery is associated with residual axonal integrity and independent of the extent of intact myelin at the lesion epicenter.

Background: Multiple sclerosis (MS) and neuromyelitis optica (NMO) both affect spinal cord with notable differences in pathology. Objective: Determine the utility of diffusion tensor imaging (DTI) to differentiate the spinal cord lesions of NMO from MS within and outside T2 lesions. Methods: Subjects greater than or equal to 12 months from a clinical episode of transverse myelitis underwent a novel transaxial cervical spinal cord DTI sequence. Ten subjects with NMO, 10 with MS and 10 healthy controls were included. Results: Within T2 affected white matter regions, radial diffusivity was increased in both NMO and MS compared with healthy controls ( pConclusions: Higher radial diffusivity within spinal cord white matter tracts derived from diffusion tensor imaging were appreciated in NMO compared with MS, consistent with the known greater tissue destruction seen in NMO. DTI also detected tissue alterations outside T2 lesions and may be a surrogate of anterograde and retrograde degeneration.

Acute necrotizing encephalopathy and acute disseminated encephalomyelitis are 2 rare types of acute postinfectious encephalopathy in children. Acute necrotizing encephalopathy is characterized by multiple symmetric lesions in the thalami, putamena, cerebral and cerebellar white matter, and brainstem. Acute disseminated encephalomyelitis is an immune-mediated demyelinating central nervous system disorder that predominantly affects the white matter. Diffusion magnetic resonance imaging is sensitive to measuring water diffusion in the central nervous system in human and animal models. Recent studies have demonstrated that by using an analytical approach to directional diffusivity-derived parameters, the axial diffusivity and the radial diffusivity, one can assess the extent of axonal or myelin injury in the central nervous system white matter. We applied directional diffusivity to acute necrotizing encephalopathy, acute disseminated encephalomyelitis, and control subjects correlating with neuropathology findings. In acute necrotizing encephalopathy, axonal injury without demyelination, noted on biopsy samples of brain tissue, was suggested by a decreased apparent diffusion coefficient, unchanged fractional anisotropy, and decreased axial and radial diffusivity. In acute disseminated encephalomyelitis, an increased apparent diffusion coefficient, decreased fractional anisotropy, unchanged axial diffusivity, and markedly increased radial diffusivity compatible with active inflammatory demyelination were noted, consistent with tissue biopsy sample neuropathology. In conclusion, diffusion tensor parameters can potentially depict more microstructural changes than conventional magnetic resonance imaging in postinfectious encephalopathy in children.

Degeneration of motor neurons and their associated axons is a hallmark of amyotrophic lateral sclerosis, but reliable noninvasive lesion detection is lacking. In vivo diffusion tensor imaging was performed to evaluate neurodegeneration in the brainstem and cervical spinal cord of wild-type and G93A-SOD1 transgenic mice, an animal model of amyotrophic lateral sclerosis. A statistically significant reduction in the apparent diffusion coefficient was observed in the motor nuclei VII and XII of G93A-SOD1 transgenic mice relative to wild-type mice. No significant difference in diffusion anisotropy was observed in dorsal white or gray matter in cervical and lumbar segments of the spinal cord. In contrast, statistically significant decreases in axial diffusivity (diffusivity parallel to the axis of the spinal cord) and apparent diffusion coefficient were found in the ventrolateral white matter of G93A-SOD1 mice in both the cervical and lumbar spinal cord. The reduction in axial diffusivity, suggestive of axonal injury, in the white matter of the spinal cord of G93A-SOD1 mice was verified by immunostaining with nonphosphorylated neurofilament. The present study demonstrates that in vivo diffusion tensor imaging-derived axial diffusivity may be used to accurately evaluate axonal degeneration in an animal model of amyotrophic lateral sclerosis.

Magnetic resonance imaging (MRI) is a key tool for non-invasive spinal cord lesion analysis; however, accurate, quantitative methods for this analysis are lacking. A new, multi-step, multidimensional approach, utilizing the Classification Expectation Maximization (CEM) algorithm, is proposed for MRI segmentation of spinal cord tissues. Diffusion tensor imaging is used to generate multiple images of each spinal slice with different diffusion direction weightings. The maximum likelihood tissue classifications are then jointly estimated to produce a binary classification image, corresponding to voxels containing either spinal cord or background. Edge detection is employed to find a non-parametric curve encapsulating the entire spinal cord. The algorithm is evaluated using data from in vivo DTI of control and injured mouse spinal cords. The algorithm is shown to remain accurate for whole spinal cord, white matter, and hemorrhage segmentation in the presence of significant injury. The results of the method are shown to be at least on par with expert manual segmentation.

Accurate diagnosis of spinal cord injury (SCI) severity must be achieved before highly aggressive experimental therapies can be tested responsibly in the early phases after trauma. These studies demonstrate for the first time that axial diffusivity (lambda||), derived from diffusion tensor imaging (DTI) within 3 h after SCI, accurately predicts long-term locomotor behavioral recovery in mice. Female C57BL/6 mice underwent sham laminectomy or graded contusive spinal cord injuries at the T9 vertebral level (5 groups, n = 8 for each group). In-vivo DTI examinations were performed immediately after SCI. Longitudinal measurements of hindlimb locomotor recovery were obtained using the Basso mouse scale (BMS). Injured and spared regions of ventrolateral white matter (VLWM) were reliably separated in the hyperacute phase by threshold segmentation. Measurements of lambda|| were compared with histology in the hyperacute phase and 14 days after injury. The spared normal VLWM determined by hyperacute lambda|| and 14-day histology correlated well (r = 0.95). A strong correlation between hindlimb locomotor function recovery and lambda||-determined spared normal VLWM was also observed. The odds of significant locomotor recovery increased by 18% with each 1% increase in normal VLWM measured in the hyperacute phase (odds ratio = 1.18, p = 0.037). The capability of measuring subclinical changes in spinal cord physiology and murine genetic advantages offer an early window into the basic mechanisms of SCI that was not previously possible. Although significant obstacles must still be overcome to derive similar data in human patients, the path to clinical translation is foreseeable and achievable.

Globoid cell leukodystrophy is an inherited neurodegenerative disorder caused by a deficiency of the lysosomal enzyme galactosylceramidase. In both human patients and the authentic murine Twitcher model, pathological findings include demyelination as well as axonal damage in both the central and peripheral nervous system. Diffusion tensor imaging (DTI) has emerged as a powerful noninvasive technique that is sensitive to these white matter disease processes. Increases in radial diffusivity (λ⊥) and decreases in axial diffusivity (λ||) correlate with histopathological evidence of demyelination and axonal damage, respectively. Compared to age-matched, normal littermates, DTI of optic nerve and trigeminal nerve in end-stage Twitcher mice displayed a statistically significant increase in λ⊥ and decrease in λ|| consistent with previously characterized demyelination and axonal damage in these regions. In the Twitcher spinal cord, a statistically significant decrease in λ|| was identified in both the dorsal and ventrolateral white matter relative to normal controls. These results were consistent with immunofluorescent evidence of axonal damage in these areas as detected by staining for nonphosphorylated neurofilaments (SMI32). Increase in λ⊥ in Twitcher spinal cord white matter relative to normal controls reached statistical significance in the dorsal columns and approached statistical significance in the ventrolateral region. Reduced levels of myelin basic protein were detected by immunofluorescent staining in both these white matter regions in the Twitcher spinal cord. Fractional anisotropy, a nonspecific but sensitive indicator of white matter disease, was significantly reduced in optic nerve, trigeminal nerve, and throughout the spinal cord white matter of Twitcher mice relative to normal controls. This first reported application of spinal cord DTI in the setting of GLD holds potential as a noninvasive, quantitative assay of therapeutic efficacy in future treatment studies.

In vivo diffusion tensor imaging measurements of the mouse brain stem and cervical spinal cord are presented. Utilizing actively decoupled transmit/receive coils, high resolution diffusion images (117 microm x 59 microm x 500 microm) were acquired at 4.7 T within an hour. Both brain stem and cervical spine displayed clear gray-white matter contrast. The cervical spinal cord white matter showed similar tissue characteristics as seen in the thoracic cord. The coherent fiber orientation in the white matter was observed in both the brain stem and the cervical spinal cord. The results may serve as a reference for future inter-lab comparison in mouse brain stem and cervical spine diffusion measurements.

Recent studies have suggested that axonal damage, and not demyelination, is the primary cause of long-term neurological impairment in multiple sclerosis and its animal model, experimental autoimmune encephalomyelitis (EAE). The axial and radial diffusivities derived from diffusion tensor imaging have shown promise as non-invasive surrogate markers of axonal damage and demyelination, respectively. In this study, in vivo diffusion tensor imaging of the spinal cords from mice with chronic EAE was performed to determine if axial diffusivity correlated with neurological disability in EAE assessed by the commonly used clinical scoring system. Axial diffusivity in the ventrolateral white matter showed a significant negative correlation with EAE clinical score and was significantly lower in mice with severe EAE than in mice with moderate EAE. Furthermore, the greater decreases in axial diffusivity were associated with greater amounts of axonal damage, as confirmed by quantitative staining for non-phosphorylated neurofilaments (SMI32). Radial diffusivity and relative anisotropy could not distinguish between the groups of mice with moderate EAE and those with severe EAE. The results further the notion that axial diffusivity is a non-invasive marker of axonal damage in white matter and could provide the necessary link between pathology and neurological disability.

Traumatic axonal injury (TAI) is thought to be a major contributor to cognitive dysfunction following traumatic brain injury (TBI), however TAI is difficult to diagnose or characterize non-invasively. Diffusion tensor imaging (DTI) has shown promise in detecting TAI, but direct comparison to histologically-confirmed axonal injury has not been performed. In the current study, mice were imaged with DTI, subjected to a moderate cortical controlled impact injury, and re-imaged 4-6 hours and 24 hours post-injury. Axonal injury was detected by amyloid beta precursor protein (APP) and neurofilament immunohistochemistry in pericontusional white matter tracts. The severity of axonal injury was quantified using stereological methods from APP stained histological sections. Two DTI parameters – axial diffusivity and relative anisotropy – were significantly reduced in the injured, pericontusional corpus callosum and external capsule, while no significant changes were seen with conventional MRI in these regions. The contusion was easily detectible on all MRI sequences. Significant correlations were found between changes in relative anisotropy and the density of APP tained axons across mice and across subregions spanning the spatial gradient of injury. The predictive value of DTI was tested using a region with DTI changes (hippocampal commissure) and a region without DTI changes (anterior commissure). Consistent with DTI predictions, there was histological detection of axonal injury in the hippocampal commissure and none in the anterior commissure. These results demonstrate that DTI is able to detect axonal injury, and support the hypothesis that DTI may be more sensitive than conventional imaging methods for this purpose.

We examined in vivo measurements of directional diffusivity derived from diffusion tensor imaging (DTI) to study the evolution of ventrolateral white matter (VWM) changes following contusive spinal cord injury (SCI) in C57BL/6 mice at 1, 3, 7, and 14 days postinjury. Relative anisotropy maps provided excellent gray matter (GM)/white matter (WM) contrast for characterization of evolving WM injury at all time points. Longitudinal DTI measurements clearly demonstrated rostral-caudal injury asymmetry. Axial diffusivity provided a sensitive, noninvasive measure of axonal integrity within the injury epicenter and at remote levels. Quantitative measurements of axial and radial diffusivities in VWM showed a trend of acute primary axonal injury followed by delayed, subacute myelin damage at the impact site, with good histological correlation.

This study was designed to determine whether formalin fixation alters diffusion parameters in the infarcted brain. Diffusion tensor images were obtained from anesthetized mice 1 hr after middle cerebral artery occlusion and repeated after formalin fixation of brains. In live animals, there was a significant decrease in the trace of the diffusion tensor (Tr(D)) in infarcted cortex and external capsule compared with contralateral brain areas, with no change in relative anisotropy (RA). After formalin fixation, Tr(D) was reduced 30-80%. However, the Tr(D) differential present in vivo between injured and healthy tissues was lost, with Tr(D) reduced to similar values in all tissues except for the edge of the cortical infarction, where it was lower than in surrounding tissues. RA values were unchanged after fixation. This study supports the preservation of diffusion anisotropy for both healthy and injured white matter in fixed mouse brain. However, the sensitivity of water diffusion in detecting tissue injury in vivo is not preserved in fixed tissues.

Using magnetic resonance diffusion tensor imaging (DTI), the present study investigates changes in both gray and white matter in the APPsw transgenic mouse (Tg2576), a model of beta-amyloid plaque deposition associated with Alzheimer's disease (AD). DTI analyses were performed in cross-sectional groups of transgene-positive and -negative mice at 8, 12, 16, and 18 months of age to assess the magnitude of water diffusion in gray matter (i.e., Tr(D)) and changes in diffusion in white matter that may be indicative of axonal degeneration (i.e., reduced water diffusion parallel to axonal tracts, lambda(||)) and myelin degradation (i.e., increased water diffusion perpendicular to axonal tracts, lambda(perpendicular)). No appreciable changes in gray or white matter were observed between the APPsw and the age-matched control mice at 8 months of age. Reduced Tr(D) and lambda(||) were observed in gray and white matter, respectively, for the APPsw mice at ages greater than 8 months, which coincides with the time period when appreciable amyloid plaque accumulation was confirmed by ex vivo histopathological studies. The decreases in lambda(||) suggest the presence of axonal injury in multiple white matter tracts of APPsw mice. Unlike lambda(||), lambda(perpendicular) was unaltered between control and APPsw mice in most white matter tracts. However, in the corpus collosum (CC), lambda(perpendicular) increased at 16 and 18 months of age, suggesting the possibility of myelin damage in the CC at these later ages. This work demonstrates the potential for DTI as a noninvasive modality to detect evolving pathology associated with changes in tissue water diffusion properties in brain tissues.

Increasing evidence demonstrates that there is marked damage and dysfunction not only in the gray matter but also in the white matter in Alzheimer's disease (AD). In this study, transgenic mice overexpressing beta-amyloid precursor protein (APP) under control of the platelet-derived growth factor promoter (PDAPP mice) were examined using diffusion tensor magnetic resonance imaging (DTI) to evaluate the extent of white matter injury before and following the development of AD-like pathology. The profile of DTI parameters was significantly different in old PDAPP mice compared to that of old control mice following the development of AD-like pathology. No difference in DTI parameters was observed between the young PDAPP and control mice. Our results suggest that as amyloid beta (Abeta) deposition and levels increase over time in PDAPP mice, these changes lead to primary or secondary white matter injury that can be detected by DTI.

Both axon and myelin degeneration have significant impact on the long-term disability of patients with white matter disorder. However, the clinical manifestations of the neurological dysfunction caused by white matter disorders are not sufficient to determine the origin of neurological deficits. A noninvasive biological marker capable of detecting and differentiating axon and myelin degeneration would be a significant addition to currently available tools. Directional diffusivities derived from diffusion tensor imaging (DTI) have been previously proposed by this group as potential biological markers to detect and differentiate axon and myelin degeneration. To further test the hypothesis that axial (lambdaparallel) and radial (lambdaperpendicular) diffusivities reflect axon and myelin pathologies, respectively, the optic nerve was examined serially using DTI in a mouse model of retinal ischemia. A significant decrease of lambdaparallel, the putative DTI axonal marker, was observed 3 days after ischemia without concurrently detectable changes in lambdaperpendicular, the putative myelin marker. This result is consistent with histological findings of significant axonal degeneration with no detectable demyelination at 3 days after ischemia. The elevation of lambdaperpendicular observed 5 days after ischemia is consistent with histological findings of myelin degeneration at this time. These results support the hypothesis that lambdaparallel and lambdaperpendicular hold promise as specific markers of axonal and myelin injury, respectively, and, further, that the coexistence of axonal and myelin degeneration does not confound this utility.

Formalin fixation of tissue is a common laboratory practice. A direct comparison of diffusion tensor imaging (DTI) parameters from mouse brains before (in vivo) and after (ex vivo) formalin fixation is reported herein. Five diffusion indices were examined in a cohort of seven mice: relative anisotropy (RA), directional correlation (DC), trace (Tr(D)), trace-normalized axial diffusivity (D∥), and radial diffusivity (D⟂). Seven regions of interest (ROIs), including five in white matter and two in gray matter, were selected for examination. Consistent with previous findings, a significant decrease of Tr(D) was observed for all ROIs after fixation. However, water diffusion anisotropy, as defined by the indices RA, DC, D∥, and D⟂, remained unchanged after fixation. Thus, fixation does not appear to alter diffusion anisotropy in the mouse brain. This finding supports the utility of diffusion anisotropy analysis of fixed tissue. The combination of DTI measurements and standard histology may shed light on the microstructural determinants of diffusion anisotropy in normal and disease states. Magn Reson Med 50:743–748, 2003. © 2003 Wiley-Liss, Inc.

To study the architectural characteristics of white matter (WM) tracts, the directional correlation (DC), defined as the inner product of the major eigenvector of adjacent pixels, was used as a quantitative index to investigate directional similarity in WM tracts. A region-growing algorithm was employed to propagate an area from a seed point as a function of the DC threshold (DCt) to critically evaluate the directional properties of WM tracts. As the DCt was increased, more pixels were excluded from the propagated region as their DC fell below the DCt, and neighboring WM tracts could be distinguished as the area decreased. Taking the DC into account, a systematic classification routine for WM tracts was devised and tested on a mouse brain in vivo. The results show that individual WM tracts possess a high degree of directional similarity, and, by careful choice of the DCt value, the proposed classification algorithm can recognize all possible WM tracts in a given data set.

Promising treatments are being developed to promote functional recovery after spinal cord injury (SCI). Magnetic resonance imaging, specifically Diffusion Tensor Imaging (DTI) has been shown to non-invasively measure both axonal and myelin integrity following traumatic brain and SCI. A novel data-driven model-selection algorithm known as Diffusion Basis Spectrum Imaging (DBSI) has been proposed to more accurately delineate white matter injury. The objective of this study was to investigate whether DTI/DBSI changes that extend to level of the cerebral peduncle and internal capsule following a SCI could be correlated with clinical function. A prospective non-randomized cohort of 23 patients with chronic spinal cord injuries and 17 control subjects underwent cranial diffusion weighted imaging, followed by whole brain DTI and DBSI computations. Region-based analyses were performed on cerebral peduncle and internal capsule. Three subgroups of patients were included in the region-based analysis. Tract-Based Spatial Statistics (TBSS) was also applied to allow whole-brain white matter analysis between controls and all patients. Functional assessments were made using International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI) as modified by the American Spinal Injury Association (ASIA) Scale. Whole brain white matter analysis using TBSS finds no statistical difference between controls and all patients. Only cervical ASIA A/B patients in cerebral peduncle showed differences from controls in DTI and DBSI results with region-based analysis. Cervical ASIA A/B SCI patients had higher levels of axonal injury and edema/tissue loss as measured by DBSI at the level of the cerebral peduncle. DTI Fractional Anisotropy (FA), Axial Diffusivity (AD) and Radial Diffusivity (RD) was able to detect differences in cervical ASIA A/B patients, but were non-specific to pathologies. Increased water fraction indicated by DBSI non-restricted isotropic diffusion fraction in the cerebral peduncle, explains the simultaneously increased DTI AD and DTI RD values. Our results further demonstrate the utility of DTI to detect disruption in axonal integrity in white matter, yet a clear shortcoming in differentiating true axonal injury from inflammation/tissue loss. Our results suggest a preservation of axonal integrity at the cortical level and has implications for future regenerative clinical trials.

During year 2 of this funding support, we have developed more tools to demonstrate that DBSI is the future of diffusion MRI and neuroimaging modality to effectively detect underlying white matter tact pathologies noninvasively. We developed an objective quantitative histology analysis approach that allows an exact match between histology images and MRI maps. For situations where co-registered MRI-histology is not available due to data acquisition difficulties, the objective quantitative analysis of histology remains readily applicable. Current preliminary results suggest that DBSI detected axonal injury, demyelination, and inflammation closely correlated with histology findings. Most interestingly, results from the shorter time course of DBSI of optic nerve from EAE mice during acute ON indicated that visual impairment did not reflect underlying severity of optic nerve damage. DBSI detects all pathologies in optic nerves during ON.

Optic neuritis is a frequent and early symptom of multiple sclerosis (MS). Conventional magnetic resonance (MR) techniques provide means to assess multiple MS-related pathologies, including axonal injury, demyelination, and inflammation. A method to directly and non-invasively probe white-matter function could further elucidate the interplay of underlying pathologies and functional impairments. Previously, we demonstrated a significant 27% activation-associated decrease in the apparent diffusion coefficient of water perpendicular to the axonal fibers (ADC⊥) in normal C57BL/6 mouse optic nerve with visual stimulation using diffusion fMRI. Here we apply this approach to explore the relationship between visual acuity, optic nerve pathology, and diffusion fMRI in the experimental autoimmune encephalomyelitis (EAE) mouse model of optic neuritis. Visual stimulation produced a significant 25% (vs. baseline) ADC⊥ decrease in sham EAE optic nerves, while only a 7% (vs. baseline) ADC⊥ decrease was seen in EAE mice with acute optic neuritis. The reduced activation-associated ADC⊥ response correlated with post-MRI immunohistochemistry determined pathologies (including inflammation, demyelination, and axonal injury). The negative correlation between activation-associated ADC⊥ response and visual acuity was also found when pooling EAE-affected and sham groups under our experimental criteria. Results suggest that reduction in diffusion fMRI directly reflects impaired axonal-activation in EAE mice with optic neuritis. Diffusion fMRI holds promise for directly gauging in vivo white-matter dysfunction or therapeutic responses in MS patients.

The effect of extra-fiber structural and pathological components confounding diffusion tensor imaging (DTI) computation was quantitatively investigated using data generated by both Monte-Carlo simulations and tissue phantoms. Increased extent of vasogenic edema, by addition of various amount of gel to fixed normal mouse trigeminal nerves or by increasing non-restricted isotropic diffusion tensor components in Monte-Carlo simulations, significantly decreased fractional anisotropy (FA) and increased radial diffusivity, while less significantly increased axial diffusivity derived by DTI. Increased cellularity, mimicked by graded increase of the restricted isotropic diffusion tensor component in Monte-Carlo simulations, significantly decreased FA and axial diffusivity with limited impact on radial diffusivity derived by DTI. The MC simulation and tissue phantom data were also analyzed by the recently developed diffusion basis spectrum imaging (DBSI) to simultaneously distinguish and quantify the axon/myelin integrity and extra-fiber diffusion components. Results showed that increased cellularity or vasogenic edema did not affect the DBSI-derived fiber FA, axial or radial diffusivity. Importantly, the extent of extra-fiber cellularity and edema estimated by DBSI correlated with experimentally added gel and Monte-Carlo simulations. We also examined the feasibility of applying 25-direction diffusion encoding scheme for DBSI analysis on coherent white matter tracts. Results from both phantom experiments and simulations suggested that the 25-direction diffusion scheme provided comparable DBSI estimation of both fiber diffusion parameters and extra-fiber cellularity/edema extent as those by 99-direction scheme. An in vivo 25-direction DBSI analysis was performed on experimental autoimmune encephalomyelitis (EAE, an animal model of human multiple sclerosis) optic nerve as an example to examine the validity of derived DBSI parameters with post-imaging immunohistochemistry verification. Results support that in vivo DBSI using 25-direction diffusion scheme correctly reflect the underlying axonal injury, demyelination, and inflammation of optic nerves in EAE mice.

Non-invasive assessment of white-matter functionality in the nervous system would be a valuable basic neuroscience and clinical diagnostic tool. Using standard MRI techniques, a visual-stimulus-induced 27% decrease in the apparent diffusion coefficient of water perpendicular to the axonal fibers (ADC(perpendicular)) is demonstrated for C57BL/6 mouse optic nerve in vivo. No change in ADC(||) (diffusion parallel to the optic nerve fibers) was observed during visual stimulation. The stimulus-induced changes are completely reversible. A possible vascular contribution was sought by carrying out the ADC(perpendicular) measurements in hypercapnic mice with and without visual stimulus. Similar effects were seen in room-air-breathing and hypercapnic animals. The in vivo stimulus-induced ADC(perpendicular) decreases are roughly similar to literature reports for ex vivo rat optic nerve preparations under conditions of osmotic swelling. The experimental results strongly suggest that osmotic after-effects of nerve impulses through the axonal fibers are responsible for the observed ADC decrease.

We describe a cardiac gated high in-plane resolution axial human cervical spinal cord diffusion tensor imaging (DTI) protocol. Multiple steps were taken to optimize both image acquisition and image processing. The former includes slice-by-slice cardiac triggering and individually tiltable slices. The latter includes (i) iterative 2D retrospective motion correction, (ii) image intensity outlier detection to minimize the influence of physiological noise, (iii) a non-linear DTI estimation procedure incorporating non-negative eigenvalue priors, and (iv) tract-specific region-of-interest (ROI) identification based on an objective geometry reference. Using these strategies in combination, radial diffusivity (λ(⊥)) was reproducibly measured in white matter (WM) tracts (adjusted mean [95% confidence interval]=0.25 [0.22, 0.29] μm(2)/ms), lower than previously reported λ(⊥) values in the in vivo human spinal cord DTI literature. Radial diffusivity and fractional anisotropy (FA) measured in WM varied from rostral to caudal as did mean translational motion, likely reflecting respiratory motion effect. Given the considerable sensitivity of DTI measurements to motion artifact, we believe outlier detection is indispensable in spinal cord diffusion imaging. We also recommend using a mixed-effects model to account for systematic measurement bias depending on cord segment.

Multiple sclerosis is characterized by inflammatory demyelination and irreversible axonal injury leading to permanent neurological disabilities. Diffusion tensor imaging demonstrates an improved capability over standard magnetic resonance imaging to differentiate axon from myelin pathologies. However, the increased cellularity and vasogenic oedema associated with inflammation cannot be detected or separated from axon/myelin injury by diffusion tensor imaging, limiting its clinical applications. A novel diffusion basis spectrum imaging, capable of characterizing water diffusion properties associated with axon/myelin injury and inflammation, was developed to quantitatively reveal white matter pathologies in central nervous system disorders. Tissue phantoms made of normal fixed mouse trigeminal nerves juxtaposed with and without gel were employed to demonstrate the feasibility of diffusion basis spectrum imaging to quantify baseline cellularity in the absence and presence of vasogenic oedema. Following the phantom studies, in vivo diffusion basis spectrum imaging and diffusion tensor imaging with immunohistochemistry validation were performed on the corpus callosum of cuprizone treated mice. Results demonstrate that in vivo diffusion basis spectrum imaging can effectively separate the confounding effects of increased cellularity and/or grey matter contamination, allowing successful detection of immunohistochemistry confirmed axonal injury and/or demyelination in middle and rostral corpus callosum that were missed by diffusion tensor imaging. In addition, diffusion basis spectrum imaging-derived cellularity strongly correlated with numbers of cell nuclei determined using immunohistochemistry. Our findings suggest that diffusion basis spectrum imaging has great potential to provide non-invasive biomarkers for neuroinflammation, axonal injury and demyelination coexisting in multiple sclerosis.

In adult rats, locomotor deficits following a contusive thoracic spinal cord injury (SCI) are caused primarily by white matter loss/dysfunction at the epicenter. This loss/dysfunction decreases descending input from the brain and cervical spinal cord, and decreases ascending signals in long propriospinal, spinocerebellar and somatosensory pathways, among many others. Predicting the long-term functional consequences of a contusive injury acutely, without knowledge of the injury severity is difficult due to the temporary flaccid paralysis and loss of reflexes that accompanies spinal shock. It is now well known that recovery of high quality hindlimb stepping requires only 12-15% spared white matter at the epicenter, but that forelimb-hindlimb coordination and precision stepping (grid or horizontal ladder) requires substantially more trans-contusion communication. In order to translate our understanding of the neural substrates for functional recovery in the rat to the clinical arena, common outcome measures and imaging modalities are required. In the current study we furthered the exploration of one of these approaches, diffusion tensor magnetic resonance imaging (DTI), a technique now used commonly to image the brain in clinical research but rarely used diagnostically or prognostically for spinal cord injury. In the adult rat model of SCI, we found that hyper-acute (

Background Multiple Sclerosis (MS) is characterized by the pathological trafficking of leukocytes into the central nervous system (CNS). Using the murine MS model, experimental autoimmune encephalomyelitis (EAE), we previously demonstrated that antagonism of the chemokine receptor CXCR7 blocks endothelial cell sequestration of CXCL12, thereby enhancing the abluminal localization of CXCR4-expressing leukocytes. CXCR7 antagonism led to decreased parenchymal entry of leukocytes and amelioration of ongoing disease during EAE. Of note, animals that received high doses of CXCR7 antagonist recovered to baseline function, as assessed by standard clinical scoring. Because functional recovery reflects axonal integrity, we utilized diffusion tensor imaging (DTI) to evaluate axonal injury in CXCR7 antagonist- versus vehicle-treated mice after recovery from EAE. Methods C57BL6/J mice underwent adoptive transfer of MOG-reactive Th1 cells and were treated daily with either CXCR7 antagonist or vehicle for 28 days; and then evaluated by DTI to assess for axonal injury. After imaging, spinal cords underwent histological analysis of myelin and oligodendrocytes via staining with luxol fast blue (LFB), and immunofluorescence for myelin basic protein (MBP) and glutathione S-transferase-π (GST-π). Detection of non-phosphorylated neurofilament H (NH-F) was also performed to detect injured axons. Statistical analysis for EAE scores, DTI parameters and non-phosphorylated NH-F immunofluorescence were done by ANOVA followed by Bonferroni post-hoc test. For all statistical analysis a p < 0.05 was considered significant. Results In vivo DTI maps of spinal cord ventrolateral white matter (VLWM) axial diffusivities of naïve and CXCR7 antagonist-treated mice were indistinguishable, while vehicle-treated animals exhibited decreased axial diffusivities. Quantitative differences in injured axons, as assessed via detection of non-phosphorylated NH-F, were consistent with axial diffusivity measurements. Overall, qualitative myelin content and presence of oligodendrocytes were similar in all treatment groups, as expected by their radial diffusivity values. Quantitative assessment of persistent inflammatory infiltrates revealed significant decreases within the parenchyma of CXCR7 antagonist-treated mice versus controls. Conclusions These data suggest that CXCR7 antagonism not only prevents persistent inflammation but also preserves axonal integrity. Thus, targeting CXCR7 modifies both disease severity and recovery during EAE, suggesting a role for this molecule in both phases of disease.

In vivo diffusion tensor imaging (DTI) derived indices have been demonstrated to quantify accurately white-matter injury after contusion spinal cord injury (SCI) in rodents. In general, a full diffusion tensor analysis requires the acquisition of diffusion-weighted images (DWI) along at least six independent directions of diffusion-sensitizing gradients. Thus, DTI measurements of the rodent central nervous system are time consuming. In this study, diffusion indices derived using the two-direction DWI (parallel and perpendicular to axonal tracts) were compared with those obtained using six-direction DTI in a mouse model of SCI. It was hypothesized that the mouse spinal cord ventral-lateral white-matter (VLWM) tracts, T8–T10 in this study, aligned with the main magnet axis (z) allowing the apparent diffusion coefficient parallel and perpendicular to the axis of the spine to be derived with diffusion-weighting gradients in the z and y axes of the magnet coordinate respectively. Compared with six-direction full tensor DTI, two-direction DWI provided comparable diffusion indices in mouse spinal cords. The measured extent of spared white matter after injury, estimated by anisotropy indices, using both six-direction DTI and two-direction DWI were in close agreement and correlated well with histological staining and behavioral assessment. The results suggest that the two-direction DWI derived indices may be used, with significantly reduced imaging time, to estimate accurately spared white matter in mouse SCI.