Cognitive function in severe progressive multiple sclerosis.

Cognitive impairment is common in multiple sclerosis and negatively impacts quality of life. Cognitive status has yet to be described in people with severe progressive multiple sclerosis, in whom conventional neuropsychological testing is exceptionally difficult. The objective for the study was to characterize cognitive performance in severe progressive multiple sclerosis and compare them with age-, sex- and disease duration-matched less disabled people with multiple sclerosis using a specifically developed auditory, non-motor test of attention/cognitive processing speed-Auditory Test of Processing Speed. Also, we aimed to determine the relationship between cognitive performance and MRI-based outcomes in these matched cohorts. The Comprehensive Assessment of Severely Affected Multiple Sclerosis study was carried out at the University at Buffalo and the Boston Home, a skilled nursing facility in Dorchester, MA. Inclusion criteria were age 30-80 years and expanded disability status scale 3.0-6.5 for community-dwelling and 7.0-9.5 for skilled nursing facility people with multiple sclerosis. The cognitive assessment was performed using the Brief International Cognitive Assessment for Multiple Sclerosis consisting of Symbol Digit Modalities Test, Brief Visuospatial Memory Test-Revised, California Verbal Learning Test-2nd edition along with Auditory Test of Processing Speed, Paced Auditory Serial Addition Test-3 second and Controlled Oral Word Association Test. MRI scans were retrospectively collected and analysed for lesion and volumetric brain measurements. The rate of completion and performance of the cognitive tests was compared between the groups, and the relationship with MRI measures was determined using sex, age and years of education-adjusted linear regression models. Significantly greater percentage of the severe multiple sclerosis group completed Auditory Test of Processing Speed when compared with the current gold standard of Symbol Digit Modalities Test (93.2% versus 65.9%). Severe progressive multiple sclerosis had worse cognitive performance in all cognitive domains with greatest differences for cognitive processing speed (Symbol Digit Modalities Test > Paced Auditory Serial Addition Test-3 second > Auditory Test of Processing Speed, Cohen's d < 2.13, P < 0.001), learning and memory (Cohen's d < 1.1, P < 0.001) and language (Controlled Oral Word Association Test with Cohen's d = 0.97, P < 0.001). Multiple cognitive domains were significantly associated with lower thalamic (standardized ß < 0.419, P < 0.006) and cortical (standardized ß < 0.26, P < 0.031) volumes. Specially designed (auditory) cognitive processing speed tests may provide more sensitive screening of cognitive function in severe progressive multiple sclerosis. The cognitive profile of severe multiple sclerosis is proportional to their physical outcomes and best explained by decreased grey matter volume.

Clinical risk stratification: Development and validation of the DAAE score, a tool for estimating patient risk of transition to secondary progressive multiple sclerosis.

BACKGROUND: Because secondary progressive multiple sclerosis (SPMS) is associated with worse prognosis, early predictive tools are needed. We aimed to use systematic literature review and advanced methods to create and validate a clinical tool for estimating individual patient risk of transition to SPMS over five years. METHODS: Data from the Jacobs Multiple Sclerosis Center (JMSC) and the Multiple Sclerosis Center Amsterdam (MSCA) was collected between 1994 and 2022. Participants were relapsing-remitting adult patients at initial evaluation. We created the tool in four stages: (1) identification of candidate predictors from systematic literature review, (2) ordinal cutoff determination, (3) feature selection, (4) feature weighting. RESULTS: Patients in the development/internal-validation/external-validation datasets respectively (n = 787/n = 522/n = 877) had a median age of 44.1/42.4/36.6 and disease duration of 7.7/6.2/4.4 years. From these, 12.6 %/10.2 %/15.4 % converted to SPMS (median=4.9/5.2/5.0 years). The DAAE Score was named from included predictors: Disease duration, Age at disease onset, Age, EDSS. It ranges from 0 to 12 points, with risk groups of very-low=0-2, low=3-7, medium=8-9, and high≥10. Risk of transition to SPMS increased proportionally across these groups in development (2.7 %/7.4 %/18.8 %/40.2 %), internal-validation (2.9 %/6.8 %/26.8 %/36.5 %), and external-validation (7.5 %/9.6 %/22.4 %/37.5 %). CONCLUSION: The DAAE Score estimates individual patient risk of transition to SPMS consistently across datasets internationally using clinically-accessible data. With further validation, this tool could be used for clinical risk estimation.

Decoding Gray Matter Involvement in Multiple Sclerosis via Imaging.

Multiple sclerosis (MS) is increasingly understood not only as a white matter disease but also involving both the deep and cortical gray matter (GM). GM pathology in people with MS (pwMS) includes the presence of lesions, leptomeningeal inflammation, atrophy, altered iron concentration, and microstructural changes. Studies using 7T and 3T MR imaging with optimized protocols established that GM damage is a principal driver of disease progression in pwMS. Future work is needed to incorporate the assessment of these GM imaging biomarkers into the clinical workup of pwMS and the assessment of treatment efficacy.

Thalamic atrophy and dysconnectivity are associated with cognitive impairment in a multi-center, clinical routine, real-word study of people with relapsing-remitting multiple sclerosis.

BACKGROUND: Prior research has established a link between thalamic pathology and cognitive impairment (CI) in people with multiple sclerosis (pwMS). However, the translation of these findings to pwMS in everyday clinical settings has been insufficient. OBJECTIVE: To assess which global and/or thalamic imaging biomarkers can be used to identify pwMS at risk for CI and cognitive worsening (CW) in a real-world setting. METHODS: This was an international, multi-center (11 centers), longitudinal, retrospective, real-word study of people with relapsing-remitting MS (pwRRMS). Brain MRI exams acquired at baseline and follow-up were collected. Cognitive status was evaluated using the Symbol Digit Modalities Test (SDMT). Thalamic volume (TV) measurement was performed on T2-FLAIR, as well as on T1-WI, when available. Thalamic dysconnectivity, T2-lesion volume (T2-LV), and volumes of gray matter (GM), whole brain (WB) and lateral ventricles (LVV) were also assessed. RESULTS: 332 pwMS were followed for an average of 2.8 years. At baseline, T2-LV, LVV, TV and thalamic dysconnectivity on T2-FLAIR (p < 0.016), and WB, GM and TV volumes on T1-WI (p < 0.039) were significantly worse in 90 (27.1 %) CI vs. 242 (62.9 %) non-CI pwRRMS. Greater SDMT decline over the follow-up was associated with lower baseline TV on T2-FLAIR (standardized ß = 0.203, p = 0.002) and greater thalamic dysconnectivity (standardized ß = -0.14, p = 0.028) in a linear regression model. CONCLUSIONS: PwRRMS with thalamic atrophy and worse thalamic dysconnectivity present more frequently with CI and experience greater CW over mid-term follow-up in a real-world setting.

Glial cell injury and atrophied lesion volume as measures of chronic multiple sclerosis inflammation.

BACKGROUND: Atrophied lesion volume (aLV), a proposed biomarker of disability progression in multiple sclerosis (MS) and transition into progressive MS (PMS), depicts chronic periventricular white matter (WM) pathology. Meningeal infiltrates, imaged as leptomeningeal contrast enhancement (LMCE), are linked with greater cortical pathology. OBJECTIVES: To determine the relationship between serum-derived proteomic data with the development of aLV and LMCE in a heterogeneous group of people with MS (pwMS). METHODS: Proteomic and MRI data for 202 pwMS (148 clinically isolated syndrome /relapsing-remitting MS and 54 progressive MS (PMS)) were acquired at baseline and at 5.4-year follow-up. The concentrations of 21 proteins related to multiple MS pathophysiology pathways were derived using a custom-developed Proximity Extension Assay on the Olink™ platform. The accrual of aLV was determined as the volume of baseline T2-weighted lesions that were replaced by cerebrospinal fluid over the follow-up. Regression models and age-adjusted analysis of covariance (ANCOVA) were used. RESULTS: Older age (standardized beta = 0.176, p = 0.022), higher glial fibrillary acidic protein (standardized beta = 0.312, p = 0.001), and lower myelin oligodendrocyte glycoprotein levels (standardized beta = -0.271, p = 0.002) were associated with accrual of aLV over follow-up. This relationship was driven by the pwPMS population. The presence of LMCE at the follow-up visit was not predicted by any baseline proteomic biomarker nor cross-sectionally associated with any protein concentration. CONCLUSION: Proteomic markers of glial activation are associated with chronic lesional WM pathology (measured as aLV) and may be specific to the progressive MS phenotype. LMCE presence in MS does not appear to relate to proteomic measures.

Choroid plexus enlargement is associated with future periventricular neurodegeneration in multiple sclerosis.

BACKGROUND: The choroid plexus (CP), located within the ventricles of the brain and the primary producer of cerebrospinal fluid, has been shown to be enlarged in patients with multiple sclerosis (MS) and linked to periventricular remyelination failure. Atrophied T2-lesion volume (aT2-LV), a promising neurodegenerative imaging marker in progressive MS (PMS), reflects the volume of periventricular lesions subsumed into cerebrospinal fluid over the follow-up. METHODS: In a cohort of 143 people with relapsing-remitting MS (RRMS) and 53 with PMS, we used 3T magnetic resonance imaging (MRI) to quantify CP volume (CPV) at baseline and aT2-LV over an average of 5.4 years of follow-up. Partial correlations, adjusting for age and sex, and linear regression analyses were used to assess the relationships between imaging measures. RESULTS: In both cohorts, CPV was associated with aT2-LV in both the RRMS group (r = 0.329, p < 0.001) as well as the PMS group (r = 0.522, p < 0.001). In regression analyses predicting aT2-LV, ventricular volume (final adjusted R2 = 0.407, p < 0.001) explained additional variance beyond age, sex, and T2-lesion volume in the RRMS group while CPV (final adjusted R2 = 0.446, p = 0.009) was retained in the PMS group. CONCLUSION: Findings from this study suggest that the CP enlargement is associated with future neurodegeneration, with a particularly relevant role in PMS.

Lower arterial cerebral blood flow is associated with worse neuroinflammation and immunomodulation composite proteomic scores.

BACKGROUND: Brain hypoperfusion is linked with worse physical, cognitive and MRI outcomes in multiple sclerosis (MS). Understanding the proteomic signatures related to hypoperfusion could provide insights into the pathophysiological mechanism. METHODS: 140 people with MS (pwMS; 86 clinically isolated syndrome (CIS)/relapsing-remitting (RRMS) and 54 progressive (PMS)) were included. Cerebral arterial blood flow (CABF) was determined using ultrasound Doppler measurement as the sum of blood flow in the bilateral common carotid arteries and vertebral arteries. Proteomic analysis was performed using the Multiple Sclerosis Disease Activity (MSDA) test assay panel performed on the Olink™ platform. The MSDA test measures the concentrations of 18 proteins that are age and sex-adjusted. It utilizes a stacked classifier logistic regression model to determine 4 disease pathway scores (immunomodulation, neuroinflammation, myelin biology, and neuroaxonal integrity) as well as an overall disease activity score (1 to 10). MRI measures of T2 lesion volume (LV) and whole brain volume (WBV) were derived. RESULTS: The pwMS were on average 54 years old and had an average CABF of 951 mL/min. There were no differences in CABF between CIS/RRMS vs. PMS groups. Lower CABF levels were correlated with the overall disease activity score (r = -0.26, p = 0.003) and with the neuroinflammation (r = -0.29, p = 0.001), immunomodulation (r = -0.26, p = 0.003) and neuroaxonal integrity (r = -0.23, p = 0.007) pathway scores. After age and body mass index (BMI)-adjustment, lower CABF remained associated with the neuroinflammatory (r = -0.23, p = 0.011) and immunomodulation (r = -0.20, p = 0.024) pathway scores. The relationship between CABF and the neuroinflammation pathway score remained significant after adjusting for T2-LV and WBV (p = 0.038). Individual analyses identified neurofilament light chain, CCL-20 and TNFSF13B as contributors. When compared to the highest quartile (>1133.5 mL/min), the pwMS in the lowest CABF quartile (<764 mL/min) had greater overall disease activity score (p = 0.003), neuroinflammation (p = 0.001), immunomodulation (p = 0.004) and neuroaxonal integrity pathway scores (p = 0.007). CONCLUSION: Lower cerebral arterial perfusion in MS is associated with changes in neuroinflammatory/immunomodulation pathways and their respective proteomic biomarkers. These findings may suggest a relationship between the hypoperfusion and pro-inflammatory MS changes rather than being merely an epiphenomenon subsequent to lower energy demands.

Neuroimaging assessment of facility-bound severely-affected MS reveals the critical role of cortical gray matter pathology: results from the CASA-MS case-controlled study.

BACKGROUND: A subgroup of people with multiple sclerosis (pwMS) will develop severe disability. The pathophysiology underlying severe MS is unknown. The comprehensive assessment of severely affected MS (CASA-MS) was a case-controlled study that compared severely disabled in skilled nursing (SD/SN) (EDSS ≥ 7.0) to less-disabled (EDSS 3.0-6.5) community dwelling (CD) progressive pwMS, matched on age-, sex- and disease-duration (DDM). OBJECTIVES: To identify neuroimaging and molecular biomarker characteristics that distinguish SD/SN from DDM-CD progressive pwMS. METHODS: This study was carried at SN facility and at a tertiary MS center. The study collected clinical, molecular (serum neurofilament light chain, sNfL and glial acidic fibrillary protein, sGFAP) and MRI quantitative lesion-, brain volume-, and tissue integrity-derived measures. Statistical analyses were controlled for multiple comparisons. RESULTS: 42 SD/SN and 42 DDM-CD were enrolled. SD/SN pwMS showed significantly lower cortical volume (CV) (p < 0.001, d = 1.375) and thalamic volume (p < 0.001, d = 0.972) compared to DDM-CD pwMS. In a logistic stepwise regression model, the SD/SN pwMS were best differentiated from the DDM-CD pwMS by lower CV (p < 0.001) as the only significant predictor, with the accuracy of 82.3%. No significant differences between the two groups were observed for medulla oblongata volume, a proxy for spinal cord atrophy and white matter lesion burden, while there was a statistical trend for numerically higher sGFAP in SD/SN pwMS. CONCLUSIONS: The CASA-MS study showed significantly more gray matter atrophy in severe compared to less-severe progressive MS.

MRIO: the Magnetic Resonance Imaging Acquisition and Analysis Ontology.

Magnetic resonance imaging of the brain is a useful tool in both the clinic and research settings, aiding in the diagnosis and treatments of neurological disease and expanding our knowledge of the brain. However, there are many challenges inherent in managing and analyzing MRI data, due in large part to the heterogeneity of data acquisition. To address this, we have developed MRIO, the Magnetic Resonance Imaging Acquisition and Analysis Ontology. MRIO provides well-reasoned classes and logical axioms for the acquisition of several MRI acquisition types and well-known, peer-reviewed analysis software, facilitating the use of MRI data. These classes provide a common language for the neuroimaging research process and help standardize the organization and analysis of MRI data for reproducible datasets. We also provide queries for automated assignment of analyses for given MRI types. MRIO aids researchers in managing neuroimaging studies by helping organize and annotate MRI data and integrating with existing standards such as Digital Imaging and Communications in Medicine and the Brain Imaging Data Structure, enhancing reproducibility and interoperability. MRIO was constructed according to Open Biomedical Ontologies Foundry principles and has contributed several classes to the Ontology for Biomedical Investigations to help bridge neuroimaging data to other domains. MRIO addresses the need for a "common language" for MRI that can help manage the neuroimaging research, by enabling researchers to identify appropriate analyses for sets of scans and facilitating data organization and reporting.

Human restricted CHRFAM7A gene increases brain efficiency.

Introduction: CHRFAM7A, a uniquely human fusion gene, has been associated with neuropsychiatric disorders including Alzheimer's disease, schizophrenia, anxiety, and attention deficit disorder. Understanding the physiological function of CHRFAM7A in the human brain is the first step to uncovering its role in disease. CHRFAM7A was identified as a potent modulator of intracellular calcium and an upstream regulator of Rac1 leading to actin cytoskeleton reorganization and a switch from filopodia to lamellipodia implicating a more efficient neuronal structure. We performed a neurocognitive-MRI correlation exploratory study on 46 normal human subjects to explore the effect of CHRFAM7A on human brain. Methods: Dual locus specific genotyping of CHRFAM7A was performed on genomic DNA to determine copy number (TaqMan assay) and orientation (capillary sequencing) of the CHRFAM7A alleles. As only the direct allele is expressed at the protein level and affects α7 nAChR function, direct allele carriers and non-carriers are compared for neuropsychological and MRI measures. Subjects underwent neuropsychological testing to measure motor (Timed 25-foot walk test, 9-hole peg test), cognitive processing speed (Symbol Digit Modalities Test), Learning and memory (California Verbal Learning Test immediate and delayed recall, Brief Visuospatial Memory Test-Revised immediate and delayed recall) and Beck Depression Inventory-Fast Screen, Fatigue Severity Scale. All subjects underwent MRI scanning on the same 3 T GE scanner using the same protocol. Global and tissue-specific volumes were determined using validated cross-sectional algorithms including FSL's Structural Image Evaluation, using Normalization, of Atrophy (SIENAX) and FSL's Integrated Registration and Segmentation Tool (FIRST) on lesion-inpainted images. The cognitive tests were age and years of education-adjusted using analysis of covariance (ANCOVA). Age-adjusted analysis of covariance (ANCOVA) was performed on the MRI data. Results: CHRFAM7A direct allele carrier and non-carrier groups included 33 and 13 individuals, respectively. Demographic variables (age and years of education) were comparable. CHRFAM7A direct allele carriers demonstrated an upward shift in cognitive performance including cognitive processing speed, learning and memory, reaching statistical significance in visual immediate recall (FDR corrected p = 0.018). The shift in cognitive performance was associated with smaller whole brain volume (uncorrected p = 0.046) and lower connectivity by resting state functional MRI in the visual network (FDR corrected p = 0.027) accentuating the cognitive findings. Conclusion: These data suggest that direct allele carriers harbor a more efficient brain consistent with the cellular biology of actin cytoskeleton and synaptic gain of function. Further larger human studies of cognitive measures correlated with MRI and functional imaging are needed to decipher the impact of CHRFAM7A on brain function.

Dynamic disability measures decrease the clinico-radiological gap in people with severely affected multiple sclerosis.

BACKGROUND: Expanded Disability Status Scale (EDSS) is limited when utilized in highly disabled people with multiple sclerosis (pwMS). OBJETIVE: To explore the relationship between disability measures and MRI outcomes in severely-affected pwMS. METHODS: PwMS recruited from The Boston Home (TBH), a specialized residential facility for severly-affected pwMS and University at Buffalo (UB) MS Center were assessed using EDSS, MS Severity Scale, age-related MSS, Scripps Neurological Rating Scale (SNRS) and Combinatorial Weight-Adjusted Disability Score (CombiWISE). In all scores except SNRS, higher score indicates greater disability. MRI measures of T1, T2-lesion volume (LV), whole brain, gray matter, medulla oblongata and thalamic volumes (WBV, GMV, MOV, TV) and thalamic dysconnectivity were obtained. RESULTS: Greatest disability differences between the TBH and UB pwMS were in SNRS (24.4 vs 71.9, p < 0.001, Cohen's d = 4.05) and CombiWISE (82.3 vs. 38.9, p < 0.001, Cohen's d = 4.02). In combined analysis of all pwMS, worse SNRS scores were correlated with worse MRI pathology in 8 out of 9 outcomes. EDSS only with 3 measures (GMV, MOV and TV). In severely-affected pwMS, SNRS was associated with T1-LV, T2-LV and WBV (not surviving false discovery rate (FDR) correction for multiple comparisons) whereas EDSS did not. CONCLUSION: Granular and dynamic disability measures may bridge the clinico-radiologcal gap present in severely affected pwMS.

An Automated Tool to Classify and Transform Unstructured MRI Data into BIDS Datasets.

The increasing use of neuroimaging in clinical research has driven the creation of many large imaging datasets. However, these datasets often rely on inconsistent naming conventions in image file headers to describe acquisition, and time-consuming manual curation is necessary. Therefore, we sought to automate the process of classifying and organizing magnetic resonance imaging (MRI) data according to acquisition types common to the clinical routine, as well as automate the transformation of raw, unstructured images into Brain Imaging Data Structure (BIDS) datasets. To do this, we trained an XGBoost model to classify MRI acquisition types using relatively few acquisition parameters that are automatically stored by the MRI scanner in image file metadata, which are then mapped to the naming conventions prescribed by BIDS to transform the input images to the BIDS structure. The model recognizes MRI types with 99.475% accuracy, as well as a micro/macro-averaged precision of 0.9995/0.994, a micro/macro-averaged recall of 0.9995/0.989, and a micro/macro-averaged F1 of 0.9995/0.991. Our approach accurately and quickly classifies MRI types and transforms unstructured data into standardized structures with little-to-no user intervention, reducing the barrier of entry for clinical scientists and increasing the accessibility of existing neuroimaging data.

Paramagnetic rim lesions predict greater long-term relapse rates and clinical progression over 10 years.

BACKGROUND: Paramagnetic rim lesions (PRLs) have been linked to higher clinical disease severity and relapse frequency. However, it remains unclear whether PRLs predict future, long-term disease progression. OBJECTIVES: The study aimed to assess whether baseline PRLs were associated with subsequent long-term (10 years) Expanded Disability Status Scale (EDSS) increase and relapse frequency and, if so, whether PRL-associated EDSS increase was mediated by relapse. METHODS: This retrospective analysis included 172 people with multiple sclerosis (pwMS) with 1868 yearly clinical visits over a mean follow-up time of 10.2 years. 3T magnetic resonance imaging (MRI) was acquired at baseline and PRLs were assessed on quantitative susceptibility mapping (QSM) images. The associations between PRLs, relapse, and rate of EDSS change were assessed using linear models. RESULTS: PRL+ pwMS had greater overall annual relapse rate (ß = 0.068; p = 0.010), three times greater overall odds of relapse (exp(ß) = 3.472; p = 0.009), and greater rate of yearly EDSS change (ß = 0.045; p = 0.010) than PRL- pwMS. Greater PRL number was associated with greater odds of at least one progression independent of relapse activity (PIRA) episode over follow-up (exp(ß) = 1.171, p = 0.009). Mediation analysis showed that the association between PRL presence (yes/no) and EDSS increase was 96.7% independent of relapse number. CONCLUSION: PRLs are a marker of aggressive ongoing disease inflammatory activity, including more frequent future clinical relapses and greater long-term, relapse-independent disability progression.

Proteomic signatures of physical, cognitive, and imaging outcomes in multiple sclerosis.

BACKGROUND: A quantitative measurement of serum proteome biomarkers that would associate with disease progression endpoints can provide risk stratification for persons with multiple sclerosis (PwMS) and supplement the clinical decision-making process. MATERIALS AND METHODS: In total, 202 PwMS were enrolled in a longitudinal study with measurements at two time points with an average follow-up time of 5.4 years. Clinical measures included the Expanded Disability Status Scale, Timed 25-foot Walk, 9-Hole Peg, and Symbol Digit Modalities Tests. Subjects underwent magnetic resonance imaging to determine the volumetric measures of the whole brain, gray matter, deep gray matter, and lateral ventricles. Serum samples were analyzed using a custom immunoassay panel on the Olink™ platform, and concentrations of 18 protein biomarkers were measured. Linear mixed-effects models and adjustment for multiple comparisons were performed. RESULTS: Subjects had a significant 55.6% increase in chemokine ligand 20 (9.7 pg/mL vs. 15.1 pg/mL, p < 0.001) and neurofilament light polypeptide (10.5 pg/mL vs. 11.5 pg/mL, p = 0.003) at the follow-up time point. Additional changes in CUB domain-containing protein 1, Contactin 2, Glial fibrillary acidic protein, Myelin oligodendrocyte glycoprotein, and Osteopontin were noted but did not survive multiple comparison correction. Worse clinical performance in the 9-HPT was associated with neurofilament light polypeptide (p = 0.001). Increases in several biomarker candidates were correlated with greater neurodegenerative changes as measured by different brain volumes. CONCLUSION: Multiple proteins, selected from a disease activity test that represent diverse biological pathways, are associated with physical, cognitive, and radiographic outcomes. Future studies should determine the utility of multiple protein assays in routine clinical care.

Cognitive phenotypes predict response to restorative cognitive rehabilitation in multiple sclerosis.

BACKGROUND: Cognitive phenotyping may be useful for predicting rehabilitation response in multiple sclerosis. OBJECTIVE: To evaluate the association between cognitive phenotype(s) and response to restorative cognitive rehabilitation (RRCR). METHODS: In a post hoc retrospective analysis of the RRCR study including 51 multiple sclerosis patients, we evaluated both impairment within specific cognitive domains as well as overall global impairment severity to investigate their relationship to improvement following rehabilitation. RESULTS: Greater improvement in executive function was predicted by impairment within this domain as well as by having fewer impaired cognitive domains overall. Similar results were observed for visuospatial memory. CONCLUSIONS: Patients most likely to benefit from restorative cognitive rehabilitation may exhibit impairment within the domain of interest yet lower cognitive burden overall.

Evolution of atrophied T2 lesion volume in primary-progressive multiple sclerosis: results from the phase 3 ORATORIO study.

BACKGROUND: Atrophied T2-lesion volume (aT2-LV) is an exploratory imaging marker in multiple sclerosis (MS) reflecting the volume of lesions subsumed into cerebrospinal fluid (CSF). OBJECTIVE: To investigate the effect of ocrelizumab (OCR) versus placebo (PBO) over 120 weeks on the accumulation of aT2-LV in a double-blind placebo-controlled (DBP) phase 3, primary-progressive (PP) MS study (ORATORIO; NCT01194570). METHODS: This post-hoc, MRI-blinded analysis evaluated 732 PPMS randomised to OCR (488) or PBO (244). Atrophied T2-LV was calculated by overlaying baseline T2-lesion masks on follow-up CSF maps. Clinical data from DBP and open-label extension (OLE) periods were available. Treatment effect was evaluated by a mixed-effect model with repeated measures, while logistic regression explored the association of aT2-LV at week 120 and clinical outcomes in the OLE period. RESULTS: OCR treatment significantly reduced accumulation of aT2-LV compared with PBO (319.4 mm3 vs 366.1 mm3, p=0.015) at 120 weeks. OCR showed superiority over PBO in reducing aT2-LV in patients who developed confirmed disability progression (CDP) during the DBP period at 12 (CDP12) and 24 (CDP24) weeks for the composite of Expanded Disability Status Scale (EDSS), Nine-Hole Peg Test and Timed 25-Foot Walk test. Accumulation of aT2-LV at week 120 was related to CDP12-EDSS (p=0.018) and CDP24-EDSS (p=0.022) in the OLE for the patients who were treated by PBO in the DBP only. CONCLUSIONS: OCR showed a significant effect of reducing the accumulation of aT2-LV in PPMS in the DBP period and was related to CDP-EDSS in OLE only in the PBO arm.

Auditory Test of Processing Speed: Preliminary validation of a smartphone-based test of mental speed.

BACKGROUND: The Symbol Digit Modalities Test (SDMT) is a gold-standard measure of cognitive efficiency and processing speed for people with multiple sclerosis (PwMS) but relies on vision and oculomotor function. OBJECTIVES: To develop and validate a new processing speed test with minimal memory involvement and no eye function requirements. METHODS: We created an Auditory Test of Processing Speed (ATOPS). A total of 122 PwMS, of whom 33 were severely disabled (median Expanded Disability Status Scale 8.0) and 37 healthy volunteers (HVs), were enrolled. We assessed sensitivity to discriminate MS participants from HVs, convergent validity between ATOPS and SDMT, sensitivity to discriminate between cognitively impaired (CI) and cognitively preserved (CP) MS participants, and correlations with MS pathology (overall brain lesion burden). Acceptability was examined with completion rates and participant ratings of ATOPS. RESULTS: ATOPS discriminated PwMS from HVs (d = 0.739-0.856), correlated with SDMT (|r| = 0.528-0.587), discriminated between CI and CP PwMS (d = 0.623-0.776), and correlated with lesion burden (r = 0.332-0.436). All groups indicated high favorability of ATOPS and severely disabled MS patients could be assessed by ATOPS more frequently than by SDMT (100% vs. 72.4% completion). CONCLUSIONS: ATOPS is a novel, accessible, and acceptable cognitive processing speed test that may be useful in clinical and/or research settings.

Detecting isolated cognitive relapses in persons with MS.

BACKGROUND: The existence of isolated cognitive relapses (ICRs) in persons with MS (PwMS) has been debated. OBJECTIVE: To examine relapses with decline on Symbol Digit Modalities Test (SDMT) but no change on Expanded Disability Status Scale (EDSS). METHODS: This 3-year prospective cohort study identified PwMS experiencing a relapse with decrease on SDMT. Participants with SDMT decline/stable EDSS were labeled "ICR," while those with a corresponding decrease on EDSS were classified "Relapse with Cognitive Decline (RCD)." Two definitions of SDMT decline were explored: (1) ⩾ 8 points, and (2) ⩾ 4 points. Logistic regression was used to analyze the relationship between ICR and RCD. RESULTS: The full cohort had 592 participants: 83 experienced relapses; 22 (26.5%) had an SDMT decrease of ⩾ 8 points; 14 (63.6%) met ICR criteria. Logistic regression (X2(1) = 5.112, p = 0.024) using demographics and disease characteristics explained 28.4% of the variance in ICR versus RCD. Only the MS Neuropsychological Questionnaire was associated with ICR (odds ratio (OR): 8.6; 95% confidence interval (CI): 1.1-16.4) 40 relapsing participants with SDMT decrease of ⩾ 4 points were identified: 26 (65%) had a stable EDSS (ICR). Logistic regression did not find any variable predictive of ICR. CONCLUSION: This prospective study demonstrates evidence of ICR in PwMS.

Reliability of paramagnetic rim lesion classification on quantitative susceptibility mapping (QSM) in people with multiple sclerosis: Single-site experience and systematic review.

BACKGROUND: Recent developments in iron-sensitive MRI techniques have enabled visualization of chronic active lesions as paramagnetic rim lesions (PRLs) in vivo. Although PRLs have potential as a diagnostic and prognostic tool for multiple sclerosis (MS), limited studies have reported the reliability of PRL assessment. Further evaluation of PRL reliability, through original investigations and review of PRL literature, are warranted. METHODS: A single-center cohort study was conducted to evaluate the inter-rater reliability of PRL identification on quantitative susceptibiltiy mapping (QSM) in 10 people with MS, 5 people with clinically isolated syndrome, and 5 healthy controls. An additional systematic literature search was then conducted of published PRL reliability data, and these results were synthesized. RESULTS: In the single-center study, both inter-rater and intra-rater reliability of per-subject PRL number were at an "Excellent" (intraclass correlation coefficient (ICC) of 0.901 for both) level with only 2-years lesion classification experience. Across the reported literature values, reliability of per-lesion rim presence was on average "Near perfect" (for intra-rater; Cohen's κ = 0.833) and "Substantial" (for inter-rater; Cohens κ = 0.687), whereas inter-rater reliability of per-subject PRL number was "Good" (ICC = 0.874). Only 4/22 studies reported complete information on rater experience, rater level of training, detailed PRL classification criteria, and reliability cohort size and disease subtypes. CONCLUSION: PRLs can be reliably detected both at per-lesion and per-subject level. We recommend that future PRL studies report detailed reliability results, including rater experience level, and use a standardized set of reliability metrics (Cohen's κ or ICC) for improved comparability between studies.

MRIO: The Magnetic Resonance Imaging Acquisition and Analysis Ontology.

Objective: Magnetic resonance imaging of the brain is a useful tool in both the clinic and research settings, aiding in the diagnosis and treatments of neurological disease and expanding our knowledge of the brain. However, there are many challenges inherent in managing and analyzing MRI data, due in large part to the heterogeneity of data acquisition. Materials and Methods: To address this, we have developed MRIO, the Magnetic Resonance Imaging Acquisition and Analysis Ontology. Results: MRIO provides well-reasoned classes and logical axioms for the acquisition of several MRI acquisition types and well-known, peer-reviewed analysis software, facilitating the use of MRI data. These classes provide a common language for the neuroimaging research process and help standardize the organization and analysis of MRI data for reproducible datasets. We also provide queries for automated assignment of analyses for given MRI types. Discussion: MRIO aids researchers in managing neuroimaging studies by helping organize and annotate MRI data and integrating with existing standards such as Digital Imaging and Communications in Medicine and the Brain Imaging Data Structure, enhancing reproducibility and interoperability. MRIO was constructed according to Open Biomedical Ontologies Foundry principals and has contributed several terms to the Ontology for Biomedical Investigations to help bridge neuroimaging data to other domains. Conclusion: MRIO addresses the need for a "common language" for MRI that can help manage the neuroimaging research, by enabling researchers to identify appropriate analyses for sets of scans and facilitating data organization and reporting.