Article ID Journal Published Year Pages File Type
6920517 Computers in Biology and Medicine 2018 13 Pages PDF
Abstract
Intravascular photoacoustic (IVPA) imaging can discriminate between normal arterial tissues and atheromatous plaques in images, particularly images of lipid-rich plaques with high spatial resolution and optical contrast. However, conventional IVPA only recovers the deposited optical energy that is the product of the tissue optical absorption coefficient and local optical fluence. Herein, a one-step model-based method for single-wavelength IVPA imaging system is proposed. The proposed method directly reconstructs the optical absorption coefficient from the boundary measurement of acoustic pressure. To obtain the theoretical optical deposition, light illumination and transport in multilayered vessel-wall tissues are numerically modelled with the diffusion approximation to radiative transfer equation. Then, the generation and propagation of photoacoustic (PA) waves in acoustically homogeneous vessel-wall tissues are modelled by using the PA wave equation. The theoretical acoustic pressure series is thus obtained. Finally, the optical absorption coefficient is iteratively updated from an initial guess by minimising a nonlinear least-square error function to quantify the difference between the measured and theoretical acoustic pressure with split Bregman optimisation based on total-variation regularisation. The numerical simulation experiments demonstrated that optical absorption coefficient maps can be directly recovered on the basis of the acoustic boundary measurement of vascular cross-sections. Compared with the optical deposition map, the optical absorption coefficient map can provide more reliable qualitative and quantitative information on the morphology and optical properties of the imaged arteries. The proposed method enables the accurate and reliable evaluation of atheromatous lesions and the early identification of vulnerable plaques.
Related Topics
Physical Sciences and Engineering Computer Science Computer Science Applications
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