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From Histology and Imaging Data to Models for In-Stent Restenosis. Int J Artif Organs 2014; 37:786-800. [DOI: 10.5301/ijao.5000336] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/29/2014] [Indexed: 11/20/2022]
Abstract
The implantation of stents has been used to treat coronary artery stenosis for several decades. Although stenting is successful in restoring the vessel lumen and is a minimally invasive approach, the long-term outcomes are often compromised by in-stent restenosis (ISR). Animal models have provided insights into the pathophysiology of ISR and are widely used to evaluate candidate drug inhibitors of ISR. Such biological models allow the response of the vessel to stent implantation to be studied without the variation of lesion characteristics encountered in patient studies. This paper describes the development of complementary in silico models employed to improve the understanding of the biological response to stenting using a porcine model of restenosis. This includes experimental quantification using microCT imaging and histology and the use of this data to establish numerical models of restenosis. Comparison of in silico results with histology is used to examine the relationship between spatial localization of fluid and solid mechanics stimuli immediately post-stenting. Multi-scale simulation methods are employed to study the evolution of neointimal growth over time and the variation in the extent of neointimal hyperplasia within the stented region. Interpretation of model results through direct comparison with the biological response contributes to more detailed understanding of the pathophysiology of ISR, and suggests the focus for follow-up studies. In conclusion we outline the challenges which remain to both complete our understanding of the mechanisms responsible for restenosis and translate these models to applications in stent design and treatment planning at both population-based and patient-specific levels.
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Sun C, Nolte F, Cheng KHY, Vuong B, Lee KKC, Standish BA, Courtney B, Marotta TR, Mariampillai A, Yang VXD. In vivo feasibility of endovascular Doppler optical coherence tomography. BIOMEDICAL OPTICS EXPRESS 2012; 3:2600-10. [PMID: 23082299 PMCID: PMC3470007 DOI: 10.1364/boe.3.002600] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/21/2012] [Revised: 09/12/2012] [Accepted: 09/15/2012] [Indexed: 05/20/2023]
Abstract
Feasibility of detecting intravascular flow using a catheter based endovascular optical coherence tomography (OCT) system is demonstrated in a porcine carotid model in vivo. The effects of A-line density, radial distance, signal-to-noise ratio, non-uniform rotational distortion (NURD), phase stability of the swept wavelength laser and interferometer system on Doppler shift detection limit were investigated in stationary and flow phantoms. Techniques for NURD induced phase shift artifact removal were developed by tracking the catheter sheath. Detection of high flow velocity (~51 cm/s) present in the porcine carotid artery was obtained by phase unwrapping techniques and compared to numerical simulation, taking into consideration flow profile distortion by the eccentrically positioned imaging catheter. Using diluted blood in saline mixture as clearing agent, simultaneous Doppler OCT imaging of intravascular flow and structural OCT imaging of the carotid artery wall was feasible. To our knowledge, this is the first in vivo demonstration of Doppler imaging and absolute measurement of intravascular flow using a rotating fiber catheter in carotid artery.
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Affiliation(s)
- Cuiru Sun
- Biophotonics and Bioengineering Laboratory, Dept.
Electrical and Computer Engineering, Ryerson University, 350 Victoria St.
Toronto, ON, M5B2K3 Canada
- These authors contributed equally to this work
| | - Felix Nolte
- Biophotonics and Bioengineering Laboratory, Dept.
Electrical and Computer Engineering, Ryerson University, 350 Victoria St.
Toronto, ON, M5B2K3 Canada
- Faculty of Electrical Engineering and Information
Technology, University of Applied Sciences, Karlsruhe, Moltkestraße 30,
76133 Karlsruhe, Germany
- These authors contributed equally to this work
| | - Kyle H. Y. Cheng
- Biophotonics and Bioengineering Laboratory, Dept.
Electrical and Computer Engineering, Ryerson University, 350 Victoria St.
Toronto, ON, M5B2K3 Canada
- Dept. Electrical and Computer Engineering, University
of Toronto, 27 King's College Circle, Toronto, Ontario, M5S 1A1,
Canada
| | - Barry Vuong
- Biophotonics and Bioengineering Laboratory, Dept.
Electrical and Computer Engineering, Ryerson University, 350 Victoria St.
Toronto, ON, M5B2K3 Canada
| | - Kenneth K. C. Lee
- Biophotonics and Bioengineering Laboratory, Dept.
Electrical and Computer Engineering, Ryerson University, 350 Victoria St.
Toronto, ON, M5B2K3 Canada
- Dept. Electrical and Computer Engineering, University
of Toronto, 27 King's College Circle, Toronto, Ontario, M5S 1A1,
Canada
| | - Beau A. Standish
- Biophotonics and Bioengineering Laboratory, Dept.
Electrical and Computer Engineering, Ryerson University, 350 Victoria St.
Toronto, ON, M5B2K3 Canada
- Faculty of Electrical Engineering and Information
Technology, University of Applied Sciences, Karlsruhe, Moltkestraße 30,
76133 Karlsruhe, Germany
| | - Brian Courtney
- Colibri Technologies Inc., 3080 Yonge Street,
Toronto, ON, M4N 3N1, Canada
| | - Thomas R. Marotta
- Dept. of Medical Imaging, St. Michael’s
Hospital, 30 Bond Street, Toronto, ON, M5B 1W8, Canada
| | - Adrian Mariampillai
- Biophotonics and Bioengineering Laboratory, Dept.
Electrical and Computer Engineering, Ryerson University, 350 Victoria St.
Toronto, ON, M5B2K3 Canada
| | - Victor X. D. Yang
- Biophotonics and Bioengineering Laboratory, Dept.
Electrical and Computer Engineering, Ryerson University, 350 Victoria St.
Toronto, ON, M5B2K3 Canada
- Dept. Electrical and Computer Engineering, University
of Toronto, 27 King's College Circle, Toronto, Ontario, M5S 1A1,
Canada
- Dept. of Medical Imaging, St. Michael’s
Hospital, 30 Bond Street, Toronto, ON, M5B 1W8, Canada
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