“At present the various automated brain volume measurement tools are not good enough to use on individual subjects in clinical practice. There are two issues; (1) physiological variability and (2) measurement error and variability. The physiological variability can be overcome by standardising hydration status, co-medication, alcohol status, time of day and other variables that are known to affect brain volume. The measurement variability and error is a technological challenge and should improve with time. At the moment the best we can do is select a cut-off in brain volume change above which we can be confident brain atrophy is clearly abnormal, for example above 0.6%, 0.8% or 1% per annum. This threshold will depend on the performance characteristics of the measurement tool. The other option is to switch to better, more reliable, neurodegenerative marker, for example CSF neurofilament levels. We are hedging our bets and doing both. We are test driving the MSmetrix software below and we are implementing regular CSF neurofilament monitoring in a select group of patients in whom we think the data will inform clinical decision making.”
“Please watch this space; with a focus on reducing, or trying to prevent, end-organ damage in MS these tools are going to become increasingly important as part of routine clinical practice.”
Smeets et al. Reliable measurements of brain atrophy in individual patients with multiple sclerosis. Brain Behav. 2016 Jul 19;6(9):e00518. eCollection 2016.
INTRODUCTION: As neurodegeneration is recognized as a major contributor to disability in multiple sclerosis (MS), brain atrophy quantification could have a high added value in clinical practice to assess treatment efficacy and disease progression, provided that it has a sufficiently low measurement error to draw meaningful conclusions for an individual patient.
METHOD: In this paper, we present an automated longitudinal method based on Jacobian integration for measuring whole-brain and gray matter atrophy based on anatomical magnetic resonance images (MRI), named MSmetrix. MSmetrix is specifically designed to measure atrophy in patients with MS, by including iterative lesion segmentation and lesion filling based on FLAIR and T1-weighted MRI scans.
RESULTS: MS metrix is compared with SIENA with respect to test-retest error and consistency, resulting in an average test-retest error on an MS data set of 0.13% (MS metrix) and 0.17% (SIENA) and a consistency error of 0.07% (MS metrix) and 0.05% (SIENA). On a healthy subject data set including physiological variability the test-retest is 0.19% (MS metrix) and 0.31% (SIENA).