Critical analysis on the present methods for brain volume measurements in multiple sclerosis

Brain atrophy assessment in multiple sclerosis: technical- and subject-related barriers for translation to real-world application in individual subjects

INTRODUCTION

Brain atrophy is a well-established MRI outcome for predicting clinical progression and monitoring treatment response in persons with multiple sclerosis (pwMS) at the group level. Despite the important progress made, the translation of brain atrophy assessment into clinical practice faces several challenges.

AREAS COVERED

In this review, the authors discuss technical- and subject-related barriers for implementing brain atrophy assessment as part of the clinical routine at the individual level. Substantial progress has been made to understand and mitigate technical barriers behind MRI acquisition. Numerous research and commercial segmentation techniques for volume estimation are available and technically validated, but their clinical value has not been fully established. A systematic assessment of subject-related barriers, which include genetic, environmental, biological, lifestyle, comorbidity, and aging confounders, is critical for the interpretation of brain atrophy measures at the individual subject level. Educating both medical providers and pwMS will help better clarify the benefits and limitations of assessing brain atrophy for disease monitoring and prognosis.

EXPERT OPINION

Integrating brain atrophy assessment into clinical practice for pwMS requires overcoming technical and subject-related challenges. Advances in MRI standardization, artificial intelligence, and clinician education will facilitate this process, improving disease management and potentially reducing long-term healthcare costs.

Predictors of multiple sclerosis progression: A systematic review of conventional magnetic resonance imaging studies

INTRODUCTION

Multiple Sclerosis (MS) is a chronic neurodegenerative disorder that affects the central nervous system (CNS) and results in progressive clinical disability and cognitive decline. Currently, there are no specific imaging parameters available for the prediction of longitudinal disability in MS patients. Magnetic resonance imaging (MRI) has linked imaging anomalies to clinical and cognitive deficits in MS. In this study, we aimed to evaluate the effectiveness of MRI in predicting disability, clinical progression, and cognitive decline in MS.

METHODS

In this study, according to PRISMA guidelines, we comprehensively searched the Web of Science, PubMed, and Embase databases to identify pertinent articles that employed conventional MRI in the context of Relapsing-Remitting and progressive forms of MS. Following a rigorous screening process, studies that met the predefined inclusion criteria were selected for data extraction and evaluated for potential sources of bias.

RESULTS

A total of 3028 records were retrieved from database searching. After a rigorous screening, 53 records met the criteria and were included in this study. Lesions and alterations in CNS structures like white matter, gray matter, corpus callosum, thalamus, and spinal cord, may be used to anticipate disability progression. Several prognostic factors associated with the progression of MS, including presence of cortical lesions, changes in gray matter volume, whole brain atrophy, the corpus callosum index, alterations in thalamic volume, and lesions or alterations in cross-sectional area of the spinal cord. For cognitive impairment in MS patients, reliable predictors include cortical gray matter volume, brain atrophy, lesion characteristics (T2-lesion load, temporal, frontal, and cerebellar lesions), white matter lesion volume, thalamic volume, and corpus callosum density.

CONCLUSION

This study indicates that MRI can be used to predict the cognitive decline, disability progression, and disease progression in MS patients over time.

Neuroimaging characteristics may aid in diagnosis, subtyping, and prognosis in autoimmune encephalitis

OBJECTIVE

To examine the utility of neuroimaging characteristics as biomarkers of prognosis in seropositive autoimmune encephalitis (AE).

METHODS

In this multi-center study, we retrospectively analyzed 66 cases of seropositive AE. The MRI and PET imaging was assessed by independent visual inspection. Whole brain and regional volumes were imputed by IcoMetrix, an automated volumetric assessment package. The modified Rankin Scale (mRS) was utilized to assess the patients' follow-up disability. Other outcomes were mortality, first line treatment failure, medial temporal lobe (MTL) atrophy, and clinical relapse. Univariate and multivariable regression analysis was performed.

RESULTS

Abnormalities on MRI were detected in 35.1% of patients, while PET was abnormal in 46.4%. Initial median whole brain and hippocampal volumes were below the 5th and 20th percentile respectively compared to an age-matched healthy database. After a median follow-up of 715 days, 85.2% had good functional outcome (mRS ≤ 2). Nine patients developed MTL atrophy during follow-up. On multivariable analysis, inflammatory MTL changes were associated with development of MTL atrophy (HR 19.6, p = 0.007) and initial hippocampal volume had an inverse relationship with mortality (HR 0.04, p = 0.011). Patients who developed MTL atrophy had a reduced chance of good final mRS (HR 0.16, p = 0.015).

CONCLUSIONS

Neuroimaging on initial hospital admission may be provide important diagnostic and prognostic information. This study demonstrates that structural and inflammatory changes of the MTL may have importance in clinical and radiological prognosis in seropositive AE.

Predictive MRI Biomarkers in MS—A Critical Review

Background and Objectives: In this critical review, we explore the potential use of MRI measurements as prognostic biomarkers in multiple sclerosis (MS) patients, for both conventional measurements and more novel techniques such as magnetization transfer, diffusion tensor, and proton spectroscopy MRI. Materials and Methods: All authors individually and comprehensively reviewed each of the aspects listed below in PubMed, Medline, and Google Scholar. Results: There are numerous MRI metrics that have been proven by clinical studies to hold important prognostic value for MS patients, most of which can be readily obtained from standard 1.5T MRI scans. Conclusions: While some of these parameters have passed the test of time and seem to be associated with a reliable predictive power, some are still better interpreted with caution. We hope this will serve as a reminder of how vast a resource we have on our hands in this versatile tool—it is up to us to make use of it.

Neurofilament light chain in the assessment of patients with multiple sclerosis

Multiple sclerosis (MS) is an autoimmune, inflammatory, and degenerative disease of the central nervous system. Axonal degeneration is triggered by inflammation and is the pathological substrate of progressive disability in patients with MS. Therapeutic interventions can reduce inflammatory activity, thus delaying neurodegeneration and the progression of disability. Disease activity and neurodegeneration are assessed mainly through clinical evaluation and magnetic resonance imaging. These measures lack sensitivity and accuracy, so new biomarkers are necessary. Several markers have been studied and to date the most promising is neurofilament light (NfL), a component of the axonal cytoskeleton, which is released into cerebrospinal fluid (CSF) following axonal damage. In the present study, we review the current knowledge about CSF NfL determination in MS, clinically isolated syndrome, and radiologically isolated syndrome, and critically discuss how CSF NfL measurement may contribute to therapeutic decision-making in these patients.