title: Characterizing iron deposition in multiple sclerosis lesions using susceptibility weighted imaging.
abstract: OBJECTIVE
  To investigate whether the variable forms of putative iron deposition seen with susceptibility weighted imaging (SWI) will lead to a set of multiple sclerosis (MS) lesion characteristics different than that seen in conventional MR imaging.
  
  
  METHODS
  Twenty-seven clinically definite MS patients underwent brain scans using magnetic resonance imaging including: pre- and postcontrast T1-weighted imaging, T2-weighted imaging, FLAIR, and SWI at 1.5 T, 3 T, and 4 T. MS lesions were identified separately in each imaging sequence. Lesions identified in SWI were reevaluated for their iron content using the SWI filtered phase images.
  
  
  RESULTS
  There were a variety of new lesion characteristics identified by SWI, and these were classified into six types. A total of 75 lesions were seen only with conventional imaging, 143 only with SWI, and 204 by both. From the iron quantification measurements, a moderate linear correlation between signal intensity and iron content (phase) was established.
  
  
  CONCLUSIONS
  The amount of iron deposition in the brain may serve as a surrogate biomarker for different MS lesion characteristics. SWI showed many lesions missed by conventional methods and six different lesion characteristics. SWI was particularly effective at recognizing the presence of iron in MS lesions and in the basal ganglia and pulvinar thalamus.
authors.affiliation: Department of Radiology, Wayne State University, Detroit, Michigan 48201, USA. nmrimaging@aol.com
authors.forename: E Mark
authors.initials: EM
authors.lastname: Haacke
authors.forename: Malek
authors.initials: M
authors.lastname: Makki
authors.forename: Yulin
authors.initials: Y
authors.lastname: Ge
authors.forename: Megha
authors.initials: M
authors.lastname: Maheshwari
authors.forename: Vivek
authors.initials: V
authors.lastname: Sehgal
authors.forename: Jiani
authors.initials: J
authors.lastname: Hu
authors.forename: Madeswaran
authors.initials: M
authors.lastname: Selvan
authors.forename: Zhen
authors.initials: Z
authors.lastname: Wu
authors.forename: Zahid
authors.initials: Z
authors.lastname: Latif
authors.forename: Yang
authors.initials: Y
authors.lastname: Xuan
authors.forename: Omar
authors.initials: O
authors.lastname: Khan
authors.forename: James
authors.initials: J
authors.lastname: Garbern
authors.forename: Robert I
authors.initials: RI
authors.lastname: Grossman
mesh_terms: D000328:Adult; D000368:Aged; D015415:Biomarkers / Q000378:metabolism; D001921:Brain / Q000378:metabolism* / Q000473:pathology*; D001931:Brain Mapping / Q000379:methods; D003287:Contrast Media; D017352:Echo-Planar Imaging / Q000379:methods; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007091:Image Processing, Computer-Assisted / Q000379:methods; D021621:Imaging, Three-Dimensional / Q000379:methods; D007501:Iron / Q000378:metabolism*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D009103:Multiple Sclerosis / Q000175:diagnosis / Q000378:metabolism* / Q000473:pathology*; D055815:Young Adult
chemical_list: D015415:Biomarkers; D003287:Contrast Media; D007501:Iron