THU0335 Support vector machines classification of texture parameters of white matter lesions in childhood-onset systemic lupus erythematosus. Possible mechanism to distinguish between demyelination and ischemia. (23rd January 2014)

• Record Type: Journal Article
• Authors: Lapa, A.T.; Bento, M.P.; Rittner, L.; Ruocco, H.H.; Castellano, G.; Damasceno, B.P.; Costallat, L.T.L.; Lotufo, R.; Cendes, F.; Appenzeller, S.
• Is Part Of: Annals of the rheumatic diseases. Volume 71(2012)Supplement 3
• Page Start: 269
• Page End: 269
• Publication Date: 2014-01-23
• Subjects: Rheumatism -- Periodicals; 616.723005
• DOI: 10.1136/annrheumdis-2012-eular.2300
• Languages: English
• ISSNs: 0003-4967

Abstract

Abstract : Background: Texture analysis (TA) is a branch of image processing which seeks to reduce image information by extracting texture descriptors from the image. White matter hyperintensities (WMH) are frequently observed in childhood-onset systemic lupus erythematosus (cSLE); however the etiology is still unknown. Ischemic and demyelination have been proposed as possible etiologies. Support vector machines (SVM) are a group of supervised learning methods that can be applied to classification or regression Objectives: To determine etiology of WMH in cSLE patients using texture analysis of magnetic resonance (MR) parameters basedon neural network Methods: TA was applied to axial FLAIR magnetic resonance images (MRI) in 43 patients with cSLE (mean age 17.25 years (SD ± 3.57), 30 patients with multiple sclerosis (MS), 30 patients with stroke and 30 normal age and sex-matched controls. The TA approach used was based on the Gray Level Co-occurrence Matrices (GLCM). The WMH were manually segmented for each subject, classified in periventricular, subcortical, deep white matter and cortical WMH and 256 texture parameters were computed for each lesion. A SVM classifier previously developed and validated (accuracy 93%) was used to classify WMH in patients with cSLE. Nature of the classified WMH, demographic, clinical and laboratory features were included in a regression model to determine which variables could support the possible nature of WMH in clinical practice Results: In cSLE, of the 125 of periventricular lesions, 59% were classified as ischemic and 41% as demyelinating. Of the 738 subcortical lesions 63% were classified as ischemic and 37% as demyelinating. Of the 64 cortical lesions, 61% were classified as ischemic and 39% as demyelinating. Of the deep white matter WMH, 72% were classified as ischemic and 28% as demyelinating in nature. In controls all lesions were classified as ischemic. Positive antiphospholipid antibodies (aPL) (OR=3.2; 95%CI 1.2-7.3) and higher total corticosteroid dose (OR=2.1; 95%CI 1.2-3.7) were variables associated with stroke, whereas cutaneous vasculitis (OR=4.2; 95%CI 2.1-7.2), anti-SM antibodies (OR=2.9; 95%CI 1.3-8.7) and disease activity (OR=3.7; 95%CI 1.3-7.8) were associated with demyelination in all cerebral regions. Conclusions: In cSLE, the majority of WMH were classified as ischemic in nature; however aproximately 30% of the lesions were demyelinating. Positive aPL and higher total corticosteroid dose were variables associated with stroke, whereas cutaneous vasculitis, anti-SM antibodies and disease activity were associated with demyelination in all cerebral regions.SVM of TA is a useful method to help to determine etiology of WMH in cSLE. Disclosure of Interest: A. Lapa Grant/Research support from: FAPESP 2010/13639-1, M. Bento: None Declared, L. Rittner: None Declared, H. Ruocco: None Declared, G. Castellano: None Declared, B. Damasceno: None Declared, L. Costallat: None Declared, R. Lotufo: None Declared, F. Cendes: None Declared, S. Appenzeller Grant/Research support from: FAPESP 2008/02917-0; Conselho Nacional Pesquisa Desenvolvimento-Brasil CNPq (300447/2009-4)