title: Progressive iron accumulation across multiple sclerosis phenotypes revealed by sparse classification of deep gray matter.
abstract: To create an automated framework for localized analysis of deep gray matter (DGM) iron accumulation and demyelination using sparse classification by combining quantitative susceptibility (QS) and transverse relaxation rate (R2*) maps, for evaluation of DGM in multiple sclerosis (MS) phenotypes relative to healthy controls.
  
  
  
  R2*/QS maps were computed using a 4.7T 10-echo gradient echo acquisition from 16 clinically isolated syndrome (CIS), 41 relapsing-remitting (RR), 40 secondary-progressive (SP), 13 primary-progressive (PP) MS patients, and 75 controls. Sparse classification for R2*/QS maps of segmented caudate nucleus (CN), putamen (PU), thalamus (TH), and globus pallidus (GP) structures produced localized maps of iron/myelin in MS patients relative to controls. Paired t-tests, with age as a covariate, were used to test for statistical significance (P ≤ 0.05).
  
  
  
  In addition to DGM structures found significantly different in patients compared to controls using whole region analysis, singular sparse analysis found significant results in RRMS PU R2* (P = 0.03), TH R2* (P = 0.04), CN QS (P = 0.04); in SPMS CN R2* (P = 0.04), GP R2* (P = 0.05); and in PPMS CN R2* (P = 0.04), TH QS (P = 0.04). All sparse regions were found to conform to an iron accumulation pattern of changes in R2*/QS, while none conformed to demyelination. Intersection of sparse R2*/QS regions also resulted in RRMS CN R2* becoming significant, while RRMS R2* TH and PPMS QS TH becoming insignificant. Common iron-associated volumes in MS patients and their effect size progressively increased with advanced phenotypes.
  
  
  
  A localized technique for identifying sparse regions indicative of iron or myelin in the DGM was developed. Progressive iron accumulation with advanced MS phenotypes was demonstrated, as indicated by iron-associated sparsity and effect size.
  
  
  
  1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1464-1473.
authors.affiliation: Department of Biomedical Engineering, University of Alberta, Edmonton, AB, Canada.
authors.forename: Ahmed M
authors.initials: AM
authors.lastname: Elkady
authors.affiliation: Department of Biomedical Engineering, University of Alberta, Edmonton, AB, Canada.
authors.forename: Dana
authors.initials: D
authors.lastname: Cobzas
authors.affiliation: Department of Biomedical Engineering, University of Alberta, Edmonton, AB, Canada.
authors.forename: Hongfu
authors.initials: H
authors.lastname: Sun
authors.affiliation: Division of Neurology, University of Alberta, Edmonton, AB, Canada.
authors.forename: Gregg
authors.initials: G
authors.lastname: Blevins
authors.affiliation: Department of Biomedical Engineering, University of Alberta, Edmonton, AB, Canada.
authors.forename: Alan H
authors.initials: AH
authors.lastname: Wilman
mesh_terms: D000328:Adult; D001921:Brain / Q000000981:diagnostic imaging; D001931:Brain Mapping; D016022:Case-Control Studies; D001330:Electronic Data Processing; D005260:Female; D066128:Gray Matter / Q000000981:diagnostic imaging* / Q000503:physiopathology*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D007091:Image Processing, Computer-Assisted; D007501:Iron / Q000737:chemistry*; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D009103:Multiple Sclerosis / Q000000981:diagnostic imaging* / Q000503:physiopathology*; D010641:Phenotype
chemical_list: D007501:Iron
keywords: R2*; brain iron; deep gray matter; multiple sclerosis; quantitative susceptibility mapping; sparse classification