Abstract #2537
Is automatic analysis of multicontrast MRI ready for clinical studies on plaque tissue composition?
Taku Yoneyama 1 , Jie Sun 1 , Daniel Hippe 1 , Dongxiang Xu 1 , William Kerwin 1 , Thomas Hatsukami 1 , and Chun Yuan 1
1
University of Washington, Seattle, WA,
United States
Automatic plaque segmentation algorithms have been
proposed to be helpful for large-scale and/or
multicenter studies. Yet few data are their performance
in real-world applications. In this study, by using a
prospective cohort study with baseline and follow-up
imaging, quantitative measurements on plaque tissue
composition including calcification and lipid-rich
necrotic core as analyzed by an automatic classifier
were compared to expert human review. Results showed
excellent correlation between MEPPS and manual review in
analyzing compositional volumes with images of a single
time point, and moderate to good correlation in
analyzing compositional changes with images of multiple
time points.
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