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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.

Crucial transitions in cancer-including tumor initiation, local expansion, metastasis, and therapeutic resistance-involve complex interactions between cells within the dynamic tumor ecosystem. Transformative single-cell genomics technologies and spatial multiplex in situ methods now provide an opportunity to interrogate this complexity at unprecedented resolution. The Human Tumor Atlas Network (HTAN), part of the National Cancer Institute (NCI) Cancer Moonshot Initiative, will establish a clinical, experimental, computational, and organizational framework to generate informative and accessible three-dimensional atlases of cancer transitions for a diverse set of tumor types. This effort complements both ongoing efforts to map healthy organs and previous large-scale cancer genomics approaches focused on bulk sequencing at a single point in time. Generating single-cell, multiparametric, longitudinal atlases and integrating them with clinical outcomes should help identify novel predictive biomarkers and features as well as therapeutically relevant cell types, cell states, and cellular interactions across transitions. The resulting tumor atlases should have a profound impact on our understanding of cancer biology and have the potential to improve cancer detection, prevention, and therapeutic discovery for better precision-medicine treatments of cancer patients and those at risk for cancer.

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.

Diffusion basis spectrum imaging (DBSI) combines discrete anisotropic diffusion tensors and the spectrum of isotropic diffusion tensors to model the underlying multiple sclerosis (MS) pathologies. We used clinical MS subtypes as a surrogate of underlying pathologies to assess DBSI as a biomarker of pathology in 55 individuals with MS. Restricted isotropic fraction (reflecting cellularity) and fiber fraction (representing apparent axonal density) were the most important DBSI metrics to classify MS using brain white matter lesions. These DBSI metrics outperformed lesion volume. When analyzing the normal‐appearing corpus callosum, the most significant DBSI metrics were fiber fraction, radial diffusivity (reflecting myelination), and nonrestricted isotropic fraction (representing edema). This study provides preliminary evidence supporting the ability of DBSI as a potential noninvasive biomarker of MS neuropathology.

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.

OBJECTIVE: Basal ganglia regions are part of the brain’s reward-processing networks and are implicated in the neurobiology of obesity and eating disorders. This study examines basal ganglia microstructural properties in adults with and without obesity. METHODS: Diffusion basis spectrum imaging (DBSI) images were analyzed to obtain putative imaging markers of neuroinflammation. Relationships between basal ganglia DBSI metrics and reward sensitivity and eating behaviors were also explored. RESULTS: A total of 46 participants (25 people with obesity; aged 20–40 years; 37 women) were included. Relative to the people in the normal-weight group, people with obesity had smaller caudate and larger nucleus accumbens (NAcc) volumes (p < 0.05) and lower DBSI fiber fraction (reflecting apparent axonal/dendrite density) in NAcc and putamen, higher DBSI nonrestricted fraction (reflecting tissue edema) in NAcc and caudate, and higher DBSI restricted fraction (reflecting tissue cellularity) in putamen (p ≤ 0.01, all). Increased emotional and reward eating behaviors were related to lower NAcc axonal/dendrite density and greater tissue edema (p ≤ 0.002). The relationships between emotional eating and adiposity measures were mediated by NAcc microstructure. CONCLUSIONS: These findings provide evidence that microstructural alterations in basal ganglia relate to obesity and insights linking NAcc microstructure and eating behavior in adults.

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.

Highlights • DBSI quantified optic nerve axon loss in EAE mice. • DBSI detected axonal preservation with ten-week fingolimod treatment. • DBSI could serve as an outcome measure to profile disease progression., Objective To prospectively determine whether diffusion basis spectrum imaging (DBSI) detects, differentiates and quantitates coexisting inflammation, demyelination, axonal injury and axon loss in mice with optic neuritis (ON) due to experimental autoimmune encephalomyelitis (EAE), and to determine if DBSI accurately measures effects of fingolimod on underlying pathology. Methods EAE was induced in 7-week-old C57BL/6 female mice. Visual acuity (VA) was assessed daily to detect onset of ON after which daily oral-treatment with either fingolimod (1 mg/kg) or saline was given for ten weeks. In vivo DBSI scans of optic nerves were performed at baseline, 2-, 6- and 10-weeks post treatment. DBSI-derived metrics including restricted isotropic diffusion tensor fraction (putatively reflecting cellularity), non-restricted isotropic diffusion tensor fraction (putatively reflecting vasogenic edema), DBSI-derived axonal volume, axial diffusivity, λ∥ (putatively reflecting axonal integrity), and increased radial diffusivity, λ⊥ (putatively reflecting demyelination). Mice were killed immediately after the last DBSI scan for immunohistochemical assessment. Results Optic nerves of fingolimod-treated mice exhibited significantly better (p 0.05) from the baseline values in fingolimod-treated mice. Transient DBSI-λ∥ decrease and DBSI-λ⊥ increase were detected during Fingolimod treatment. DBSI-derived metrics assessed in vivo significantly correlated (p

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.

Background The blood–brain and blood–tumor barriers (BBB and BTB), which restrict the entry of most drugs into the brain and tumor, respectively, are a significant challenge in the treatment of glioblastoma. Laser interstitial thermal therapy (LITT) is a minimally invasive surgical technique increasingly used clinically for tumor cell ablation. Recent evidence suggests that LITT might locally disrupt BBB integrity, creating a potential therapeutic window of opportunity to deliver otherwise brain-impermeant agents. Methods We established a LITT mouse model to test if laser therapy can increase BBB/BTB permeability in vivo. Mice underwent orthotopic glioblastoma tumor implantation followed by LITT in combination with BBB tracers or the anticancer drug doxorubicin. BBB/BTB permeability was measured using fluorimetry, microscopy, and immunofluorescence. An in vitro endothelial cell model was also used to corroborate findings. Results LITT substantially disrupted the BBB and BTB locally, with increased permeability up to 30 days after the intervention. Remarkably, molecules as large as human immunoglobulin extravasated through blood vessels and permeated laser-treated brain tissue and tumors. Mechanistically, LITT decreased tight junction integrity and increased brain endothelial cell transcytosis. Treatment of mice bearing glioblastoma tumors with LITT and adjuvant doxorubicin, which is typically brain-impermeant, significantly increased animal survival. Conclusions Together, these results suggest that LITT can locally disrupt the BBB and BTB, enabling the targeted delivery of systemic therapies, including, potentially, antibody-based agents.

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

PurposeGlioblastoma (GBM) is one of the deadliest cancers with no cure. While conventional MRI has been widely adopted for examining GBM clinically, accurate neuroimaging assessment of tumor histopathology for improved diagnosis, surgical planning, and treatment evaluation, remains an unmet need in the clinical management of GBMs.Experimental DesignWe employ a novel Diffusion Histology Imaging (DHI) approach, combining diffusion basis spectrum imaging (DBSI) and machine learning, to detect, differentiate, and quantify areas of high cellularity, tumor necrosis, and tumor infiltration in GBM.ResultsGd-enhanced T1W or hyper-intense FLAIR failed to reflect the morphological complexity underlying tumor in GBM patients. Contrary to the conventional wisdom that apparent diffusion coefficient (ADC) negatively correlates with increased tumor cellularity, we demonstrate disagreement between ADC and histologically confirmed tumor cellularity in glioblastoma specimens, whereas DBSI-derived restricted isotropic diffusion fraction positively correlated with tumor cellularity in the same specimens. By incorporating DBSI metrics as classifiers for a supervised machine learning algorithm, we accurately predicted high tumor cellularity, tumor necrosis, and tumor infiltration with 87.5%, 89.0% and 93.4% accuracy, respectively.ConclusionOur results suggest that DHI could serve as a favorable alternative to current neuroimaging techniques for guiding biopsy or surgery as well as monitoring therapeutic response in the treatment of glioblastoma.Translational RelevanceCurrent clinical diagnosis, surgical planning, and assessment of treatment response for GBM patients relies heavily on gadolinium-enhanced T1-weighted MRI, which is non-specific for tumor growth and merely reflects a disrupted blood-brain barrier. The complex tumor microenvironment and spatial heterogeneity make GBM difficult to characterize using current clinical imaging modalities. In this study, we developed a novel imaging technique to characterize and accurately predict key histological features of GBM - high tumor cellularity, tumor necrosis, and tumor infiltration. While further validation in a larger cohort of patients is needed, the current proof-of-concept approach could provide a solution to resolve important clinical questions such as the identification of true tumor progression vs. pseudoprogression or radiation necrosis.

Human obesity is associated with low-grade chronic systemic inflammation, alterations in brain structure and function, and cognitive impairment. Rodent models of obesity show that high-calorie diets cause brain inflammation (neuroinflammation) in multiple regions, including the hippocampus, and impairments in hippocampal-dependent memory tasks. To determine if similar effects exist in humans with obesity, we applied Diffusion Basis Spectrum Imaging (DBSI) to evaluate neuroinflammation and axonal integrity. We examined diffusion-weighted magnetic resonance imaging (MRI) data in two independent cohorts of obese and non-obese individuals (Cohort 1: 25 obese/21 non-obese; Cohort 2: 18 obese/41 non-obese). We applied Tract-based Spatial Statistics (TBSS) to allow whole-brain white matter (WM) analyses and compare DBSI-derived isotropic and anisotropic diffusion measures between the obese and non-obese groups. In both cohorts, the obese group had significantly greater DBSI-derived restricted fraction (DBSI-RF; an indicator of neuroinflammation-related cellularity), and significantly lower DBSI-derived fiber fraction (DBSI-FF; an indicator of apparent axonal density) in several WM tracts (all corrected p < 0.05). Moreover, using region of interest analyses, average DBSI-RF and DBSI-FF values in the hippocampus were significantly greater and lower, respectively, in obese relative to non-obese individuals (Cohort 1: p = 0.045; Cohort 2: p = 0.008). Hippocampal DBSI-FF and DBSI-RF and amygdalar DBSI-FF metrics related to cognitive performance in Cohort 2. In conclusion, these findings suggest that greater neuroinflammation-related cellularity and lower apparent axonal density are associated with human obesity and cognitive performance. Future studies are warranted to determine a potential role for neuroinflammation in obesity-related cognitive impairment.

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.

BACKGROUND Immune effector cell associated neurotoxicity syndrome (ICANS) remains a devastating, frequent complication of chimeric antigen receptor (CAR) T cell therapy for advanced-stage hematologic malignancies. Symptoms range from encephalopathy and headaches to aphasia, strokes, and diffuse cerebral edema. Persistent mild cognitive symptoms have also been reported. Unfortunately, the underlying pathophysiology driving ICANS is poorly understood. Current proposed models center on systemic inflammatory changes leading to endothelial dysfunction, blood-brain barrier (BBB) breakdown, and systemic cytokine and/or monocytes infiltration into the central nervous system (CNS). However, these models do not integrate predisposing risk factors for the development of ICANS. We previously demonstrated that pre-infusion plasma neurofilament light chain (NfL), a marker of neurodegeneration, may predict development of ICANS. Early elevations in NfL suggest development of ICANS is also related to pre-existing neuroaxonal injury. The longitudinal relationship between latent neuroaxonal injury, blood brain barrier (BBB) integrity, neuroinflammation, and cognition remains unknown. METHODS This prospective, observational trial examines the relationship between multi-modal (blood, cerebrospinal fluid (CSF), neuroimaging) biomarkers and cognition in a cohort of twenty patients undergoing standard-of-care CAR T cellular therapy. Biomarkers for neural injury include blood and CSF NfL and volumetric measures derived from structural magnetic resonance imaging (MRI). Biomarkers for neuroinflammation include blood and CSF glial fibrillary acidic protein (GFAP) and qualification of white matter hyper-intensity burden on MRI. BBB integrity will be quantified using the serum/CSF albumin ratio. Finally, neuropsychological performance testing will assay cognitive performance across multiple cortical domains including attention, memory, and executive function. Participants will undergo a baseline (pre-infusion) examination, followed by evaluation (blood draw, voluntary lumbar puncture, MRI scan, and cognitive testing) on post-infusion day 3 (D3), D30, D90, and D180. The primary outcome is percent change in a given biomarker level. RESULTS/CONCLUSIONS This ongoing trial has 2 of 20 planned participants enrolled.

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.

STUDY DESIGN A prospective cohort study. OBJECTIVE In this study, we employed diffusion basis spectrum imaging (DBSI) to quantitatively assess axon/myelin injury, cellular inflammation, and axonal loss of cervical spondylotic myelopathy (CSM) spinal cords. SUMMARY OF BACKGROUND DATA A major shortcoming in the management of CSM is the lack of an effective diagnostic approach to stratify treatments and to predict outcomes. No current clinical diagnostic imaging approach is capable of accurately reflecting underlying spinal cord pathologies. METHODS Seven patients with mild (mJOA ≥15), five patients with moderate (14≥mJOA ≥11), and two patients with severe (mJOA

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.

In vivo human optic nerve diffusion magnetic resonance imaging (dMRI) is technically challenging with two outstanding issues not yet well addressed: (i) non-linear optic nerve movement, independent of head motion, and (ii) effect from partial-volumed cerebrospinal fluid or interstitial fluid such as in edema. In this work, we developed a non-linear optic nerve registration algorithm for improved volume alignment in axial high resolution optic nerve dMRI. During eyes-closed dMRI data acquisition, optic nerve dMRI measurements by diffusion tensor imaging (DTI) with and without free water elimination (FWE), and by diffusion basis spectrum imaging (DBSI), as well as optic nerve motion, were characterized in healthy adults at various locations along the posterior-to-anterior dimension. Optic nerve DTI results showed consistent trends in microstructural parametric measurements along the posterior-to-anterior direction of the entire intraorbital optic nerve, while the anterior portion of the intraorbital optic nerve exhibited the largest spatial displacement. Multi-compartmental dMRI modeling, such as DTI with FWE or DBSI, was less subject to spatially dependent biases in diffusivity and anisotropy measurements in the optic nerve which corresponded to similar spatial distributions of the estimated fraction of isotropic diffusion components. DBSI results derived from our clinically feasible (∼10 min) optic nerve dMRI protocol in this study are consistent with those from small animal studies, which provides the basis for evaluating the utility of multi-compartmental dMRI modeling in characterizing coexisting pathophysiology in human optic neuropathies.

Pressures in the intracranial, intraocular and intravascular spaces are clinically useful for the diagnosis and management of traumatic brain injury, glaucoma and hypertension, respectively. Conventional devices for measuring these pressures require surgical extraction after a relevant operational time frame. Bioresorbable sensors, by contrast, eliminate this requirement, thereby minimizing the risk of infection, decreasing the costs of care and reducing distress and pain for the patient. However, the operational lifetimes of bioresorbable pressure sensors available at present fall short of many clinical needs. Here, we present materials, device structures and fabrication procedures for bioresorbable pressure sensors with lifetimes exceeding those of previous reports by at least tenfold. We demonstrate measurement accuracies that compare favourably to those of the most sophisticated clinical standards for non-resorbable devices by monitoring intracranial pressures in rats for 25 days. Assessments of the biodistribution of the constituent materials, complete blood counts, blood chemistry and magnetic resonance imaging compatibility confirm the biodegradability and clinical utility of the device. Our findings establish routes for the design and fabrication of bioresorbable pressure monitors that meet requirements for clinical use.

Despite 253,000 spinal cord injury (SCI) patients in the United States, little is known about how SCI affects brain networks. Spinal MRI provides only structural information with no insight into functional connectivity. Resting-state functional MRI (RS-fMRI) quantifies network connectivity through the identification of resting-state networks (RSNs) and allows detection of functionally relevant changes during disease. Given the robust network of spinal cord afferents to the brain, we hypothesized that SCI produces meaningful changes in brain RSNs. RS-fMRIs and functional assessments were performed on 10 SCI subjects. Blood oxygen-dependent RS-fMRI sequences were acquired. Seed-based correlation mapping was performed using five RSNs: default-mode (DMN), dorsal-attention (DAN), salience (SAL), control (CON), and somatomotor (SMN). RSNs were compared with normal control subjects using false-discovery rate-corrected two way t tests. SCI reduced brain network connectivity within the SAL, SMN, and DMN and disrupted anti-correlated connectivity between CON and SMN. When divided into separate cohorts, complete but not incomplete SCI disrupted connectivity within SAL, DAN, SMN and DMN and between CON and SMN. Finally, connectivity changed over time after SCI: the primary motor cortex decreased connectivity with the primary somatosensory cortex, the visual cortex decreased connectivity with the primary motor cortex, and the visual cortex decreased connectivity with the sensory parietal cortex. These unique findings demonstrate the functional network plasticity that occurs in the brain as a result of injury to the spinal cord. Connectivity changes after SCI may serve as biomarkers to predict functional recovery following an SCI and guide future therapy.

Hippocampal CA1 inflammation and dendritic loss are common in epilepsy. Quantitative detection of coexisting brain inflammation and injury could be beneficial in monitoring disease progression and assessing therapeutic efficacy. In this work, we used conventional diffusion tensor imaging (DTI, known to detect axonal injury and demyelination) and a novel diffusion basis spectrum imaging (DBSI, known to detect axonal injury, demyelination, and inflammation) to detect hippocampal CA1 lesions resulting from neuronal dendritic injury/loss and concomitant inflammation in Theiler's murine encephalomyelitis virus (TMEV)-induced seizure mice. Following the cross-sectional ex vivo diffusion magnetic resonance imaging measurements, immunohistochemistry was performed to validate DTI and DBSI findings. Both DTI and DBSI detected immunohistochemistry-confirmed dendritic injury in the hippocampal CA1 region. Additionally, DBSI-derived restricted isotropic diffusion tensor fraction correlated with 4',6-diamidine-2'-phenylindole dihydrochloride (DAPI)-positive nucleus counts, and DBSI-derived fiber fraction correlated with dendrite density assessed by microtubule-associated protein 2 staining. DTI-derived fractional anisotropy (FA) correlated with dendrite density and negatively correlated with DAPI-positive nucleus counts. Although both DTI and DBSI detected hippocampal injury/inflammation, DTI-FA was less specific than DBSI-derived pathological metrics for hippocampal CA1 dendritic injury and inflammation in TMEV-induced seizure mice.

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.

Manganese-enhanced MRI (MEMRI) with topical loading of MnCl2 provides optic nerve enhancement comparable to that seen by intravitreal injection. However, the impact of this novel and non-invasive Mn(2+) loading method on visual function requires further assessments. The objective of this study is to determine the optimal topical Mn(2+) loading dosage for MEMRI and to assess visual function after MnCl2 loading. Intravitreal administration was performed to compare the two approaches of MnCl2 loading. Twenty-four hours after topical loading of 0, 0.5, 0.75, and 1 M MnCl2 , T1 -weighted, T2-weighted, diffusion tensor imaging and visual acuity (VA) assessments were performed to determine the best topical loading dosage for MEMRI measurements and to assess the integrity of retinas and optic nerves. Mice were perfusion fixed immediately after in vivo experiments for hematoxylin and eosin and immunohistochemistry staining. Topical loading of 1 M MnCl2 damaged the retinal photoreceptor layer with no detectable damage to retina ganglion cell layers or prechiasmatic optic nerves. For the topical loading, 0.75 M MnCl2 was required to see sufficient enhancement of the optic nerve. At this concentration the visual function was significantly affected, followed by a slow recovery. Intravitreal injection (0.25 μL of 0.2 M MnCl2 ) slightly affected VA, with full recovery a day later. To conclude, intravitreal MnCl2 injection provides more reproducible results with less adverse side-effects than topical loading.

PurposeTo evaluate optic nerve diffusion tensor imaging (DTI) parameters in glaucoma patients and controls, and to correlate DTI parameters with the rim area obtained with Heidelberg retina tomography (HRT) and with the severity of glaucomatous damage using the Glaucoma Staging System.DesignPilot study.MethodsTwenty-seven patients with glaucoma and 12 control subjects underwent DTI and HRT imaging. Main outcome measures included: fractional anisotropy, mean diffusivity, axial diffusivity, radial diffusivity, HRT rim area, and Glaucoma Staging System stage.ResultsIn group comparison, mean diffusivity (1.33 vs. 0.91 μm/ms, P=0.0002), axial diffusivity (1.70 vs. 1.43 μm/ms, P=0.036), and radial diffusivity (1.24 vs. 0.71 μm/ms, P0.05).ConclusionsDTI may be a useful technique for detection and evaluation of glaucomatous damage in the optic nerve, particularly for patients in whom conventional imaging and perimetry are not possible. Future studies are needed to evaluate how DTI parameters change longitudinally with glaucomatous damage within the visual pathways and address cerebrospinal fluid partial volume effects in diffusion tensor quantification, especially for patients with advanced glaucoma stage.

Fingolimod (FTY720) is an orally available sphingosine-1-phosphate (S1P) receptor modulator reducing relapse frequency in patients with relapsing–remitting multiple sclerosis (RRMS). In addition to immunosuppression, neuronal protection by FTY720 has also been suggested, but remains controversial. Axial and radial diffusivities derived from in vivo diffusion tensor imaging (DTI) were employed as noninvasive biomarkers of axonal injury and demyelination to assess axonal protection by FTY720 in experimental autoimmune encephalomyelitis (EAE) mice. EAE was induced through active immunization of C57BL/6 mice using myelin oligodendrocyte glycoprotein peptide 35–55 (MOG35–55). We evaluated both the prophylactic and therapeutic treatment effect of FTY720 at doses of 3 and 10 mg/kg on EAE mice by daily clinical scoring and end-point in vivo DTI. Prophylactic administration of FTY720 suppressed the disease onset and prevented axon and myelin damage when compared with EAE mice without treatment. Therapeutic treatment by FTY720 did not prevent EAE onset, but reduced disease severity, improving axial and radial diffusivity towards the control values without statistical significance. Consistent with previous findings, in vivo DTI-derived axial and radial diffusivity correlated with clinical scores in EAE mice. The results support the use of in vivo DTI as an effective outcome measure for preclinical drug development. Copyright © 2013 John Wiley & Sons, Ltd.

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.

This study assessed the tissue integrity of major cervical cord tracts by using diffusion tensor imaging (DTI) to determine the relationship with specific clinical functions carried by those tracts.This was a cross-sectional study of 37 patients with multiple sclerosis or neuromyelitis optica with remote cervical cord disease. Finger vibratory thresholds, 25-foot timed walk (25FTW), 9-hole peg test (9HPT), and Expanded Disability Status Scale were determined. DTI covered cervical regions C1 through C6 with 17 5-mm slices (0.9 × 0.9 mm in-plane resolution). Regions of interest included posterior columns (PCs) and lateral corticospinal tracts (CSTs). Hierarchical linear mixed-effect modeling included covariates of disease subtype (multiple sclerosis vs neuromyelitis optica), disease duration, and sex.Vibration thresholds were associated with radial diffusivity (RD) and fractional anisotropy (FA) in the PCs (both p0.01), but not CSTs (RD, p = 0.29; FA, p = 0.14). RD and FA in PCs, and RD in CSTs were related to 9HPT (each p0.0001). 25FTW was associated with RD and FA in PCs (p0.0001) and RD in CSTs (p = 0.008). Expanded Disability Status Scale was related to RD and FA in PCs and CSTs (p0.0001). Moderate/severe impairments in 9HPT (p = 0.006) and 25FTW (p = 0.017) were more likely to show combined moderate/severe tissue injury within both PCs and CSTs by DTI.DTI can serve as an imaging biomarker of spinal cord tissue injury at the tract level. RD and FA demonstrate strong and consistent relationships with clinical outcomes, specific to the clinical modality.

Many brain diseases have been linked to abnormal oxygen metabolism and blood perfusion; nevertheless, there is still a lack of robust diagnostic tools for directly imaging cerebral metabolic rate of oxygen (CMRO(2)) and cerebral blood flow (CBF), as well as the oxygen extraction fraction (OEF) that reflects the balance between CMRO(2) and CBF. This study employed the recently developed in vivo (17)O MR spectroscopic imaging to simultaneously assess CMRO(2), CBF and OEF in the brain using a preclinical middle cerebral arterial occlusion mouse model with a brief inhalation of (17)O-labeled oxygen gas. The results demonstrated high sensitivity and reliability of the noninvasive (17)O-MR approach for rapidly imaging CMRO(2), CBF and OEF abnormalities in the ischemic cortex of the MCAO mouse brain. It was found that in the ischemic brain regions both CMRO(2) and CBF were substantially lower than that of intact brain regions, even for the mildly damaged brain regions that were unable to be clearly identified by the conventional MRI. In contrast, OEF was higher in the MCAO affected brain regions. This study demonstrates a promising (17)O MRI technique for imaging abnormal oxygen metabolism and perfusion in the diseased brain regions. This (17)O MRI technique is advantageous because of its robustness, simplicity, noninvasiveness and reliability: features that are essential to potentially translate it to human patients for early diagnosis and monitoring of treatment efficacy.

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.

Globoid-cell leukodystrophy (GLD) is an inherited demyelinating disease caused by the deficiency of the lysosomal enzyme galactosylceramidase (GALC). A previous study in the murine model of GLD (twitcher) demonstrated a dramatic synergy between CNS-directed adeno-associated virus 2/5 (AAV2/5) gene therapy and myeloreductive bone marrow transplantation (BMT). However, the mechanism by which these two disparate therapeutic approaches synergize is not clear. In addition, the therapeutic efficacy may have been limited since the CNS-directed gene therapy was restricted to the forebrain and thalamus. In the current study, intrathecal and intracerebellar injections were added to the therapeutic regimen and the mechanism of synergy between BMT and gene therapy was determined. Although AAV2/5 alone provided supraphysiological levels of GALC activity and reduced psychosine levels in both the brain and spinal cord, it significantly increased CNS inflammation. Bone marrow transplantation alone provided essentially no GALC activity to the CNS and did not reduce psychosine levels. When AAV2/5 is combined with BMT, there are sustained improvements in motor function and the median life span is increased to 123 d (range, 92–282 d) compared with 41 d in the untreated twitcher mice. Interestingly, addition of BMT virtually eliminates both the disease and AAV2/5-associated inflammatory response. These data suggest that the efficacy of AAV2/5-mediated gene therapy is limited by the associated inflammatory response and BMT synergizes with AAV2/5 by modulating inflammation.

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.

Retinal degeneration-1 (rd1) mice are animal models of retinitis pigmentosa, a blinding disease caused by photoreceptor cell degeneration. This study aims to determine magnetic resonance imaging (MRI) changes in retinas of 1- and 3-month-old rd1 mice. Apparent diffusion coefficient in retina was measured using diffusion MRI. The blood-retinal barrier leakage was evaluated using gadolinium-diethylenetriaminepentaacetic acid-enhanced T(1)-weighted MRI before and after systemic gadolinium-diethylenetriaminepentaacetic acid injection. Photoreceptor degeneration in rd1 retina was apparent by decreased retinal thickness and loss of water diffusion anisotropy in both 1- and 3-month-old rd1 mice. Furthermore, statistically significant increase of mean retinal apparent diffusion coefficient and gadolinium-diethylenetriaminepentaacetic acid-enhanced T(1)-weighted MRI signals were observed in 3-month-old rd1 mice comparing with age-matched wild-type mice. Together, these data suggest that MRI parameter changes can signature common pathological changes in photoreceptor-degenerated eyes, particularly blood-retinal barrier leakage-induced retinal edema.

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.

Diffusion tensor MRI (DTI) is a method for the noninvasive assessment of cellular organization and integrity in vivo. In this study, in vivo DTI was performed to demonstrate its ability to reflect photoreceptor cell alignment in adult C57BL/6 wild-type mice. Age-matched retinal degeneration 1 (rd1) mice were employed as a negative control, i.e. loss of the photoreceptor cell layer. In wild-type mice, DTI-estimated cell alignment suggests that the MR-detected outer retinal layer comprises cells aligning perpendicular to the retinal surface, consistent with the known organization of photoreceptor cells. The MR-detected outer retinal layer exhibits a lower apparent diffusion coefficient and higher fractional anisotropy than the other two MR-detected retinal layers (p

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.

Objective: B cells and the humoral immune system have been implicated in the pathogenesis of multiple sclerosis (MS). This study sought to evaluate the efficacy, safety, and tolerability of add-on therapy with rituximab, a monoclonal antibody that depletes circulating B cells, in subjects with relapsing MS with breakthrough disease defined by clinical and MRI activity (Class III evidence). Methods: Thirty subjects with a relapse within the past 18 months despite use of an injectable disease-modifying agent, and with at least 1 gadolinium-enhancing (GdE) lesion on any of 3 pretreatment MRIs, received rituximab administered at 375 mg/m 2 weekly × 4 doses. Three monthly posttreatment brain MRI scans were obtained beginning 12 weeks after the first infusion. Multiple Sclerosis Functional Composite (MSFC) and Expanded Disability Status Scale (EDSS) were obtained at baseline and throughout the posttreatment follow-up. Results: GdE lesions were reduced after treatment with rituximab, with 74% of posttreatment MRI scans being free of GdE activity compared with 26% free of GdE activity at baseline ( p p = 0.02). EDSS remained stable. Conclusion: Rituximab add-on therapy was effective based upon blinded radiologic endpoints in this phase II study. In combination with standard injectable therapies, rituximab was well-tolerated with no serious adverse events. B-cell–modulating therapy remains a potential option for treatment of patients with relapsing MS with an inadequate response to standard injectable therapies. Classification of evidence: This study provides Class III evidence that add-on rituximab reduces gadolinium-enhancing brain lesions in multiple sclerosis.

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.