Master of Science
McIntyre, Christopher W.
Lawson Health Research Institute
Introduction. Fractional flow reserve (FFR) is presently an invasive coronary clinical index. Non-invasive CT imaging combined with computational coronary flow modelling may reduce the patient’s burden of undergoing invasive testing.
Research statement. The ability to obtain information of the hemodynamic significance of detected lesions would streamline decision making in escalation to invasive angiography.
Methods. A reduced order (lumped parameter) model of the coronary vasculature was further developed. The model was used in the assessment of the roles of structure and function on the FFR. Sophisticated methods were used to elicit numerical
solutions. Further, CT imaging (n = 10) provided multiple porcine geometries based upon algorithms encoded within an existing scientific platform.
Results. It was found that the length of large vessel stenosis and presence of microvascular disease are primary regulators of FFR. Further, the CT data provided a basis to investigate relationships between coronary geometry (structure) and blood flow (function) attributes.
Discussion. The presented model, upon personalization, may compliment and streamline ongoing imaging efforts by guiding FFR assessment. It is likely to assist in preliminary data generation for future projects. The computational geometries will contribute to an open source service that will be made available to our University’s researchers.
Summary for Lay Audience
A buildup of plaque in the coronary arteries that supply blood to the heart’s muscle is often fatal. To assess the severity of these buildups on the heart’s blood supply, physicians measure the pressure along the artery to estimate severity by an index known as fractional flow reserve. This index is obtained by inserting a pressure wire through the patient’s artery of interest and measuring the pressure before and after the plaque build-up. Although this is an invasive, expensive, and high-risk procedure, it has been shown to be very useful in assisting clinical decisions regarding whether the patient requires surgery. To avoid the invasive nature of this procedure, this thesis explores how one may use mathematical modelling of coronary blood flow to generate a virtual subject specific fractional flow reserve. One mode is the utilizing the routinely obtained using Computerized Tomography (CT) images of the coronary arteries. Using images from ten patients, the arteries and geometric properties were extracted to create both reduced order models (0D and 1D) as well as 3D representations. Using the reduced order models, this thesis explored various disease conditions and factors that may affect fractional flow reserve. Such conditions include implementing varying severities of stenosis as well as inducing microvascular disease within the patient geometries to investigate the combined effects. Our findings suggest that a spectrum of pathological conditions, several of which are outside the heart, should be accounted for in diagnosing the severity of coronary plaques.
Joseph, Jermiah, "Multi-scale computational modeling of coronary blood flow: application to fractional flow reserve." (2022). Electronic Thesis and Dissertation Repository. 8918.