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Journal of Biomedical Optics

Optimization of dual-wavelength intravascular photoacoustic imaging of atherosclerotic plaques using Monte Carlo optical modeling
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Paper Abstract

Coronary heart disease (the presence of coronary atherosclerotic plaques) is a significant health problem in the industrialized world. A clinical method to accurately visualize and characterize atherosclerotic plaques is needed. Intravascular photoacoustic (IVPA) imaging is being developed to fill this role, but questions remain regarding optimal imaging wavelengths. We utilized a Monte Carlo optical model to simulate IVPA excitation in coronary tissues, identifying optimal wavelengths for plaque characterization. Near-infrared wavelengths ( 1800    nm ) were simulated, and single- and dual-wavelength data were analyzed for accuracy of plaque characterization. Results indicate light penetration is best in the range of 1050 to 1370 nm, where 5% residual fluence can be achieved at clinically relevant depths of 2    mm in arteries. Across the arterial wall, fluence may vary by over 10-fold, confounding plaque characterization. For single-wavelength results, plaque segmentation accuracy peaked at 1210 and 1720 nm, though correlation was poor ( < 0.13 ). Dual-wavelength analysis proved promising, with 1210 nm as the most successful primary wavelength ( 1.0 ). Results suggest that, without flushing the luminal blood, a primary and secondary wavelength near 1210 and 1350 nm, respectively, may offer the best implementation of dual-wavelength IVPA imaging. These findings could guide the development of a cost-effective clinical system by highlighting optimal wavelengths and improving plaque characterization.

Paper Details

Date Published: 27 October 2017
PDF: 12 pages
J. Biomed. Opt. 22(10) 106012 doi: 10.1117/1.JBO.22.10.106012
Published in: Journal of Biomedical Optics Volume 22, Issue 10
Show Author Affiliations
Nicholas Dana, The Univ. of Texas at Austin (United States)
Timothy Sowers, Georgia Institute of Technology (United States)
Andrei Karpiouk, Georgia Institute of Technology (United States)
Donald VanderLaan, Georgia Institute of Technology (United States)
Stanislav Emelianov, Georgia Institute of Technology (United States)
Emory Univ. School of Medicine (United States)

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