Open Access
27 October 2017 Optimization of dual-wavelength intravascular photoacoustic imaging of atherosclerotic plaques using Monte Carlo optical modeling
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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.
© 2017 Society of Photo-Optical Instrumentation Engineers (SPIE) 1083-3668/2017/$25.00 © 2017 SPIE
Nicholas Dana, Timothy Sowers, Andrei Karpiouk, Donald VanderLaan, and Stanislav Emelianov "Optimization of dual-wavelength intravascular photoacoustic imaging of atherosclerotic plaques using Monte Carlo optical modeling," Journal of Biomedical Optics 22(10), 106012 (27 October 2017). https://doi.org/10.1117/1.JBO.22.10.106012
Received: 21 July 2017; Accepted: 28 September 2017; Published: 27 October 2017
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Cited by 7 scholarly publications.
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KEYWORDS
Tissues

Image segmentation

Absorption

Data modeling

Monte Carlo methods

Tissue optics

Photoacoustic imaging

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