Simulated imaging of atherosclerotic & radiofrequency ablation lesions using phase subtraction

John R. Jameson, David R. Holmes, Benjamin R. Buhrow, Erik S. Daniel, Barry K. Gilbert, Clifton R. Haider

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Cardiovascular diseases are the main cause of death worldwide. Atherosclerosis and atrial fibrillation are structural and electrical pathophysiology, respectively, that can lead to acute events such as stroke or myocardial infarction. We used particle-based Monte Carlo methods to simulate X-ray phase imaging of atherosclerotic plaque types IV-VIII in the aorta, iliac, and coronary arteries. We also assessed scar lesion development in radiofrequency catheter ablation treatment of atrial fibrillation by simulating lesions 2, 5, 10, 30, and 60 days post-procedure. For both applications, we found high signal-to-noise and contrast-to-noise ratios in all lesions. These results suggest that X-ray phase imaging is a viable technique for non-invasive quantitative cardiovascular lesion characterization.

Original languageEnglish (US)
Title of host publication2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5630-5633
Number of pages4
ISBN (Electronic)9781424492718
DOIs
StatePublished - Nov 4 2015
Event37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 - Milan, Italy
Duration: Aug 25 2015Aug 29 2015

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume2015-November
ISSN (Print)1557-170X

Other

Other37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
Country/TerritoryItaly
CityMilan
Period8/25/158/29/15

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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