Quantitative MRI Measures Research Articles

Role of Apparent Diffusion Coefficient Value and Apparent Diffusion Coefficient Ratio as Prognostic Factors for Prostate Cancer Aggressiveness.

Prostate cancer is one of the most prevalent cancers in the male population. To determine the aggressiveness of suspected lesions precisely, predictive models are increasingly being developed using quantitative MRI measurements, and particularly the ADC value. This study aimed to determine whether ADC values could be used to establish the aggressiveness of prostate cancer. A retrospective single-center study included 398 patients with prostate cancer who underwent a multiparametric MRI prior to radical prostatectomy. DWI ADC values were measured (µm2/s) using b values of 50 and 1000. The dominant lesion best visualized on MRI was analyzed. The ADC values of the index lesion and reference tissue were compared to tumor aggressivity according to the Gleason grade groups based on radical prostatectomy results. Statistical analysis was performed using the Mann-Whitney U test, Kruskal-Wallis H test, Spearman's rank correlation, and ROC curves. A very strong negative correlation (rs = -0.846, p < 0.001) between ADC and GS was found. ROC analysis revealed an AUC of 0.958 and an ADC threshold value of 758 µm2/s in clinically significant prostate cancer diagnoses using the absolute ADC value, with no advantage of using the ADC ratio over the absolute ADC value being identified. DWI ADC values and the calculated ADC ratio have a significant inverse correlation with GS. The findings indicate a strong capability in determining prostate cancer aggressiveness, as well as the possibility of assisting with assigning PI-RADS categories using ADC as quantitative metrics.

Quantitative MRI Measures and Cognitive Function in People With Drug-Resistant Juvenile Myoclonic Epilepsy.

Neuroimaging studies have so far identified structural changes in individuals with juvenile myoclonic epilepsy (JME) when compared with controls. However, the underlying mechanisms of drug-resistant JME remain unknown. In this study, we aimed at characterizing the structural underpinnings of drug-resistant JME using MRI-derived cortical morphologic markers. In this prospective cross-sectional 2-center study, T1-weighted MRI and neuropsychological measures of verbal memory and executive function were obtained in individuals with drug-resistant and drug-responsive JME recruited from epilepsy outpatient clinics and healthy controls. We performed vertexwise measurements of cortical thickness, surface area, and local gyrification index (LGI). Vertexwise group comparisons were corrected for multiple comparisons at a familywise error (FWE) of 0.05. The neuropsychological profile of disease subgroups was analyzed through principal component analysis. We studied 42 individuals with drug-resistant JME (mean age 29 ± 11 years, 50% female), 37 with drug-responsive JME (mean age 34 ± 10, years, 59% female), and 71 healthy controls (mean age 21 ± 9 years, 61% female). Surface area was increased in participants with drug-resistant JME in the left temporal lobe (Cohen d = 0.82 [-0.52 to -1.12], pFWE < 0.05) when compared with the drug-responsive group. Although no cortical thickness changes were observed between disease subgroups, drug-resistant and drug-sensitive participants showed discrete cortical thinning against controls (Cohen d = -0.42 [-0.83 to -0.01], pFWE < 0.05; Cohen d = -0.57 [-1.03 to -0.11], pFWE < 0.05, respectively). LGI was increased in the left temporal and occipital lobes in drug-resistant participants (Cohen d = 0.60 [0.34-0.86], pFWE < 0.05) when contrasting against drug-sensitive participants, but not controls. The composite executive function score was reduced in drug-resistant individuals compared with controls and drug-sensitive individuals (-1.74 [-2.58 to -0.90], p < 0.001 and -1.29 [-2.25 to -0.33], p < 0.01, respectively). Significant correlations were observed between executive function impairment and increased surface area in the precuneus and medial prefrontal regions (r = -0.79, pFWE < 0.05) in participants with drug-resistant JME. We identified a developmental phenotype in individuals with drug-resistant JME characterized by changes in cortical surface area and folding complexity, the extent of which correlates with executive dysfunction. No association was observed between cortical thickness and disease severity. Our findings support a neurodevelopmental basis for drug resistance and cognitive impairment in JME.

Quantitative MRI distinguishes different leukodystrophies and correlates with clinical measures.

The leukodystrophy "vanishing white matter" (VWM) and "metachromatic leukodystrophy" (MLD) affect the brain's white matter, but have very different underlying pathology. We aim to determine whether quantitative MRI reflects known neuropathological differences and correlates with clinical scores in these leukodystrophies. VWM and MLD patients and controls were prospectively included between 2020 and 2023. Clinical scores were recorded. MRI at 3 T included multi-compartment relaxometry diffusion-informed myelin water imaging (MCR-DIMWI) and multi-echo T2-relaxation imaging with compressed sensing (METRICS) to determine myelin water fractions (MWF). Multi-shell diffusion-weighted data were used for diffusion tensor imaging measures and neurite orientation dispersion and density imaging (NODDI) analysis, which estimates neurite density index, orientation dispersion index, and free water fraction. As quantitative MRI measures are age-dependent, ratios between actual and age-expected MRI measures were calculated. We performed the multilevel analysis with subsequent post-hoc and correlation tests to assess differences between groups and clinico-radiological correlations. Sixteen control (age range: 2.3-61.3 years, 8 male), 37 VWM (2.4-56.5 years, 20 male), and 14 MLD (2.2-41.7 years, 6 male) subjects were included. Neurite density index and MWF were lower in patients than in controls (p < 0.001). Free water fraction was highest in VWM (p = 0.01), but similar to controls in MLD (p = 0.99). Changes in diffusion tensor imaging measures relative to controls were generally more pronounced in VWM than in MLD. In both patient groups, MCR-DIMWI MWF correlated strongest with clinical measures. Quantitative MRI correlates to clinical measures and yields differential profiles in VWM and MLD, in line with differences in neuropathology. Question Can quantitative MRI reflect known neuropathological differences and correlate with clinical scores for these leukodystrophies? Finding Quantitative MRI measures, e.g., MWF, neurite density index, and free water fraction differ between leukodystrophies and controls, in correspondence to known histological differences. Clinical relevance MRI techniques producing quantitative, biologically-specific, measures regarding the health of myelin and axons deliver more comprehensive information regarding pathological changes in leukodystrophies than current approaches, and are thus viable tools for monitoring patients and providing clinical trial outcome measures.

Investigating MRI-Associated Biological Aspects of Racial Disparities in Prostate Cancer for African American and White Men.

Understanding the characteristics of multiparametric MRI (mpMRI) in patients from different racial/ethnic backgrounds is important for reducing the observed gaps in clinical outcomes. To investigate the diagnostic performance of mpMRI and quantitative MRI parameters of prostate cancer (PCa) in African American (AA) and matched White (W) men. Retrospective. One hundred twenty-nine patients (43 AA, 86 W) with histologically proven PCa who underwent mpMRI before radical prostatectomy. 3.0 T, T2-weighted turbo spin echo imaging, a single-shot spin-echo EPI sequence diffusion-weighted imaging, and a gradient echo sequence dynamic contrast-enhanced MRI with an ultrafast 3D spoiled gradient-echo sequence. The diagnostic performance of mpMRI in AA and W men was assessed using detection rates (DRs) and positive predictive values (PPVs) in zones defined by the PI-RADS v2.1 prostate sector map. Quantitative MRI parameters, including Ktrans and ve of clinically significant (cs) PCa (Gleason score ≥ 7) tumors were compared between AA and W sub-cohorts after matching age, prostate-specific antigen (PSA), and prostate volume. Weighted Pearson's chi-square and Mann-Whitney U tests with a statistically significant level of 0.05 were used to examine differences in DR and PPV and to compare parameters between AA and matched W men, respectively. A total number of 264 PCa lesions were identified in the study cohort. The PPVs in the peripheral zone (PZ) and posterior prostate of mpMRI for csPCa lesions were significantly higher in AA men than in matched W men (87.8% vs. 68.1% in PZ, and 89.3% vs. 69.6% in posterior prostate). The Ktrans of index csPCa lesions in AA men was significantly higher than in W men (0.25 ± 0.12 vs. 0.20 ± 0.08 min-1; P < 0.01). This study demonstrated race-related differences in the diagnostic performances and quantitative MRI measures of csPCa that were not reflected in age, PSA, and prostate volume. 3 TECHNICAL EFFICACY: Stage 2.

Achilles tendon assessment on quantitative MRI: Sources of variability and relationships to tendinopathy.

Quantitative MRI (qMRI) measures are useful in assessing musculoskeletal tissues, but application to tendon has been limited. The purposes of this study were to optimize, identify sources of variability, and establish reproducibility of qMRI to assess Achilles tendon. Additionally, preliminarily estimates of effect of tendon pathology on qMRI metrics and structure-function relationships between qMRI measures and ankle performance were examined. T1, T1ρ, T2, and T2* maps of the Achilles tendon were obtained using a 3T MRI scanner. In participants with asymptomatic tendons (n = 21), MRI procedures were repeated twice, and region of interest selection was performed by three raters. Variance decomposition and reproducibility statistics were completed. To estimate the effect of pathology, qMRI measures from individuals with asymptomatic tendons were compared to qMRI measures from a pilot group of individuals with Achilles tendinopathy (n = 7). Relationships between qMRI and ankle performance measures were assessed. Between-participant variation accounted for the majority of variability (46.7%-64.0%) in all qMRI measures except T2*. ICCs met or exceeded 0.7 for all qMRI measures when averaged across raters or scans. Relaxation times were significantly longer in tendinopathic tendons (mean (SD) T1: 977.8 (208.6) ms, T1ρ: 35.4 (7.1) ms, T2: 42.8 (7.9) ms, T2*: 14.1 (7.6) ms, n = 7) compared to asymptomatic control tendons (T1: 691.7 (32.4) ms, T1ρ: 24.0 (3.6) ms, T2: 24.4 (7.5) ms, T2*: 9.5 (3.4) ms, n = 21) (p < 0.011 for all comparisons). T1 related to functional performance measures in symptomatic and asymptomatic groups. Study findings suggest that qMRI is reliable to assess the Achilles tendon. qMRI quantitatively assesses the presence of tendon pathology and relates to functional performance outcomes, supporting the utility of incorporating qMRI in research and clinic.

Limited Value of Radiomics Compared to Quantitative MRI Measures for Predicting 10-year Disability in Newly Diagnosed Multiple Sclerosis: A Real-world Data Exploratory Study (P11-6.018)

Limited Value of Radiomics Compared to Quantitative MRI Measures for Predicting 10-year Disability in Newly Diagnosed Multiple Sclerosis: A Real-world Data Exploratory Study (P11-6.018)

Persistent MRI Findings Unique to Blast and Repetitive Mild TBI: Analysis of the CENC/LIMBIC Cohort Injury Characteristics.

MRI represents one of the clinical tools at the forefront of research efforts aimed at identifying diagnostic and prognostic biomarkers following traumatic brain injury (TBI). Both volumetric and diffusion MRI findings in mild TBI (mTBI) are mixed, making the findings difficult to interpret. As such, additional research is needed to continue to elucidate the relationship between the clinical features of mTBI and quantitative MRI measurements. Volumetric and diffusion imaging data in a sample of 976 veterans and service members from the Chronic Effects of Neurotrauma Consortium and now the Long-Term Impact of Military-Relevant Brain Injury Consortium observational study of the late effects of mTBI in combat with and without a history of mTBI were examined. A series of regression models with link functions appropriate for the model outcome were used to evaluate the relationships among imaging measures and clinical features of mTBI. Each model included acquisition site, participant sex, and age as covariates. Separate regression models were fit for each region of interest where said region was a predictor. After controlling for multiple comparisons, no significant main effect was noted for comparisons between veterans and service members with and without a history of mTBI. However, blast-related mTBI were associated with volumetric reductions of several subregions of the corpus callosum compared to non-blast-related mTBI. Several volumetric (i.e., hippocampal subfields, etc.) and diffusion (i.e., corona radiata, superior longitudinal fasciculus, etc.) MRI findings were noted to be associated with an increased number of repetitive mTBIs versus. In deployment-related mTBI, significant findings in this cohort were only observed when considering mTBI sub-groups (blast mechanism and total number/dose). Simply comparing healthy controls and those with a positive mTBI history is likely an oversimplification that may lead to non-significant findings, even in consortium analyses.

Residual volume of extruded disc material and residual spinal cord compression measured on postoperative MRI do not predict neurological outcomes in dogs following decompressive surgery for thoracolumbar intervertebral disc extrusion.

Published studies on the validity of using quantitative MRI measures of pre- and postoperative spinal cord (SC) compression as prognostic indicators for dogs undergoing surgery for intervertebral disc extrusion (IVDE) are currently limited. The aim of this retrospective analytical study was to describe the volume of postoperative residual extradural material (VREM) and the ratio of the cross-sectional area (CSA) of maximum SC compression to the CSA of SC in a compression-free intervertebral space as MRI measures of preoperative and postoperative compression (residual spinal cord compression, RSCC), and to compare these measures between the neurological outcome in a group of dogs. Inclusion criteria were dogs that underwent surgery for thoracolumbar IVDE, were imaged pre- and immediately postoperatively by MRI, and had a neurological follow-up examination 2 to 5 weeks postoperatively. Two blinded observers independently performed measurements in pre- and postoperative MRI studies. Dogs were classified into positive outcome (PO) and negative outcome (NO) groups based on follow-up neurologic examination scores. Seventeen dogs were included (12 PO, 5 NO). Interobserver agreement for MRI measurements was good to excellent (ICCs: 0.76-0.97). The prevalence of residual extradural material in postoperative MRI studies was 100%. No significant differences in mean preoperative SC compression, mean RSCC, mean SC decompression, or VREM were found between outcome groups (P=.25; P=.28; P=.91, P=.98). In conclusion, neither postoperative VREM nor RSCC could predict successful neurological outcomes.

The relationship between Event‐Related Potentials and MRI cortical atrophy in a memory disorders clinic

AbstractBackgroundThere is a need for accessible and affordable ways to assess biomarkers of Alzheimer’s disease (AD). Event‐related potentials (ERPs) are associated with disease severity of AD (Fruehwirt et al., 2019) and are a candidate biomarker for AD (Olichney et al., 2022). There is, however, little understanding of how ERP components relate to neurodegeneration of specific brain structures in AD.MethodWe investigated the correlation between electrophysiology, as measured by ERPs and brain structure using quantitative structural MRI measurements using FreeSurfer. A dataset containing older veteran memory disorders patients (N = 25) from VA Boston Healthcare System was analyzed. Participants completed an MRI and an auditory oddball task ERP paradigm.ResultAn exploratory analysis was performed using a Pearson correlation coefficient to evaluate the relationship between ERPs and the thickness and volume of different cortical areas. There was a negative relationship between P300 target amplitude and inferior temporal volume (p &lt; .05), as well as P300 target latency and thickness of the superior temporal (p &lt; .05) and transverse temporal regions (p &lt; .01). P200 standard amplitude had a positive correlation with thickness in the middle temporal (p &lt; .01), and superior temporal regions (p ≤ .05), and P200 target latency had a negative correlation with thickness of the superior temporal region (p &lt; .05). N200 target amplitude had a negative correlation with the superior parietal volume (right hemisphere = p ≤ .05, left hemisphere = p ≤ .01), left inferior temporal volume (p ≤ .05), and the middle temporal volume (left = p ≤ .05, right = p ≤ .01). N200 target latency was negatively correlated with right superior parietal volume (p ≤ .05).ConclusionA correlation was found between ERP measures P200, N200 and P300 with cortical thickness and volume of areas that are commonly impacted by AD pathology, further substantiating use of ERPs as possible AD biomarkers. We conclude that ERPs provide insights as to structural changes of brain structures affected by AD pathology. ERPs could help inform areas of brain atrophy and related patterns of cognitive impairment.

Ultra‐high‐resolution quantitative MRI at the grey/white interface in Alzheimer’s disease and posterior cortical atrophy

AbstractBackgroundCortical grey matter (CGM) and superficial white matter (SWM) undergo pathological changes, but standard MRI spatial resolutions make interpreting disease‐related effects at their interface challenging. We present findings from a study investigating the grey/white interface in typical amnestic Alzheimer’s disease (tAD), posterior cortical atrophy (PCA) and healthy controls using ultra‐high‐resolution quantitative MRI measures sensitive to microstructural properties.MethodEleven participants (Table 1) were scanned at 7T using multi‐echo FLASH (0.5mm isotropic resolution with prospective motion correction) and diffusion MRI (dMRI) (1.25mm isotropic resolution). The hMRI toolbox produced multi‐parametric mapping (MPM) measures: R1, R2* and Proton Density (PD) (Vaculciakova et al., 2021https://doi.org/10.1002/mrm.29253). dMRI processing included denoising and correcting for Gibbs ringing, eddy currents, susceptibility artifacts and motion. Metrics from dMRI were fractional anisotropy (FA), and mean diffusivity (MD), as well as tissue fraction (TF), neurite density index (NDI) and orientation dispersion index (ODI) from Neurite Orientation Dispersion and Density Imaging (NODDI). A deep learning segmentation approach estimated the grey/white boundary (Billot et al., 2021, arXiv:2107.09559). MPM and dMRI measures were sampled from the CGM into the SWM at 0.5mm increments in regions of interest (Harvard‐Oxford cortical atlas). Tissue‐weighted (tw) averages were calculated for NDI and ODI. Metrics were visualized across the grey/white interface using boxplots.ResultFigures 1‐2 show MPM and dMRI measures in the precuneus (dashed lines indicate group medians). Qualitatively, most tAD and PCA participants had lower R1 and R2* than controls, most prominently 0.5mm into the SWM (Figure 1). PD appeared higher in tAD and PCA patients across the grey/white interface. Qualitatively, most tAD and PCA participants had lower TF and higher MD in the CGM, where twNDI and FA appeared lower than controls across grey/white interface (Figure 2). Most tAD and PCA had qualitatively lower twODI in CGM and a flatter slope across the grey/white interface compared to controls.ConclusionMacromolecular (R1, R2* and twNDI) and iron content (R2*) MR measures at 7T appear reduced in tAD and PCA across the grey/white interface, whereas neurite organisational complexity (twODI) may become more homogeneous. Ongoing study will assess if these findings are consistent with further participants.

Deep learning for the prediction of type 2 diabetes mellitus from neck-to-knee Dixon MRI in the UK biobank

Rationale and objectivesWe evaluate the automatic identification of type 2 diabetes from neck-to-knee, two-point Dixon MRI scans with 3D convolutional neural networks on a large, population-based dataset. To this end, we assess the best combination of MRI contrasts and stations for diabetes prediction, and the benefit of integrating risk factors. Materials and methodsSubjects with type 2 diabetes mellitus have been identified in the prospective UK Biobank Imaging study, and a matched control sample has been created to avoid confounding bias. Five-fold cross-validation is used for the evaluation. All scans from the two-point Dixon neck-to-knee sequence have been standardized. A neural network that considers multi-channel MRI input was developed and integrates clinical information in tabular format. An ensemble strategy is used to combine multi-station MRI predictions. A subset with quantitative fat measurements is identified for comparison to prior approaches. ResultsMRI scans from 3406 subjects (mean age, 66.2 years ± 7.1 [standard deviation]; 1128 women) were analyzed with 1703 diabetics. A balanced accuracy of 78.7 %, AUC ROC of 0.872, and an average precision of 0.878 was obtained for the classification of diabetes. The ensemble over multiple Dixon MRI stations yields better performance than selecting the individually best station. Moreover, combining fat and water scans as multi-channel inputs to the networks improves upon just using single contrasts as input. Integrating clinical information about known risk factors of diabetes in the network boosts the performance across all stations and the ensemble. The neural network achieved superior results compared to the prediction based on quantitative MRI measurements. ConclusionsThe developed deep learning model accurately predicted type 2 diabetes from neck-to-knee two-point Dixon MRI scans.

Difference in quantitative MRI measurements of cartilage between Wiberg type III patella and stable patella based on a 3.0-T synthetic MRI sequence

PurposeThe purpose of this study was to investigate the difference between the quantitative MRI values of Wiberg type III and stable patellar cartilage, and to improve the accuracy of MRI quantification in early patellar cartilage damage. MethodsThe knee joints of 94 healthy volunteers were scanned by a GE Signa Pioneer 3.0-T synthetic MRI machine. According to the Wiberg classification, the patella was divided into types I-III. Types I-II made up the stable patella group, and type III made up the unstable patella group. Two radiologists independently measured patellar cartilage thickness and quantitative synthetic MRI values (T1, T2, PD) in both groups. Interobserver agreement for quantitative variables was assessed using the BlandAltman method. A third radiologist assessed differences in measurements. ResultsThe medial T2 and T1 value of Wiberg III patella did not show a normal distribution (all P > 0.05). Compared with the stable group, the Wiberg type III group had thinner cartilage of the medial surface of the patella (P < 0.05), lower cartilage T2 and PD values (P < 0.05), but a similar cartilage T1 value (P > 0.05). There was no significant difference in the cartilage thickness, T1, T2, or PD value of the lateral patella between the Wiberg type III and the stable group (P > 0.05). ConclusionThere were certain differences in the cartilage thickness of the medial surface of the patella and the quantitative value of synthetic MRI in Wiberg type III patellas. Quantitative studies of patellar cartilage MRI measurements need to consider the influence of patellar morphology.

Correlation analysis of quantitative MRI measurements of thigh muscles with histopathology in patients with idiopathic inflammatory myopathy

ObjectivesTo validate the correlation between histopathological findings and quantitative magnetic resonance imaging (qMRI) fat fraction (FF) and water T2 mapping in patients with idiopathic inflammatory myopathy (IIM).MethodsThe study included 13 patients with histopathologically confirmed IIM who underwent dedicated thigh qMRI scanning within 1 month before open muscle biopsy. For the biopsied muscles, FF derived from the iterative decomposition of water and fat with echo asymmetry and least-squares estimation quantitation (IDEAL-IQ) and T2 time from T2 mapping with chemical shift selective fat saturation were measured using a machine learning software. Individual histochemical and immunohistochemical slides were evaluated using a 5-point Likert score. Inter-reader agreement and the correlation between qMRI markers and histopathological scores were analyzed.ResultsReaders showed good to perfect agreement in qMRI measurements and most histopathological scores. FF of the biopsied muscles was positively correlated with the amount of fat in histopathological slides (p = 0.031). Prolonged T2 time was associated with the degree of variation in myofiber size, inflammatory cell infiltration, and amount of connective tissues (p ≤ 0.008 for all).ConclusionsUsing the machine learning-based muscle segmentation method, a positive correlation was confirmed between qMRI biomarkers and histopathological findings of patients with IIM. This finding provides a basis for using qMRI as a non-invasive tool in the diagnostic workflow of IIM.Relevance statementBy using ML-based muscle segmentation, a correlation between qMRI biomarkers and histopathology was found in patients with IIM: qMRI is a potential non-invasive tool in this clinical setting.Key points• Quantitative magnetic resonance imaging measurements using machine learning-based muscle segmentation have good consistency and reproductivity.• Fat fraction of idiopathic inflammatory myopathy (IIM) correlated with the amount of fat at histopathology.• Prolonged T2 time was associated with muscle inflammation in IIM.Graphical

Improved multimodal prediction of progression from MCI to Alzheimer's disease combining genetics with quantitative brain MRI and cognitive measures.

There is a pressing need for non-invasive, cost-effective tools for early detection of Alzheimer's disease (AD). Using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), Cox proportional models were conducted to develop a multimodal hazard score (MHS) combining age, a polygenic hazard score (PHS), brain atrophy, and memory to predict conversion from mild cognitive impairment (MCI) to dementia. Power calculations estimated required clinical trial sample sizes after hypothetical enrichment using the MHS. Cox regression determined predicted age of onset for AD pathology from the PHS. The MHS predicted conversion from MCI to dementia (hazard ratio for 80th versus 20th percentile: 27.03). Models suggest that application of the MHS could reduce clinical trial sample sizes by 67%. The PHS alone predicted age of onset of amyloid and tau. The MHS may improve early detection of AD for use in memory clinics or for clinical trial enrichment. A multimodal hazard score (MHS) combined age, genetics, brain atrophy, and memory. The MHS predicted time to conversion from mild cognitive impairment to dementia. MHS reduced hypothetical Alzheimer's disease (AD) clinical trial sample sizes by 67%. A polygenic hazard score predicted age of onset of AD neuropathology.

Association of Daily Physical Activity with Cervical Spinal Cord Areas in Multiple Sclerosis

Background and purpose Remote activity monitoring has the potential to evaluate real-world motor function and disability outside of the clinic. The relationships of daily physical activity with spinal cord white matter and grey matter areas, MS disability, and leg function are unknown. Our purpose was to evaluate the association of remotely captured ambulatory activity with structural central nervous system pathology via quantitative magnetic imaging, in people with multiple sclerosis (MS). Methods Fifty adults with progressive or relapsing MS with motor disability who could walk at least 2 minutes, were assessed using clinical, patient-reported, and quantitative brain and spinal cord MRI measures. Fitbit Flex2, worn on the non-dominant wrist, remotely assessed activity over 30 consecutive days. Univariate and multivariate analyses were performed to assess correlations between remote physical activity and other disability metrics. Results The mean age of the cohort was 53.3 years and the median EDSS was 4.0. Average daily step counts (STEPS) were highly correlated with EDSS and walking measures (i.e., Timed 25-foot Walk, Timed up and Go tests, and subjective 12- item MS Walking Scale). Greater STEPS correlated with greater C2-C3 spinal cord grey matter areas (rho=0.39, p=0.04), total cord area (rho=0.35, p=0.04), and brain volume (rho=0.32, p=0.04). Discussion These results provide preliminary evidence that spinal cord grey matter area is a neuroanatomical substrate associated with STEPS. STEPS could serve as a proxy to alert clinicians and researchers to possible changes in structural nervous system pathology. Longitudinal observations are needed to determine directionality and value of STEPS as a proxy for generalized brain and cord volume loss. These results have potential implications for structural and functional modification of disease progression via therapeutic interventions aimed at altering STEPS. Remote activity monitoring has the potential to evaluate real-world motor function and disability outside of the clinic. The relationships of daily physical activity with spinal cord white matter and grey matter areas, MS disability, and leg function are unknown. Our purpose was to evaluate the association of remotely captured ambulatory activity with structural central nervous system pathology via quantitative magnetic imaging, in people with multiple sclerosis (MS). Fifty adults with progressive or relapsing MS with motor disability who could walk at least 2 minutes, were assessed using clinical, patient-reported, and quantitative brain and spinal cord MRI measures. Fitbit Flex2, worn on the non-dominant wrist, remotely assessed activity over 30 consecutive days. Univariate and multivariate analyses were performed to assess correlations between remote physical activity and other disability metrics. The mean age of the cohort was 53.3 years and the median EDSS was 4.0. Average daily step counts (STEPS) were highly correlated with EDSS and walking measures (i.e., Timed 25-foot Walk, Timed up and Go tests, and subjective 12- item MS Walking Scale). Greater STEPS correlated with greater C2-C3 spinal cord grey matter areas (rho=0.39, p=0.04), total cord area (rho=0.35, p=0.04), and brain volume (rho=0.32, p=0.04). These results provide preliminary evidence that spinal cord grey matter area is a neuroanatomical substrate associated with STEPS. STEPS could serve as a proxy to alert clinicians and researchers to possible changes in structural nervous system pathology. Longitudinal observations are needed to determine directionality and value of STEPS as a proxy for generalized brain and cord volume loss. These results have potential implications for structural and functional modification of disease progression via therapeutic interventions aimed at altering STEPS.

Latinx with multiple sclerosis have greater disability and loss of deep and cortical gray matter (S31.003)

<h3>Objective:</h3> To characterize clinical and MRI features of Latinx with multiple sclerosis (MS). <h3>Background:</h3> MS affects an increasing number of Latinx patients. The clinical and radiological phenotype of Latinx MS is not well understood and may have biological or social underpinnings. <h3>Design/Methods:</h3> A retrospective cross-sectional study in the MS PATHS network was conducted with Latinx and White non-Latinx carrying a diagnosis of MS. Brain MRI conducted within 1 year of clinical visits were included in the MRI cohort. Clinical and quantitative MRI measures were extracted from MS PATHS including age- and education-adjusted processing speed tests. Comparisons between Latinx and White subjects were conducted using two-sample t-test and Wilcoxon rank-sum. Mixed effect models were used to examine clinical and MRI differences between Latinx and White subjects while adjusting for covariates including education, insurance, and employment. <h3>Results:</h3> A total of 660 Latinx and 9957 White subjects were identified with 388 Latinx and 5726 White subjects in the MRI cohort. Compared with White subjects, Latinx were younger (45.4 years [12.2] vs: 52.9 years [12.7], p &lt;0.001), had shorter disease duration (17.2 years [19.6] vs. 19.5 years [11.5], p &lt;0.001), and had lower processing speed z-score (−0.81 [1.3] vs. −0.40 [1.2], p &lt;0.001). Latinx had higher T2 lesion volume (8.0 ml [IQR 3.5–16] vs 6.5 ml [IQR 3.0–14.1], p = 0.009), and lower thalamic volume (12.8 ml [1.7] vs 13.3 ml [1.6], p &lt;0.001) compared to White subjects. Adjusted mixed models showed that Latinx subjects had lower processing speed, brain parenchymal fraction, thalamic volume, cortical volume, and deep gray matter volume (all p &lt;0.001) as well as slower walking speed (p=0.04), non-dominant manual dexterity (&lt;0.01), and higher PDDS (p=0.045). <h3>Conclusions:</h3> Latinx, despite being younger and having a shorter disease duration than Whites, had more physical disability, cognitive dysfunction, greater lesion burden, and loss of deep and cortical gray matter. <b>Disclosure:</b> Dr. Ontaneda has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Novartis. Dr. Ontaneda has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Genentech/Roche. Dr. Ontaneda has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Biogen Idec. Dr. Ontaneda has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Genentech/Roche. The institution of Dr. Ontaneda has received research support from NIH. The institution of Dr. Ontaneda has received research support from PCORI. The institution of Dr. Ontaneda has received research support from NMSS. The institution of Dr. Ontaneda has received research support from Genetech. Dr. McGinley has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Octave. Dr. McGinley has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Genentech. Dr. McGinley has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for EMD Serono. The institution of Dr. McGinley has received research support from Novartis. The institution of Dr. McGinley has received research support from Biogen. The institution of Dr. McGinley has received research support from Genentech. The institution of Dr. McGinley has received research support from NIH. Mr. Harvey has nothing to disclose. The institution of Dr. Fitzgerald has received research support from NIH. The institution of Dr. Fitzgerald has received research support from National MS Society. Dr. Mowry has received personal compensation in the range of $500-$4,999 for serving as an Editor, Associate Editor, or Editorial Advisory Board Member for UpToDate. The institution of Dr. Mowry has received research support from Biogen. The institution of Dr. Mowry has received research support from Teva. The institution of Dr. Mowry has received research support from Genzyme. The institution of Dr. Mowry has received research support from Genentech. Dr. Cohen has received personal compensation in the range of $10,000-$49,999 for serving as a Consultant for Convelo. Dr. Cohen has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Mylan. Dr. Cohen has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Biogen. Dr. Cohen has received personal compensation in the range of $500-$4,999 for serving as a Consultant for PSI. Dr. Cohen has received personal compensation in the range of $500-$4,999 for serving as a Consultant for EMD Serono. Dr. Cohen has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Gossamer Bio. Dr. Cohen has received personal compensation in the range of $500-$4,999 for serving as an Editor, Associate Editor, or Editorial Advisory Board Member for Sage. The institution of Prof. Briggs has received research support from NIH. The institution of Prof. Briggs has received research support from Michael J. Fox Foundation.

Association of Daily Physical Activity with Cervical Spinal Cord Areas in Multiple Sclerosis (S27.009)

Association of Daily Physical Activity with Cervical Spinal Cord Areas in Multiple Sclerosis (S27.009)

High-frequency longitudinal white matter diffusion- and myelin-based MRI database: Reliability and variability.

Assessing the consistency of quantitative MRI measurements is critical for inclusion in longitudinal studies and clinical trials. Intraclass coefficient correlation and coefficient of variation were used to evaluate the different consistency aspects of diffusion- and myelin-based MRI measures. Multi-shell diffusion and inhomogeneous magnetization transfer data sets were collected from 20 healthy adults at a high-frequency of five MRI sessions. The consistency was evaluated across whole bundles and the track-profile along the bundles. The impact of the fiber populations on the consistency was also evaluated using the number of fiber orientations map. For whole and profile bundles, moderate to high reliability of diffusion and myelin measures were observed. We report higher reliability of measures for multiple fiber populations than single. The overall portrait of the most consistent measurements and bundles drawn from a wide range of MRI techniques presented here will be particularly useful for identifying reliable biomarkers capable of detecting, monitoring and predicting white matter changes in clinical applications and has the potential to inform patient-specific treatment strategies.

Patterns of inflammation, microstructural alterations, and sodium accumulation define multiple sclerosis subtypes after 15 years from onset.

Conventional MRI is routinely used for the characterization of pathological changes in multiple sclerosis (MS), but due to its lack of specificity is unable to provide accurate prognoses, explain disease heterogeneity and reconcile the gap between observed clinical symptoms and radiological evidence. Quantitative MRI provides measures of physiological abnormalities, otherwise invisible to conventional MRI, that correlate with MS severity. Analyzing quantitative MRI measures through machine learning techniques has been shown to improve the understanding of the underlying disease by better delineating its alteration patterns. In this retrospective study, a cohort of healthy controls (HC) and MS patients with different subtypes, followed up 15 years from clinically isolated syndrome (CIS), was analyzed to produce a multi-modal set of quantitative MRI features encompassing relaxometry, microstructure, sodium ion concentration, and tissue volumetry. Random forest classifiers were used to train a model able to discriminate between HC, CIS, relapsing remitting (RR) and secondary progressive (SP) MS patients based on these features and, for each classification task, to identify the relative contribution of each MRI-derived tissue property to the classification task itself. Average classification accuracy scores of 99 and 95% were obtained when discriminating HC and CIS vs. SP, respectively; 82 and 83% for HC and CIS vs. RR; 76% for RR vs. SP, and 79% for HC vs. CIS. Different patterns of alterations were observed for each classification task, offering key insights in the understanding of MS phenotypes pathophysiology: atrophy and relaxometry emerged particularly in the classification of HC and CIS vs. MS, relaxometry within lesions in RR vs. SP, sodium ion concentration in HC vs. CIS, and microstructural alterations were involved across all tasks.

Editors' Note: Prospective Natural History Study in 24 Adult Patients With LGMDR12 Over 2 Years of Follow-up: Quantitative MRI and Clinical Outcome Measures.

De Wel et al. prospectively studied 24 patients with autosomal recessive limb-girdle muscular dystrophy type 12 (LGMDR12). Patients with LGMDR12 had no appreciable clinical worsening over a 2-year period according to repeated standardized clinical assessments, such as the 6-minute walk distance, 10-meter walk test, or Medical Research Council sum scores of muscle power. However, for patients with LGMDR12 and intermediate-stage fatty replacement of muscle tissue (20%–70% proton density fat fraction), there was a significant worsening of Biodex Isometric Dynamometry even after 1 year. The investigators conclude this quantitative tool may be useful in monitoring clinical progression and response to targeted treatments for LGMDR12. Dr. Kawada expresses a concern regarding lead-time bias in the cohort (unclear time of disease onset in a recessive condition) which may have confounded any differences in the various qualitative and quantitative assessments over time. In response, the investigators confirmed that patients were included at the time of clinical symptom onset. Both investigators agree that sex-related differences in disease progression are less well understood, and additional studies are suggested to explore reasons for the variability in prognosis between sexes and age groups. De Wel et al. prospectively studied 24 patients with autosomal recessive limb-girdle muscular dystrophy type 12 (LGMDR12). Patients with LGMDR12 had no appreciable clinical worsening over a 2-year period according to repeated standardized clinical assessments, such as the 6-minute walk distance, 10-meter walk test, or Medical Research Council sum scores of muscle power. However, for patients with LGMDR12 and intermediate-stage fatty replacement of muscle tissue (20%–70% proton density fat fraction), there was a significant worsening of Biodex Isometric Dynamometry even after 1 year. The investigators conclude this quantitative tool may be useful in monitoring clinical progression and response to targeted treatments for LGMDR12. Dr. Kawada expresses a concern regarding lead-time bias in the cohort (unclear time of disease onset in a recessive condition) which may have confounded any differences in the various qualitative and quantitative assessments over time. In response, the investigators confirmed that patients were included at the time of clinical symptom onset. Both investigators agree that sex-related differences in disease progression are less well understood, and additional studies are suggested to explore reasons for the variability in prognosis between sexes and age groups.