Three-dimensional quantitative coronary angiography and the registration with intravascular ultrasound and optical coherence tomography

This thesis proposes several new algorithms including X-ray angiographic image enhancement, three-dimensional (3D) angiographic reconstruction, angiographic overlap prediction, and the co-registration of X-ray angiography with intracoronary imaging devices, such as intravascular ultrasound (IVUS) and optical coherence tomography (OCT). The algorithms were integrated into prototype software packages that were validated at a number of clinical centers. The feasibility of using such software packages in typical clinical population was verified, while the advantages and accuracy of the proposed algorithms were demonstrated by phantoms and in-vivo clinical studies. In addition, based on the proposed approaches and the conducted studies, this thesis reports a number of findings including the impact of acquisition angle difference on 3D quantitative coronary angiography (QCA), the clinical characteristics of bifurcation optimal viewing angles and bifurcation angles, and the discrepancy of lumen dimensions as assessed by 3D QCA and by IVUS or OCT.UBL - phd migration 201

3D reconstruction of cerebral blood flow and vessel morphology from x-ray rotational angiography

Three-dimensional (3D) information on blood flow and vessel morphology is important when assessing cerebrovascular disease and when monitoring interventions. Rotational angiography is nowadays routinely used to determine the geometry of the cerebral vasculature. To this end, contrast agent is injected into one of the supplying arteries and the x-ray system rotates around the head of the patient while it acquires a sequence of x-ray images. Besides information on the 3D geometry, this sequence also contains information on blood flow, as it is possible to observe how the contrast agent is transported by the blood. The main goal of this thesis is to exploit this information for the quantitative analysis of blood flow. I propose a model-based method, called flow map fitting, which determines the blood flow waveform and the mean volumetric flow rate in the large cerebral arteries. The method uses a model of contrast agent transport to determine the flow parameters from the spatio-temporal progression of the contrast agent concentration, represented by a flow map. Furthermore, it overcomes artefacts due to the rotation (overlapping vessels and foreshortened vessels at some projection angles) of the c-arm using a reliability map. For the flow quantification, small changes to the clinical protocol of rotational angiography are desirable. These, however, hamper the standard 3D reconstruction. Therefore, a new method for the 3D reconstruction of the vessel morphology which is tailored to this application is also presented. To the best of my knowledge, I have presented the first quantitative results for blood flow quantification from rotational angiography. Additionally, the model-based approach overcomes several problems which are known from flow quantification methods for planar angiography. The method was mainly validated on images from different phantom experiments. In most cases, the relative error was between 5% and 10% for the volumetric mean flow rate and between 10% and 15% for the blood flow waveform. Additionally, the applicability of the flow model was shown on clinical images from planar angiographic acquisitions. From this, I conclude that the method has the potential to give quantitative estimates of blood flow parameters during cerebrovascular interventions

Effective Computational Coronary Haemodynamics for Clinical Application

Coronary artery disease (CAD) is one of the most common causes of death in the world. Diagnosis is based on imaging of the artery, either by CT or conventional angiography. Conventional angiography is an invasive technique which involves the introduction of a system of guide-wires, catheters and radiopaque contrast agent into the patient’s coronary arteries. Fractional Flow Reserve (FFR) is widely considered to be the gold-standard assessment of the physiological significance of CAD. FFR is measured invasively by the passage of a pressure wire through the diseased artery. It is hypothesised that a computational model can be employed to characterise the haemodynamics of blood flow in patient-specific coronary arteries in order to compute clinical indices of interest, including FFR, in an effective and reliable way. The aims of this project are to combine a coronary artery reconstruction tool with Computational Fluid Dynamics (CFD) and Reduced Order Modelling (ROM) techniques to estimate the pressure drop and FFR in patient-specific coronary arteries in a fast and accurate way. This thesis comprises two parts, both associated with the effective computation of FFR from angiographic data: i. The first part addresses the problem of accurate reconstruction of coronary artery anatomy from multiple, single-plane coronary angiography (MSPCA), to underpin the creation of a computational model. A segmentation tool with a user-friendly graphical user interface (GUI) was developed in MATLAB to generate the surfaces meshes required for the CFD studies and to obtain other clinically-relevant coronary parameters. ii. The second part focuses on the effective and accurate computation of the pressure gradient and the FFR using ROMs built from CFD solutions in ANSYS-Fluent, exploiting the ANSYS ROMBuilder suite. The methods were applied to compute pressure profiles along the length of the artery, and FFR, in representations of coronary stenosis. The study includes the identification of an appropriate parameterisation of the artery shape to support the effective construction and operation of a ROM, as well as an evaluation of the sources of error and a comparison between results from Bernoulli estimates, from 1D models, from ROM, from CFD and from clinical measurement. Sequential increases in complexity of the anatomical representation are made, from axisymmetric with idealised stenoses to realistic radius variations from a coronary artery dataset and finally to curved arteries. In all cases each arterial cross-section is assumed to be circular. The study includes analysis of the interaction between idealised serial stenoses, and of a dataset of 140 patient-specific arteries characterised by angiography It was demonstrated that ROM applied to idealised coronary geometries achieved accuracies comparable with CFD results, and better than other approaches, in dramatically reduced timescales (order 900 times reduction relative to CFD). Limitations and opportunities for improvement include more accurate reconstruction of the cross-sectional profiles, more comprehensive representation of 3D curvature in the ROM and improved automation of segmentation, but the ROM approach shows great promise for this application in the delivery of solutions of sufficient accuracy in timescales consistent with the clinical process