Diffusion basis spectrum imaging detects pathological alterations in substantia nigra and white matter tracts with early-stage Parkinson's disease.

OBJECTIVES: Using diffusion basis spectrum imaging (DBSI) to examine the microstructural changes in the substantia nigra (SN) and global white matter (WM) tracts of patients with early-stage PD. METHODS: Thirty-seven age- and sex-matched patients with early-stage PD and 22 healthy controls (HCs) were enrolled in this study. All participants underwent clinical assessments and diffusion-weighted MRI scans, analyzed by diffusion tensor imaging (DTI) and DBSI to assess the pathologies of PD in SN and global WM tracts. RESULTS: The lower DTI fraction anisotropy (FA) was seen in SN of PD patients (PD: 0.316 ± 0.034 vs HCs: 0.331 ± 0.019, p = 0.015). The putative cells marker-DBSI-restricted fraction (PD: 0.132 ± 0.051 vs HCs: 0.105 ± 0.039, p = 0.031) and the edema/extracellular space marker-DBSI non-restricted-fraction (PD: 0.150 ± 0.052 vs HCs: 0.122 ± 0.052, p = 0.020) were both significantly higher and the density of axons/dendrites marker-DBSI fiber-fraction (PD: 0.718 ± 0.073 vs HCs: 0.773 ± 0.071, p = 0.003) was significantly lower in SN of PD patients. DBSI-restricted fraction in SN was negatively correlated with HAMA scores (r = - 0.501, p = 0.005), whereas DTI-FA was not correlated with any clinical scales. In WM tracts, only higher DTI axial diffusivity (AD) among DTI metrics was found in multiple WM regions in PD, while lower DBSI fiber-fraction and higher DBSI non-restricted-fraction were detected in multiple WM regions. DBSI non-restricted-fraction in both left fornix (cres)/stria terminalis (r = -0.472, p = 0.004) and right posterior thalamic radiation (r = - 0.467, p = 0.005) was negatively correlated with MMSE scores. CONCLUSION: DBSI could potentially detect and quantify the extent of inflammatory cell infiltration, fiber/dendrite loss, and edema in both SN and WM tracts in patients with early-stage PD, a finding remains to be further investigated through more extensive longitudinal DBSI analysis. CLINICAL RELEVANCE STATEMENT: Our study shows that DBSI indexes can potentially detect early-stage PD's pathological changes, with a notable ability to distinguish between inflammation and edema. This implies that DBSI has the potential to be an imaging biomarker for early PD diagnosis. KEY POINTS: • Diffusion basis spectrum imaging detected higher restricted-fraction in Parkinson's disease, potentially reflecting inflammatory cell infiltration. • Diffusion basis spectrum imaging detected higher non-restricted-fraction and lower fiber-fraction in Parkinson's disease, indicating the presence of edema and/or dopaminergic neuronal/dendritic loss. • Diffusion basis spectrum imaging metrics correlated with non-motor symptoms, suggesting its potential diagnostic role to detect early-stage PD dysfunctions.

Feasibility of postoperative diffusion-weighted imaging to assess representations of spinal cord microstructure in cervical spondylotic myelopathy.

OBJECTIVE: Diffusion basis spectrum imaging (DBSI) has shown promise in evaluating cervical spinal cord structural changes in patients with cervical spondylotic myelopathy (CSM). DBSI may also be valuable in the postoperative setting by serially tracking spinal cord microstructural changes following decompressive cervical spine surgery. Currently, there is a paucity of studies investigating this topic, likely because of challenges in resolving signal distortions from spinal instrumentation. Therefore, the objective of this study was to assess the feasibility of DBSI metrics extracted from the C3 spinal level to evaluate CSM patients postoperatively. METHODS: Fifty CSM patients and 20 healthy controls were enrolled in a single-center prospective study between 2018 and 2020. All patients and healthy controls underwent preoperative and postoperative diffusion-weighted MRI (dMRI) at a 2-year follow-up. All CSM patients underwent decompressive cervical surgery. The modified Japanese Orthopaedic Association (mJOA) score was used to categorize CSM patients as having mild, moderate, or severe myelopathy. DBSI metrics were extracted from the C3 spinal cord level to minimize image artifact and reduce partial volume effects. DBSI anisotropic tensors evaluated white matter tracts through fractional anisotropy, axial diffusivity, radial diffusivity, and fiber fraction. DBSI isotropic tensors assessed extra-axonal pathology through restricted and nonrestricted fractions. RESULTS: Of the 50 CSM patients, both baseline and postoperative dMR images with sufficient quality for analysis were obtained in 27 patients. These included 15 patients with mild CSM (mJOA scores 15-17), 7 with moderate CSM (scores 12-14), and 5 with severe CSM (scores 0-11), who were followed up for a mean of 23.5 (SD 4.1, range 11-31) months. All preoperative C3-level DBSI measures were significantly different between CSM patients and healthy controls (p < 0.05), except DBSI fractional anisotropy (p = 0.31). At the 2-year follow-up, the same significance pattern was found between CSM patients and healthy controls, except DBSI radial diffusivity was no longer statistically significant (p = 0.75). When assessing change (i.e., postoperative - preoperative values) in C3-level DBSI measures, CSM patients exhibited significant decreases in DBSI radial diffusivity (p = 0.02), suggesting improvement in myelin integrity (i.e., remyelination) at the 2-year follow-up. Among healthy controls, there was no significant difference in DBSI metrics over time. CONCLUSIONS: DBSI metrics derived from dMRI at the C3 spinal level can be used to provide meaningful insights into representations of the spinal cord microstructure of CSM patients at baseline and 2-year follow-up. DBSI may have the potential to characterize white matter tract recovery and inform outcomes following decompressive cervical surgery for CSM.

Characterization of multiple sclerosis neuroinflammation and neurodegeneration with relaxation and diffusion basis spectrum imaging.

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.

Non-invasive quantification of inflammation, axonal and myelin injury in multiple sclerosis.

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 <0.001) and between lesions' centre and rim (P < 0.001) for all the metrics. When comparing the three subject groups in terms of metrics derived from corpus callosum normal appearing white matter and T2-hyperintense lesions, a significant difference was found between healthy controls and relapsing-remitting patients for all metrics except restricted fraction and fractional anisotropy; between healthy controls and progressive patients for all metrics except restricted fraction and between relapsing-remitting and progressive multiple sclerosis patients for all metrics except fibres and restricted fractions (P ranging from 0.05 to <0.001 for all). Significant associations were found between corpus callosum normal-appearing white matter fibres fraction/non-restricted fraction and the Symbol Digit Modality Test (respectively, r = 0.35, P = 0.043; r = -0.35, P = 0.046), and between black holes radial diffusivity and Expanded Disability Status Score (r = 0.59, P = 0.002). We showed the feasibility of diffusion basis spectrum imaging metrics at 7 T, confirmed the role of the derived metrics in the characterization of lesions and normal appearing white matter tissue in different stages of the disease and demonstrated their clinical relevance. Thus, suggesting that diffusion basis spectrum imaging is a promising tool to investigate multiple sclerosis pathophysiology, monitor disease progression and treatment response.

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

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

MRI-based assessment of function and dysfunction in myelinated axons.

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 T2 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 T2 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.

Incorporating non-linear alignment and multi-compartmental modeling for improved human optic nerve diffusion imaging.

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.

Histopathological correlation of diffusion basis spectrum imaging metrics of a biopsy-proven inflammatory demyelinating brain lesion: A brief report.

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.

Diffusion MRI quantifies early axonal loss in the presence of nerve swelling.

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.

Signal-to-noise ratio-enhancing joint reconstruction for improved diffusion imaging of mouse spinal cord white matter injury.

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.

Differentiation and quantification of inflammation, demyelination and axon injury or loss in multiple sclerosis.

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.

Axonal transport rate decreased at the onset of optic neuritis in EAE mice.

Optic neuritis is frequently the first symptom of multiple sclerosis (MS), an inflammatory demyelinating neurodegenerative disease. Impaired axonal transport has been considered as an early event of neurodegenerative diseases. However, few studies have assessed the integrity of axonal transport in MS or its animal models. We hypothesize that axonal transport impairment occurs at the onset of optic neuritis in experimental autoimmune encephalomyelitis (EAE) mice. In this study, we employed manganese-enhanced MRI (MEMRI) to assess axonal transport in optic nerves in EAE mice at the onset of optic neuritis. Axonal transport was assessed as (a) optic nerve Mn(2+) accumulation rate (in % signal change/h) by measuring the rate of increased total optic nerve signal enhancement, and (b) Mn(2+) transport rate (in mm/h) by measuring the rate of change in optic nerve length enhanced by Mn(2+). Compared to sham-treated healthy mice, Mn(2+) accumulation rate was significantly decreased by 19% and 38% for EAE mice with moderate and severe optic neuritis, respectively. The axonal transport rate of Mn(2+) was significantly decreased by 43% and 65% for EAE mice with moderate and severe optic neuritis, respectively. The degree of axonal transport deficit correlated with the extent of impaired visual function and diminished microtubule-associated tubulins, as well as the severity of inflammation, demyelination, and axonal injury at the onset of optic neuritis.

Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema.

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.

Diffusion fMRI detects white-matter dysfunction in mice with acute optic neuritis.

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.

Manganese-enhanced MRI (MEMRI) via topical loading of Mn(2+) significantly impairs mouse visual acuity: a comparison with intravitreal injection.

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.

Diffusion basis spectrum imaging detects and distinguishes coexisting subclinical inflammation, demyelination and axonal injury in experimental autoimmune encephalomyelitis mice.

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 Hao-Fountain syndrome protein USP7 regulates neuronal connectivity in the brain via a novel p53-independent ubiquitin signaling pathway.

Precise control of protein ubiquitination is essential for brain development, and hence, disruption of ubiquitin signaling networks can lead to neurological disorders. Mutations of the deubiquitinase USP7 cause the Hao-Fountain syndrome (HAFOUS), characterized by developmental delay, intellectual disability, autism, and aggressive behavior. Here, we report that conditional deletion of USP7 in excitatory neurons in the mouse forebrain triggers diverse phenotypes including sensorimotor deficits, learning and memory impairment, and aggressive behavior, resembling clinical features of HAFOUS. USP7 deletion induces neuronal apoptosis in a manner dependent of the tumor suppressor p53. However, most behavioral abnormalities in USP7 conditional mice persist despite p53 loss. Strikingly, USP7 deletion in the brain perturbs the synaptic proteome and dendritic spine morphogenesis independently of p53. Integrated proteomics analysis reveals that the neuronal USP7 interactome is enriched for proteins implicated in neurodevelopmental disorders and specifically identifies the RNA splicing factor Ppil4 as a novel neuronal substrate of USP7. Knockdown of Ppil4 in cortical neurons impairs dendritic spine morphogenesis, phenocopying the effect of USP7 loss on dendritic spines. These findings reveal a novel USP7-Ppil4 ubiquitin signaling link that regulates neuronal connectivity in the developing brain, with implications for our understanding of the pathogenesis of HAFOUS and other neurodevelopmental disorders.

Diffusion basis spectrum imaging and diffusion tensor imaging predict persistent black hole formation in multiple sclerosis.

BACKGROUND AND OBJECTIVES: Diffusion basis spectrum imaging (DBSI) extracts multiple anisotropic and isotropic diffusion tensors, providing greater histopathologic specificity than diffusion tensor imaging (DTI). Persistent black holes (PBH) represent areas of severe tissue damage in multiple sclerosis (MS), and a high PBH burden is associated with worse MS disability. This study evaluated the ability of DBSI and DTI to predict which acute contrast-enhancing lesions (CELs) would persist as T1 hypointensities (i.e. PBHs) 12 months later. We expected that a higher radial diffusivity (RD), representing demyelination, and higher DBSI-derived isotropic non-restricted fraction, representing edema and increased extracellular space, of the acute CEL would increase the likelihood of future PBH development. METHODS: In this prospective cohort study, relapsing MS patients with ≥1 CEL(s) underwent monthly MRI scans for 4 to 6 months until gadolinium resolution. DBSI and DTI metrics were quantified when the CEL was most conspicuous during the monthly scans. To determine whether the CEL became a PBH, a follow-up MRI was performed at least 12 months after the final monthly scan. RESULTS: The cohort included 20 MS participants (median age 33 years; 13 women) with 164 CELs. Of these, 59 (36 %) CELs evolved into PBHs. At Gd-max, DTI RD and AD of all CELs increased, and both metrics were significantly elevated for CELs which became PBHs, as compared to non-black holes (NBHs). DTI RD above 0.74 conferred an odds ratio (OR) of 7.76 (CI 3.77-15.98) for a CEL becoming a PBH (AUC 0.80, CI 0.73-0.87); DTI axial diffusivity (AD) above 1.22 conferred an OR of 7.32 (CI 3.38-15.86) for becoming a PBH (AUC 0.75, CI 0.66-0.83). DBSI RD and AD did not predict PBH development in a multivariable model. At Gd-max, DBSI restricted fraction decreased and DBSI non-restricted fraction increased in all CELs, and both metrics were significantly different for CELs which became PBHs, as compared to NBHs. A CEL with a DBSI non-restricted fraction above 0.45 had an OR of 4.77 (CI 2.35-9.66) for becoming a PBH (AUC 0.74, CI 0.66-0.81); a CEL with a DBSI restricted fraction below 0.07 had an OR of 9.58 (CI 4.59-20.02) for becoming a PBH (AUC 0.80, 0.72-0.87). CONCLUSION: Our findings suggest that greater degree of edema/extracellular space in a CEL is a predictor of tissue destruction, as evidenced by PBH evolution.

Diffusion MRI Metrics Characterize Postoperative Clinical Outcomes After Surgery for Cervical Spondylotic Myelopathy.

BACKGROUND AND OBJECTIVES: Advanced diffusion-weighted MRI (DWI) modeling, such as diffusion tensor imaging (DTI) and diffusion basis spectrum imaging (DBSI), may help guide rehabilitation strategies after surgical decompression for cervical spondylotic myelopathy (CSM). Currently, however, postoperative DWI is difficult to interpret, owing to signal distortions from spinal instrumentation. Therefore, we examined the relationship between postoperative DTI/DBSI-extracted from the rostral C3 spinal level-and clinical outcome measures at 2-year follow-up after decompressive surgery for CSM. METHODS: Fifty patients with CSM underwent complete clinical and DWI evaluation-followed by DTI/DBSI analysis-at baseline and 2-year follow-up. Clinical outcomes included the modified Japanese Orthopedic Association score and comprehensive patient-reported outcomes. DTI metrics included apparent diffusion coefficient, fractional anisotropy, axial diffusivity, and radial diffusivity. DBSI metrics evaluated white matter tracts through fractional anisotropy, fiber fraction, axial diffusivity, and radial diffusivity as well as extra-axonal pathology through restricted and nonrestricted fraction. Cross-sectional Spearman's correlations were used to compare postoperative DTI/DBSI metrics with clinical outcomes. RESULTS: Twenty-seven patients with CSM, including 15, 7, and 5 with mild, moderate, and severe disease, respectively, possessed complete baseline and postoperative DWI scans. At 2-year follow-up, there were 10 significant correlations among postoperative DBSI metrics and postoperative clinical outcomes compared with 3 among postoperative DTI metrics. Of the 13 significant correlations, 7 involved the neck disability index (NDI). The strongest relationships were between DBSI axial diffusivity and NDI (r = 0.60, P < .001), DBSI fiber fraction and NDI (rs = -0.58, P < .001), and DBSI restricted fraction and NDI (rs = 0.56, P < .001). The weakest correlation was between DTI apparent diffusion coefficient and NDI (r = 0.35, P = .02). CONCLUSION: Quantitative measures of spinal cord microstructure after surgery correlate with postoperative neurofunctional status, quality of life, and pain/disability at 2 years after decompressive surgery for CSM. In particular, DBSI metrics may serve as meaningful biomarkers for postoperative disease severity for patients with CSM.

Spinal cord metrics derived from diffusion MRI: improvement in prognostication in cervical spondylotic myelopathy compared with conventional MRI.

OBJECTIVE: A major shortcoming in optimizing care for patients with cervical spondylotic myelopathy (CSM) is the lack of robust quantitative imaging tools offered by conventional MRI. Advanced MRI modalities, such as diffusion MRI (dMRI), including diffusion tensor imaging (DTI) and diffusion basis spectrum imaging (DBSI), may help address this limitation by providing granular evaluations of spinal cord microstructure. METHODS: Forty-seven patients with CSM underwent comprehensive clinical assessments and dMRI, followed by DTI and DBSI modeling. Conventional MRI metrics included 10 total qualitative and quantitative assessments of spinal cord compression in both the sagittal and axial planes. The dMRI metrics included 12 unique measures including anisotropic tensors, reflecting axonal diffusion, and isotropic tensors, describing extraaxonal diffusion. The primary outcome was the modified Japanese Orthopaedic Association (mJOA) score measured at 2 years postoperatively. Extreme gradient boosting-supervised classification algorithms were used to classify patients into disease groups and to prognosticate surgical outcomes at 2-year follow-up. RESULTS: Forty-seven patients with CSM, including 24 (51%) with a mild mJOA score, 12 (26%) with a moderate mJOA score, and 11 (23%) with a severe mJOA score, as well as 21 control subjects were included. In the classification task, the traditional MRI metrics correctly assigned patients to healthy control versus mild CSM versus moderate/severe CSM cohorts, with an accuracy of 0.647 (95% CI 0.64-0.65). In comparison, the DTI model performed with an accuracy of 0.52 (95% CI 0.51-0.52) and the DBSI model's accuracy was 0.81 (95% CI 0.808-0.814). In the prognostication task, the traditional MRI metrics correctly predicted patients with CSM who improved at 2-year follow-up on the basis of change in mJOA, with an accuracy of 0.58 (95% CI 0.57-0.58). In comparison, the DTI model performed with an accuracy of 0.62 (95% CI 0.61-0.62) and the DBSI model had an accuracy of 0.72 (95% CI 0.718-0.73). CONCLUSIONS: Conventional MRI is a powerful tool to assess structural abnormality in CSM but is inherently limited in its ability to characterize spinal cord tissue injury. The results of this study demonstrate that advanced imaging techniques, namely DBSI-derived metrics from dMRI, provide granular assessments of spinal cord microstructure that can offer better diagnostic and prognostic utility.