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Signal features of the atherosclerotic plaque at 3.0 Tesla versus 1.5 Tesla: Impact on automatic classification
Author(s) -
Kerwin William S.,
Liu Fei,
Yarnykh Vasily,
Underhill Hunter,
Oikawa Minako,
Yu Wei,
Hatsukami Thomas S.,
Yuan Chun
Publication year - 2008
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.21529
Subject(s) - calcification , segmentation , medicine , classifier (uml) , fibrous cap , computer science , pattern recognition (psychology) , nuclear medicine , biomedical engineering , artificial intelligence , radiology , pathology
Abstract 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. J. Magn. Reson. Imaging 2008;28:987–995. © 2008 Wiley‐Liss, Inc.