Diffusion Basis Spectrum Imaging Research Articles

374 Feasibility of Postoperative Diffusion Weighted Imaging to Assess Neural Recovery in Cervical Spondylotic Myelopathy

INTRODUCTION: Following decompressive surgery for cervical spondylotic myelopathy (CSM), advanced diffusion-weighted MRI, such as diffusion basis spectrum imaging (DBSI), may hold significant value by quantifying and tracking spinal cord microstructure. However, there is a paucity of studies investigating this topic, likely due to challenges in resolving signal distortions from spinal instrumentation. METHODS: A single-center prospective study enrolled 50 CSM patients and 20 control patients. All patients underwent preoperative and repeat diffusion-weighted MRI at two-year follow-up. All CSM patients underwent decompressive cervical surgery. DBSI metrics were extracted from the C3 spinal cord level only 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 non-restricted fraction. RESULTS: Of 50 CSM patients, 27 patients underwent both baseline and postoperative diffusion-weighted MRI scans with sufficient quality for analysis. This included 15 mild, 7 moderate, and 5 severe CSM patients, who were followed up to 23.2 (5.6, range 11.1-32.8) months. All preoperative C3 DBSI measures were significantly different between CSM and control patients (p < 0.001), except DBSI fractional anisotropy (p = 0.31). At two-year follow-up, the same significance pattern was found, except DBSI radial diffusivity lost statistical significance (p = 0.75). When assessing change in C3 DBSI measures, CSM patients exhibited significant decreases in DBSI radial diffusivity (p = 0.02). Among control patients, there was no significant difference in DBSI metrics between timepoints. CONCLUSIONS: DBSI may have potential in the postoperative setting to inform clinicians of white matter tract recovery after decompressive cervical surgery for CSM.

Cortical-cerebellar circuits changes in preschool ASD children by multimodal MRI.

To investigate the alterations in cortical-cerebellar circuits and assess their diagnostic potential in preschool children with autism spectrum disorder using multimodal magnetic resonance imaging. We utilized diffusion basis spectrum imaging approaches, namely DBSI_20 and DBSI_combine, alongside 3D structural imaging to examine 31 autism spectrum disorder diagnosed patients and 30 healthy controls. The participants' brains were segmented into 120 anatomical regions for this analysis, and a multimodal strategy was adopted to assess the brain networks using a multi-kernel support vector machine for classification. The results revealed consensus connections in the cortical-cerebellar and subcortical-cerebellar circuits, notably in the thalamus and basal ganglia. These connections were predominantly positive in the frontoparietal and subcortical pathways, whereas negative consensus connections were mainly observed in frontotemporal and subcortical pathways. Among the models tested, DBSI_20 showed the highest accuracy rate of 86.88%. In addition, further analysis indicated that combining the 3 models resulted in the most effective performance. The connectivity network analysis of the multimodal brain data identified significant abnormalities in the cortical-cerebellar circuits in autism spectrum disorder patients. The DBSI_20 model not only provided the highest accuracy but also demonstrated efficiency, suggesting its potential for clinical application in autism spectrum disorder diagnosis.

Abstract 4150: Development of a three-dimensional spatialomics map of lethal prostate cancer driven by clinical imaging

Abstract Prostate adenocarcinoma (PCa) is the most common malignancy and the second leading cause of cancer-related mortality in United States men. Following treatment for localized PCa, up to 50% of these men can experience disease recurrence, with subsequent metastasis and death. This indicates that there is suboptimal identification of lethal PCa at the time of diagnosis, despite advancements in imaging, genomics, and biomarkers. To improve the noninvasive diagnosis of lethal PCa at initial diagnosis, we have developed a novel magnetic resonance imaging (MRI) method, diffusion basis spectrum imaging (DBSI), that noninvasively measures cancer, stromal, and immune cell contributions to the prostate tumor microenvironment (TME). To validate DBSI for PCa, we have applied novel technologies to matched prostatectomy specimens that include (i) fully automated tissue section processing with serial 2-photon tomographic (STP) imaging of the sections to generate 3D volumetric structural maps of the tumor tissue and (ii) multiplex MALDI mass spectrometry imaging of untargeted glycans and extracellular matrix (ECM) peptides and of proteins targeted with novel photocleavable-mass-tagged antibodies (MALDI-IHC) to spatially resolve hundreds of biomolecules from the TME. To establish the feasibility of this approach, we recruited a patient with an unusually aggressive prostate cancer consisting of Gleason 5+4 acinar adenocarcinoma histology with intraductal growth that was locally invasive and lymph node positive at prostatectomy (stage T3bN1). This patient also had the unusual finding of low activity on prostate specific membrane antigen positron emission tomography (PSMA-PET). Following gross sectioning of the prostate with MRI-guided 3D printed molds to co-register clinical DBSI with histology, a 5-mm thick tissue cross-section containing tumor and normal prostate was imaged with high resolution ex vivo DBSI followed by 3D structural mapping with STP imaging. Selected slides in the 3D stack were subject to multiplexed MALDI imaging to identify relationships between cellular and molecular heterogeneity with tumor structure identified with DBSI and STP imaging. We discovered unique structural differences in the prostate tumor compared with the surrounding stroma based upon collagen and glycan modifications to the ECM that were recapitulated with second harmonic maps of collagen from STP imaging as well as stromal maps generated from DBSI imaging. Additional novel protein and glycan ECM components were expressed in this tumor known to be associated with poor patient outcomes. Together, these data represent the first evidence successfully linking noninvasive in vivo clinical imaging and de novo spatialomics technologies with potential to improve PCa diagnostics. This advanced imaging workflow can be applied to any tissue type, underscoring its relevance to translational cancer research. Citation Format: Joseph E. Ippolito, David H. Ballard, Karla Bergeron, Ritesh Chidambaram, Anusha Elumalai, Tyler J. Fraum, Huaping Jing, Peter Kamelin, Eric H. Kim, Catherine Kita, Aleksandra Klim, Anthony Knesis, Mark Lim, José Marcio Luna, Hani Nakhoul, Timothy Ragan, Kenneth J. Rothschild, Sheng-Kwei Song, Kainen Utt, Cody Weimholt, Gargey Yagnik, Elijah Yew, Peggi M. Angel, Richard R. Drake. Development of a three-dimensional spatialomics map of lethal prostate cancer driven by clinical imaging [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4150.

Associations between COVID-19 and putative markers of neuroinflammation: A diffusion basis spectrum imaging study

COVID-19 remains a significant international public health concern. Yet, the mechanisms through which symptomatology emerges remain poorly understood. While SARS-CoV-2 infection may induce prolonged inflammation within the central nervous system, the evidence primarily stems from limited small-scale case investigations. To address this gap, our study capitalized on longitudinal UK Biobank neuroimaging data acquired prior to and following COVID-19 testing (N = 416 including n = 224 COVID-19 cases; Mage = 58.6). Putative neuroinflammation was assessed in gray matter structures and white matter tracts using non-invasive Diffusion Basis Spectrum Imaging (DBSI), which estimates inflammation-related cellularity (DBSI-restricted fraction; DBSI-RF) and vasogenic edema (DBSI-hindered fraction; DBSI-HF). We hypothesized that COVID-19 case status would be associated with increases in DBSI markers after accounting for potential confound (age, sex, race, body mass index, smoking frequency, and data acquisition interval) and multiple testing.COVID-19 case status was not significantly associated with DBSI-RF (|β|’s < 0.28, pFDR >0.05), but with greater DBSI-HF in left pre- and post-central gyri and right middle frontal gyrus (β′s > 0.3, all pFDR = 0.03). Intriguingly, the brain areas exhibiting increased putative vasogenic edema had previously been linked to COVID-19-related functional and structural alterations, whereas brain regions displaying subtle differences in cellularity between COVID-19 cases and controls included regions within or functionally connected to the olfactory network, which has been implicated in COVID-19 psychopathology.Nevertheless, our study might not have captured acute and transitory neuroinflammatory effects linked to SARS-CoV-2 infection, possibly due to symptom resolution before the imaging scan. Future research is warranted to explore the potential time- and symptom-dependent neuroinflammatory relationship with COVID-19.

Diffusion basis spectrum imaging detects subclinical traumatic optic neuropathy in a closed-head impact mouse model of traumatic brain injury.

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

Severe central nervous system demyelination in Sanfilippo disease.

Chronic progressive neuroinflammation is a hallmark of neurological lysosomal storage diseases, including mucopolysaccharidosis III (MPS III or Sanfilippo disease). Since neuroinflammation is linked to white matter tract pathology, we analyzed axonal myelination and white matter density in the mouse model of MPS IIIC HgsnatP304L and post-mortem brain samples of MPS III patients. Brain and spinal cord tissues of human MPS III patients, 6-month-old HgsnatP304L mice and age- and sex-matching wild type mice were analyzed by immunofluorescence to assess levels of myelin-associated proteins, primary and secondary storage materials, and levels of microgliosis. Corpus callosum (CC) region was studied by transmission electron microscopy to analyze axon myelination and morphology of oligodendrocytes and microglia. Mouse brains were analyzed ex vivo by high-filed MRI using Diffusion Basis Spectrum Imaging in Python-Diffusion tensor imaging algorithms. Analyses of CC and spinal cord tissues by immunohistochemistry revealed substantially reduced levels of myelin-associated proteins including Myelin Basic Protein, Myelin Associated Glycoprotein, and Myelin Oligodendrocyte Glycoprotein. Furthermore, ultrastructural analyses revealed disruption of myelin sheath organization and reduced myelin thickness in the brains of MPS IIIC mice and human MPS IIIC patients compared to healthy controls. Oligodendrocytes (OLs) in the CC of MPS IIIC mice were scarce, while examination of the remaining cells revealed numerous enlarged lysosomes containing heparan sulfate, GM3 ganglioside or "zebra bodies" consistent with accumulation of lipids and myelin fragments. In addition, OLs contained swollen mitochondria with largely dissolved cristae, resembling those previously identified in the dysfunctional neurons of MPS IIIC mice. Ex vivo Diffusion Basis Spectrum Imaging revealed compelling signs of demyelination (26% increase in radial diffusivity) and tissue loss (76% increase in hindered diffusivity) in CC of MPS IIIC mice. Our findings demonstrate an important role for white matter injury in the pathophysiology of MPS III. This study also defines specific parameters and brain regions for MRI analysis and suggests that it may become a crucial non-invasive method to evaluate disease progression and therapeutic response.

Imaging and quantifying microglial activation in vivo and ex vivo using diffusion MRI – with validation by immunohistochemistry

AbstractBackgroundAlzheimer disease (AD) is the most common type of dementia.There is growing evidence that the amyloid plaques in postmortem AD human brains are surrounded by activated microglia. Using diffusion basis spectrum imaging (DBSI), we have previously observed increased cellular diffusivity in AD patients, suggesting increased microglia activation as a key pathology in AD. To better understand the underlying mechanism and further establish the noninvasive and nonradioactive DBSI biomarkers of microglia activation, we conducted a realistic Monte Carlo (MC) simulation to model diffusion MRI signals associated with microglia in various activation states.MethodFirst, realistic microglia diffusion signals were generated using MC simulation with real 3D microglia geometry obtained from neuromorpho.org (Fig. 1A). We simulated different pathophysiological scenarios to validate DBSI’s capability in quantitatively detecting microglia activation (Fig. 1B). Second, we conducted and ex vivo MRI scans on human postmortem AD brain samples, followed by immunohistochemical (IHC) staining of microglia (Iba‐1) in aligned sections from the same tissue. DBSI cell apparent diffusion coefficients (ADC), reflecting microglia activation, were estimated and compared to quantitative histological assessments of microglia activation. Finally, in vivo DBSI was conducted on 200 participants who were classified into healthy control, preclinical AD, and early symptomatic AD groups based on cognitive assessments and measures of CSF amyloid (Aβ42) and pTau181.ResultTwo exemplary regions in grey matter (GM) and white matter (WM) of a postmortem AD brain were selected (Fig. 1C). We found that GM had significantly higher DBSI‐derived cell ADC than WM (Fig. 1D). Iba‐1 IHC revealed that WM had significantly larger average microglial area (p&lt;0.005) and bigger max microglia larea (Fig. 1E‐F). MC Simulation was conducted on 700 microglia models. Microglial activation would result in an increased DBSI cell ADC (Fig. 1G). According to MC simulation, increased DBSI‐derived cell ADC in preclinical and early symptomatic AD indicated microglial activation in preclinical and early symptomatic AD (Fig. 1H).ConclusionDBSI‐derived cell ADC increases with microglial activation as assessed by quantitative Iba‐1 IHC. This finding is supported by MC simulation using real 3D microglia geometry. The study indicates that DBSI has the potential to provide non‐invasive MRI biomarkers of microglia activation.

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

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. 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. 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. 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.

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

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. 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. 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. 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. 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. • 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.

12‐weeks of caloric restriction diet improves cortical cerebral blood flow in healthy middle‐age adults

AbstractBackgroundCaloric restriction (CR) improves neuronal stress resistance in animals and improves cognitive performance in older adults (1‐3). Neuroinflammation is an increasingly recognized mechanism relevant to Alzheimer disease (AD). We investigated the effect of a 12‐week CR diet on imaging markers of dementia and neuroinflammation in midlife individuals with multiple sclerosis (MS), a prototype neuroinflammatory disease.MethodsIn a single‐blind randomized controlled trial, 10 participants with MS (8 women and 2 men, age: 45.5±10.67 and education: 16.4±2.5 years) were recruited from the Washington University John L. Trotter MS Center and randomly assigned to participate in either a 12‐week CR or control group on their regular diet. Participants fasted 2 days a week and during those days eating no more than 500 calories. Participants underwent MRI scanning at the time of recruitment and at the end of the 12‐week program. Volumetric analyses were conducted through FreeSurfer 7.1.1 (4), relative regional cerebral blood flow (rCBF) was obtained through ASL‐MRICloud (5), and hindered and restricted diffusion fractions (HF and RF) were calculated through the diffusion basis spectrum imaging (DBSI), representing tissue edema and inflammatory cell infiltration respectivelyResultsSix participants were obese, two were overweight and two had normal weight with an average BMI of 30.3±5.48 kg/m2 across participants. Following 12‐weeks of CR, participants showed an increase in normalized hippocampal volume (p:0.02) compared to those on regular diet. CR also resulted in improved cortical thickness in the bilateral medial orbitofrontal cortices compared to the control group (p:0.014). An average increase in relative perfusion (rCBF) in the bilateral inferior temporal gyri (p:0.02, &amp; p:0.004) and bilateral fusiform gyri (p:0.008 &amp; p:0.002) was observed in participants undergoing CR compared to those on a regular diet at the end of 12‐weeks (Figure 1 and 2). Being on a CR diet was associated with reduced HF and RF in the bilateral inferior longitudinal fasciculi (p:0.04 &amp; p:0.002) indicating reduced edema and cellularity (6).ConclusionCR is associated with alterations in brain’s structure and function in terms of improved volumetric measurements, regional perfusion and reduced tissue inflammation, and hence implicated as a neuroprotective intervention in midlife persons.

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 9-11years) 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.

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.

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. To investigate the effect of intermittent caloric restriction on neuroimaging markers of MS. 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. 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). These pilot data suggest therapeutic effects of iCR in improving cortical volume and thickness and mitigating neuroinflammation in midlife adults with MS.

Neuroinflammation and white matter alterations in occupational manganese exposure assessed by diffusion basis spectrum imaging

ObjectiveTo evaluate in-vivo neuroinflammation and white matter (WM) microstructural integrity in occupational manganese (Mn) exposure. MethodsWe assessed brain inflammation using Diffusion Basis Spectrum Imaging (DBSI) in 26 Mn-exposed welders, 17 Mn-exposed workers, and 26 non-exposed participants. Cumulative Mn exposure was estimated from work histories and the Unified Parkinson's Disease Rating Scale motor subsection 3 (UPDRS3) scores were completed by a movement specialist. Tract-based Spatial Statistics allowed for whole-brain voxel-wise WM analyses to compare WM DBSI-derived measures between the Mn-exposed and non-exposed groups. Exploratory grey matter region of interest (ROI) analyses examined the presence of similar alterations in the basal ganglia. We used voxelwise general linear modeling and linear regression to evaluate the association between cumulative Mn exposure, WM or basal ganglia DBSI metrics, and UPDRS3 scores, while adjusting for age. ResultsMn-exposed welders had higher DBSI-derived restricted fraction (DBSI-RF), higher DBSI-derived nonrestricted fraction (DBSI-NRF), and lower DBSI-derived fiber fraction (DBSI-FF) in multiple WM tracts (all p < 0.05) in comparison to less-exposed workers and non-exposed participants. Basal ganglia ROI analyses revealed higher average caudate DBSI-NRF and DBSI-derived radial diffusion (DBSI-RD) values in Mn-exposed welders relative to non-exposed participants (p < 0.05). Caudate DBSI-NRF was also associated with greater cumulative Mn exposure and higher UPRDS3 scores. ConclusionsMn-exposed welders demonstrate greater DBSI-derived indicators of neuroinflammation-related cellularity (DBSI-RF), greater extracellular edema (DBSI-NRF), and lower apparent axonal density (DBSI-FF) in multiple WM tracts suggesting a neuroinflammatory component in the pathophysiology of Mn neurotoxicity. Caudate DBSI-NRF was positively associated with both cumulative Mn exposure and clinical parkinsonism, indicating a possible dose-dependent effect on extracellular edema with associated motor effects.

672 Diffusion Basis Spectrum Imaging Provides Insights into Cervical Spondylotic Myelopathy Pathology

INTRODUCTION: Diffusion basis spectrum imaging (DBSI) is a non-invasive quantitative imaging modality that may improve understanding of cervical spondylotic myelopathy (CSM) pathology through detailed evaluations of spinal cord microstructural compartments. METHODS: A single-center prospective cohort study enrolled fifty CSM patients and twenty controls from 2018-2020. All patients underwent clinical evaluation and diffusion-weighted MRI, followed by diffusion tensor imaging (DTI) 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 non-restricted fraction. Including an intra-axonal diffusion compartment, DBSI improves estimations of axonal injury via intra-axonal axial diffusivity. Patients were categorized into mild, moderate, and severe CSM using mJOA classifications. Imaging parameters were compared among patient groups using independent-samples t-tests and ANOVA. RESULTS: Twenty controls, 27 mild (mJOA 15-17), 12 moderate (12-14) and 11 severe (0-11) CSM patients were enrolled. All patient-reported outcome measures were worse in CSM patients (all p &lt; 0.001). DTI and DBSI fractional anisotropy, axial diffusivity, and radial diffusivity were significantly different between control and CSM patients (p &lt; 0.05). DBSI fiber fraction, restricted fraction, and non-restricted fraction were significantly different between groups (p &lt; 0.01). DBSI intra-axonal axial diffusivity was lower in mild compared to moderate (mean difference [95% CI]: 1.1 [0.3, 2.1], p &lt; 0.01) and severe (1.9 [1.3, 2.4], p &lt; 0.001) CSM. CONCLUSIONS: 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.

498 Feasibility and Efficacy of Postoperative Diffusion Basis Spectrum Imaging to Evaluate Recovery After Surgery in Cervical Spondylotic Myelopathy

INTRODUCTION: Previous studies evaluating diffusion tensor imaging (DTI) in cervical spondylotic myelopathy (CSM) have demonstrated limitations in assessing postoperative outcomes following surgery. Diffusion basis spectrum imaging (DBSI), capable of providing granular assessments of spinal cord microstructure, may help address these shortcomings. METHODS: Twenty-seven CSM patients underwent preoperative diffusion-weighted MRI followed by cervical decompressive surgery and repeat imaging at two-years follow-up. DTI and DBSI metrics were extracted from the C3 spinal cord level. Diffusion-weighted MRI 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 non-restricted fraction. Improvement after surgery was defined as a 2-point increase in the mJOA at two-years follow-up. Support vector machine classification algorithms were used to predict surgical outcomes. RESULTS: Fifteen mild (mJOA 15-17), 7 moderate (12-14) and 5 severe (0-11) CSM patients underwent surgical decompression and were followed-up to 23.2 (5.6, range 11.1-32.8) months postoperatively. Among DBSI metrics, isotropic diffusion components changed significantly from baseline to latest follow-up (p &lt; 0.01), whereas anisotropic components remained stable (p &gt; 0.05). When predicting improvement in the mJOA, SVM models built with DTI metrics had an accuracy of 74.1 [95% CI: 73.6, 74.6] compared to 85.2 [84.5, 85.3] in the DBSI model. CONCLUSIONS: Postoperative DBSI metrics predicted long-term outcomes with high accuracy. DBSI may have utility in assessing recovery trajectories for CSM patients following surgery.

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

INTRODUCTION: Despite advancements in diffusion-weighted imaging, few studies have examined associations between diffusion MRI markers and CSM-specific clinical domains at baseline and long-term follow-up. METHODS: A single-center prospective cohort study enrolled fifty CSM patients who underwent surgical decompression and twenty controls from 2018-2020. 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 non-restricted fraction. Clinical assessments were performed at baseline and two-year follow-up and included the mJOA, SF-36 PCS, SF-36 MCS, NDI, MDI, and DASH. Pearson’s 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/MCS, and increased NDI, MDI, DASH). At latest follow-up, increased preoperative DBSI intra-axonal axial diffusivity and extra-axonal anisotropic fraction were significantly correlated with improved mJOA. CONCLUSIONS: Our findings demonstrate that DBSI measures may reflect baseline disease burden and long-term prognosis of CSM as compared to DTI. With further validation, DBSI may serve as a non-invasive biomarker following decompressive surgery.

674 Diffusion Basis Spectrum Imaging Predicts Comprehensive Clinical Outcomes Following Surgery for Cervical Spondylotic Myelopathy

INTRODUCTION: 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. METHODS: A prospective cohort study enrolled fifty CSM patients who underwent cervical decompressive surgery. DBSI metrics assessed white matter tract integrity by fractional anisotropy, axial diffusivity, radial diffusivity, and fiber fraction. To evaluate extra-axonal diffusion, DBSI measures restricted and non-restricted fractions. Neurofunctional status was assessed by the mJOA, MDI, and DASH. Quality of life was measured by the SF-36 PCS and MCS. The NDI was used to measure self-reported neck pain. Patient satisfaction was assessed by the NASS satisfaction index. Support vector machine classification algorithms were used to predict surgical outcomes. Specifically, three models were built for each clinical outcome measure (e.g., mJOA), including clinical, DBSI, and combined models. RESULTS: Twenty-seven mild (mJOA 15-17), 12 moderate (12-14) and 11 severe (0-11) CSM patients were enrolled. Twenty-four (60%) underwent anterior surgery compared to 16 (40%) posterior surgery. The mean (SD) follow-up was 23.2 (5.6, range 6.1-32.8) months. The best performing model was for the prediction of the NASS satisfaction index, with an accuracy [95% CI] of 94.4 [94.3, 94.8]. Conversely, the worst performing model was for the NDI, with an accuracy of 73.8 [73.6, 74.5]. When predicting improvement in the mJOA, the clinically-driven model had an accuracy of 61.9 [61.6, 62.5], compared to 78.6 [78.4, 79.2] in the DBSI model, and 90.5 [90.2, 90.8] in the combined model. CONCLUSIONS: When combined with key clinical covariates, DBSI metrics predicted improvement after surgical decompression with high accuracy. These results suggest that DBSI may serve as a non-invasive imaging biomarker for CSM.

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

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

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

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. 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. 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. 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 predicts long-term clinical outcomes following surgery in cervical spondylotic myelopathy

BACKGROUND CONTEXTA 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. PURPOSETo examine the ability of DBSI to predict clinically important CSM outcome measures at 2-years follow-up. STUDY DESIGN/SETTINGProspective cohort study. PATIENT SAMPLEPatients undergoing decompressive cervical surgery for CSM. OUTCOME MEASURESNeurofunctional 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. METHODSFifty 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. RESULTSTwenty-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. CONCLUSIONSWhen 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 EVIDENCEII