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Research paper
Brain atrophy and lesion load predict long term disability in multiple sclerosis
  1. Veronica Popescu1,
  2. Federica Agosta2,
  3. Hanneke E Hulst1,3,
  4. Ingrid C Sluimer1,
  5. Dirk L Knol4,
  6. Maria Pia Sormani5,
  7. Christian Enzinger6,
  8. Stefan Ropele6,
  9. Julio Alonso7,
  10. Jaume Sastre-Garriga8,
  11. Alex Rovira8,
  12. Xavier Montalban7,
  13. Benedetta Bodini9,
  14. Olga Ciccarelli9,10,
  15. Zhaleh Khaleeli9,
  16. Declan T Chard9,10,
  17. Lucy Matthews11,
  18. Jaqueline Palace12,
  19. Antonio Giorgio13,
  20. Nicola De Stefano13,
  21. Philipp Eisele14,
  22. Achim Gass14,15,
  23. Chris H Polman16,
  24. Bernard M J Uitdehaag4,
  25. Maria Jose Messina17,
  26. Giancarlo Comi17,
  27. Massimo Filippi2,17,
  28. Frederik Barkhof1,
  29. Hugo Vrenken1,18,
  30. on behalf of the MAGNIMS Study Group19
  1. 1Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands
  2. 2Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, Vita-Salute University and San Raffaele Scientific Institute, Milan, Italy
  3. 3Department of Anatomy and Neurosciences, VU University Medical Center, Amsterdam, The Netherlands
  4. 4Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands
  5. 5Biostatistics Unit, Department of Health Sciences, University of Genoa, Genoa, Italy
  6. 6Department of Neurology, Medical University of Graz, Austria
  7. 7Magnetic Resonance Unit, Department of Radiology, Vall d'Hebron University Hospital, Autonomous University of Barcelona, Barcelona, Spain
  8. 8Neurology/Neuroimmunology Unit, MS Centre of Catalonia (Cemcat), Vall d’Hebron University Hospital, Barcelona, Spain
  9. 9NMR Research Unit, University College London (UCL) Institute of Neurology, London, UK
  10. 10National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre, UK
  11. 11Nuffield Department of Clinical Neurosciences, University of Oxford, UK
  12. 12Centre for Functional Magnetic Resonance Imaging of the Brain, University of Oxford, UK
  13. 13Department of Medicine, Surgery & Neuroscience, University of Siena, Siena, Italy
  14. 14Department of Neurology, UniversitätsMedizin Mannheim, University of Heidelberg, Germany
  15. 15Department of Neurology, University Hospital Basel, Switzerland
  16. 16Department of Neurology, VU University Medical Center, Amsterdam, The Netherlands
  17. 17Department of Neurology, Institute of Experimental Neurology, Vita-Salute University and San Raffaele Scientific Institute, Milan, Italy
  18. 18Department of Physics and Medical Technology, VU University Medical Center, Amsterdam, The Netherlands
  19. 19The members of MAGNIMS Study Group Steering Committee are A Rovira, N de Stefano, X Montalban, F Barkhof, C Enzinger, M Filippi, J Frederiksen, L Kappos, O Ciccarelli, J Palace, H Vrenken, MA Rocca, T Yousry
  1. Correspondence to Dr V Popescu, Department of Radiology, VU University Medical Centre, Room PK -1 X 108, De Boelelaan 1118, Amsterdam 1081 HZ, The Netherlands; v.popescu{at}


Objective To determine whether brain atrophy and lesion volumes predict subsequent 10 year clinical evolution in multiple sclerosis (MS).

Design From eight MAGNIMS (MAGNetic resonance Imaging in MS) centres, we retrospectively included 261 MS patients with MR imaging at baseline and after 1–2 years, and Expanded Disability Status Scale (EDSS) scoring at baseline and after 10 years. Annualised whole brain atrophy, central brain atrophy rates and T2 lesion volumes were calculated. Patients were categorised by baseline diagnosis as primary progressive MS (n=77), clinically isolated syndromes (n=18), relapsing–remitting MS (n=97) and secondary progressive MS (n=69). Relapse onset patients were classified as minimally impaired (EDSS=0–3.5, n=111) or moderately impaired (EDSS=4–6, n=55) according to their baseline disability (and regardless of disease type). Linear regression models tested whether whole brain and central atrophy, lesion volumes at baseline, follow-up and lesion volume change predicted 10 year EDSS and MS Severity Scale scores.

Results In the whole patient group, whole brain and central atrophy predicted EDSS at 10 years, corrected for imaging protocol, baseline EDSS and disease modifying treatment. The combined model with central atrophy and lesion volume change as MRI predictors predicted 10 year EDSS with R2=0.74 in the whole group and R2=0.72 in the relapse onset group. In subgroups, central atrophy was predictive in the minimally impaired relapse onset patients (R2=0.68), lesion volumes in moderately impaired relapse onset patients (R2=0.21) and whole brain atrophy in primary progressive MS (R2=0.34).

Conclusions This large multicentre study points to the complementary predictive value of atrophy and lesion volumes for predicting long term disability in MS.

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