PARE: A framework for removal of confounding effects from any distance-based dimension reduction method.

Dimension reduction tools preserving similarity and graph structure such as t-SNE and UMAP can capture complex biological patterns in high-dimensional data. However, these tools typically are not designed to separate effects of interest from unwanted effects due to confounders. We introduce the partial embedding (PARE) framework, which enables removal of confounders from any distance-based dimension reduction method. We then develop partial t-SNE and partial UMAP and apply these methods to genomic and neuroimaging data. For lower-dimensional visualization, our results show that the PARE framework can remove batch effects in single-cell sequencing data as well as separate clinical and technical variability in neuroimaging measures. We demonstrate that the PARE framework extends dimension reduction methods to highlight biological patterns of interest while effectively removing confounding effects.

Early Predictors of Clinical and MRI Outcomes Using Least Absolute Shrinkage and Selection Operator (LASSO) in Multiple Sclerosis.

OBJECTIVE: The objective of this study was to identify predictors in common between different clinical and magnetic resonance imaging (MRI) outcomes in multiple sclerosis (MS) by comparing predictive models. METHODS: We analyzed 704 patients from our center seen at MS onset, measuring 37 baseline demographic, clinical, treatment, and MRI predictors, and 10-year outcomes. Our primary aim was identifying predictors in common among clinical outcomes: aggressive MS, benign MS, and secondary-progressive (SP)MS. We also investigated MRI outcomes: T2 lesion volume (T2LV) and brain parenchymal fraction (BPF). The performance of the full 37-predictor model was compared with a least absolute shrinkage and selection operator (LASSO)-selected model of predictors in common between each outcome by the area under the receiver operating characteristic curves (AUCs). RESULTS: The full 37-predictor model was highly predictive of clinical outcomes: in-sample AUC was 0.91 for aggressive MS, 0.81 for benign MS, and 0.81 for SPMS. After variable selection, 10 LASSO-selected predictors were in common between each clinical outcome: age, Expanded Disability Status Scale, pyramidal, cerebellar, sensory and bowel/bladder signs, timed 25-foot walk ≥6 seconds, poor attack recovery, no sensory attacks, and time-to-treatment. This reduced model had comparable cross-validation AUC as the full 37-predictor model: 0.84 versus 0.81 for aggressive MS, 0.75 versus 0.73 for benign MS, and 0.76 versus 0.75 for SPMS, respectively. In contrast, 10-year MRI outcomes were more strongly influenced by initial T2LV and BPF than clinical outcomes. INTERPRETATION: Early prognostication of MS is possible using LASSO modeling to identify a limited set of accessible clinical features. These predictive models can be clinically usable in treatment decision making once implemented into web-based calculators. ANN NEUROL 2022;92:87-96.

Serum NfL but not GFAP predicts cognitive decline in active progressive multiple sclerosis patients.

BACKGROUND: Cognitive decline is inadequately captured by the standard neurological examination. Serum neurofilament light chain (sNfL) and glial fibrillary acidic protein (sGFAP) are biomarkers of neuronal damage and astrocytic reactivity that may offer an accessible measure of the multiple sclerosis (MS) pathology linked to cognitive decline. OBJECTIVE: To investigate the association of sNfL and sGFAP with cognitive decline in MS patients at high risk for progressive pathology. METHODS: We included 94 MS patients with sustained Expanded Disability Status Score (EDSS) ⩾ 3, available serum samples and cognitive assessment performed by symbol digit modalities test (SDMT) over a median of 3.1 years. The visit for sGFAP/sNfL quantification was at confirmed EDSS ⩾ 3. Linear regression analysis on log-transformed sGFAP/sNfL assessed the association with current and future SDMT. Analyses were adjusted for age, sex, EDSS, treatment group, and recent relapse. RESULTS: sNfL was significantly associated with concurrent SDMT (adjusted change in mean SDMT = -4.5; 95% confidence interval (CI): -8.7, -0.2; p = 0.039) and predicted decline in SDMT (adjusted change in slope: -1.14; 95% CI: -1.83, -0.44; p = 0.001), particularly in active patients. sGFAP was not associated with concurrent or future SDMT. CONCLUSIONS: Higher levels of sNfL were associated with cognitive impairment and predicted cognitive decline in MS patients at high risk for having an underlying progressive pathology.

Accuracy of serum neurofilament light to identify contrast-enhancing lesions in multiple sclerosis.

BACKGROUND: Contrast-enhancing magnetic resonance imaging (MRI) lesions (CELs) indicate acute multiple sclerosis inflammation. Serum biomarkers, neurofilament light (sNfL), and glial fibrillary acidic protein (sGFAP) may increase in the presence of CELs, and indicate a need to perform MRI. OBJECTIVE: We assessed the accuracy of biomarkers to detect CELs. METHODS: Patients with two gadolinium-enhanced MRIs and serum biomarkers tested within 3 months were included (N = 557, 66% female). Optimal cut-points from Bland-Altman analysis for spot biomarker level and Youden's index for delta-change from remission were evaluated. RESULTS: A total of 116 patients (21%) had CELs. A spot sNfL measurement >23.0 pg/mL corresponded to 7.0 times higher odds of CEL presence (95% CI: 3.8, 12.8), with 25.9% sensitivity, 95.2% specificity, operating characteristic curve (AUC) 0.61; while sNfL delta-change >30.8% from remission corresponded to 5.0 times higher odds (95% CI: 3.2, 7.8), 52.6% sensitivity, 81.9% specificity, AUC 0.67. sGFAP had poor CEL detection. In patients > 50 years, neither cut-point remained significant. sNfL delta-change outperformed spot levels at identifying asymptomatic CELs (AUC 0.67 vs 0.59) and in patients without treatment escalation between samples (AUC 0.67 vs 0.57). CONCLUSION: Spot sNfL >23.0 pg/mL or a 30.8% increase from remission provides modest prediction of CELs in patients <50 years; however, low sNfL does not obviate the need for MRI.

A local group differences test for subject-level multivariate density neuroimaging outcomes.

A great deal of neuroimaging research focuses on voxel-wise analysis or segmentation of damaged tissue, yet many diseases are characterized by diffuse or non-regional neuropathology. In simple cases, these processes can be quantified using summary statistics of voxel intensities. However, the manifestation of a disease process in imaging data is often unknown, or appears as a complex and nonlinear relationship between the voxel intensities on various modalities. When the relevant pattern is unknown, summary statistics are often unable to capture differences between disease groups, and their use may encourage post hoc searches for the optimal summary measure. In this study, we introduce the multi-modal density testing (MMDT) framework for the naive discovery of group differences in voxel intensity profiles. MMDT operationalizes multi-modal magnetic resonance imaging (MRI) data as multivariate subject-level densities of voxel intensities and utilizes kernel density estimation to develop a local two-sample test for individual points within the density space. Through simulations, we show that this method controls type I error and recovers relevant differences when applied to a specified point. Additionally, we demonstrate the ability to maintain power while controlling the family-wise error rate and false discovery rate when applying the test over a grid of points within the density space. Finally, we apply this method to a study of subjects with either multiple sclerosis (MS) or conditions that tend to mimic MS on MRI, and find significant differences between the two groups in their voxel intensity profiles within the thalamus.

Gut Microbiome in Progressive Multiple Sclerosis.

OBJECTIVE: This study was undertaken to investigate the gut microbiome in progressive multiple sclerosis (MS) and how it relates to clinical disease. METHODS: We sequenced the microbiota from healthy controls and relapsing-remitting MS (RRMS) and progressive MS patients and correlated the levels of bacteria with clinical features of disease, including Expanded Disability Status Scale (EDSS), quality of life, and brain magnetic resonance imaging lesions/atrophy. We colonized mice with MS-derived Akkermansia and induced experimental autoimmune encephalomyelitis (EAE). RESULTS: Microbiota ß-diversity differed between MS patients and controls but did not differ between RRMS and progressive MS or differ based on disease-modifying therapies. Disease status had the greatest effect on the microbiome ß-diversity, followed by body mass index, race, and sex. In both progressive MS and RRMS, we found increased Clostridium bolteae, Ruthenibacterium lactatiformans, and Akkermansia and decreased Blautia wexlerae, Dorea formicigenerans, and Erysipelotrichaceae CCMM. Unique to progressive MS, we found elevated Enterobacteriaceae and Clostridium g24 FCEY and decreased Blautia and Agathobaculum. Several Clostridium species were associated with higher EDSS and fatigue scores. Contrary to the view that elevated Akkermansia in MS has a detrimental role, we found that Akkermansia was linked to lower disability, suggesting a beneficial role. Consistent with this, we found that Akkermansia isolated from MS patients ameliorated EAE, which was linked to a reduction in RORγt+ and IL-17-producing γδ T cells. INTERPRETATION: Whereas some microbiota alterations are shared in relapsing and progressive MS, we identified unique bacteria associated with progressive MS and clinical measures of disease. Furthermore, elevated Akkermansia in MS may be a compensatory beneficial response in the MS microbiome. ANN NEUROL 2021;89:1195-1211.

Younger age at multiple sclerosis onset is associated with worse outcomes at age 50.

OBJECTIVE: Older age at multiple sclerosis (MS) onset has been associated with worse 10-year outcomes. However, disease duration often exceeds 10 years and age-related comorbidities may also contribute to disability. We investigated patients with>10 years disease duration to determine how age at MS onset is associated with clinical, MRI and occupational outcomes at age 50. METHODS: We included patients enrolled in the Comprehensive Longitudinal Investigation of Multiple Sclerosis at the Brigham and Women's Hospital with disease duration>10 years. Outcomes at age 50 included the Expanded Disability Status Scale (EDSS), development of secondary-progressive multiple sclerosis (SPMS), brain T2-lesion volume (T2LV) and brain parenchymal fraction (BPF), and occupational status. We assessed how onset age was independently associated with each outcome when adjusting for the date of visit closest to age 50, sex, time to first treatment, number of treatments by age 50 and exposure to high-efficacy treatments by age 50. RESULTS: We included 661 patients with median onset at 31.4 years. The outcomes at age 50 were worse the younger first symptoms developed: for every 5 years earlier, the EDSS was 0.22 points worse (95% CI: 0.04 to 0.40; p=0.015), odds of SPMS 1.33 times higher (95% CI: 1.08 to 1.64; p=0.008), T2LV 1.86 mL higher (95% CI: 1.02 to 2.70; p<0.001), BPF 0.97% worse (95% CI: 0.52 to 1.42; p<0.001) and odds of unemployment from MS 1.24 times higher (95% CI: 1.01 to 1.53; p=0.037). CONCLUSIONS: All outcomes at age 50 were worse in patients with younger age at onset. Decisions to provide high-efficacy treatments should consider younger age at onset, equating to a longer expected disease duration, as a poor prognostic factor.

Anti-SARS-CoV-2 monoclonal antibodies for the treatment of active COVID-19 in multiple sclerosis: An observational study.

Monoclonal antibodies (mAbs) against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) received emergency use authorization for the acute treatment of COVID-19. We are not aware of published data on their use in immunosuppressed people with multiple sclerosis (pwMS). We report 23 pwMS (mean age = 49 years, ocrelizumab (n = 19), fingolimod (n = 2), vaccinated with at least an initial series (n = 19)) who received mAb for acute COVID-19. Following mAb receipt, approximately half recovered in <7 days (48%). There were no adverse events or deaths. Use of mAb for pwMS treated with fingolimod or ocrelizumab was not observed to be harmful and is likely helpful for treatment of acute COVID-19.

Trajectories of Symbol Digit Modalities Test performance in individuals with multiple sclerosis.

BACKGROUND: Although cognitive problems have been identified in people with multiple sclerosis (PwMS), few studies have investigated the long-term change in cognitive functioning. OBJECTIVE: To identify trajectories of change in cognitive functioning for PwMS. METHODS: Participants enrolled in the quality-of-life subgroup from the Comprehensive Longitudinal Investigation of Multiple Sclerosis at Brigham and Women's Hospital (CLIMB) were eligible for our analysis. In 2006, participants in this group began to complete the Symbol Digit Modalities Test (SDMT) annually. Latent trajectory models were used to identify groups of participants with similar longitudinal change in SDMT scores. Linear and quadratic trajectory models were fit, and the models were compared. Latent trajectory models were also fit adjusting for baseline age and disease duration as well as using normalized SDMT scores. The groups identified across the approaches were compared. RESULTS: We found that classes with higher-than-average baseline values improved, classes with average baseline values remained relatively constant, and classes with lower baseline values experienced cognitive worsening. Similar results were observed in the alternative latent trajectory models accounting for other variables. CONCLUSION: Our models show that subjects with higher SDMT scores at baseline showed improvement, while subjects with lower SDMT scores at baseline showed worsening. Baseline age and disease duration were also associated with SDMT performance.

7 T imaging reveals a gradient in spinal cord lesion distribution in multiple sclerosis.

We used 7 T MRI to: (i) characterize the grey and white matter pathology in the cervical spinal cord of patients with early relapsing-remitting and secondary progressive multiple sclerosis; (ii) assess the spinal cord lesion spatial distribution and the hypothesis of an outside-in pathological process possibly driven by CSF-mediated immune cytotoxic factors; and (iii) evaluate the association of spinal cord pathology with brain burden and its contribution to neurological disability. We prospectively recruited 20 relapsing-remitting, 15 secondary progressive multiple sclerosis participants and 11 age-matched healthy control subjects to undergo 7 T imaging of the cervical spinal cord and brain as well as conventional 3 T brain acquisition. Cervical spinal cord imaging at 7 T was used to segment grey and white matter, including lesions therein. Brain imaging at 7 T was used to segment cortical and white matter lesions and 3 T imaging for cortical thickness estimation. Cervical spinal cord lesions were mapped voxel-wise as a function of distance from the inner central canal CSF pool to the outer subpial surface. Similarly, brain white matter lesions were mapped voxel-wise as a function of distance from the ventricular system. Subjects with relapsing-remitting multiple sclerosis showed a greater predominance of spinal cord lesions nearer the outer subpial surface compared to secondary progressive cases. Inversely, secondary progressive participants presented with more centrally located lesions. Within the brain, there was a strong gradient of lesion formation nearest the ventricular system that was most evident in participants with secondary progressive multiple sclerosis. Lesion fractions within the spinal cord grey and white matter were related to the lesion fraction in cerebral white matter. Cortical thinning was the primary determinant of the Expanded Disability Status Scale, white matter lesion fractions in the spinal cord and brain of the 9-Hole Peg Test and cortical thickness and spinal cord grey matter cross-sectional area of the Timed 25-Foot Walk. Spinal cord lesions were localized nearest the subpial surfaces for those with relapsing-remitting and the central canal CSF surface in progressive disease, possibly implying CSF-mediated pathogenic mechanisms in lesion development that may differ between multiple sclerosis subtypes. These findings show that spinal cord lesions involve both grey and white matter from the early multiple sclerosis stages and occur mostly independent from brain pathology. Despite the prevalence of cervical spinal cord lesions and atrophy, brain pathology seems more strongly related to physical disability as measured by the Expanded Disability Status Scale.

Multiple sclerosis lesions in motor tracts from brain to cervical cord: spatial distribution and correlation with disability.

Despite important efforts to solve the clinico-radiological paradox, correlation between lesion load and physical disability in patients with multiple sclerosis remains modest. One hypothesis could be that lesion location in corticospinal tracts plays a key role in explaining motor impairment. In this study, we describe the distribution of lesions along the corticospinal tracts from the cortex to the cervical spinal cord in patients with various disease phenotypes and disability status. We also assess the link between lesion load and location within corticospinal tracts, and disability at baseline and 2-year follow-up. We retrospectively included 290 patients (22 clinically isolated syndrome, 198 relapsing remitting, 39 secondary progressive, 31 primary progressive multiple sclerosis) from eight sites. Lesions were segmented on both brain (T2-FLAIR or T2-weighted) and cervical (axial T2- or T2*-weighted) MRI scans. Data were processed using an automated and publicly available pipeline. Brain, brainstem and spinal cord portions of the corticospinal tracts were identified using probabilistic atlases to measure the lesion volume fraction. Lesion frequency maps were produced for each phenotype and disability scores assessed with Expanded Disability Status Scale score and pyramidal functional system score. Results show that lesions were not homogeneously distributed along the corticospinal tracts, with the highest lesion frequency in the corona radiata and between C2 and C4 vertebral levels. The lesion volume fraction in the corticospinal tracts was higher in secondary and primary progressive patients (mean = 3.6 ± 2.7% and 2.9 ± 2.4%), compared to relapsing-remitting patients (1.6 ± 2.1%, both P < 0.0001). Voxel-wise analyses confirmed that lesion frequency was higher in progressive compared to relapsing-remitting patients, with significant bilateral clusters in the spinal cord corticospinal tracts (P < 0.01). The baseline Expanded Disability Status Scale score was associated with lesion volume fraction within the brain (r = 0.31, P < 0.0001), brainstem (r = 0.45, P < 0.0001) and spinal cord (r = 0.57, P < 0.0001) corticospinal tracts. The spinal cord corticospinal tracts lesion volume fraction remained the strongest factor in the multiple linear regression model, independently from cord atrophy. Baseline spinal cord corticospinal tracts lesion volume fraction was also associated with disability progression at 2-year follow-up (P = 0.003). Our results suggest a cumulative effect of lesions within the corticospinal tracts along the brain, brainstem and spinal cord portions to explain physical disability in multiple sclerosis patients, with a predominant impact of intramedullary lesions.

7T MRI cerebral leptomeningeal enhancement is common in relapsing-remitting multiple sclerosis and is associated with cortical and thalamic lesions.

BACKGROUND: Meningeal inflammation may contribute to gray matter (GM) involvement in multiple sclerosis (MS) and is proposed to manifest as magnetic resonance imaging (MRI) leptomeningeal enhancement (LME). OBJECTIVE: To investigate how LME relates to GM lesions in relapsing-remitting multiple sclerosis (RRMS) at 7T. METHODS: A total of 30 RRMS subjects (age (mean ± standard deviation (SD)): 44.0 ± 11.3 years, 93% on disease-modifying treatment) and 15 controls underwent gadolinium-enhanced three-dimensional (3D) MP2RAGE (magnetization-prepared 2 rapid gradient-echo) and fluid-attenuated inversion recovery (FLAIR) MRI. LME, cortical lesions (CLs), thalamic lesions (TLs), and white matter (WM) lesions were expert-quantified. Wilcoxon rank-sum, two-sample t-tests, Spearman correlations, and regression models were employed. RESULTS: Two-thirds (20/30) of MS subjects and 1/15 controls (6.7%) had LME. LME+ MS subjects had 2.7 ± 1.5 foci, longer disease duration (14.9 ± 10.4 vs. 8.1 ± 5.7 years, p = 0.028), increased CL number (21.5 ± 12.6 vs. 5.5 ± 5.0, p < 0.001) and volume (0.80 ± 1.13 vs. 0.13 ± 0.13 mL, p = 0.002), and increased TL number (3.95 ± 2.11 vs. 0.70 ± 1.34, p < 0.001) and volume (0.106 ± 0.09 vs. 0.007 ± 0.01 mL, p < 0.001) versus LME- subjects. LME focus number correlated more highly with CL (rs = 0.50, p = 0.01) and TL (rs = 0.81, p < 0.001) than WM lesion (rs = 0.34, p > 0.05) volume. Similar LME-CL number associations were observed in unadjusted and WM lesion-adjusted comparisons (both p < 0.001). CONCLUSION: Cerebral LME is common in RRMS at 7T and is independently associated with GM injury. We hypothesize that cerebrospinal fluid (CSF)-related inflammation links cortical and thalamic injury.

Spatial distribution of multiple sclerosis lesions in the cervical spinal cord.

Spinal cord lesions detected on MRI hold important diagnostic and prognostic value for multiple sclerosis. Previous attempts to correlate lesion burden with clinical status have had limited success, however, suggesting that lesion location may be a contributor. Our aim was to explore the spatial distribution of multiple sclerosis lesions in the cervical spinal cord, with respect to clinical status. We included 642 suspected or confirmed multiple sclerosis patients (31 clinically isolated syndrome, and 416 relapsing-remitting, 84 secondary progressive, and 73 primary progressive multiple sclerosis) from 13 clinical sites. Cervical spine lesions were manually delineated on T2- and T2*-weighted axial and sagittal MRI scans acquired at 3 or 7 T. With an automatic publicly-available analysis pipeline we produced voxelwise lesion frequency maps to identify predilection sites in various patient groups characterized by clinical subtype, Expanded Disability Status Scale score and disease duration. We also measured absolute and normalized lesion volumes in several regions of interest using an atlas-based approach, and evaluated differences within and between groups. The lateral funiculi were more frequently affected by lesions in progressive subtypes than in relapsing in voxelwise analysis (P < 0.001), which was further confirmed by absolute and normalized lesion volumes (P < 0.01). The central cord area was more often affected by lesions in primary progressive than relapse-remitting patients (P < 0.001). Between white and grey matter, the absolute lesion volume in the white matter was greater than in the grey matter in all phenotypes (P < 0.001); however when normalizing by each region, normalized lesion volumes were comparable between white and grey matter in primary progressive patients. Lesions appearing in the lateral funiculi and central cord area were significantly correlated with Expanded Disability Status Scale score (P < 0.001). High lesion frequencies were observed in patients with a more aggressive disease course, rather than long disease duration. Lesions located in the lateral funiculi and central cord area of the cervical spine may influence clinical status in multiple sclerosis. This work shows the added value of cervical spine lesions, and provides an avenue for evaluating the distribution of spinal cord lesions in various patient groups.

Automatic segmentation of the spinal cord and intramedullary multiple sclerosis lesions with convolutional neural networks.

The spinal cord is frequently affected by atrophy and/or lesions in multiple sclerosis (MS) patients. Segmentation of the spinal cord and lesions from MRI data provides measures of damage, which are key criteria for the diagnosis, prognosis, and longitudinal monitoring in MS. Automating this operation eliminates inter-rater variability and increases the efficiency of large-throughput analysis pipelines. Robust and reliable segmentation across multi-site spinal cord data is challenging because of the large variability related to acquisition parameters and image artifacts. In particular, a precise delineation of lesions is hindered by a broad heterogeneity of lesion contrast, size, location, and shape. The goal of this study was to develop a fully-automatic framework - robust to variability in both image parameters and clinical condition - for segmentation of the spinal cord and intramedullary MS lesions from conventional MRI data of MS and non-MS cases. Scans of 1042 subjects (459 healthy controls, 471 MS patients, and 112 with other spinal pathologies) were included in this multi-site study (n = 30). Data spanned three contrasts (T1-, T2-, and T2∗-weighted) for a total of 1943 vol and featured large heterogeneity in terms of resolution, orientation, coverage, and clinical conditions. The proposed cord and lesion automatic segmentation approach is based on a sequence of two Convolutional Neural Networks (CNNs). To deal with the very small proportion of spinal cord and/or lesion voxels compared to the rest of the volume, a first CNN with 2D dilated convolutions detects the spinal cord centerline, followed by a second CNN with 3D convolutions that segments the spinal cord and/or lesions. CNNs were trained independently with the Dice loss. When compared against manual segmentation, our CNN-based approach showed a median Dice of 95% vs. 88% for PropSeg (p ≤ 0.05), a state-of-the-art spinal cord segmentation method. Regarding lesion segmentation on MS data, our framework provided a Dice of 60%, a relative volume difference of -15%, and a lesion-wise detection sensitivity and precision of 83% and 77%, respectively. In this study, we introduce a robust method to segment the spinal cord and intramedullary MS lesions on a variety of MRI contrasts. The proposed framework is open-source and readily available in the Spinal Cord Toolbox.

Multisite reliability and repeatability of an advanced brain MRI protocol.

BACKGROUND: MRI is the imaging modality of choice for diagnosis and intervention assessment in neurological disease. Its full potential has not been realized due in part to challenges in harmonizing advanced techniques across multiple sites. PURPOSE: To develop a method for the assessment of reliability and repeatability of advanced multisite-multisession neuroimaging studies and specifically to assess the reliability of an advanced MRI protocol, including multiband fMRI and diffusion tensor MRI, in a multisite setting. STUDY TYPE: Prospective. POPULATION: Twice repeated measurement of a single subject with stable relapsing-remitting multiple sclerosis (MS) at seven institutions. FIELD STRENGTH/SEQUENCE: A 3 T MRI protocol included higher spatial resolution anatomical scans, a variable flip-angle longitudinal relaxation rate constant (R1 ≡ 1/T1 ) measurement, quantitative magnetization transfer imaging, diffusion tensor imaging, and a resting-state fMRI (rsFMRI) series. ASSESSMENT: Multiple methods of assessing intrasite repeatability and intersite reliability were evaluated for imaging metrics derived from each sequence. STATISTICAL TESTS: Student's t-test, Pearson's r, and intraclass correlation coefficient (ICC) (2,1) were employed to assess repeatability and reliability. Two new statistical metrics are introduced that frame reliability and repeatability in the respective units of the measurements themselves. RESULTS: Intrasite repeatability was excellent for quantitative R1 , magnetization transfer ratio (MTR), and diffusion-weighted imaging (DWI) based metrics (r > 0.95). rsFMRI metrics were less repeatable (r = 0.8). Intersite reliability was excellent for R1 , MTR, and DWI (ICC >0.9), and moderate for rsFMRI metrics (ICC∼0.4). DATA CONCLUSION: From most reliable to least, using a new reliability metric introduced here, MTR > R1 > DWI > rsFMRI; for repeatability, MTR > DWI > R1 > rsFMRI. A graphical method for at-a-glance assessment of reliability and repeatability, effect sizes, and outlier identification in multisite-multisession neuroimaging studies is introduced. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:878-888.

The neutrophil-to-lymphocyte and monocyte-to-lymphocyte ratios are independently associated with neurological disability and brain atrophy in multiple sclerosis.

BACKGROUND: Serum hematological indices such as the neutrophil-lymphocyte ratio (NLR) or monocyte-lymphocyte ratio (MLR) have been used as biomarkers of pathogenic inflammation and prognostication in multiple areas of medicine; recent evidence shows correlation with psychological parameters as well. OBJECTIVES/AIMS: To characterize clinical, neuroimaging, and psycho-neuro-immunological associations with NLR and MLR in persons with multiple sclerosis (MS). METHODS: We identified a large cohort of clinically well-defined patients from our longitudinal database that included MS-related outcomes, disease-modifying therapy, patient-reported outcome (PRO) measures, and quantified cerebral MRI at 1.5 T. We queried hospital records for complete blood counts within 2 months of each clinic visit and excluded those obtained during clinical relapses. Four hundred eighty-three patients, with a mean of 3 longitudinal observations each, were identified who met these criteria. Initial analyses assessed the association between NLR and MLR as the outcomes, and psychological and demographic predictors in univariable and multivariable models controlling for age, gender and treatment. The second set of analyses assessed the association between clinical and MRI outcomes including whole brain atrophy and T2-hyperintense lesion volume, with NLR and MLR as predictors in univariable and multivariable models. All analyses used a mixed effects linear or logistic regression model with repeated measures. RESULTS: Unadjusted analyses demonstrated significant associations between higher (log-transformed) NLR (but not MLR) and PRO measures including increasing depression (p = 0.01), fatigue (p < 0.01), and decreased physical quality of life (p < 0.01). Higher NLR and MLR strongly predicted increased MS-related disability as assessed by the Expanded Disability Status Scale, independent of all demographic, clinical, treatment-related, and psychosocial variables (p < 0.001). Lastly, higher NLR and MLR significantly discriminated progressive from relapsing status (p ≤ 0.01 for both), and higher MLR correlated with increased whole-brain atrophy (p < 0.05) but not T2 hyperintense lesion volume (p > 0.05) even after controlling for all clinical and demographic covariates. Sensitivity analyses using a subset of untreated patients (N = 146) corroborated these results. CONCLUSIONS: Elevated NLR and MLR may represent hematopoetic bias toward increased production and pro-inflammatory priming of the myeloid innate immune system (numerator) in conjunction with dysregulated adaptive immune processes (denominator), and consequently reflect a complementary and independent marker for severity of MS-related neurological disability and MRI outcomes.

Gradient nonlinearity effects on upper cervical spinal cord area measurement from 3D T1 -weighted brain MRI acquisitions.

PURPOSE: To explore (i) the variability of upper cervical cord area (UCCA) measurements from volumetric brain 3D T1 -weighted scans related to gradient nonlinearity (GNL) and subject positioning; (ii) the effect of vendor-implemented GNL corrections; and (iii) easily applicable methods that can be used to retrospectively correct data. METHODS: A multiple sclerosis patient was scanned at seven sites using 3T MRI scanners with the same 3D T1 -weighted protocol without GNL-distortion correction. Two healthy subjects and a phantom were additionally scanned at a single site with varying table positions. The 2D and 3D vendor-implemented GNL-correction algorithms and retrospective methods based on (i) phantom data fit, (ii) normalization with C2 vertebral body diameters, and (iii) the Jacobian determinant of nonlinear registrations to a template were tested. RESULTS: Depending on the positioning of the subject, GNL introduced up to 15% variability in UCCA measurements from volumetric brain T1 -weighted scans when no distortion corrections were used. The 3D vendor-implemented correction methods and the three proposed methods reduced this variability to less than 3%. CONCLUSIONS: Our results raise awareness of the significant impact that GNL can have on quantitative UCCA studies, and point the way to prospectively and retrospectively managing GNL distortions in a variety of settings, including clinical environments. Magn Reson Med 79:1595-1601, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

The NAIMS cooperative pilot project: Design, implementation and future directions.

The North American Imaging in Multiple Sclerosis (NAIMS) Cooperative represents a network of 27 academic centers focused on accelerating the pace of magnetic resonance imaging (MRI) research in multiple sclerosis (MS) through idea exchange and collaboration. Recently, NAIMS completed its first project evaluating the feasibility of implementation and reproducibility of quantitative MRI measures derived from scanning a single MS patient using a high-resolution 3T protocol at seven sites. The results showed the feasibility of utilizing advanced quantitative MRI measures in multicenter studies and demonstrated the importance of careful standardization of scanning protocols, central image processing, and strategies to account for inter-site variability.

Automated segmentation of cerebral deep gray matter from MRI scans: effect of field strength on sensitivity and reliability.

BACKGROUND: The cerebral subcortical deep gray matter nuclei (DGM) are a common, early, and clinically-relevant site of atrophy in multiple sclerosis (MS). Robust and reliable DGM segmentation could prove useful to evaluate putative neuroprotective MS therapies. The objective of the study was to compare the sensitivity and reliability of DGM volumes obtained from 1.5T vs. 3T MRI. METHODS: Fourteen patients with MS [age (mean, range) 50.2 (32.0-60.8) years, disease duration 18.4 (8.2-35.5) years, Expanded Disability Status Scale score 3.1 (0-6), median 3.0] and 15 normal controls (NC) underwent brain 3D T1-weighted paired scan-rescans at 1.5T and 3T. DGM (caudate, thalamus, globus pallidus, and putamen) segmentation was obtained by the fully automated FSL-FIRST pipeline. Both raw and normalized volumes were derived. RESULTS: DGM volumes were generally higher at 3T vs. 1.5T in both groups. For raw volumes, 3T showed slightly better sensitivity (thalamus: p = 0.02; caudate: p = 0.10; putamen: p = 0.02; globus pallidus: p = 0.0004; total DGM: p = 0.01) than 1.5T (thalamus: p = 0.05; caudate: p = 0.09; putamen: p = 0.03; globus pallidus: p = 0.0006; total DGM: p = 0.02) for detecting DGM atrophy in MS vs. NC. For normalized volumes, 3T but not 1.5T detected atrophy in the globus pallidus in the MS group. Across all subjects, scan-rescan reliability was generally very high for both platforms, showing slightly higher reliability for some DGM volumes at 3T. Raw volumes showed higher reliability than normalized volumes. Raw DGM volume showed higher reliability than the individual structures. CONCLUSIONS: These results suggest somewhat higher sensitivity and reliability of DGM volumes obtained from 3T vs. 1.5T MRI. Further studies should assess the role of this 3T pipeline in tracking potential MS neurotherapeutic effects.

A longitudinal uncontrolled study of cerebral gray matter volume in patients receiving natalizumab for multiple sclerosis.

OBJECTIVE: Brain atrophy in multiple sclerosis (MS) selectively affects gray matter (GM), which is highly relevant to disability and cognitive impairment. We assessed cerebral GM volume (GMV) during one year of natalizumab therapy. DESIGN/METHODS: Patients with relapsing-remitting (n = 18) or progressive (n = 2) MS had MRI ∼1 year apart during natalizumab treatment. At baseline, patients were on natalizumab for (mean ± SD) 16.6 ± 10.9 months with age 38.5 ± 7.4 and disease duration 9.7 ± 4.3 years. RESULTS: At baseline, GMV was 664.0 ± 56.4 ml, Expanded Disability Status Scale (EDSS) score was 2.3 ± 2.0, timed 25-foot walk (T25FW) was 6.1±3.4 s; two patients (10%) had gadolinium (Gd)-enhancing lesions. At follow-up, GMV was 663.9 ± 60.2 mL; EDSS was 2.6 ± 2.1 and T25FW was 5.9 ± 2.9 s. One patient had a mild clinical relapse during the observation period (0.052 annualized relapse rate for the entire cohort). No patients had Gd-enhancing lesions at follow-up. Linear mixed-effect models showed no significant change in annualized GMV [estimated mean change per year 0.338 mL, 95% confidence interval -9.66, 10.34, p = 0.94)], GM fraction (p = 0.92), whole brain parenchymal fraction (p = 0.64), T2 lesion load (p = 0.64), EDSS (p = 0.26) or T25FW (p = 0.79). CONCLUSIONS: This pilot study shows no GM atrophy during one year of natalizumab MS therapy. We also did not detect any loss of whole brain volume or progression of cerebral T2 hyperintense lesion volume during the observation period. These MRI results paralleled the lack of clinical worsening.