Brain white matter lesions classification in multiple sclerosis subjects for the prognosis of future disability

Christos P. Loizou, Efthyvoulos C. Kyriacou, Ioannis Seimenis, Marios Pantziaris, Christodoulos Christodoulou, Constantinos S. Pattichis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

This study investigates the application of classification methods for the prognosis of future disability on MRI-detectable brain white matter lesions in subjects diagnosed with clinical isolated syndrome (CIS) of multiple sclerosis (MS). For this purpose, MS lesions and normal appearing white matter (NAWM) from 30 symptomatic untreated MS subjects, as well as normal white matter (NWM) from 20 healthy volunteers, were manually segmented, by an experienced MS neurologist, on transverse T2-weighted images obtained from serial brain MR imaging scans. A support vector machines classifier (SVM) based on texture features was developed to classify MRI lesions detected at the onset of the disease into two classes, those belonging to patients with EDSS≤2 and EDSS>2 (expanded disability status scale (EDSS) that was measured at 24 months after the onset of the disease). The highest percentage of correct classification's score achieved was 77%. The findings of this study provide evidence that texture features of MRI-detectable brain white matter lesions may have an additional potential role in the clinical evaluation of MRI images in MS. However, a larger scale study is needed to establish the application of texture analysis in clinical practice.

Original languageEnglish
Title of host publicationArtificial Intelligence Applications and Innovations - 12th INNS EANN-SIG International Conference, EANN 2011 and 7th IFIP WG 12.5 International Conference, AIAI 2011, Proceedings
Pages400-409
Number of pages10
Volume364 AICT
EditionPART 2
DOIs
Publication statusPublished - 2011
Event7th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2011 - Corfu, Greece
Duration: 15 Sep 201118 Sep 2011

Publication series

NameIFIP Advances in Information and Communication Technology
NumberPART 2
Volume364 AICT
ISSN (Print)1868-4238

Other

Other7th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2011
CountryGreece
CityCorfu
Period15/09/1118/09/11

Keywords

  • MRI
  • multiple sclerosis
  • texture classification

Fingerprint Dive into the research topics of 'Brain white matter lesions classification in multiple sclerosis subjects for the prognosis of future disability'. Together they form a unique fingerprint.

  • Cite this

    Loizou, C. P., Kyriacou, E. C., Seimenis, I., Pantziaris, M., Christodoulou, C., & Pattichis, C. S. (2011). Brain white matter lesions classification in multiple sclerosis subjects for the prognosis of future disability. In Artificial Intelligence Applications and Innovations - 12th INNS EANN-SIG International Conference, EANN 2011 and 7th IFIP WG 12.5 International Conference, AIAI 2011, Proceedings (PART 2 ed., Vol. 364 AICT, pp. 400-409). (IFIP Advances in Information and Communication Technology; Vol. 364 AICT, No. PART 2). https://doi.org/10.1007/978-3-642-23960-1_47