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.

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 detects subclinical traumatic optic neuropathy in a closed-head impact mouse model of traumatic brain injury

Introduction

Traumatic optic neuropathy (TON) is the optic nerve injury secondary to brain trauma leading to visual impairment and vision loss. Current clinical visual function assessments often fail to detect TON due to slow disease progression and clinically silent lesions resulting in potentially delayed or missed treatment in patients with traumatic brain injury (TBI).

Methods

Diffusion basis spectrum imaging (DBSI) is a novel imaging modality that can potentially fill this diagnostic gap. Twenty-two, 16-week-old, male mice were equally divided into a sham or TBI (induced by moderate Closed-Head Impact Model of Engineered Rotational Acceleration device) group. Briefly, mice were anesthetized with isoflurane (5% for 2.5 min followed by 2.5% maintenance during injury induction), had a helmet placed over the head, and were placed in a holder prior to a 2.1-joule impact. Serial visual acuity (VA) assessments, using the Virtual Optometry System, and DBSI scans were performed in both groups of mice. Immunohistochemistry (IHC) and histological analysis of optic nerves was also performed after in vivo MRI.

Results

VA of the TBI mice showed unilateral or bilateral impairment. DBSI of the optic nerves exhibited bilateral involvement. IHC results of the optic nerves revealed axonal loss, myelin injury, axonal injury, and increased cellularity in the optic nerves of the TBI mice. Increased DBSI axon volume, decreased DBSI λ||, and elevated DBSI restricted fraction correlated with decreased SMI-312, decreased SMI-31, and increased DAPI density, respectively, suggesting that DBSI can detect coexisting pathologies in the optic nerves of TBI mice.

Conclusion

DBSI provides an imaging modality capable of detecting subclinical changes of indirect TON in TBI mice.

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.

Childhood obesity is linked to putative neuroinflammation in brain white matter, hypothalamus, and striatum

Neuroinflammation is both a consequence and driver of overfeeding and weight gain in rodent obesity models. Advances in magnetic resonance imaging (MRI) enable investigations of brain microstructure that suggests neuroinflammation in human obesity. To assess the convergent validity across MRI techniques and extend previous findings, we used diffusion basis spectrum imaging (DBSI) to characterize obesity-associated alterations in brain microstructure in 601 children (age 9-11 years) from the Adolescent Brain Cognitive DevelopmentSM Study. Compared with children with normal-weight, greater DBSI restricted fraction (RF), reflecting neuroinflammation-related cellularity, was seen in widespread white matter in children with overweight and obesity. Greater DBSI-RF in hypothalamus, caudate nucleus, putamen, and, in particular, nucleus accumbens, correlated with higher baseline body mass index and related anthropometrics. Comparable findings were seen in the striatum with a previously reported restriction spectrum imaging (RSI) model. Gain in waist circumference over 1 and 2 years related, at nominal significance, to greater baseline RSI-assessed restricted diffusion in nucleus accumbens and caudate nucleus, and DBSI-RF in hypothalamus, respectively. Here we demonstrate that childhood obesity is associated with microstructural alterations in white matter, hypothalamus, and striatum. Our results also support the reproducibility, across MRI methods, of findings of obesity-related putative neuroinflammation in children.

Diffusion Basis Spectrum Imaging Identifies Clinically Relevant Disease Phenotypes of Cervical Spondylotic Myelopathy

STUDY DESIGN

Prospective cohort study.

OBJECTIVE

Apply a machine learning clustering algorithm to baseline imaging data to identify clinically relevant cervical spondylotic myelopathy (CSM) patient phenotypes.

SUMMARY OF BACKGROUND DATA

A major shortcoming in improving care for CSM patients is the lack of robust quantitative imaging tools to guide surgical decision-making. Advanced diffusion-weighted magnetic resonance imaging (MRI) techniques, such as diffusion basis spectrum imaging (DBSI), may help address this limitation by providing detailed evaluations of white matter injury in CSM.

METHODS

Fifty CSM patients underwent comprehensive clinical assessments and diffusion-weighted MRI, followed by DBSI modeling. DBSI metrics included fractional anisotropy, axial and radial diffusivity, fiber fraction, extra-axonal fraction, restricted fraction, and nonrestricted fraction. Neurofunctional status was assessed by the modified Japanese Orthopedic Association, myelopathic disability index, and disabilities of the arm, shoulder, and hand. Quality-of-life was measured by the 36-Item Short Form Survey physical component summary and mental component summary. The neck disability index was used to measure self-reported neck pain. K-means clustering was applied to baseline DBSI measures to identify 3 clinically relevant CSM disease phenotypes. Baseline demographic, clinical, radiographic, and patient-reported outcome measures were compared among clusters using one-way analysis of variance (ANOVA).

RESULTS

Twenty-three (55%) mild, 9 (21%) moderate, and 10 (24%) severe myelopathy patients were enrolled. Eight patients were excluded due to MRI data of insufficient quality. Of the remaining 42 patients, 3 groups were generated by k-means clustering. When compared with clusters 1 and 2, cluster 3 performed significantly worse on the modified Japanese Orthopedic Association and all patient-reported outcome measures (P<0.001), except the 36-Item Short Form Survey mental component summary (P>0.05). Cluster 3 also possessed the highest proportion of non-Caucasian patients (43%, P=0.04), the worst hand dynamometer measurements (P<0.05), and significantly higher intra-axonal axial diffusivity and extra-axonal fraction values (P<0.001).

CONCLUSIONS

Using baseline imaging data, we delineated a clinically meaningful CSM disease phenotype, characterized by worse neurofunctional status, quality-of-life, and pain, and more severe imaging markers of vasogenic edema.

LEVEL OF EVIDENCE

II.

Diffusion basis spectrum imaging predicts long-term clinical outcomes following surgery in cervical spondylotic myelopathy

BACKGROUND CONTEXT

A major shortcoming in improving care for cervical spondylotic myelopathy (CSM) patients is the lack of robust quantitative imaging tools to guide surgical decision-making. Diffusion basis spectrum imaging (DBSI), an advanced diffusion-weighted MRI technique, provides objective assessments of white matter tract integrity that may help prognosticate outcomes in patients undergoing surgery for CSM.

PURPOSE

To examine the ability of DBSI to predict clinically important CSM outcome measures at 2-years follow-up.

STUDY DESIGN/SETTING

Prospective cohort study.

PATIENT SAMPLE

Patients undergoing decompressive cervical surgery for CSM.

OUTCOME MEASURES

Neurofunctional status was assessed by the mJOA, MDI, and DASH. Quality-of-life was measured by the SF-36 PCS and SF-36 MCS. The NDI evaluated self-reported neck pain, and patient satisfaction was assessed by the NASS satisfaction index.

METHODS

Fifty CSM patients who underwent cervical decompressive surgery were enrolled. Preoperative DBSI metrics assessed white matter tract integrity through fractional anisotropy, fiber fraction, axial diffusivity, and radial diffusivity. To evaluate extra-axonal diffusion, DBSI measures restricted and nonrestricted fractions. Patient-reported outcome measures were evaluated preoperatively and up to 2-years follow-up. Support vector machine classification algorithms were used to predict surgical outcomes at 2-years follow-up. Specifically, three feature sets were built for each of the seven clinical outcome measures (eg, mJOA), including clinical only, DBSI only, and combined feature sets.

RESULTS

Twenty-seven mild (mJOA 15-17), 12 moderate (12-14) and 11 severe (0-11) CSM patients were enrolled. Twenty-four (60%) patients underwent anterior decompressive surgery compared with 16 (40%) posterior approaches. The mean (SD) follow-up was 23.2 (5.6, range 6.1-32.8) months. Feature sets built on combined data (ie, clinical+DBSI metrics) performed significantly better for all outcome measures compared with those only including clinical or DBSI data. When predicting improvement in the mJOA, the clinically driven feature set had an accuracy of 61.9 [61.6, 62.5], compared with 78.6 [78.4, 79.2] in the DBSI feature set, and 90.5 [90.2, 90.8] in the combined feature set.

CONCLUSIONS

When combined with key clinical covariates, preoperative DBSI metrics predicted improvement after surgical decompression for CSM with high accuracy for multiple outcome measures. These results suggest that DBSI may serve as a noninvasive imaging biomarker for CSM valuable in guiding patient selection and informing preoperative counseling.

LEVEL OF EVIDENCE

II.

Diffusion basis spectrum imaging as an adjunct to conventional MRI leads to earlier diagnosis of high-grade glioma tumor progression versus treatment effect

Background

Following chemoradiotherapy for high-grade glioma (HGG), it is often challenging to distinguish treatment changes from true tumor progression using conventional MRI. The diffusion basis spectrum imaging (DBSI) hindered fraction is associated with tissue edema or necrosis, which are common treatment-related changes. We hypothesized that DBSI hindered fraction may augment conventional imaging for earlier diagnosis of progression versus treatment effect.

Methods

Adult patients were prospectively recruited if they had a known histologic diagnosis of HGG and completed standard-of-care chemoradiotherapy. DBSI and conventional MRI data were acquired longitudinally beginning 4 weeks post-radiation. Conventional MRI and DBSI metrics were compared with respect to their ability to diagnose progression versus treatment effect.

Results

Twelve HGG patients were enrolled between August 2019 and February 2020, and 9 were ultimately analyzed (5 progression, 4 treatment effect). Within new or enlarging contrast-enhancing regions, DBSI hindered fraction was significantly higher in the treatment effect group compared to progression group (P = .0004). Compared to serial conventional MRI alone, inclusion of DBSI would have led to earlier diagnosis of either progression or treatment effect in 6 (66.7%) patients by a median of 7.7 (interquartile range = 0-20.1) weeks.

Conclusions

In the first longitudinal prospective study of DBSI in adult HGG patients, we found that in new or enlarging contrast-enhancing regions following therapy, DBSI hindered fraction is elevated in cases of treatment effect compared to those with progression. Hindered fraction map may be a valuable adjunct to conventional MRI to distinguish tumor progression from treatment effect.

Diffusion Basis Spectrum Imaging Provides Insights Into Cervical Spondylotic Myelopathy Pathology

BACKGROUND

Diffusion basis spectrum imaging (DBSI) is a noninvasive quantitative imaging modality that may improve understanding of cervical spondylotic myelopathy (CSM) pathology through detailed evaluations of spinal cord microstructural compartments.

OBJECTIVE

To determine the utility of DBSI as a biomarker of CSM disease severity.

METHODS

A single-center prospective cohort study enrolled 50 patients with CSM and 20 controls from 2018 to 2020. All patients underwent clinical evaluation and diffusion-weighted MRI, followed by diffusion tensor imaging and DBSI analyses. Diffusion-weighted MRI metrics assessed white matter integrity by fractional anisotropy, axial diffusivity, radial diffusivity, and fiber fraction. In addition, DBSI further evaluates extra-axonal changes by isotropic restricted and nonrestricted fraction. Including an intra-axonal diffusion compartment, DBSI improves estimations of axonal injury through intra-axonal axial diffusivity. Patients were categorized into mild, moderate, and severe CSM using modified Japanese Orthopedic Association classifications. Imaging parameters were compared among patient groups using independent samples t tests and ANOVA.

RESULTS

Twenty controls, 27 mild (modified Japanese Orthopedic Association 15-17), 12 moderate (12-14), and 11 severe (0-11) patients with CSM were enrolled. Diffusion tensor imaging and DBSI fractional anisotropy, axial diffusivity, and radial diffusivity were significantly different between control and patients with CSM ( P < .05). DBSI fiber fraction, restricted fraction, and nonrestricted fraction were significantly different between groups ( P < .01). DBSI intra-axonal axial diffusivity was lower in mild compared with moderate (mean difference [95% CI]: 1.1 [0.3-2.1], P < .01) and severe (1.9 [1.3-2.4], P < .001) CSM.

CONCLUSION

DBSI offers granular data on white matter tract integrity in CSM that provide novel insights into disease pathology, supporting its potential utility as a biomarker of CSM disease progression.

Twelve Weeks of Intermittent Caloric Restriction Diet Mitigates Neuroinflammation in Midlife Individuals with Multiple Sclerosis: A Pilot Study with Implications for Prevention of Alzheimer's Disease

BACKGROUND

Multiple sclerosis (MS) is a prototype neuroinflammatory disorder with increasingly recognized role for neurodegeneration. Most first-line treatments cannot prevent the progression of neurodegeneration and the resultant disability. Interventions can improve symptoms of MS and might provide insights into the underlying pathology.

OBJECTIVE

To investigate the effect of intermittent caloric restriction on neuroimaging markers of MS.

METHODS

We randomized ten participants with relapsing remitting MS to either a 12-week intermittent calorie restriction (iCR) diet (n = 5) or control (n = 5). Cortical thickness and volumes were measured through FreeSurfer, cortical perfusion was measured by arterial spin labeling and neuroinflammation through diffusion basis spectrum imaging.

RESULTS

After 12 weeks of iCR, brain volume increased in the left superior and inferior parietal gyri (p: 0.050 and 0.049, respectively) and the banks of the superior temporal sulcus (p: 0.01). Similarly in the iCR group, cortical thickness improved in the bilateral medial orbitofrontal gyri (p: 0.04 and 0.05 in right and left, respectively), the left superior temporal gyrus (p: 0.03), and the frontal pole (p: 0.008) among others. Cerebral perfusion decreased in the bilateral fusiform gyri (p: 0.047 and 0.02 in right and left, respectively) and increased in the bilateral deep anterior white matter (p: 0.03 and 0.013 in right and left, respectively). Neuroinflammation, demonstrated through hindered and restricted water fractions (HF and RF), decreased in the left optic tract (HF p: 0.02), and the right extreme capsule (RF p: 0.007 and HF p: 0.003).

CONCLUSION

These pilot data suggest therapeutic effects of iCR in improving cortical volume and thickness and mitigating neuroinflammation in midlife adults with MS.

Utility of Diffusion Basis Spectrum Imaging in Quantifying Baseline Disease Severity and Prognosis of Cervical Spondylotic Myelopathy

STUDY DESIGN

Prospective cohort study.

OBJECTIVE

The aim was to assess the association between diffusion tensor imaging (DTI) and diffusion basis spectrum imaging (DBSI) measures and cervical spondylotic myelopathy (CSM) clinical assessments at baseline and two-year follow-up.

SUMMARY OF BACKGROUND DATA

Despite advancements in diffusion-weighted imaging, few studies have examined associations between diffusion magnetic resonance imaging (MRI) markers and CSM-specific clinical domains at baseline and long-term follow-up.

MATERIALS AND METHODS

A single-center prospective cohort study enrolled 50 CSM patients who underwent surgical decompression and 20 controls from 2018 to 2020. At initial evaluation, all patients underwent diffusion-weighted MRI acquisition, followed by DTI and DBSI analyses. Diffusion-weighted MRI metrics assessed white matter integrity by fractional anisotropy, axial diffusivity, radial diffusivity, and fiber fraction. To improve estimations of intra-axonal anisotropic diffusion, DBSI measures intra-/extra-axonal fraction and intra-axonal axial diffusivity. DBSI also evaluates extra-axonal isotropic diffusion by restricted and nonrestricted fraction. Clinical assessments were performed at baseline and two-year follow-up and included the modified Japanese Orthopedic Association (mJOA); 36-Item Short Form Survey physical component summary (SF-36 PCS); SF-36 mental component summary; neck disability index; myelopathy disability index; and disability of the arm, shoulder, and hand. Pearson correlation coefficients were computed to compare associations between DTI/DBSI and clinical measures. A False Discovery Rate correction was applied for multiple comparisons testing.

RESULTS

At baseline presentation, of 36 correlations analyzed between DTI metrics and CSM clinical measures, only DTI fractional anisotropy showed a positive correlation with SF-36 PCS ( r =0.36, P =0.02). In comparison, there were 30/81 (37%) significant correlations among DBSI and clinical measures. Increased DBSI axial diffusivity, intra-axonal axial diffusivity, intra-axonal fraction, restricted fraction, and extra-axonal anisotropic fraction were associated with worse clinical presentation (decreased mJOA; SF-36 PCS/mental component summary; and increased neck disability index; myelopathy disability index; disability of the arm, shoulder, and hand). At latest follow-up, increased preoperative DBSI intra-axonal axial diffusivity and extra-axonal anisotropic fraction were significantly correlated with improved mJOA.

CONCLUSIONS

This findings demonstrate that DBSI measures may reflect baseline disease burden and long-term prognosis of CSM as compared with DTI. With further validation, DBSI may serve as a noninvasive biomarker following decompressive surgery.

LEVEL OF EVIDENCE

3.

NIMG-43. DIFFUSION BASIS SPECTRUM IMAGING DISTINGUISHES HIGH-GRADE GLIOMA TREATMENT EFFECT FROM TUMOR PROGRESSION

BACKGROUND

Following standard-of-care chemoradiation therapy for high-grade glioma, it is often challenging to distinguish treatment changes from true tumor progression using conventional magnetic resonance imaging (MRI). Diffusion basis spectrum imaging (DBSI) uses a data-driven multiple-tensor modeling approach to disentangle specific histologic components and structural features present within individual imaging voxels, offering an opportunity to noninvasively differentiate treatment effect from tumor progression. This represents the first study of in vivo longitudinal DBSI for brain tumors in patients.

METHODS

Adult patients were prospectively recruited who met the criteria of known pathological diagnosis of high-grade glioma or glioblastoma (WHO grade III-IV) and undergoing or completing standard-of-care radiation therapy with concurrent chemotherapy. DBSI and conventional MRI data were acquired longitudinally beginning with a 4-week post-radiation therapy MRI until progression as defined by standard RANO criteria or biopsy. DBSI analyses were performed with isotropic diffusion profiles defined as restricted fraction (0 ≤ D ≤ 1.0 μm2/ms) and hindered fraction (1.0 &lt; D ≤ 1.5 μm2/ms).

RESULTS

Eleven patients with contrast-enhancing high-grade gliomas were enrolled between June 2019 and March 2020, with final DBSI data obtained in November 2020. Of these, eight patients had tumor progression, two had treatment effect, and one had stable disease during the study period. Within the contrast-enhancing regions, the DBSI hindered fraction map demonstrated hypointensity for all cases of tumor progression, and hyperintensity for cases of treatment effect. DBSI-based biomarkers were present 0.7 to 12.0 months (median 2.4, IQR 2.8) before definitive diagnosis of treatment effect or tumor progression using conventional methods of MRI and/or biopsy.

CONCLUSIONS

DBSI hindered fraction can distinguish new contrast-enhancing lesions in the setting of high-grade glioma as treatment effect or tumor progression in advance of conventional MRI. Future work will incorporate machine learning algorithms to further improve DBSI-based predictions of tumor histopathology.

Analysis of combined clinical and diffusion basis spectrum imaging metrics to predict the outcome of chronic cervical spondylotic myelopathy following cervical decompression surgery

OBJECTIVE

Cervical spondylotic myelopathy (CSM) is the most common cause of chronic spinal cord injury, a significant public health problem. Diffusion tensor imaging (DTI) is a neuroimaging technique widely used to assess CNS tissue pathology and is increasingly used in CSM. However, DTI lacks the needed accuracy, precision, and recall to image pathologies of spinal cord injury as the disease progresses. Thus, the authors used diffusion basis spectrum imaging (DBSI) to delineate white matter injury more accurately in the setting of spinal cord compression. It was hypothesized that the profiles of multiple DBSI metrics can serve as imaging outcome predictors to accurately predict a patient's response to therapy and his or her long-term prognosis. This hypothesis was tested by using DBSI metrics as input features in a support vector machine (SVM) algorithm.

METHODS

Fifty patients with CSM and 20 healthy controls were recruited to receive diffusion-weighted MRI examinations. All spinal cord white matter was identified as the region of interest (ROI). DBSI and DTI metrics were extracted from all voxels in the ROI and the median value of each patient was used in analyses. An SVM with optimized hyperparameters was trained using clinical and imaging metrics separately and collectively to predict patient outcomes. Patient outcomes were determined by calculating changes between pre- and postoperative modified Japanese Orthopaedic Association (mJOA) scale scores.

RESULTS

Accuracy, precision, recall, and F1 score were reported for each SVM iteration. The highest performance was observed when a combination of clinical and DBSI metrics was used to train an SVM. When assessing patient outcomes using mJOA scale scores, the SVM trained with clinical and DBSI metrics achieved accuracy and an area under the curve of 88.1% and 0.95, compared with 66.7% and 0.65, respectively, when clinical and DTI metrics were used together.

CONCLUSIONS

The accuracy and efficacy of the SVM incorporating clinical and DBSI metrics show promise for clinical applications in predicting patient outcomes. These results suggest that DBSI metrics, along with the clinical presentation, could serve as a surrogate in prognosticating outcomes of patients with CSM.

Spatially restricted drivers and transitional cell populations cooperate with the microenvironment in untreated and chemo-resistant pancreatic cancer

Pancreatic ductal adenocarcinoma is a lethal disease with limited treatment options and poor survival. We studied 83 spatial samples from 31 patients (11 treatment-naïve and 20 treated) using single-cell/nucleus RNA sequencing, bulk-proteogenomics, spatial transcriptomics and cellular imaging. Subpopulations of tumor cells exhibited signatures of proliferation, KRAS signaling, cell stress and epithelial-to-mesenchymal transition. Mapping mutations and copy number events distinguished tumor populations from normal and transitional cells, including acinar-to-ductal metaplasia and pancreatic intraepithelial neoplasia. Pathology-assisted deconvolution of spatial transcriptomic data identified tumor and transitional subpopulations with distinct histological features. We showed coordinated expression of TIGIT in exhausted and regulatory T cells and Nectin in tumor cells. Chemo-resistant samples contain a threefold enrichment of inflammatory cancer-associated fibroblasts that upregulate metallothioneins. Our study reveals a deeper understanding of the intricate substructure of pancreatic ductal adenocarcinoma tumors that could help improve therapy for patients with this disease.

Microstructural Periventricular White Matter Injury in Post-hemorrhagic Ventricular Dilatation

BACKGROUND AND OBJECTIVES

The 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.

METHODS

A 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.

RESULTS

Ninety-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.

DISCUSSION

PHH 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.

CLRM-10. THE INTER-RELATIONSHIP BETWEEN MULTI-MODAL LONGITUDINAL BIOMARKERS OF NEURAL DAMAGE, INFLAMMATION, AND COGNITION AFTER CAR T CELLULAR THERAPY: A SINGLE-CENTER PROSPECTIVE OBSERVATIONAL TRIAL (NCT04614987)

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.

Nucleus accumbens microstructure mediates the relationship between obesity and eating behavior in adults

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.

Diffusion basis spectrum imaging measures anti-inflammatory and neuroprotective effects of fingolimod on murine optic neuritis

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) VA than saline-treated group at each time point. During ten-week of treatment, DBSI-derived non-restricted and restricted-isotropic-diffusion-tensor fractions, and axonal volumes were not significantly different (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 < 0.05) with the corresponding histological markers.

CONCLUSION

DBSI was used to assess changes of the underlying optic nerve pathologies in EAE mice with ON, exhibiting great potential as a noninvasive outcome measure for monitoring disease progression and therapeutic efficacy for MS.

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.

Diffusion Basis Spectrum Imaging Detects Axonal Loss After Transient Dexamethasone Treatment in Optic Neuritis Mice

Optic neuritis is a frequent first symptom of multiple sclerosis (MS) for which corticosteroids are a widely employed treatment option. The Optic Neuritis Treatment Trial (ONTT) reported that corticosteroid treatment does not improve long-term visual acuity, although the evolution of underlying pathologies is unclear. In this study, we employed non-invasive diffusion basis spectrum imaging (DBSI)-derived fiber volume to quantify 11% axonal loss 2 months after corticosteroid treatment (vs. baseline) in experimental autoimmune encephalomyelitis mouse optic nerves affected by optic neuritis. Longitudinal DBSI was performed at baseline (before immunization), after a 2-week corticosteroid treatment period, and 1 and 2 months after treatment, followed by histological validation of neuropathology. Pathological metrics employed to assess the optic nerve revealed axonal protection and anti-inflammatory effects of dexamethasone treatment that were transient. Two months after treatment, axonal injury and loss were indistinguishable between PBS- and dexamethasone-treated optic nerves, similar to results of the human ONTT. Our findings in mice further support that corticosteroid treatment alone is not sufficient to prevent eventual axonal loss in ON, and strongly support the potential of DBSI as an in vivo imaging outcome measure to assess optic nerve pathology.

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.

Diffusion Histology Imaging Combining Diffusion Basis Spectrum Imaging (DBSI) and Machine Learning Improves Detection and Classification of Glioblastoma Pathology

PURPOSE

Glioblastoma (GBM) is one of the deadliest cancers with no cure. While conventional MRI has been widely adopted to examine 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 DESIGN

We 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.

RESULTS

Gadolinium-enhanced T1-weighted or hyperintense fluid-attenuated inversion recovery failed to reflect the morphologic complexity underlying tumor in patients with GBM. 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 GBM 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.

CONCLUSIONS

Our results suggest that DHI could serve as a favorable alternative to current neuroimaging techniques in guiding biopsy or surgery as well as monitoring therapeutic response in the treatment of GBM.

Therapeutic enhancement of blood-brain and blood-tumor barriers permeability by laser interstitial thermal therapy

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.

Probiotics, lactic acid bacteria and bacilli: interesting supplementation for aquaculture

Probiotics administration in aquafeed is known to increase feed consumption and absorption due to their capacity to release a wide range of digestive enzymes and nutrients which can participate in digestion process and feed utilization, along with the absorption of diet components led to an increase in host's health and well-being. Furthermore, probiotics improve gut maturation, prevention of intestinal disorders, predigestion of antinutrient factors found in the feed ingredients, gut microbiota, disease resistance against pathogens and metabolism. The beneficial immune effects of probiotics are well established in finfish. However, in comparison, similar studies are less abundant in the shellfish. In this review, the discussions will mainly focus on studies reported the last 2 years. In recent studies, native probiotic bacteria were isolated and fed back to their hosts. Although beneficial effects were demonstrated, some studies showed adverse effects when treated with a high concentration. This adverse effect may be due to the imbalance of the gut microbiota caused by the replenished commensal probiotics. Probiotics revealed greatest effect on the shrimp digestive system particularly in the larval and early post-larval stages, and stimulate the production of endogenous enzymes in shrimp and contribute with improved the enzyme activities in the gut, as well as disease resistance.

Deep learning with diffusion basis spectrum imaging for classification of multiple sclerosis lesions

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.

Neuroinflammation and White Matter Alterations in Obesity Assessed by Diffusion Basis Spectrum Imaging

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 provides insights into MS pathology

Objective

To 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).

Methods

Using 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.

Results

Normal-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.

Conclusions

DBSI 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.

Diffusion basis spectrum imaging for identifying pathologies in MS subtypes

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.

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.

Noninvasive Quantification of Axonal Loss in the Presence of Tissue Swelling in Traumatic Spinal Cord Injury Mice

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.

Bioresorbable pressure sensors protected with thermally grown silicon dioxide for the monitoring of chronic diseases and healing processes

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.

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 Basis Spectrum and Diffusion Tensor Imaging Detect Hippocampal Inflammation and Dendritic Injury in a Virus-Induced Mouse Model of Epilepsy

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.

Spinal Cord Injury Disrupts Resting-State Networks in the Human Brain

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.

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.

"A new imaging modality to non-invasively assess multiple sclerosis pathology"

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.

Fractional anisotropy to quantify cervical spondylotic myelopathy severity

BACKGROUND

A number of clinical tools exist for measuring the severity of cervical spondylotic myelopathy (CSM). Several studies have recently described the use of non-invasive imaging biomarkers to assess severity of disease. These imaging markers may provide an additional tool to measure disease progression and represent a surrogate marker of response to therapy. Correlating these imaging biomarkers with clinical quantitative measures is critical for accurate therapeutic stratification and quantification of axonal injury.

METHODS

Fourteen patients and seven healthy control subjects were enrolled. Patients were classified as mildly (7) or moderately (7) impaired based on Modified Japanese Orthopedic Association Scale. All patients underwent diffusion tensor imaging (DTI) and diffusion basis spectrum imaging (DBSI) analyses. In addition to standard neurological examination, all participants underwent 30-m Walking Test, 9-hole Peg Test (9HPT), grip strength, key pinch, and vibration sensation thresholds in the index finger and great toe. Differences in assessment scores between controls, mild and moderate CSM patients were correlated with DTI and DBSI derived fractional anisotropy (FA).

RESULTS

Clinically, 30-meter walking times were significantly longer in the moderately impaired group than in the control group. Maximum 9HPT times were significantly longer in both the mildly and moderately impaired groups as compared to normal controls. Scores on great toe vibration sensation thresholds were lower in the mildly impaired and moderately impaired groups as compared to controls. We found no clear evidence for any differences in minimum grip strength, minimum key pinch, or index finger vibration sensation thresholds. There were moderately strong associations between DTI and DBSI FA values and 30-meter walking times and 9HPT.

CONCLUSIONS

The 30-m Walking Test and 9HPT were both moderately to strongly associated with DTI/DBSI FA values. FA may represent an additional measure to help differentiate and stratify patients with mild or moderate CSM.

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.

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 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.

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.

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.