Signal features of the atherosclerotic plaque at 3.0 Tesla versus 1.5 Tesla: impact on automatic classification.

Purpose: To investigate the impact of different field strengths on determining plaque composition with an automatic classifier.Materials and Methods: We applied a previously developed automatic classifier-the morphology enhanced probabilistic plaque segmentation (MEPPS) algorithm-to images from 20 s...

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Published in:Journal of Magnetic Resonance Imaging Vol. 28; no. 4; pp. 987 - 996
Main Authors: Kerwin WS, Liu F, Yarnykh V, Underhill H, Oikawa M, Yu W, Hatsukami TS, Yuan C, Kerwin, William S, Liu, Fei, Yarnykh, Vasily, Underhill, Hunter, Oikawa, Minako, Yu, Wei, Hatsukami, Thomas S, Yuan, Chun
Format: research Journal Article
Published: Wiley-Blackwell Oct2008
Online Access:View this record in EBSCOhost
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      jtl: Journal of Magnetic Resonance Imaging
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      dt: Oct2008
      vid: 28
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      pub: Wiley-Blackwell
      place: Malden, Massachusetts
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        10.1002/jmri.21529
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        atl: Signal features of the atherosclerotic plaque at 3.0 Tesla versus 1.5 Tesla: impact on automatic classification.
      aug:
        au:
          Kerwin WS
          Liu F
          Yarnykh V
          Underhill H
          Oikawa M
          Yu W
          Hatsukami TS
          Yuan C
          Kerwin, William S
          Liu, Fei
          Yarnykh, Vasily
          Underhill, Hunter
          Oikawa, Minako
          Yu, Wei
          Hatsukami, Thomas S
          Yuan, Chun
        affil: Department of Radiology, University of Washington, Seattle, Washington 98109, USA
      sug:
        subj:
          Atherosclerosis Classification
          Carotid Stenosis Pathology
          Magnetic Resonance Imaging Methods
          Aged
          Algorithms
          Contrast Media
          Female
          Image Processing, Computer Assisted
          Male
          Signal Processing, Computer Assisted
          Human
          Aged: 65+ years
          Female
          Male
      ab: Purpose: To investigate the impact of different field strengths on determining plaque composition with an automatic classifier.Materials and 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).Conclusion: 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.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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