Central nervous system atrophy predicts future dynamics of disability progression in a real-world multiple sclerosis cohort.
Adult
Atrophy
/ pathology
Brain
/ diagnostic imaging
Disability Evaluation
Disease Progression
Female
Gray Matter
/ pathology
Humans
Magnetic Resonance Imaging
/ methods
Middle Aged
Multiple Sclerosis
/ diagnostic imaging
Multiple Sclerosis, Chronic Progressive
/ diagnostic imaging
Multiple Sclerosis, Relapsing-Remitting
/ diagnostic imaging
MRI
atrophy
biomarkers
multiple sclerosis
prediction models
Journal
European journal of neurology
ISSN: 1468-1331
Titre abrégé: Eur J Neurol
Pays: England
ID NLM: 9506311
Informations de publication
Date de publication:
12 2021
12 2021
Historique:
received:
07
07
2021
accepted:
20
08
2021
pubmed:
7
9
2021
medline:
2
4
2022
entrez:
6
9
2021
Statut:
ppublish
Résumé
In an era of individualized multiple sclerosis (MS) patient management, biomarkers for accurate prediction of future clinical outcomes are needed. We aimed to evaluate the potential of short-term magnetic resonance imaging (MRI) atrophy measures and serum neurofilament light chain (sNfL) as predictors of the dynamics of disability accumulation in relapse-onset MS. Brain gray and white matter, thalamic, striatal, pallidal and cervical spinal cord volumes, and lesion load were measured over three available time points (mean time span 2.24 ± 0.70 years) for 183 patients (140 relapsing-remitting [RRMS] and 43 secondary-progressive MS (SPMS); 123 female, age 46.4 ± 11.0 years; disease duration 15.7 ± 9.3 years), and their respective annual changes were calculated. Baseline sNfL was also measured at the third available time point for each patient. Subsequently, patients underwent annual clinical examinations over 5.4 ± 3.7 years including Expanded Disability Status Scale (EDSS) scoring, the nine-hole peg test and the timed 25-foot walk test. Higher annual spinal cord atrophy rates and lesion load increase predicted higher future EDSS score worsening over time in SPMS. Lower baseline thalamic volumes predicted higher walking speed worsening over time in RRMS. Lower baseline gray matter, as well as higher white matter and spinal cord atrophy rates, lesion load increase, baseline striatal volumes and baseline sNfL, predicted higher future hand dexterity worsening over time. All models showed reasonable to high prediction accuracy. This study demonstrates the capability of short-term MRI metrics to accurately predict future dynamics of disability progression in a real-world relapse-onset MS cohort. The present study represents a step towards the utilization of structural MRI measurements in patient care.
Sections du résumé
BACKGROUND AND PURPOSE
In an era of individualized multiple sclerosis (MS) patient management, biomarkers for accurate prediction of future clinical outcomes are needed. We aimed to evaluate the potential of short-term magnetic resonance imaging (MRI) atrophy measures and serum neurofilament light chain (sNfL) as predictors of the dynamics of disability accumulation in relapse-onset MS.
METHODS
Brain gray and white matter, thalamic, striatal, pallidal and cervical spinal cord volumes, and lesion load were measured over three available time points (mean time span 2.24 ± 0.70 years) for 183 patients (140 relapsing-remitting [RRMS] and 43 secondary-progressive MS (SPMS); 123 female, age 46.4 ± 11.0 years; disease duration 15.7 ± 9.3 years), and their respective annual changes were calculated. Baseline sNfL was also measured at the third available time point for each patient. Subsequently, patients underwent annual clinical examinations over 5.4 ± 3.7 years including Expanded Disability Status Scale (EDSS) scoring, the nine-hole peg test and the timed 25-foot walk test.
RESULTS
Higher annual spinal cord atrophy rates and lesion load increase predicted higher future EDSS score worsening over time in SPMS. Lower baseline thalamic volumes predicted higher walking speed worsening over time in RRMS. Lower baseline gray matter, as well as higher white matter and spinal cord atrophy rates, lesion load increase, baseline striatal volumes and baseline sNfL, predicted higher future hand dexterity worsening over time. All models showed reasonable to high prediction accuracy.
CONCLUSION
This study demonstrates the capability of short-term MRI metrics to accurately predict future dynamics of disability progression in a real-world relapse-onset MS cohort. The present study represents a step towards the utilization of structural MRI measurements in patient care.
Identifiants
pubmed: 34487400
doi: 10.1111/ene.15098
pmc: PMC9292558
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
4153-4166Informations de copyright
© 2021 The Authors. European Journal of Neurology published by John Wiley & Sons Ltd on behalf of European Academy of Neurology.
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