Ruhr University Bochum
Institute of Neuroradiology, St. Josef Hospital

Author Of 2 Presentations

Diagnostic Criteria and Differential Diagnosis Poster Presentation

P0263 - Serum neurofilament predicts clinical progression and increases diagnostic accuracy in patients with early multiple sclerosis (ID 1336)

Abstract

Background

Up to date prognostic estimation in newly diagnosed patients is hardly possible while the differentiation between disabling versus more benign courses is of utmost relevance. Reliable blood-based biomarkers that are associated with diagnosis and prognosis of multiple sclerosis (MS) have not been established.

Objectives

Can serum neurofilament light chain measurements serve as a reliable biomarker for diagnostic accuracy and prognosis for multiple sclerosis patients at the time point of diagnosis?

Methods

In a multicenter prospective longitudinal observational cohort, patients with a first diagnosis of multiple sclerosis (MS) or clinically isolated syndrome (CIS) were recruited between August 2010 and November 2015 in 22 centers and assessed yearly with a standardized protocol. Patients were offered standard immunotherapies according to national treatment guidelines. Serum NfL concentrations were measured using an ultrasensitive single-molecule array (Simoa).

Results

A possible association between sNfL levels and clinical diagnosis, relapses, MRI parameters and treatment decisions was tested in 814 patients classified according to current (2017) and older (2010) McDonald criteria at time point of diagnosis and two years after study inclusion sNfL levels correlated with number of T2 and Gd+ lesions and clinical relapses. After reclassification of CIS[2010] patients with existing CSF analysis, according to 2017 criteria, sNfL levels were lower in CIS[2017] than RRMS[2017] patients (9.1 pg/ml, IQR 6.2-13.7 pg/ml, n = 45; 10.8 pg/ml, IQR 7.4-20.1 pg/ml, n = 213; p = 0.036) and increased accuracy of distinction between CIS and RRMS, when including ≥ 90th percentile of sNfL values. Patients receiving disease-modifying treatment (DMT) during the first two years had higher sNfl baseline levels (11.8 pg/ml, 7.5-20.9 pg/ml, n = 727) than patients never receiving DMT (9.5 pg/ml, IQR 6.4-14.1 pg/ml, n = 87, p = 0.002). Longitudinal sNfL levels reflected treatment decisions within the first four years.

Conclusions

sNfL is associated with diagnosis and prognosis of MS patients at the time point of first diagnosis and may be of use for initial treatment stratification.

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Neuromyelitis Optica and Anti-MOG Disease Poster Presentation

P0708 - Differential MRI biomarkers between MOGAD, AQP4-NMOSD and RRMS: a MAGNIMS multicenter study (ID 1335)

Abstract

Background

Clinical and imaging features of myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) may overlap with those of aquaporin 4-neuromyelitis optica spectrum disorder (AQP4-NMOSD) and relapsing remitting multiple sclerosis (RRMS). There is an unmet need for MRI biomarkers which reflect biological mechanisms involved in MOGAD and can help in the differential diagnosis.

Objectives

We aim to identify imaging features able to differentiate between non-acute MOG-antibody disease, AQP4-NMOSD and RRMS.

Methods

In this ongoing retrospective, cross-sectional MAGNIMS study, we analyzed data collected from 8 centers. All subjects (n=352) had brain and cervical cord 3T MRI. Quantification of MRI biomarkers included brain white matter lesions (WMLs), cortical lesions (CL), brain parenchymal fraction (BPF), white matter fraction (WMF), cortical and deep grey matter fractions (GMF) and cross-sectional cervical cord area (CSA) at C1-C2. Linear regression models were used to compare MRI measures between groups, corrected for age, sex, and centre. Statistical significance was considered when p was <0.05.

Results

91 patients with MOGAD (50F, mean age: 41yrs [±15]), 85 with AQP4-NMOSD (68F, 49yrs [±14]), 90 with RRMS (56F, 41yrs [±11]) and 87 healthy controls (HCs) (54F, 36yrs [±11.6]) were collected. The most common phenotypes at onset were optic neuritis and transverse myelitis in MOGAD (93%) and AQP4-NMOSD (87%). WMLs were detected in 57% MOGAD, 79% AQP4-NMOSD, all RRMS (100%) patients, and in 15% HCs. The mean lesion load and number of lesions were higher in RRMS than both MOGAD (p=0.007, p<0.001) and AQP4-NMOSD (p=0.001, p<0.001). At least one CL was seen in 8% patients with MOGAD (total n=8), 10% patients with AQP4-NMOSD (n=7), and in 69% patients with RRMS (n=150). All patient groups showed lower BPF than HCs, with lower WMF in MOGAD and RRMS than HCs (all p<0.01). Between groups, deep GMF was lower in RRMS than MOGAD (p<0.001) and AQP4-NMOSD (p=0.001). CSA was reduced in all disease groups when compared to HCs (all p<0.01) and lower in AQP4-NMOSD than RRMS (p=0.01).

Conclusions

This ongoing study indicates that MOGAD and AQP4-NMOSD share similar MRI features, and no specific MRI biomarker can distinguish between them. Patients with AQP4-NMOSD showed greater spinal cord atrophy than RRMS, and RRMS patients had a higher number of cortical lesions, and greater deep GM atrophy than AQP4-NMOSD and MOGAD. The next step is to investigate whether lesion distribution differs between the two antibody-mediated disease.

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