Evaluation of a connectivity-based imaging metric that reflects functional decline in Multiple Sclerosis.
Katherine A KoenigErik B BeallKen E SakaieDaniel OntanedaLael StoneStephen M RaoKunio NakamuraStephen E JonesMark J LowePublished in: PloS one (2021)
Cognitive impairment is a common symptom in individuals with Multiple Sclerosis (MS), but meaningful, reliable biomarkers relating to cognitive decline have been elusive, making evaluation of the impact of therapeutics on cognitive function difficult. Here, we combine pathway-based MRI measures of structural and functional connectivity to construct a metric of functional decline in MS. The Structural and Functional Connectivity Index (SFCI) is proposed as a simple, z-scored metric of structural and functional connectivity, where changes in the metric have a simple statistical interpretation and may be suitable for use in clinical trials. Using data collected at six time points from a 2-year longitudinal study of 20 participants with MS and 9 age- and sex-matched healthy controls, we probe two common symptomatic domains, motor and cognitive function, by measuring structural and functional connectivity in the transcallosal motor pathway and posterior cingulum bundle. The SFCI is significantly lower in participants with MS compared to controls (p = 0.009) and shows a significant decrease over time in MS (p = 0.012). The change in SFCI over two years performed favorably compared to measures of brain parenchymal fraction and lesion volume, relating to follow-up measures of processing speed (r = 0.60, p = 0.005), verbal fluency (r = 0.57, p = 0.009), and score on the Multiple Sclerosis Functional Composite (r = 0.67, p = 0.003). These initial results show that the SFCI is a suitable metric for longitudinal evaluation of functional decline in MS.
Keyphrases
- functional connectivity
- multiple sclerosis
- resting state
- white matter
- mass spectrometry
- cognitive decline
- ms ms
- clinical trial
- cognitive impairment
- mild cognitive impairment
- magnetic resonance imaging
- quantum dots
- working memory
- computed tomography
- randomized controlled trial
- subarachnoid hemorrhage
- single molecule
- big data