Abstract
Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system (CNS) presenting with a wide spectrum of clinical and radiological phenotypes. Although MS was originally considered an inflammatory disease that predominantly affects the white matter, neurodegeneration resulting in accelerated brain and spinal cord atrophy is now recognized as an important determinant of disability. It is commonly understood that MS is a complex heterogeneous disease characterized by a broad spectrum of physical and cognitive symptoms, variable treatment response, radiological features, and neuropathology. This heterogeneous presentation of symptoms is likely attributable to complex interactions between external and hereditary factors, resulting in limited predictability of the disease and its response to treatment. Therefore, there is an urgent need for personalized treatment. Unfortunately, traditional clinical predictors are not sufficiently sensitive to reliably predict MS future and monitor ongoing disease activity. Contrastingly, abnormal magnetic resonance imaging (MRI) findings have been shown to be the most informative predictors and surrogate markers of disease activity. Not only the accumulation of the lesion burden but also the atrophy of the brain and spinal cord are important determinants of disease progression and associated with the development of physical and cognitive disabilities. Therefore, the assessment of the course of brain atrophy within individual patients could facilitate the identification of those with current disease activity and those at the highest risk of accumulating permanent disability. In this context, some efforts have been made to bring measurements of brain atrophy into clinical practice.
Unfortunately, the relatively high intra-individual variability of longitudinal brain atrophy measures renders the application of brain volumetric measures in individual patients with MS challenging. Therefore, brain atrophy measures are yet to be utilized routinely in clinical practice. In this publication, we investigated how the high intra-individual variability of volumetric brain volume measures can be overcome and whether they have practical applications in clinical decision-making. We propose several approaches, including high-frequency MRI scanning, combined clinico-radiological composite scores, and the application of cross-sectional volumetric measures. This publication is intended for neurologists, radiologists, and other specialists who treat patients with multiple sclerosis, as well as researchers in neuroimaging methods.