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Spinal cord volume loss: A marker of disease progression in multiple sclerosis


Tsagkas, Charidimos; Magon, Stefano; Gaetano, Laura; Pezold, Simon; Naegelin, Yvonne; Amann, Michael; Stippich, Christoph; Cattin, Philippe; Wuerfel, Jens; Bieri, Oliver; Sprenger, Till; Kappos, Ludwig; Parmar, Katrin (2018). Spinal cord volume loss: A marker of disease progression in multiple sclerosis. Neurology, 91(4):e349-e358.

Abstract

OBJECTIVE
Cross-sectional studies have shown that spinal cord volume (SCV) loss is related to disease severity in multiple sclerosis (MS). However, long-term data are lacking. Our aim was to evaluate SCV loss as a biomarker of disease progression in comparison to other MRI measurements in a large cohort of patients with relapse-onset MS with 6-year follow-up.
METHODS
The upper cervical SCV, the total brain volume, and the brain T2 lesion volume were measured annually in 231 patients with MS (180 relapsing-remitting [RRMS] and 51 secondary progressive [SPMS]) over 6 years on 3-dimensional, T1-weighted, magnetization-prepared rapid-acquisition gradient echo images. Expanded Disability Status Scale (EDSS) score and relapses were recorded at every follow-up.
RESULTS
Patients with SPMS had lower baseline SCV ( < 0.01) but no accelerated SCV loss compared to those with RRMS. Clinical relapses were found to predict SCV loss over time ( < 0.05) in RRMS. Furthermore, SCV loss, but not total brain volume and T2 lesion volume, was a strong predictor of EDSS score worsening over time ( < 0.05). The mean annual rate of SCV loss was the strongest MRI predictor for the mean annual EDSS score change of both RRMS and SPMS separately, while correlating stronger in SPMS. Every 1% increase of the annual SCV loss rate was associated with an extra 28% risk increase of disease progression in the following year in both groups.
CONCLUSION
SCV loss over time relates to the number of clinical relapses in RRMS, but overall does not differ between RRMS and SPMS. SCV proved to be a strong predictor of physical disability and disease progression, indicating that SCV may be a suitable marker for monitoring disease activity and severity.

Abstract

OBJECTIVE
Cross-sectional studies have shown that spinal cord volume (SCV) loss is related to disease severity in multiple sclerosis (MS). However, long-term data are lacking. Our aim was to evaluate SCV loss as a biomarker of disease progression in comparison to other MRI measurements in a large cohort of patients with relapse-onset MS with 6-year follow-up.
METHODS
The upper cervical SCV, the total brain volume, and the brain T2 lesion volume were measured annually in 231 patients with MS (180 relapsing-remitting [RRMS] and 51 secondary progressive [SPMS]) over 6 years on 3-dimensional, T1-weighted, magnetization-prepared rapid-acquisition gradient echo images. Expanded Disability Status Scale (EDSS) score and relapses were recorded at every follow-up.
RESULTS
Patients with SPMS had lower baseline SCV ( < 0.01) but no accelerated SCV loss compared to those with RRMS. Clinical relapses were found to predict SCV loss over time ( < 0.05) in RRMS. Furthermore, SCV loss, but not total brain volume and T2 lesion volume, was a strong predictor of EDSS score worsening over time ( < 0.05). The mean annual rate of SCV loss was the strongest MRI predictor for the mean annual EDSS score change of both RRMS and SPMS separately, while correlating stronger in SPMS. Every 1% increase of the annual SCV loss rate was associated with an extra 28% risk increase of disease progression in the following year in both groups.
CONCLUSION
SCV loss over time relates to the number of clinical relapses in RRMS, but overall does not differ between RRMS and SPMS. SCV proved to be a strong predictor of physical disability and disease progression, indicating that SCV may be a suitable marker for monitoring disease activity and severity.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Clinic for Neuroradiology
Dewey Decimal Classification:610 Medicine & health
Language:English
Date:27 June 2018
Deposited On:26 Oct 2018 14:42
Last Modified:17 Sep 2019 19:40
Publisher:Lippincott Williams & Wilkins
ISSN:0028-3878
OA Status:Green
Publisher DOI:https://doi.org/10.1212/WNL.0000000000005853
PubMed ID:29950437

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