Association of Gray Matter Atrophy Patterns with Clinical Phenotype and Progression in Multiple Sclerosis

OBJECTIVES: Grey matter (GM) involvement is clinically relevant in multiple sclerosis (MS). Using source-based morphometry (SBM), we characterized GM atrophy and its 1-year evolution across different MS phenotypes. METHODS: Clinical and MRI data were obtained at 8 European sites from 170 healthy controls (HCs) and 398 MS patients (34 clinically isolated syndromes [CIS], 226 relapsing-remitting [RR], 95 secondary progressive [SP] and 43 primary progressive [PP] MS). Fifty-seven HC and 144 MS underwent 1-year follow-up. Baseline GM loss, atrophy progression and correlations with disability and 1-year clinical worsening were assessed. RESULTS: SBM identified 26 cerebellar, subcortical, sensory, motor and cognitive GM components. GM atrophy was found in MS vs HC in almost all components (p=range<0.001-0.04). Compared to HCs, CIS patients showed circumscribed subcortical, cerebellar, temporal and salience GM atrophy, while RRMS patients exhibited widespread GM atrophy. Cerebellar, subcortical, sensorimotor, salience and fronto-parietal GM atrophy was found in PPMS patients vs HCs, and SPMS vs RRMS. At 1-year, 21 (15%) patients had clinically worsened. GM atrophy progressed in MS in subcortical, cerebellar, sensorimotor, and fronto-temporo-parietal components. Baseline higher disability was associated (R2=0.65) with baseline lower normalized brain volume (beta=-0.13, p=0.001), greater sensorimotor GM atrophy (beta=-0.12, p=0.002) and longer disease duration (beta=0.09, p=0.04). Baseline normalized GM volume (odds ratio=0.98, p=0.008) and cerebellar GM atrophy (odds ratio=0.40, p=0.01) independently predicted clinical worsening (area-under-the-curve=0.83). CONCLUSION: GM atrophy differed across disease phenotypes and progressed at 1-year in MS. In addition to global atrophy measures, sensorimotor and cerebellar GM atrophy explained baseline disability and clinical worsening

Quantification of Cervical Cord Cross-Sectional Area: Which Acquisition, Vertebra Level, and Analysis Software? A Multicenter Repeatability Study on a Traveling Healthy Volunteer

BACKGROUND: Considerable spinal cord (SC) atrophy occurs in multiple sclerosis (MS). While MRI-based techniques for SC cross-sectional area (CSA) quantification have improved over time, there is no common agreement on whether to measure at single vertebral levels or across larger regions and whether upper SC CSA can be reliably measured from brain images. AIM: To compare in a multicenter setting three CSA measurement methods in terms of repeatability at different anatomical levels. To analyze the agreement between measurements performed on the cervical cord and on brain MRI. METHOD: One healthy volunteer was scanned three times on the same day in six sites (three scanner vendors) using a 3T MRI protocol including sagittal 3D T1-weighted imaging of the brain (covering the upper cervical cord) and of the SC. Images were analyzed using two semiautomated methods [NeuroQLab (NQL) and the Active Surface Model (ASM)] and the fully automated Spinal Cord Toolbox (SCT) on different vertebral levels (C1–C2; C2/3) on SC and brain images and the entire cervical cord (C1–C7) on SC images only. RESULTS: CSA estimates were significantly smaller using SCT compared to NQL and ASM (p < 0.001), regardless of the cord level. Inter-scanner repeatability was best in C1–C7: coefficients of variation for NQL, ASM, and SCT: 0.4, 0.6, and 1.0%, respectively. CSAs estimated in brain MRI were slightly lower than in SC MRI (all p ≤ 0.006 at the C1–C2 level). Despite protocol harmonization between the centers with regard to image resolution and use of high-contrast 3D T1-weighted sequences, the variability of CSA was partly scanner dependent probably due to differences in scanner geometry, coil design, and details of the MRI parameter settings. CONCLUSION: For CSA quantification, dedicated isotropic SC MRI should be acquired, which yielded best repeatability in the entire cervical cord. In the upper part of the cervical cord, use of brain MRI scans entailed only a minor loss of CSA repeatability compared to SC MRI. Due to systematic differences between scanners and the CSA quantification software, both should be kept constant within a study. The MRI dataset of this study is available publicly to test new analysis approaches

Validation of mean upper cervical cord area (MUCCA) measurement techniques in multiple sclerosis (MS): High reproducibility and robustness to lesions, but large software and scanner effects

INTRODUCTION: Atrophy of the spinal cord is known to occur in multiple sclerosis (MS). The mean upper cervical cord area (MUCCA) can be used to measure this atrophy. Currently, several (semi-)automated methods for MUCCA measurement exist, but validation in clinical magnetic resonance (MR) images is lacking. METHODS: Five methods to measure MUCCA (SCT-PropSeg, SCT-DeepSeg, NeuroQLab, Xinapse JIM and ITK-SNAP) were investigated in a predefined upper cervical cord region. First, within-scanner reproducibility and between-scanner robustness were assessed using intra-class correlation coefficient (ICC) and Dice's similarity index (SI) in scan-rescan 3DT1-weighted images (brain, including cervical spine using a head coil) performed on three 3 T MR machines (GE MR750, Philips Ingenuity, Toshiba Vantage Titan) in 21 subjects with MS and 6 healthy controls (dataset A). Second, sensitivity of MUCCA measurement to lesions in the upper cervical cord was assessed with cervical 3D T1-weighted images (3 T GE HDxT using a head-neck-spine coil) in 7 subjects with MS without and 14 subjects with MS with cervical lesions (dataset B), using ICC and SI with manual reference segmentations. RESULTS: In dataset A, MUCCA differed between MR machines (p  0.176). However, there was an effect of method for both volumetric and voxel wise agreement of the segmentations (both p < 0.001). Highest volumetric and voxel wise agreement was obtained with Xinapse JIM (ICC absolute agreement = 0.940 and median SI = 0.962). CONCLUSION: Although MUCCA is highly reproducible within a scanner for each individual measurement method, MUCCA differs between scanners and between methods. Cervical cord lesions do not affect MUCCA measurement performance

Altered grey matter networks in young patients with MS at genetic risk for Alzheimer's disease [Abstract]

Background: The Apolipoprotein E (APOE) ε4 is the major susceptibility factor for cognitive impairment and Alzheimer’s disease. Cognitive decline is also a concern in patients with multiple sclerosis (MS). Whether APOE ε4 exerts an effect on brain structure and grey matter (GM) networks in MS patients that could potentiate the long-term cognitive disabilities is unclear. Moreover the description of the exact link between genetic markers and MR driven measures of brain integrity are of essential importance to study cognition in patients with MS and for interventions to prevent longitudinal deterioration. Methods: MS Patients with no immunomodulatory treatment were enrolled in the “Krankheitsbezogene Kompetenznetz Multiple Sclerosis (KKNMS)”. From this multicenter dataset 37 heterozygous APOE ε4 carriers (i.e. having the genotype ε3/ε4) and 37 non-carriers (ε3/ε3) were matched for demographics (mean age: 38.4±9.2 yrs, mean EDSS 1.23±0.99) from one site. A replication study was performed in a cohort (n=46) from a second site. Cortical thickness (CT) was derived from 3T MRI using FreeSurfer. GM connectivity networks were reconstructed from the CT correlation between the 68 regions of the Desikan-Killiany atlas. Cortical integrity and network connectivity -derived from graph theoretical approaches- were compared between the groups in both cohorts. Results corrected for multiple comparisons were considered (p< 0.05 FDR). Results: No regional or global cortical atrophy differences were attested between the two groups in both cohorts. In the network connectivity analysis a decreased local connectivity pattern (reduced transitivity, t=-3.24 p=0.008) was evident in APOE ε4 carriers. Regions with decreased connectivity were consistently seen in the medial part of the left temporal lobe. APOE ε4 status was further associated with raised whole brain connectivity, reflected by increased global efficiency (t=4.34 p=0.005) and reduced modularity (t=-2.84 p=0.02). This network pattern was shown in the frontal, parietal and lateral temporal associative cortices. The results were entirely replicated in the second cohort. Conclusion: We found that MS patients at genetic risk for cognitive decline have significant abnormalities of local GM networks and possibly compensatory increased long-range connectivity patterns. Chronic or focal neuroinflammation could lead to behaviourally relevant memory impairments in these patients through a specific break-down of the long-range paths

Disentangling Neurodegeneration From Aging in Multiple Sclerosis Using Deep Learning: The Brain-Predicted Disease Duration Gap

BACKGROUND AND OBJECTIVES: Disentangling brain aging from disease-related neurodegeneration in patients with multiple sclerosis (PwMS) is increasingly topical. The brain-age paradigm offers a window into this problem but may miss disease-specific effects. In this study, we investigated whether a disease-specific model might complement the brain-age gap (BAG) by capturing aspects unique to MS. METHODS: In this retrospective study, we collected 3D T1-weighted brain MRI scans of PwMS to build (1) a cross-sectional multicentric cohort for age and disease duration (DD) modeling and (2) a longitudinal single-center cohort of patients with early MS as a clinical use case. We trained and evaluated a 3D DenseNet architecture to predict DD from minimally preprocessed images while age predictions were obtained with the DeepBrainNet model. The brain-predicted DD gap (the difference between predicted and actual duration) was proposed as a DD-adjusted global measure of MS-specific brain damage. Model predictions were scrutinized to assess the influence of lesions and brain volumes while the DD gap was biologically and clinically validated within a linear model framework assessing its relationship with BAG and physical disability measured with the Expanded Disability Status Scale (EDSS). RESULTS: We gathered MRI scans of 4,392 PwMS (69.7% female, age: 42.8 ± 10.6 years, DD: 11.4 ± 9.3 years) from 15 centers while the early MS cohort included 749 sessions from 252 patients (64.7% female, age: 34.5 ± 8.3 years, DD: 0.7 ± 1.2 years). Our model predicted DD better than chance (mean absolute error = 5.63 years, R2 = 0.34) and was nearly orthogonal to the brain-age model (correlation between DD and BAGs: r = 0.06 [0.00-0.13], p = 0.07). Predictions were influenced by distributed variations in brain volume and, unlike brain-predicted age, were sensitive to MS lesions (difference between unfilled and filled scans: 0.55 years [0.51-0.59], p < 0.001). DD gap significantly explained EDSS changes (B = 0.060 [0.038-0.082], p < 0.001), adding to BAG (ΔR2 = 0.012, p < 0.001). Longitudinally, increasing DD gap was associated with greater annualized EDSS change (r = 0.50 [0.39-0.60], p < 0.001), with an incremental contribution in explaining disability worsening compared with changes in BAG alone (ΔR2 = 0.064, p < 0.001). DISCUSSION: The brain-predicted DD gap is sensitive to MS-related lesions and brain atrophy, adds to the brain-age paradigm in explaining physical disability both cross-sectionally and longitudinally, and may be used as an MS-specific biomarker of disease severity and progression

Grey Matter Atrophy and its Relationship with White Matter Lesions in Patients with Myelin Oligodendrocyte Glycoprotein Antibody-associated Disease, Aquaporin-4 Antibody-Positive Neuromyelitis Optica Spectrum Disorder, and Multiple Sclerosis

Objective: To evaluate: (1) the distribution of gray matter (GM) atrophy in myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD), aquaporin-4 antibody-positive neuromyelitis optica spectrum disorder (AQP4+NMOSD), and relapsing–remitting multiple sclerosis (RRMS); and (2) the relationship between GM volumes and white matter lesions in various brain regions within each disease. Methods: A retrospective, multicenter analysis of magnetic resonance imaging data included patients with MOGAD/AQP4+NMOSD/RRMS in non-acute disease stage. Voxel-wise analyses and general linear models were used to evaluate the relevance of regional GM atrophy. For significant results (p &lt; 0.05), volumes of atrophic areas are reported. Results: We studied 135 MOGAD patients, 135 AQP4+NMOSD, 175 RRMS, and 144 healthy controls (HC). Compared with HC, MOGAD showed lower GM volumes in the temporal lobes, deep GM, insula, and cingulate cortex (75.79 cm3); AQP4+NMOSD in the occipital cortex (32.83 cm3); and RRMS diffusely in the GM (260.61 cm3). MOGAD showed more pronounced temporal cortex atrophy than RRMS (6.71 cm3), whereas AQP4+NMOSD displayed greater occipital cortex atrophy than RRMS (19.82 cm3). RRMS demonstrated more pronounced deep GM atrophy in comparison with MOGAD (27.90 cm3) and AQP4+NMOSD (47.04 cm3). In MOGAD, higher periventricular and cortical/juxtacortical lesions were linked to reduced temporal cortex, deep GM, and insula volumes. In RRMS, the diffuse GM atrophy was associated with lesions in all locations. AQP4+NMOSD showed no lesion/GM volume correlation. Interpretation: GM atrophy is more widespread in RRMS compared with the other two conditions. MOGAD primarily affects the temporal cortex, whereas AQP4+NMOSD mainly involves the occipital cortex. In MOGAD and RRMS, lesion-related tract degeneration is associated with atrophy, but this link is absent in AQP4+NMOSD. ANN NEUROL 2024;96:276–288

80 Improving Documentation of DNAR Decisions on the Acute Medical Take

Abstract Introduction The BMA, Resuscitation Council and Royal College of Nursing have set out clear guidelines on documentation of Resuscitation discussions and decisions.1 On the acute medical take documentation of these discussions and decisions can be unclear despite use of an electronic patient record (EPR). The aim of this audit was to improve documentation of Do Not Attempt Resuscitation (DNAR) decisions in EPR. Methods We listed patients admitted on the medical take over 1-week, looking at resuscitation status and the documentation of the DNAR decision. We then implemented a change to the format of the EPR treatment escalation plan (TEP) form. Prior to the change the DNAR form was behind the TEP form which had to be clicked on separately and was not mandatory to complete. After the intervention the DNAR decision was placed in a box on the front page of the TEP form to ensure that it was clear and accessible. Results Pre-intervention we reviewed 114 patients notes of which 94 were DNAR. Of these 94 only 17 (18%) had correctly documented DNAR decisions in EPR. Following the intervention we again looked at all admissions to the medical take over a 1-week period, out of 151 patients 75 were DNAR and of these 75 patients 29 had correctly documented DNAR forms. This shows an increase in the percentage of the DNAR decisions filled in from 18% to 39%. Conclusion The results show that although there has been an improvement in the number of DNAR decisions being documented there are still a large percentage of patients who do not have this correctly documented. We are designing further interventions to ensure that the DNAR documentation is marked as a mandatory part of the TEP form as well as educating around the importance of this documentation. </jats:sec