title: Signal features of the atherosclerotic plaque at 3.0 Tesla versus 1.5 Tesla: impact on automatic classification.
abstract: OBJECTIVE
  To investigate the impact of different field strengths on determining plaque composition with an automatic classifier.
  
  
  METHODS
  We applied a previously developed automatic classifier-the morphology enhanced probabilistic plaque segmentation (MEPPS) algorithm-to images from 20 subjects scanned at both 1.5 Tesla (T) and 3T. Average areas per slice of lipid-rich core, intraplaque hemorrhage, calcification, and fibrous tissue were recorded for each subject and field strength.
  
  
  RESULTS
  All measurements showed close agreement at the two field strengths, with correlation coefficients of 0.91, 0.93, 0.95, and 0.93, respectively. None of these measurements showed a statistically significant difference between field strengths in the average area per slice by a paired t-test, although calcification tended to be measured larger at 3T (P = 0.09).
  
  
  CONCLUSIONS
  Automated classification results using an identical algorithm at 1.5T and 3T produced highly similar results, suggesting that with this acquisition protocol, 3T signal characteristics of the atherosclerotic plaque are sufficiently similar to 1.5T characteristics for MEPPS to provide equivalent performance.
authors.affiliation: Department of Radiology, University of Washington, Seattle, Washington 98109, USA. bkerwin@u.washington.edu
authors.forename: William S
authors.initials: WS
authors.lastname: Kerwin
authors.forename: Fei
authors.initials: F
authors.lastname: Liu
authors.forename: Vasily
authors.initials: V
authors.lastname: Yarnykh
authors.forename: Hunter
authors.initials: H
authors.lastname: Underhill
authors.forename: Minako
authors.initials: M
authors.lastname: Oikawa
authors.forename: Wei
authors.initials: W
authors.lastname: Yu
authors.forename: Thomas S
authors.initials: TS
authors.lastname: Hatsukami
authors.forename: Chun
authors.initials: C
authors.lastname: Yuan
mesh_terms: D000368:Aged; D000465:Algorithms; D050197:Atherosclerosis / Q000145:classification*; D016893:Carotid Stenosis / Q000473:pathology*; D003287:Contrast Media; D005260:Female; D019786:Gadolinium DTPA; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D012815:Signal Processing, Computer-Assisted
chemical_list: D003287:Contrast Media; C064925:gadodiamide; D019786:Gadolinium DTPA