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Method for parametric imaging of attenuation by intravascular optical coherence tomography.
Zheng, Sun; Fei, Yang; Jian, Sun.
Afiliação
  • Zheng S; Department of Electronic and Communication Engineering, North China Electric Power University, Baoding 071003, Hebei, China.
  • Fei Y; Hebei Key Laboratory of Power Internet of Things Technology, North China Electric Power University, Baoding 071003, Hebei, China.
  • Jian S; Department of Electronic and Communication Engineering, North China Electric Power University, Baoding 071003, Hebei, China.
Biomed Opt Express ; 12(4): 1882-1904, 2021 Apr 01.
Article em En | MEDLINE | ID: mdl-33996205
ABSTRACT
Catheter-based intravascular optical coherence tomography (IVOCT) is a powerful imaging modality for visualization of atherosclerosis with high resolution. Quantitative characterization of various tissue types by attenuation coefficient (AC) extraction has been proven to be a potentially significant application of OCT attenuation imaging. However, existing methods for AC extraction from OCT suffer from the challenge of variability in complex tissue types in IVOCT pullback data such as healthy vessel wall, mixed atherosclerotic plaques, plaques with a single component and stent struts, etc. This challenge leads to the ineffectiveness in the tissue differentiation by AC representation based on single scattering model of OCT signal. In this paper, we propose a novel method based on multiple scattering model for parametric imaging of optical attenuation by AC retrieval from IVOCT images conventionally acquired during cardiac catheterization. The OCT signal characterized by the AC is physically modeled by Monte Carlo simulation. Then, the pixel-wise AC retrieval is achieved by iteratively minimizing an error function regarding the modeled and measured backscattered signal. This method provides a general scheme for AC extraction from IVOCT without the premise of complete attenuation of the incident light through the imaging depths. Results of computer-simulated and clinical images demonstrate that the method can avoid overestimation at the end of the depth profile in comparison with the approaches based on the depth-resolved (DR) model. The energy error depth and structural similarity are improved by about 30% and 10% respectively compared with DR. It provides a useful way to differentiate and characterize arterial tissue types in IVOCT images.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Biomed Opt Express Ano de publicação: 2021 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Biomed Opt Express Ano de publicação: 2021 Tipo de documento: Article País de afiliação: China