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.

Performance of the European Society of Cardiology 0/1-Hour, 0/2-Hour, and 0/3-Hour Algorithms for Rapid Triage of Acute Myocardial Infarction : An International Collaborative Meta-analysis.

BACKGROUND: The 2020 European Society of Cardiology (ESC) guidelines recommend using the 0/1-hour and 0/2-hour algorithms over the 0/3-hour algorithm as the first and second choices of high-sensitivity cardiac troponin (hs-cTn)-based strategies for triage of patients with suspected acute myocardial infarction (AMI). PURPOSE: To evaluate the diagnostic accuracies of the ESC 0/1-hour, 0/2-hour, and 0/3-hour algorithms. DATA SOURCES: PubMed, Embase, Cochrane Central Register of Controlled Trials, Web of Science, and Scopus from 1 January 2011 to 31 December 2020. (PROSPERO: CRD42020216479). STUDY SELECTION: Prospective studies that evaluated the ESC 0/1-hour, 0/2-hour, or 0/3-hour algorithms in adult patients presenting with suspected AMI. DATA EXTRACTION: The primary outcome was index AMI. Twenty unique cohorts were identified. Primary data were obtained from investigators of 16 cohorts and aggregate data were extracted from 4 cohorts. Two independent authors assessed each study for methodological quality. DATA SYNTHESIS: A total of 32 studies (20 cohorts) with 30 066 patients were analyzed. The 0/1-hour algorithm had a pooled sensitivity of 99.1% (95% CI, 98.5% to 99.5%) and negative predictive value (NPV) of 99.8% (CI, 99.6% to 99.9%) for ruling out AMI. The 0/2-hour algorithm had a pooled sensitivity of 98.6% (CI, 97.2% to 99.3%) and NPV of 99.6% (CI, 99.4% to 99.8%). The 0/3-hour algorithm had a pooled sensitivity of 93.7% (CI, 87.4% to 97.0%) and NPV of 98.7% (CI, 97.7% to 99.3%). Sensitivity of the 0/3-hour algorithm was attenuated in studies that did not use clinical criteria (GRACE score <140 and pain-free) compared with studies that used clinical criteria (90.2% [CI, 82.9 to 94.6] vs. 98.4% [CI, 88.6 to 99.8]). All 3 algorithms had similar specificities and positive predictive values for ruling in AMI, but heterogeneity across studies was substantial. Diagnostic performance was similar across the hs-cTnT (Elecsys; Roche), hs-cTnI (Architect; Abbott), and hs-cTnI (Centaur/Atellica; Siemens) assays. LIMITATION: Diagnostic accuracy, inclusion and exclusion criteria, and cardiac troponin sampling time varied among studies. CONCLUSION: The ESC 0/1-hour and 0/2-hour algorithms have higher sensitivities and NPVs than the 0/3-hour algorithm for index AMI. PRIMARY FUNDING SOURCE: National Taiwan University Hospital.

Regional Cerebellar Volume Loss Predicts Future Disability in Multiple Sclerosis Patients.

Cerebellar symptoms in multiple sclerosis (MS) are well described; however, the exact contribution of cerebellar damage to MS disability has not been fully explored. Longer-term observational periods are necessary to better understand the dynamics of pathological changes within the cerebellum and their clinical consequences. Cerebellar lobe and single lobule volumes were automatically segmented on 664 3D-T1-weighted MPRAGE scans (acquired at a single 1.5 T scanner) of 163 MS patients (111 women; mean age: 47.1 years; 125 relapsing-remitting (RR) and 38 secondary progressive (SP) MS, median EDSS: 3.0) imaged annually over 4 years. Clinical scores (EDSS, 9HPT, 25FWT, PASAT, SDMT) were determined per patient per year with a maximum clinical follow-up of 11 years. Linear mixed-effect models were applied to assess the association between cerebellar volumes and clinical scores and whether cerebellar atrophy measures may predict future disability progression. SPMS patients exhibited faster posterior superior lobe volume loss over time compared to RRMS, which was related to increase of EDSS over time. In RRMS, cerebellar volumes were significant predictors of motor scores (e.g. average EDSS, T25FWT and 9HPT) and SDMT. Atrophy of motor-associated lobules (IV-VI + VIII) was a significant predictor of future deterioration of the 9HPT of the non-dominant hand. In SPMS, the atrophy rate of the posterior superior lobe (VI + Crus I) was a significant predictor of future PASAT performance deterioration. Regional cerebellar volume reduction is associated with motor and cognitive disability in MS and may serve as a predictor for future disease progression, especially of dexterity and impaired processing speed.

Classification of multiple sclerosis based on patterns of CNS regional atrophy covariance.

There is evidence that multiple sclerosis (MS) pathology leads to distinct patterns of volume loss over time (VLOT) in different central nervous system (CNS) structures. We aimed to use such patterns to identify patient subgroups. MS patients of all classical disease phenotypes underwent annual clinical, blood, and MRI examinations over 6 years. Spinal, striatal, pallidal, thalamic, cortical, white matter, and T2-weighted lesion volumes as well as serum neurofilament light chain (sNfL) were quantified. CNS VLOT patterns were identified using principal component analysis and patients were classified using hierarchical cluster analysis. 225 MS patients were classified into four distinct Groups A, B, C, and D including 14, 59, 141, and 11 patients, respectively). These groups did not differ in baseline demographics, disease duration, disease phenotype distribution, and lesion-load expansion. Interestingly, Group A showed pronounced spinothalamic VLOT, Group B marked pallidal VLOT, Group C small between-structure VLOT differences, and Group D myelocortical volume increase and pronounced white matter VLOT. Neurologic deficits were more severe and progressed faster in Group A that also had higher mean sNfL levels than all other groups. Group B experienced more frequent relapses than Group C. In conclusion, there are distinct patterns of VLOT across the CNS in MS patients, which do not overlap with clinical MS subtypes and are independent of disease duration and lesion-load but are partially associated to sNfL levels, relapse rates, and clinical worsening. Our findings support the need for a more biologic classification of MS subtypes including volumetric and body-fluid markers.

Central nervous system atrophy predicts future dynamics of disability progression in a real-world multiple sclerosis cohort.

BACKGROUND AND PURPOSE: In an era of individualized multiple sclerosis (MS) patient management, biomarkers for accurate prediction of future clinical outcomes are needed. We aimed to evaluate the potential of short-term magnetic resonance imaging (MRI) atrophy measures and serum neurofilament light chain (sNfL) as predictors of the dynamics of disability accumulation in relapse-onset MS. METHODS: Brain gray and white matter, thalamic, striatal, pallidal and cervical spinal cord volumes, and lesion load were measured over three available time points (mean time span 2.24 ± 0.70 years) for 183 patients (140 relapsing-remitting [RRMS] and 43 secondary-progressive MS (SPMS); 123 female, age 46.4 ± 11.0 years; disease duration 15.7 ± 9.3 years), and their respective annual changes were calculated. Baseline sNfL was also measured at the third available time point for each patient. Subsequently, patients underwent annual clinical examinations over 5.4 ± 3.7 years including Expanded Disability Status Scale (EDSS) scoring, the nine-hole peg test and the timed 25-foot walk test. RESULTS: Higher annual spinal cord atrophy rates and lesion load increase predicted higher future EDSS score worsening over time in SPMS. Lower baseline thalamic volumes predicted higher walking speed worsening over time in RRMS. Lower baseline gray matter, as well as higher white matter and spinal cord atrophy rates, lesion load increase, baseline striatal volumes and baseline sNfL, predicted higher future hand dexterity worsening over time. All models showed reasonable to high prediction accuracy. CONCLUSION: This study demonstrates the capability of short-term MRI metrics to accurately predict future dynamics of disability progression in a real-world relapse-onset MS cohort. The present study represents a step towards the utilization of structural MRI measurements in patient care.

Longitudinal patterns of cortical thinning in multiple sclerosis.

In multiple sclerosis (MS), cortical atrophy is correlated with clinical and neuropsychological measures. We aimed to examine the differences in the temporospatial evolution of cortical thickness (CTh) between MS-subtypes and to study the association of CTh with T2-weighted white matter lesions (T2LV) and clinical progression. Two hundred and forty-three MS patients (180 relapsing-remitting [RRMS], 51 secondary-progressive [SPMS], and 12 primary-progressive [PPMS]) underwent annual clinical (incl. expanded disability status scale [EDSS]) and MRI-examinations over 6 years. T2LV and CTh were measured. CTh did not differ between MS-subgroups. Higher total T2LV was associated with extended bilateral CTh-reduction on average, but did not correlate with CTh-changes over time. In RRMS, CTh- and EDSS-changes over time were negatively correlated in large bilateral prefrontal, frontal, parietal, temporal, and occipital areas. In SPMS, CTh was not associated with the EDSS. In PPMS, CTh- and EDSS-changes over time were correlated in small clusters predominantly in left parietal areas. Increase of brain lesion load does not lead to an immediate CTh-reduction. Although CTh did not differ between MS-subtypes, a dissociation in the correlation between CTh- and EDSS-changes over time between RRMS and progressive-MS was shown, possibly underlining the contribution of subcortical pathology to clinical progression in progressive-MS.

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.

Preferential spinal cord volume loss in primary progressive multiple sclerosis.

BACKGROUND: Little is known on longer term changes of spinal cord volume (SCV) in primary progressive multiple sclerosis (PPMS). OBJECTIVE: Longitudinal evaluation of SCV loss in PPMS and its correlation to clinical outcomes, compared to relapse-onset multiple sclerosis (MS) subtypes. METHODS: A total of 60 MS age-, sex- and disease duration-matched patients (12 PPMS, each 24 relapsing-remitting (RRMS) and secondary progressive MS (SPMS)) were analysed annually over 6 years of follow-up. The upper cervical SCV was measured on 3D T1-weighted magnetization-prepared rapid gradient-echo (MPRAGE) images using a semi-automatic software (CORDIAL), along with the total brain volume (TBV), brain T2 lesion volume (T2LV) and Expanded Disability Status Scale (EDSS). RESULTS: PPMS showed faster SCV loss over time than RRMS ( p < 0.01) and by trend ( p = 0.066) compared with SPMS. In contrast to relapse-onset MS, in PPMS SCV loss progressed independent of TBV and T2LV changes. Moreover, in PPMS, SCV was the only magnetic resonance imaging (MRI) measurement associated with EDSS increase over time ( p < 0.01), as opposed to RRMS and SPMS. CONCLUSION: SCV loss is a strong predictor of clinical outcomes in PPMS and has shown to be faster and independent of brain MRI metrics compared to relapse-onset MS.

Impact of 3 Tesla MRI on interobserver agreement in clinically isolated syndrome: A MAGNIMS multicentre study.

BACKGROUND: Compared to 1.5 T, 3 T magnetic resonance imaging (MRI) increases signal-to-noise ratio leading to improved image quality. However, its clinical relevance in clinically isolated syndrome suggestive of multiple sclerosis remains uncertain. OBJECTIVES: The purpose of this study was to investigate how 3 T MRI affects the agreement between raters on lesion detection and diagnosis. METHODS: We selected 30 patients and 10 healthy controls from our ongoing prospective multicentre cohort. All subjects received baseline 1.5 and 3 T brain and spinal cord MRI. Patients also received follow-up brain MRI at 3-6 months. Four experienced neuroradiologists and four less-experienced raters scored the number of lesions per anatomical region and determined dissemination in space and time (McDonald 2010). RESULTS: In controls, the mean number of lesions per rater was 0.16 at 1.5 T and 0.38 at 3 T ( p = 0.005). For patients, this was 4.18 and 4.40, respectively ( p = 0.657). Inter-rater agreement on involvement per anatomical region and dissemination in space and time was moderate to good for both field strengths. 3 T slightly improved agreement between experienced raters, but slightly decreased agreement between less-experienced raters. CONCLUSION: Overall, the interobserver agreement was moderate to good. 3 T appears to improve the reading for experienced readers, underlining the benefit of additional training.

Serum neurofilament as a predictor of disease worsening and brain and spinal cord atrophy in multiple sclerosis.

Neuro-axonal injury is a key factor in the development of permanent disability in multiple sclerosis. Neurofilament light chain in peripheral blood has recently emerged as a biofluid marker reflecting neuro-axonal damage in this disease. We aimed at comparing serum neurofilament light chain levels in multiple sclerosis and healthy controls, to determine their association with measures of disease activity and their ability to predict future clinical worsening as well as brain and spinal cord volume loss. Neurofilament light chain was measured by single molecule array assay in 2183 serum samples collected as part of an ongoing cohort study from 259 patients with multiple sclerosis (189 relapsing and 70 progressive) and 259 healthy control subjects. Clinical assessment, serum sampling and MRI were done annually; median follow-up time was 6.5 years. Brain volumes were quantified by structural image evaluation using normalization of atrophy, and structural image evaluation using normalization of atrophy, cross-sectional, cervical spinal cord volumes using spinal cord image analyser (cordial). Results were analysed using ordinary linear regression models and generalized estimating equation modelling. Serum neurofilament light chain was higher in patients with a clinically isolated syndrome or relapsing remitting multiple sclerosis as well as in patients with secondary or primary progressive multiple sclerosis than in healthy controls (age adjusted P < 0.001 for both). Serum neurofilament light chain above the 90th percentile of healthy controls values was an independent predictor of Expanded Disability Status Scale worsening in the subsequent year (P < 0.001). The probability of Expanded Disability Status Scale worsening gradually increased by higher serum neurofilament light chain percentile category. Contrast enhancing and new/enlarging lesions were independently associated with increased serum neurofilament light chain (17.8% and 4.9% increase per lesion respectively; P < 0.001). The higher the serum neurofilament light chain percentile level, the more pronounced was future brain and cervical spinal volume loss: serum neurofilament light chain above the 97.5th percentile was associated with an additional average loss in brain volume of 1.5% (P < 0.001) and spinal cord volume of 2.5% over 5 years (P = 0.009). Serum neurofilament light chain correlated with concurrent and future clinical and MRI measures of disease activity and severity. High serum neurofilament light chain levels were associated with both brain and spinal cord volume loss. Neurofilament light chain levels are a real-time, easy to measure marker of neuro-axonal injury that is conceptually more comprehensive than brain MRI.