As coronary heart disease (CHD) is the greatest cause of death in developed countries (nearly 1 in 6 deaths for the U.S. in 2007), a greater need to understand its etiology has driven the work involving computer-based research. Within the realm of CHD, the greatest number of mortalities is associated with atherosclerosis, a thickening and hardening of the arterial wall, which under the most severe circumstances results in restricted blood flow to the heart and ultimately heart cell death. While systemic risk factors exist which predispose patients to atherosclerosis, such as diabetes mellitus, hyperlipidemia, and smoking, the disease has been shown to be of localized origin, mainly initiating in the inner regions of curved vessels or at bifurcations. Of these regions, coronary arteries are one of the most atheroprone due to their small caliber and large degree of curvature and tortuosity. The most popular method for treatment of occlusive arterial diseases in the 21st century is placement of a metal scaffold, known as a stent, into the stenosed region through elective percutaneous coronary intervention (PCI), thus re-establishing flow and nourishment to the heart tissue. While PCI is effective in prompt relief of ischemic symptoms, the placement of a stent still possesses several drawbacks, including a neointimal hyperplasia (NIH) in the newly stented region or stent thrombosis, leading to target-lesion revascularization for significant in-stent restenosis (ISR). Binary angiographic ISR is commonly defined as a loss greater than 50% of the initial arterial diameter gained from the stenting procedure. Numerical models are an elegant means to study the interaction of biological systems with the implanted device through evaluation of the biomechanical influences. In particular, computational fluid dynamics (CFD) provides fluid domain and mass transport solutions which may not be attainable in the clinical setting. While the introduction of hypoxia as an agent of disease initiation is not a new theory, recent indications of the correlation between ISR and hypoxia have been elucidated through in vivo, and in silico studies. In fact, the inner curvature regions of the stented model within the study by Coppola and Caro (2009) were subject to a lower oxygen flux; these regions correspond to the geometry-modified distribution of WSS. The straightened effect of the geometry due to the presence of the stent has been indicated as a means for CFD to identify the risk zones capable of forming ISR. However, there is a lack of studies which show paired histology to the computational results. The aim of this work is to utilize a methodology that combines data from in vivo experiments, 3D imaging techniques and the construction of a wall-free and fluid-wall model domain for CFD and oxygen mass transport analysis. This is carried out through exploration of the use of translational pathology (i.e. micro-Computed Tomography (micro-CT) and histology on the consecutive model) to study the influence of geometric changes, such as curvature, on hemodynamics and oxygen mass transport within the real (porcine) stented vessel and compare the results with available clinical measurements of the lesion presence versus numerically presented immediate post-implant conditions.
A computational fluid dynamic and oxygen mass transport study of in-stent restenosis and coronary curvature
KELLER, BRANDIS;MIGLIAVACCA, FRANCESCO;DUBINI, GABRIELE ANGELO
2013-01-01
Abstract
As coronary heart disease (CHD) is the greatest cause of death in developed countries (nearly 1 in 6 deaths for the U.S. in 2007), a greater need to understand its etiology has driven the work involving computer-based research. Within the realm of CHD, the greatest number of mortalities is associated with atherosclerosis, a thickening and hardening of the arterial wall, which under the most severe circumstances results in restricted blood flow to the heart and ultimately heart cell death. While systemic risk factors exist which predispose patients to atherosclerosis, such as diabetes mellitus, hyperlipidemia, and smoking, the disease has been shown to be of localized origin, mainly initiating in the inner regions of curved vessels or at bifurcations. Of these regions, coronary arteries are one of the most atheroprone due to their small caliber and large degree of curvature and tortuosity. The most popular method for treatment of occlusive arterial diseases in the 21st century is placement of a metal scaffold, known as a stent, into the stenosed region through elective percutaneous coronary intervention (PCI), thus re-establishing flow and nourishment to the heart tissue. While PCI is effective in prompt relief of ischemic symptoms, the placement of a stent still possesses several drawbacks, including a neointimal hyperplasia (NIH) in the newly stented region or stent thrombosis, leading to target-lesion revascularization for significant in-stent restenosis (ISR). Binary angiographic ISR is commonly defined as a loss greater than 50% of the initial arterial diameter gained from the stenting procedure. Numerical models are an elegant means to study the interaction of biological systems with the implanted device through evaluation of the biomechanical influences. In particular, computational fluid dynamics (CFD) provides fluid domain and mass transport solutions which may not be attainable in the clinical setting. While the introduction of hypoxia as an agent of disease initiation is not a new theory, recent indications of the correlation between ISR and hypoxia have been elucidated through in vivo, and in silico studies. In fact, the inner curvature regions of the stented model within the study by Coppola and Caro (2009) were subject to a lower oxygen flux; these regions correspond to the geometry-modified distribution of WSS. The straightened effect of the geometry due to the presence of the stent has been indicated as a means for CFD to identify the risk zones capable of forming ISR. However, there is a lack of studies which show paired histology to the computational results. The aim of this work is to utilize a methodology that combines data from in vivo experiments, 3D imaging techniques and the construction of a wall-free and fluid-wall model domain for CFD and oxygen mass transport analysis. This is carried out through exploration of the use of translational pathology (i.e. micro-Computed Tomography (micro-CT) and histology on the consecutive model) to study the influence of geometric changes, such as curvature, on hemodynamics and oxygen mass transport within the real (porcine) stented vessel and compare the results with available clinical measurements of the lesion presence versus numerically presented immediate post-implant conditions.File | Dimensione | Formato | |
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