Neurologic Diagnostics in 2035: The Neurology Future Forecasting Series

Innovations and advances in technologies over the past few years have yielded faster and wider diagnostic applications to patients with neurologic diseases. This article focuses on the foreseeable developments of the diagnostic tools available to the neurologist in the next 15 years. Clinical judgment is and will remain the cornerstone of the diagnostic process, assisted by novel technologies, such as artificial intelligence and machine learning. Future neurologists must be educated to develop, cultivate, and rely on their clinical skills, while becoming familiar with novel, often complex, assistive technologies

A longitudinal study of abnormalities on MRI and disability from multiple sclerosis

Background: In patients with isolated syndromes that are clinically suggestive of multiple sclerosis, such as optic neuritis or brain-stem or spinal cord syndromes, the presence of lesions as determined by T2-weighted magnetic resonance imaging (MRI) of the brain increases the likelihood that multiple sclerosis will develop. We sought to determine the relation between early lesion volume, changes in volume, and long-term disability. Methods: Seventy-one patients in a serial MRI study of patients with isolated syndromes were reassessed after a mean of 14.1 years. Disability was measured with the use of Kurtzke's Expanded Disability Status Scale (EDSS; possible range, 0 to 10, with a higher score indicating a greater degree of disability). Results: Clinically definite multiple sclerosis developed in 44 of the 50 patients (88 percent) with abnormal results on MRI at presentation and in 4 of 21 patients (19 percent) with normal results on MRI. The median EDSS score at follow-up for those with multiple sclerosis was 3.25 (range, 0 to 10); 31 percent had an EDSS score of 6 or more (including three patients whose deaths were due to multiple sclerosis). The EDSS score at 14 years correlated moderately with lesion volume on MRI at 5 years (r=0.60) and with the increase in lesion volume over the first 5 years (r=0.61). Conclusions: In patients who first present with isolated syndromes suggestive of multiple sclerosis, the increases in the volume of the lesions seen on magnetic resonance imaging of the brain in the first five years correlate with the degree of long-term disability from multiple sclerosis. This relation is only moderate, so the volume of the lesions alone may not be an adequate basis for decisions about the use of disease-modifying treatment

A possible case of serum sickness after ocrelizumab infusion – Commentary

Serum sickness is a type III delayed hypersensitivity reaction which causes deposition of immune-complexes in the tissues. It has been reported with rituximab, and in this issue of the journal, there is a case report of a patient with relapsing remitting multiple sclerosis who developed a possible serum sickness after the third infusion of ocrelizumab. In this commentary, we discuss the current literature on serum sickness, and how to diagnose and manage it. We provide our opinion on this particular case, and encourage neurologists and patients to remain vigilant of such a possibility

Prediction of time between CIS onset and clinical conversion to MS using Random Forests

CIS is diagnosed after a first neurological attack and can be considered an early stage of MS as ~80% of all CIS patients will have a second relapse within 20 years. The prediction of this second clinical relapse which marks the clinical conversion to MS (i.e., clinically-definite MS, CDMS) is very challenging, and many clinical and radiological predictors of CDMS have been identified. Machine learning techniques such as support vector machines (SVMs) have been widely applied to neuroimaging data in order to associate MRI features with binary clinical outcomes. A single-centre study has shown that it is possible to predict short-time conversion after 1 and 3 years with an accuracy of ~75 % using a priori defined features from baseline MRI measures and clinical characteristics, which were applied to support vector machines (SVMs). Random forests are another type of machine learning techniques that can easily be applied to regression problems, and consist of an ensemble of decision trees for regression where each tree is created from independent bootstraps from the input data. The present study shows the feasibility of using random forests with European multi-centre MRI data (obtained at CIS onset) to predict the actual date of conversion to CDMS rather than just a binary outcome at a fixed time point

Dynamic MRI lesion evolution in paediatric MOG-Ab associated disease (MOGAD)

INTRODUCTION: Myelin oligodendrocyte glycoprotein (MOG) antibodies are associated clinically with either a monophasic or relapsing disease course in both children and adults. There are few studies studying lesion evolution in children with myelin oligodendrocyte glycoprotein antibody associated disorder (MOGAD). AIM: The aim of this study was to examine MRI lesion evolution over time in a large single-centre paediatric MOGAD cohort. METHODS: We retrospectively identified patients with MOGAD from a tertiary paediatric neurosciences centre (Great Ormond Street Hospital) between 2001 to 2022. RESULTS: A total of 363 MRI scans from 59 included patients were available for analysis. Median age at presentation was 4 yrs (IQR 4-9), 32 (54.2%) were female and 34 (57.6%) were of non-white ethnicities. Twenty-seven children (45.8%) had a monophasic illness and 32 (54.2%) had a relapsing disease course. In the relapsing MOGAD group, median number of relapses was 4 (range 2-30). Initial presentation was ADEM in 27(46%), ON in 18 (31%) ADEM-ON in 4 (7%), ADEM-TM in 6 (10%) TM in 2 (3%) ADEM-TM-ON in 1 (2%) and ON-Brainstem syndrome in 1 (2%). There was no difference in demographics or clinical presentation between monophasic and relapsing groups. Fifteen patients (25.4%) had gadolinium enhancement on initial attack MRI. Seven out of 32 (21.9%) relapsing patients had persistent enhancement on follow-up MRI scans. One patient with a clinical transverse myelitis at presentation was MRI negative. New asymptomatic lesions following first clinical event were seen in 5/27 (18.5%) monophasic patients and 8/32 (25%) relapsing patients. During follow-up interval scanning,38 out of 59 have had follow up neuroimaging after their first attack whereas15/32 had relapsed before having a follow up MRI. Complete lesion resolution was reported in 9/38 (23.6%) (8 monophasic, 1 relapsing) following 1st acute attack, 3/32 (9.3%) after 2nd acute attack, and 1/32 (3.1%) following 3rd acute attack and 0/32 following 4th acute attack. Partial resolution of MRI lesions was seen in 7/20 (35%) monophasic patients and 7/32 (21.8%) relapsing patients at follow-up scans. CONCLUSIONS: Demyelinating lesions in paediatric MOGAD are dynamic and timing of MRI scanning may influence CNS region involvement. Unlike in multiple sclerosis, a significant number of MOGAD patients will have complete lesion resolution at first follow-up, although the ability to repair is reduced following multiple relapses