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Brain Imaging and Behavior

, Volume 13, Issue 5, pp 1361–1374 | Cite as

MRI-based prediction of conversion from clinically isolated syndrome to clinically definite multiple sclerosis using SVM and lesion geometry

  • Kerstin BendfeldtEmail author
  • Bernd Taschler
  • Laura Gaetano
  • Philip Madoerin
  • Pascal Kuster
  • Nicole Mueller-Lenke
  • Michael Amann
  • Hugo Vrenken
  • Viktor Wottschel
  • Frederik Barkhof
  • Stefan Borgwardt
  • Stefan Klöppel
  • Eva-Maria Wicklein
  • Ludwig Kappos
  • Gilles Edan
  • Mark S. Freedman
  • Xavier Montalbán
  • Hans-Peter Hartung
  • Christoph Pohl
  • Rupert Sandbrink
  • Till Sprenger
  • Ernst-Wilhelm Radue
  • Jens Wuerfel
  • Thomas E. Nichols
Original Research

Abstract

Neuroanatomical pattern classification using support vector machines (SVMs) has shown promising results in classifying Multiple Sclerosis (MS) patients based on individual structural magnetic resonance images (MRI). To determine whether pattern classification using SVMs facilitates predicting conversion to clinically definite multiple sclerosis (CDMS) from clinically isolated syndrome (CIS). We used baseline MRI data from 364 patients with CIS, randomised to interferon beta-1b or placebo. Non-linear SVMs and 10-fold cross-validation were applied to predict converters/non-converters (175/189) at two years follow-up based on clinical and demographic data, lesion-specific quantitative geometric features and grey-matter-to-whole-brain volume ratios. We applied linear SVM analysis and leave-one-out cross-validation to subgroups of converters (n = 25) and non-converters (n = 44) based on cortical grey matter segmentations. Highest prediction accuracies of 70.4% (p = 8e-5) were reached with a combination of lesion-specific geometric (image-based) and demographic/clinical features. Cortical grey matter was informative for the placebo group (acc.: 64.6%, p = 0.002) but not for the interferon group. Classification based on demographic/clinical covariates only resulted in an accuracy of 56% (p = 0.05). Overall, lesion geometry was more informative in the interferon group, EDSS and sex were more important for the placebo cohort. Alongside standard demographic and clinical measures, both lesion geometry and grey matter based information can aid prediction of conversion to CDMS.

Keywords

Clinically isolated syndrome Multiple sclerosis Support vector machine MRI Classification Lesion geometry 

Notes

Compliance with ethical standards

Conflict of interest

Kerstin Bendfeldt declares that she has no conflict of interest.

Bernd Taschler declares that he has no conflict of interest.

Laura Gaetano declares that she has no conflict of interest.

Philip Madoerin declares that he has no conflict of interest.

Pascal Kuster declares that he has no conflict of interest.

Nicole Mueller-Lenke declares that she has no conflict of interest.

Michael Amann declares that he has no conflict of interest.

Hugo Vrenken declares that he has no conflict of interest.

Viktor Wottschel declares that he has no conflict of interest.

Frederik Barkhof declares that he has no conflict of interest.

Stefan Borgwardt declares that he has no conflict of interest.

Stefan Klöppel declares that he has no conflict of interest.

Eva-Maria Wicklein declares that she has no conflict of interest.

Ludwig Kappos declares that he has no conflict of interest.

Gilles Edan declares that he has no conflict of interest.

Mark S. Freedman declares that he has no conflict of interest.

Xavier Montalbán declares that he has no conflict of interest.

Hans-Peter Hartung declares that he has no conflict of interest.

Christoph Pohl ✝ - no conflict of interest.

Rupert Sandbrink declares that he has no conflict of interest.

Rupert Sandbrink declares that he has no conflict of interest.

Bernd Taschler declares that he has no conflict of interest.

Till Sprenger has received research grants from the Swiss MS Society, Swiss National Research Foundation, EFIC-Grünenthal and Novartis Pharmaceuticals Switzerland. Till Sprengers current and/or previous employers have received compensation for consultation and speaking activities from Mitsubishi Pharma, Eli Lilly, Sanofi Genzyme, Novartis, ATI, Actelion, Electrocore, Biogen Idec, Teva and Allergan.

Ernst-Wilhelm Radue declares that he has no conflict of interest.

Jens Wuerfel declares that he has no conflict of interest.

Thomas E. Nichols declares that he has no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Supplementary material

11682_2018_9942_MOESM1_ESM.docx (133 kb)
ESM 1 (DOCX 132 kb)

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Kerstin Bendfeldt
    • 1
    Email author
  • Bernd Taschler
    • 2
    • 3
  • Laura Gaetano
    • 1
    • 4
  • Philip Madoerin
    • 1
  • Pascal Kuster
    • 1
  • Nicole Mueller-Lenke
    • 1
  • Michael Amann
    • 1
    • 4
  • Hugo Vrenken
    • 5
  • Viktor Wottschel
    • 5
  • Frederik Barkhof
    • 5
    • 6
  • Stefan Borgwardt
    • 1
    • 7
    • 8
  • Stefan Klöppel
    • 9
  • Eva-Maria Wicklein
    • 10
  • Ludwig Kappos
    • 4
  • Gilles Edan
    • 11
  • Mark S. Freedman
    • 12
  • Xavier Montalbán
    • 13
  • Hans-Peter Hartung
    • 14
  • Christoph Pohl
    • 10
    • 15
  • Rupert Sandbrink
    • 10
    • 14
  • Till Sprenger
    • 1
    • 4
  • Ernst-Wilhelm Radue
    • 1
  • Jens Wuerfel
    • 1
    • 15
  • Thomas E. Nichols
    • 3
  1. 1.Medical Image Analysis Center (MIAC AG)BaselSwitzerland
  2. 2.German Center for Neurodegenerative DiseasesBonnGermany
  3. 3.Department of StatisticsUniversity of WarwickCoventryUK
  4. 4.Department of NeurologyUniversity Hospital BaselBaselSwitzerland
  5. 5.VU University Medical CenterAmsterdamThe Netherlands
  6. 6.Institutes of Neurology and Healthcare EngineeringUCLLondonUK
  7. 7.Department of Psychiatry (1)University of BaselBaselSwitzerland
  8. 8.King’s College London, Department of Psychosis StudiesInstitute of PsychiatryLondonUK
  9. 9.Department of Psychiatry and Psychotherapy, Freiburg Brain ImagingUniversity Medical Center FreiburgFreiburgGermany
  10. 10.Bayer Pharma AGBerlinGermany
  11. 11.CHU-Hopital PontchaillouRennesFrance
  12. 12.University of Ottawa and Ottawa Hospital Research InstituteOttawaCanada
  13. 13.Hospital Universitari Vall d’HebronBarcelonaSpain
  14. 14.Department of NeurologyHeinrich-Heine UniversitätDüsseldorfGermany
  15. 15.Charité University Medicine BerlinBerlinGermany

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