Cervical and thoracic spinal cord gray matter atrophy is associated with disability in patients with amyotrophic lateral sclerosis.

BACKGROUND AND PURPOSE: In amyotrophic lateral sclerosis (ALS), there is an unmet need for more precise patient characterization through quantitative, ideally operator-independent, assessments of disease extent and severity. Radially sampled averaged magnetization inversion recovery acquisitions (rAMIRA) magnetic resonance imaging enables gray matter (GM) and white matter (WM) area quantitation in the cervical and thoracic spinal cord (SC) with optimized contrast. We aimed to investigate rAMIRA-derived SC GM and SC WM areas and their association with clinical phenotype and disability in ALS. METHODS: A total of 36 patients with ALS (mean [SD] age 61.7 [12.6] years, 14 women) and 36 healthy, age- and sex-matched controls (HCs; mean [SD] age 63.1 [12.1] years, 14 women) underwent two-dimensional axial rAMIRA imaging at the inter-vertebral disc levels C2/3-C5/C6 and the lumbar enlargement level Tmax. ALS Functional Rating Scale-revised (ALSFRS-R) score, muscle strength, and sniff nasal inspiratory pressure (SNIP) were assessed. RESULTS: Compared to HCs, GM and WM areas were reduced in patients at all cervical levels (p < 0.0001). GM area (p = 0.0001), but not WM area, was reduced at Tmax. Patients with King's Stage 3 showed significant GM atrophy at all levels, while patients with King's Stage 1 showed significant GM atrophy selectively at Tmax. SC GM area was significantly associated with muscle force at corresponding myotomes. GM area at C3/C4 was associated with ALSFRS-R (p < 0.001) and SNIP (p = 0.0016). CONCLUSION: Patients with ALS assessed by rAMIRA imaging show significant cervical and thoracic SC GM and SC WM atrophy. SC GM area correlates with muscle strength and clinical disability. GM area reduction at Tmax may be an early disease sign. Longitudinal studies are warranted.

Intrathecal IgM Synthesis Is Associated with Spinal Cord Manifestation and Neuronal Injury in Early MS.

OBJECTIVE: Intrathecal Immunoglobulin M synthesis (IgMIntrathecal Fraction (IF) + ) and spinal MRI lesions are both strong independent predictors of higher disease activity and severity in multiple sclerosis (MS). We investigated whether IgMIF + is associated with spinal cord manifestation and higher neuroaxonal damage in early MS. METHODS: In 122 patients with a first demyelinating event associations between (1) spinal versus (vs) non-spinal clinical syndrome (2) spinal vs cerebral T2-weighted (T2w) and (3) contrast-enhancing (CE) lesion counts with IgGIF + (vs IgGIF - ) or IgMIF + (vs IgMIF - ) were investigated by logistic regression adjusted for age and sex, respectively. For serum neurofilament light chain (sNfL) analysis patients were categorized for presence or absence of oligoclonal IgG bands (OCGB), IgGIF and IgMIF (>0% vs 0%, respectively): (1) OCGB- /IgGIF - /IgMIF - ; (2) OCGB+ /IgGIF - /IgMIF - ; (3) OCGB+ /IgGIF + /IgMIF - ; and (4) OCGB+ /IgGIF + /IgMIF + . Associations between categories 2 to 4 vs category 1 with sNfL concentrations were analyzed by robust linear regression, adjusted for sex and MRI parameters. RESULTS: Patients with a spinal syndrome had a 8.36-fold higher odds of IgMIF + (95%CI 3.03-23.03; p < 0.01). Each spinal T2w lesion (odds Ratio 1.39; 1.02-1.90; p = 0.037) and CE lesion (OR 2.73; 1.22-6.09; p = 0.014) was associated with an increased risk of IgMIF + (but not of IgGIF + ); this was not the case for cerebral lesions. OCGB+ /IgGIF + /IgMIF + category patients showed highest sNfL levels (estimate:1.80; 0.55-3.06; p < 0.01). INTERPRETATION: Intrathecal IgM synthesis is strongly associated with spinal manifestation and independently more pronounced neuroaxonal injury in early MS, suggesting a distinct clinical phenotype and pathophysiology. ANN NEUROL 2022;91:814-820.

Anterior horn atrophy in the cervical spinal cord: A new biomarker in progressive multiple sclerosis.

BACKGROUND: Spinal cord (SC) gray and white matter pathology plays a central role in multiple sclerosis (MS). OBJECTIVE: We aimed to investigate the extent, pattern, and clinical relevance of SC gray and white matter atrophy in vivo. METHODS: 39 relapsing-remitting patients (RRMS), 40 progressive MS patients (PMS), and 24 healthy controls (HC) were imaged at 3T using the averaged magnetization inversion recovery acquisitions sequence. Total and lesional cervical gray and white matter, and posterior (SCPH) and anterior horn (SCAH) areas were automatically quantified. Clinical assessment included the expanded disability status scale, timed 25-foot walk test, nine-hole peg test, and the 12-item MS walking scale. RESULTS: PMS patients had significantly reduced cervical SCAH - but not SCPH - areas compared with HC and RRMS (both p < 0.001). In RRMS and PMS, the cervical SCAH areas increased significantly less in the region of cervical SC enlargement compared with HC (all p < 0.001). This reduction was more pronounced in PMS compared with RRMS (both p < 0.001). In PMS, a lower cervical SCAH area was the most important magnetic resonance imaging (MRI)-variable for higher disability scores. CONCLUSION: MS patients show clinically relevant cervical SCAH atrophy, which is more pronounced in PMS and at the level of cervical SC enlargement.

Spinal cord gray matter atrophy is associated with functional decline in post-polio syndrome.

OBJECTIVE: To determine if patients with post-polio syndrome (PPS) show spinal cord gray matter (SCGM) atrophy and to assess associations between SCGM atrophy, muscle strength and patient-reported functional decline. METHODS: Twenty patients diagnosed with PPS (March of Dimes criteria) and 20 age- and sex-matched healthy controls (HC) underwent 3T axial 2D-rAMIRA magnetic resonance imaging at the intervertebral disc levels C2/C3-C6/C7, T9/T10 and the lumbar enlargement level (Tmax ) (0.5 × 0.5 mm2 in-plane resolution). SCGM areas were segmented manually by two independent raters. Muscle strength, self-reported fatigue, depression and pain measures were assessed. RESULTS: Post-polio syndrome patients showed significantly and preferentially reduced SCGM areas at C2/C3 (p = 0.048), C3/C4 (p = 0.001), C4/C5 (p < 0.001), C5/C6 (p = 0.004) and Tmax (p = 0.041) compared to HC. SCGM areas were significantly associated with muscle strength in corresponding myotomes even after adjustment for fatigue, pain and depression. SCGM areaTmax together with age and sex explained 68% of ankle dorsiflexion strength variance. No associations were found with age at or time since infection. Patients reporting PPS-related decline in arm function showed significant cervical SCGM atrophy compared to stable patients adjusted for initial disease severity. CONCLUSIONS: Patients with PPS show significant SCGM atrophy that correlates with muscle strength and is associated with PPS-related functional decline. Our findings suggest a secondary neurodegenerative process underlying SCGM atrophy in PPS that is not explained by aging or residua of the initial infection alone. Confirmation by longitudinal studies is needed. The described imaging methodology is promising for developing novel imaging surrogates for SCGM diseases.

Accurate, rapid and reliable, fully automated MRI brainstem segmentation for application in multiple sclerosis and neurodegenerative diseases.

Neurodegenerative disorders, such as Alzheimer's disease (AD) and progressive forms of multiple sclerosis (MS), can affect the brainstem and are associated with atrophy that can be visualized by MRI. Anatomically accurate, large-scale assessments of brainstem atrophy are challenging due to lack of automated, accurate segmentation methods. We present a novel method for brainstem volumetry using a fully-automated segmentation approach based on multi-dimensional gated recurrent units (MD-GRU), a deep learning based semantic segmentation approach employing a convolutional adaptation of gated recurrent units. The neural network was trained on 67 3D-high resolution T1-weighted MRI scans from MS patients and healthy controls (HC) and refined using segmentations of 20 independent MS patients' scans. Reproducibility was assessed in MR test-retest experiments in 33 HC. Accuracy and robustness were examined by Dice scores comparing MD-GRU to FreeSurfer and manual brainstem segmentations in independent MS and AD datasets. The mean %-change/SD between test-retest brainstem volumes were 0.45%/0.005 (MD-GRU), 0.95%/0.009 (FreeSurfer), 0.86%/0.007 (manually edited segmentations). Comparing MD-GRU to manually edited segmentations the mean Dice scores/SD were: 0.97/0.005 (brainstem), 0.95/0.013 (mesencephalon), 0.98/0.006 (pons), 0.95/0.015 (medulla oblongata). Compared to the manual gold standard, MD-GRU brainstem segmentations were more accurate than FreeSurfer segmentations (p < .001). In the multi-centric acquired AD data, the mean Dice score/SD for the MD-GRU-manual segmentation comparison was 0.97/0.006. The fully automated brainstem segmentation method MD-GRU provides accurate, highly reproducible, and robust segmentations in HC and patients with MS and AD in 200 s/scan on an Nvidia GeForce GTX 1080 GPU and shows potential for application in large and longitudinal datasets.

Gray matter segmentation of the spinal cord with active contours in MR images.

OBJECTIVE: Fully or partially automated spinal cord gray matter segmentation techniques for spinal cord gray matter segmentation will allow for pivotal spinal cord gray matter measurements in the study of various neurological disorders. The objective of this work was multi-fold: (1) to develop a gray matter segmentation technique that uses registration methods with an existing delineation of the cord edge along with Morphological Geodesic Active Contour (MGAC) models; (2) to assess the accuracy and reproducibility of the newly developed technique on 2D PSIR T1 weighted images; (3) to test how the algorithm performs on different resolutions and other contrasts; (4) to demonstrate how the algorithm can be extended to 3D scans; and (5) to show the clinical potential for multiple sclerosis patients. METHODS: The MGAC algorithm was developed using a publicly available implementation of a morphological geodesic active contour model and the spinal cord segmentation tool of the software Jim (Xinapse Systems) for initial estimate of the cord boundary. The MGAC algorithm was demonstrated on 2D PSIR images of the C2/C3 level with two different resolutions, 2D T2* weighted images of the C2/C3 level, and a 3D PSIR image. These images were acquired from 45 healthy controls and 58 multiple sclerosis patients selected for the absence of evident lesions at the C2/C3 level. Accuracy was assessed though visual assessment, Hausdorff distances, and Dice similarity coefficients. Reproducibility was assessed through interclass correlation coefficients. Validity was assessed through comparison of segmented gray matter areas in images with different resolution for both manual and MGAC segmentations. RESULTS: Between MGAC and manual segmentations in healthy controls, the mean Dice similarity coefficient was 0.88 (0.82-0.93) and the mean Hausdorff distance was 0.61 (0.46-0.76) mm. The interclass correlation coefficient from test and retest scans of healthy controls was 0.88. The percent change between the manual segmentations from high and low-resolution images was 25%, while the percent change between the MGAC segmentations from high and low resolution images was 13%. Between MGAC and manual segmentations in MS patients, the average Dice similarity coefficient was 0.86 (0.8-0.92) and the average Hausdorff distance was 0.83 (0.29-1.37) mm. CONCLUSION: We demonstrate that an automatic segmentation technique, based on a morphometric geodesic active contours algorithm, can provide accurate and precise spinal cord gray matter segmentations on 2D PSIR images. We have also shown how this automated technique can potentially be extended to other imaging protocols.

Spinal cord grey matter segmentation challenge.

An important image processing step in spinal cord magnetic resonance imaging is the ability to reliably and accurately segment grey and white matter for tissue specific analysis. There are several semi- or fully-automated segmentation methods for cervical cord cross-sectional area measurement with an excellent performance close or equal to the manual segmentation. However, grey matter segmentation is still challenging due to small cross-sectional size and shape, and active research is being conducted by several groups around the world in this field. Therefore a grey matter spinal cord segmentation challenge was organised to test different capabilities of various methods using the same multi-centre and multi-vendor dataset acquired with distinct 3D gradient-echo sequences. This challenge aimed to characterize the state-of-the-art in the field as well as identifying new opportunities for future improvements. Six different spinal cord grey matter segmentation methods developed independently by various research groups across the world and their performance were compared to manual segmentation outcomes, the present gold-standard. All algorithms provided good overall results for detecting the grey matter butterfly, albeit with variable performance in certain quality-of-segmentation metrics. The data have been made publicly available and the challenge web site remains open to new submissions. No modifications were introduced to any of the presented methods as a result of this challenge for the purposes of this publication.

Power estimation for non-standardized multisite studies.

A concern for researchers planning multisite studies is that scanner and T1-weighted sequence-related biases on regional volumes could overshadow true effects, especially for studies with a heterogeneous set of scanners and sequences. Current approaches attempt to harmonize data by standardizing hardware, pulse sequences, and protocols, or by calibrating across sites using phantom-based corrections to ensure the same raw image intensities. We propose to avoid harmonization and phantom-based correction entirely. We hypothesized that the bias of estimated regional volumes is scaled between sites due to the contrast and gradient distortion differences between scanners and sequences. Given this assumption, we provide a new statistical framework and derive a power equation to define inclusion criteria for a set of sites based on the variability of their scaling factors. We estimated the scaling factors of 20 scanners with heterogeneous hardware and sequence parameters by scanning a single set of 12 subjects at sites across the United States and Europe. Regional volumes and their scaling factors were estimated for each site using Freesurfer's segmentation algorithm and ordinary least squares, respectively. The scaling factors were validated by comparing the theoretical and simulated power curves, performing a leave-one-out calibration of regional volumes, and evaluating the absolute agreement of all regional volumes between sites before and after calibration. Using our derived power equation, we were able to define the conditions under which harmonization is not necessary to achieve 80% power. This approach can inform choice of processing pipelines and outcome metrics for multisite studies based on scaling factor variability across sites, enabling collaboration between clinical and research institutions.

Spinal cord gray matter atrophy correlates with multiple sclerosis disability.

OBJECTIVE: In multiple sclerosis (MS), cerebral gray matter (GM) atrophy correlates more strongly than white matter (WM) atrophy with disability. The corresponding relationships in the spinal cord (SC) are unknown due to technical limitations in assessing SC GM atrophy. Using phase-sensitive inversion recovery (PSIR) magnetic resonance imaging, we determined the association of the SC GM and SC WM areas with MS disability and disease type. METHODS: A total of 113 MS patients and 20 healthy controls were examined at 3T with a PSIR sequence acquired at the C2/C3 disk level. Two independent, clinically masked readers measured the cord WM and GM areas. Correlations between cord areas and Expanded Disability Status Score (EDSS) were determined. Differences in areas between groups were assessed with age and sex as covariates. RESULTS: Relapsing MS (RMS) patients showed smaller SC GM areas than age- and sex-matched controls (p = 0.008) without significant differences in SC WM areas. Progressive MS patients showed smaller SC GM and SC WM areas compared to RMS patients (all p ≤ 0.004). SC GM, SC WM, and whole cord areas inversely correlated with EDSS (rho: -0.60, -0.32, -0.42, respectively; all p ≤ 0.001). The SC GM area was the strongest correlate of disability in multivariate models including brain GM and WM volumes, fluid-attenuated inversion recovery lesion load, T1 lesion load, SC WM area, number of SC T2 lesions, age, sex, and disease duration. Brain and spinal GM independently contributed to EDSS. INTERPRETATION: SC GM atrophy is detectable in vivo in the absence of WM atrophy in RMS. It is more pronounced in progressive MS than RMS and contributes more to patient disability than SC WM or brain GM atrophy.

2D phase-sensitive inversion recovery imaging to measure in vivo spinal cord gray and white matter areas in clinically feasible acquisition times.

PURPOSE: To present and assess a procedure for measurement of spinal cord total cross-sectional areas (TCA) and gray matter (GM) areas based on phase-sensitive inversion recovery imaging (PSIR). In vivo assessment of spinal cord GM and white matter (WM) could become pivotal to study various neurological diseases, but it is challenging because of insufficient GM/WM contrast provided by conventional magnetic resonance imaging (MRI). MATERIALS AND METHODS: We acquired 2D PSIR images at 3T at each disc level of the spinal axis in 10 healthy subjects and measured TCA, cord diameters, WM and GM areas, and GM area/TCA ratios. Second, we investigated 32 healthy subjects at four selected levels (C2-C3, C3-C4, T8-T9, T9-T10, total acquisition time <8 min) and generated normative reference values of TCA and GM areas. We assessed test-retest, intra- and interoperator reliability of the acquisition strategy, and measurement steps. RESULTS: The measurement procedure based on 2D PSIR imaging allowed TCA and GM area assessments along the entire spinal cord axis. The tests we performed revealed high test-retest/intraoperator reliability (mean coefficient of variation [COV] at C2-C3: TCA = 0.41%, GM area = 2.75%) and interoperator reliability of the measurements (mean COV on the 4 levels: TCA = 0.44%, GM area = 4.20%; mean intraclass correlation coefficient: TCA = 0.998, GM area = 0.906). CONCLUSION: 2D PSIR allows reliable in vivo assessment of spinal cord TCA, GM, and WM areas in clinically feasible acquisition times. The area measurements presented here are in agreement with previous MRI and postmortem studies.

Electrophysiological markers and predictors of the disease course in primary progressive multiple sclerosis.

BACKGROUND: Currently no valid surrogate marker exists for primary progressive multiple sclerosis (PPMS). OBJECTIVE: Our aim was to prospectively investigate multimodal evoked potentials (EPs) as markers and predictors of the disease course in PPMS. METHODS: Twenty-two PPMS patients were prospectively examined with visual, somatosensory and motor EPs and Expanded Disability Status Scale (EDSS) assessments at baseline (T0) and at six-month intervals over three years. Spearman rank correlation was used to determine the relationship between EP measures and EDSS. The relationship between disease evolution and a numerical score derived from z-transformed EP-latencies (s-EP-Q) and baseline characteristics was further assessed using multivariable linear regression analysis. RESULTS: s-EP-Q correlated with EDSS score at all points in time in cross-sectional comparison (0.53≤rs ≤0.68; 0.0007≤p≤0.0232) and also longitudinally by trend (rs=0.46, p=0.0740). The s-EP-QT0 correlated with the EDSS score at year 3 (T6) (r s=0.77, p<0.0001). The s-EP-Q changes became statistically significant six months before corresponding changes were seen in the EDSS score. EDSST6 as predicted by EDSST6 = -1.027+0.037* age+0.217* s-EP-QT0 + 0.695* EDSST0 correlated with the observed values (rs=0.92, p<0.0001). CONCLUSIONS: Multimodal EPs correlate well with disability in PPMS, and allow some prediction of the disease course over three years. These findings support a role of EPs as surrogate markers in clinical trials in PPMS.

Combined visual and motor evoked potentials predict multiple sclerosis disability after 20 years.

BACKGROUND: The development of predictors of multiple sclerosis (MS) disability is difficult due to the complex interplay of pathophysiological and adaptive processes. OBJECTIVE: The purpose of this study was to investigate whether combined evoked potential (EP)-measures allow prediction of MS disability after 20 years. METHODS: We examined 28 patients with clinically definite MS according to Poser's criteria with Expanded Disability Status Scale (EDSS) scores, combined visual and motor EPs at entry (T0), 6 (T1), 12 (T2) and 24 (T3) months, and a cranial magnetic resonance imaging (MRI) scan at T0 and T2. EDSS testing was repeated at year 14 (T4) and year 20 (T5). Spearman rank correlation was used. We performed a multivariable regression analysis to examine predictive relationships of the sum of z-transformed EP latencies (s-EPT0) and other baseline variables with EDSST5. RESULTS: We found that s-EPT0 correlated with EDSST5 (rho=0.72, p<0.0001) and ΔEDSST5-T0 (rho=0.50, p=0.006). Backward selection resulted in the prediction model: E (EDSST5)=3.91-2.22×therapy+0.079×age+0.057×s-EPT0 (Model 1, R (2)=0.58) with therapy as binary variable (1=any disease-modifying therapy between T3 and T5, 0=no therapy). Neither EDSST0 nor T2-lesion or gadolinium (Gd)-enhancing lesion quantities at T0 improved prediction of EDSST5. The area under the receiver operating characteristic (ROC) curve was 0.89 for model 1. CONCLUSIONS: These results further support a role for combined EP-measures as predictors of long-term disability in MS.

Chronic Pain in Patients with Spinal Muscular Atrophy in Switzerland: A Query to the Spinal Muscular Atrophy Registry.

Background and Objectives: Chronic pain is a common symptom in various types of neuromuscular disorders. However, for patients with spinal muscular atrophy (SMA), the literature regarding chronic pain is scarce. Thus, this study assessed the prevalence of chronic pain in children, adolescents, and adults with SMA and investigated the influence of clinical characteristics on chronic pain. Materials and Methods: This study used data from 141 patients, which were collected by the Swiss Registry for Neuromuscular Disorders. Extracted data included information on pain (present yes/no, pain location, and pain medication) and clinical characteristics, such as SMA type, motor function, wheelchair use, scoliosis, and contractures. Results: The analyses revealed that the highest prevalence of chronic pain was observed in adolescents with 62%, followed by adults with 48%, children (6-12 years) with 39%, and children < 6 years with 10%. The legs, back, and hips were most frequently reported as pain locations. Sex (females), age (adolescents), and the presence of contractures and scoliosis (with surgery) were factors that were associated with chronic pain. Conclusions: These findings contribute to a better understanding of pain in SMA, shedding light on its prevalence and characteristics in different age groups, which underscores the importance of assessing and managing pain in patients with SMA.

Longitudinal assessment of cervical spinal cord compartments in multiple sclerosis.

BACKGROUND: Although cervical spinal cord (cSC) area is an established biomarker in MS, there is currently a lack of longitudinal assessments of cSC gray and white matter areas. OBJECTIVE: We conducted an explorative analysis of longitudinal changes of cSC gray and white matter areas in MS patients. METHODS: 65 MS patients (33 relapsing-remitting; 20 secondary progressive and 12 primary progressive) and 20 healthy controls (HC) received clinical and upper cSC MRI assessments over 1.10±0.28 years. cSC compartments were quantified on MRI using the novel averaged magnetization inversion recovery acquisitions sequence (in-plane resolution=0.67 × 0.67mm2), and in-house developed post-processing methods. Patients were stratified regarding clinical progression. RESULTS: Patients with clinical progression showed faster reduction of cSC areas over time at the level of cSC enlargement (approximate vertebral level C4-C5) compared to stable patients (p<0.05). In addition, when compared to the rostral-cSC (approximate vertebral level C2-C3), a preferential reduction of cSC and white matter areas over time at the level of cSC enlargement (p<0.05 and p<0.01, respectively) was demonstrated only in patients with clinical progression, but not in stable MS patients and HC. Compared to HC, MS patients showed comparable changes over time in all cSC compartments. CONCLUSIONS: MS patients with clinical disease progression demonstrate subtle signs of a more pronounced tissue loss at the level of cSC enlargement. Future studies should consider larger sample sizes and more extended observation periods.

Normalization of Spinal Cord Total Cross-Sectional and Gray Matter Areas as Quantified With Radially Sampled Averaged Magnetization Inversion Recovery Acquisitions.

Background: MR imaging of the spinal cord (SC) gray matter (GM) at the cervical and lumbar enlargements' level may be particularly informative in lower motor neuron disorders, e. g., spinal muscular atrophy, but also in other neurodegenerative or autoimmune diseases affecting the SC. Radially sampled averaged magnetization inversion recovery acquisition (rAMIRA) is a novel approach to perform SC imaging in clinical settings with favorable contrast and is well-suited for SC GM quantitation. However, before applying rAMIRA in clinical studies, it is important to understand (i) the sources of inter-subject variability of total SC cross-sectional areas (TCA) and GM area (GMA) measurements in healthy subjects and (ii) their relation to age and sex to facilitate the detection of pathology-associated changes. In this study, we aimed to develop normalization strategies for rAMIRA-derived SC metrics using skull and spine-based metrics to reduce anatomical variability. Methods: Sixty-one healthy subjects (age range 11-93 years, 37.7% women) were investigated with axial two-dimensional rAMIRA imaging at 3T MRI. Cervical and thoracic levels including the level of the cervical (C4/C5) and lumbar enlargements (Tmax) were examined. SC T2-weighted sagittal images and high-resolution 3D whole-brain T1-weighted images were acquired. TCA and GMAs were quantified. Anatomical variables with associations of |r| > 0.30 in univariate association with SC areas, and age and sex were used to construct normalization models using backward selection with TCAC4/C5 as outcome. The effect of the normalization was assessed by % relative standard deviation (RSD) reductions. Results: Mean inter-individual variability and the SD of the SC area metrics were considerable: TCAC4/5: 8.1%/9.0; TCATmax: 8.9%/6.5; GMAC4/C5: 8.6%/2.2; GMATmax: 12.2%/3.8. Normalization based on sex, brain WM volume, and spinal canal area resulted in RSD reductions of 23.7% for TCAs and 12.0% for GM areas at C4/C5. Normalizations based on the area of spinal canal alone resulted in RSD reductions of 10.2% for TCAs and 9.6% for GM areas at C4/C5, respectively. Discussion: Anatomic inter-individual variability of SC areas is substantial. This study identified effective normalization models for inter-subject variability reduction in TCA and SC GMA in healthy subjects based on rAMIRA imaging.

Imaging of the thoracic spinal cord using radially sampled averaged magnetization inversion recovery acquisitions.

BACKGROUND: Spinal cord (SC) gray and white matter atrophy quantification by advanced morphometric MRI can help to better characterize the course of neurodegenerative diseases in vivo, such as e.g. lower motor neuron disorders. Imaging the lower thoracic cord - containing those motor neurons that control leg function - could be particularly informative, however, is challenging due to tissue composition, physiological motion and large field of views. NEW METHOD: An "averaged magnetization inversion recovery acquisitions" (AMIRA) approach with a radial k-space acquisition scheme was developed. The method is designed for morphometric SC imaging with a focus on the thoracic SC. RESULTS: In a typical setting, radial AMIRA acquires transverse slices with a high 0.50 × 0.50mm2 in-plane resolution and a pronounced positive contrast between thoracic gray and white matter, within typically 2:39 min. Additional proof-of-concept measurements in patients demonstrate that such contrast and resolving capability is indeed necessary to assess potential atrophy of the anterior horns. COMPARISON WITH EXISTING METHOD(S): Radial AMIRA utilizes two benefits of radial MRI techniques: being generally less prone to motion effects and that fold over artifacts can manifest less intrusively. These benefits are united with the original AMIRA approach which allows the contrast to be 'tuned' and improved based on the combination of five simultaneously acquired images of different tissue contrast. CONCLUSIONS: Radial AMIRA is a promising approach for in vivo SC gray and white matter atrophy visualization and quantification in lower motor neuron diseases and other autoimmune or genetic diseases involving the entire (not only cervical) spinal cord.

Improving Accuracy of Brainstem MRI Volumetry: Effects of Age and Sex, and Normalization Strategies.

Background: Brainstem-mediated functions are impaired in neurodegenerative diseases and aging. Atrophy can be visualized by MRI. This study investigates extrinsic sources of brainstem volume variability, intrinsic sources of anatomical variability, and the influence of age and sex on the brainstem volumes in healthy subjects. We aimed to develop efficient normalization strategies to reduce the effects of intrinsic anatomic variability on brainstem volumetry. Methods: Brainstem segmentation was performed from MPRAGE data using our deep-learning-based brainstem segmentation algorithm MD-GRU. The extrinsic variability of brainstem volume assessments across scanners and protocols was investigated in two groups comprising 11 (median age 33.3 years, 7 women) and 22 healthy subjects (median age 27.6 years, 50% women) scanned twice and compared using Dice scores. Intrinsic anatomical inter-individual variability and age and sex effects on brainstem volumes were assessed in segmentations of 110 healthy subjects (median age 30.9 years, range 18-72 years, 53.6% women) acquired on 1.5T (45%) and 3T (55%) scanners. The association between brainstem volumes and predefined anatomical covariates was studied using Pearson correlations. Anatomical variables with associations of |r| > 0.30 as well as the variables age and sex were used to construct normalization models using backward selection. The effect of the resulting normalization models was assessed by % relative standard deviation reduction and by comparing the inter-individual variability of the normalized brainstem volumes to the non-normalized values using paired t- tests with Bonferroni correction. Results: The extrinsic variability of brainstem volumetry across different field strengths and imaging protocols was low (Dice scores > 0.94). Mean inter-individual variability/SD of total brainstem volumes was 9.8%/7.36. A normalization based on either total intracranial volume (TICV), TICV and age, or v-scale significantly reduced the inter-individual variability of total brainstem volumes compared to non-normalized volumes and similarly reduced the relative standard deviation by about 35%. Conclusion: The extrinsic variability of the novel brainstem segmentation method MD-GRU across different scanners and imaging protocols is very low. Anatomic inter-individual variability of brainstem volumes is substantial. This study presents efficient normalization models for variability reduction in brainstem volumetry in healthy subjects.

Future Brain and Spinal Cord Volumetric Imaging in the Clinic for Monitoring Treatment Response in MS.

PURPOSE OF REVIEW: Volumetric analysis of brain imaging has emerged as a standard approach used in clinical research, e.g., in the field of multiple sclerosis (MS), but its application in individual disease course monitoring is still hampered by biological and technical limitations. This review summarizes novel developments in volumetric imaging on the road towards clinical application to eventually monitor treatment response in patients with MS. RECENT FINDINGS: In addition to the assessment of whole-brain volume changes, recent work was focused on the volumetry of specific compartments and substructures of the central nervous system (CNS) in MS. This included volumetric imaging of the deep brain structures and of the spinal cord white and gray matter. Volume changes of the latter indeed independently correlate with clinical outcome measures especially in progressive MS. Ultrahigh field MRI and quantitative MRI added to this trend by providing a better visualization of small compartments on highly resolving MR images as well as microstructural information. New developments in volumetric imaging have the potential to improve sensitivity as well as specificity in detecting and hence monitoring disease-related CNS volume changes in MS.

Monitoring multiple sclerosis by multimodal evoked potentials: Numerically versus ordinally scaled scoring systems.

OBJECTIVE: To compare the ability of different evoked potential scores (EPS) to monitor and predict the disease course in multiple sclerosis (MS). METHODS: Seventy-two patients with MS or clinically isolated syndrome were investigated by visual, motor, and somatosensory EP and expanded disability status scale (EDSS) at baseline (T0) and months 6, 12, 24, 36 (T4). EP results were rated according to ordinal (o), semi-quantitative (sq), and quantitative (q) EPS. Spearman rank correlation and multivariable linear regression were used to investigate the associations between EPS and clinical disability. RESULTS: All EPS correlated with EDSS cross-sectionally (0.72⩽rho⩽0.87, all p<0.001) and longitudinally (0.39⩽rho⩽0.47, all p⩽0.004). EPS(T0) and EDSS(T0) together explained 85-86% of EDSS(T4) variance. A posteriori power calculation showed that the sample sizes needed to detect significant changes over 6 months in q-EPS, sq-EPS and o-EPS with 90% certainty would be 50, 129 and 222, respectively. q-EPS change(T1-T0) correlated with EDSS change(T4-T0) (rho=0.56, p<0.001), while sq-EPS and o-EPS changes(T1-T0) did not. CONCLUSION: All three EPS allow disease course monitoring in MS. However, the quantitative EPS detects clinically relevant short-term changes with a smaller sample size than semi-quantitative or ordinal EPS. SIGNIFICANCE: These results underscore the potential of EPS to characterize MS disease evolution.

Association of HLA Genetic Risk Burden With Disease Phenotypes in Multiple Sclerosis.

IMPORTANCE: Although multiple HLA alleles associated with multiple sclerosis (MS) risk have been identified, genotype-phenotype studies in the HLA region remain scarce and inconclusive. OBJECTIVES: To investigate whether MS risk-associated HLA alleles also affect disease phenotypes. DESIGN, SETTING, AND PARTICIPANTS: A cross-sectional, case-control study comprising 652 patients with MS who had comprehensive phenotypic information and 455 individuals of European origin serving as controls was conducted at a single academic research site. Patients evaluated at the Multiple Sclerosis Center at University of California, San Francisco between July 2004 and September 2005 were invited to participate. Spinal cord imaging in the data set was acquired between July 2013 and March 2014; analysis was performed between December 2014 and December 2015. MAIN OUTCOMES AND MEASURES: Cumulative HLA genetic burden (HLAGB) calculated using the most updated MS-associated HLA alleles vs clinical and magnetic resonance imaging outcomes, including age at onset, disease severity, conversion time from clinically isolated syndrome to clinically definite MS, fractions of cortical and subcortical gray matter and cerebral white matter, brain lesion volume, spinal cord gray and white matter areas, upper cervical cord area, and the ratio of gray matter to the upper cervical cord area. Multivariate modeling was applied separately for each sex data set. RESULTS: Of the 652 patients with MS, 586 had no missing genetic data and were included in the HLAGB analysis. In these 586 patients (404 women [68.9%]; mean [SD] age at disease onset, 33.6 [9.4] years), HLAGB was higher than in controls (median [IQR], 0.7 [0-1.4] and 0 [-0.3 to 0.5], respectively; P = 1.8 × 10-27). A total of 619 (95.8%) had relapsing-onset MS and 27 (4.2%) had progressive-onset MS. No significant difference was observed between relapsing-onset MS and primary progressive MS. A higher HLAGB was associated with younger age at onset and the atrophy of subcortical gray matter fraction in women with relapsing-onset MS (standard ß = -1.20 × 10-1; P = 1.7 × 10-2 and standard ß = -1.67 × 10-1; P = 2.3 × 10-4, respectively), which were driven mainly by the HLA-DRB1*15:01 haplotype. In addition, we observed the distinct role of the HLA-A*24:02-B*07:02-DRB1*15:01 haplotype among the other common DRB1*15:01 haplotypes and a nominally protective effect of HLA-B*44:02 to the subcortical gray atrophy (standard ß = -1.28 × 10-1; P = 5.1 × 10-3 and standard ß = 9.52 × 10-2; P = 3.6 × 10-2, respectively). CONCLUSIONS AND RELEVANCE: We confirm and extend previous observations linking HLA MS susceptibility alleles with disease progression and specific clinical and magnetic resonance imaging phenotypic traits.