Advances in quantitative coronary and vascular angiography

The main objective of this thesis is to develop new, accurate and reproducible automated methods for the detection and quantification of lesions in coronary and peripheral X-ray angiograms, which make it possible to extend the straight segment analysis to analyses of sidebranches and bifurcations. We introduce new methods for the detection of pathlines (Wavepath), the detection of arterial contours (Wavecontour) and the measurement of diameter sizes in straight segments, sidebranches and bifurcations. These methods are designed to increase reproducibility and decrease the influence of user interaction. These new methods are validated extensively in coronary and vascular angiograms, proving their accuracy and reproducibility. Furthermore we developed two new bifurcation models (Y-shape and T-shape) in order to accurately measure the diameters and lesion parameters of an entire bifurcation. The models, including their edge segment analyses, are validated extensively in a clinical validation study in order to assess the inter- and intra-observer variability on pre- and post-intervention data. Overall we can conclude that our goal of improving the QCA analysis and extend it towards the new morphologies and new intervention techniques has been met.Nederlandse Hartstichting Stichting inz. Doelfonds Beeldverwerking Medis medical imaging systems bv, LeidenUBL - phd migration 201

Blood Vessel Segmentation and shape analysis for quantification of Coronary Artery Stenosis in CT Angiography

This thesis presents an automated framework for quantitative vascular shape analysis of the coronary arteries, which constitutes an important and fundamental component of an automated image-based diagnostic system. Firstly, an automated vessel segmentation algorithm is developed to extract the coronary arteries based on the framework of active contours. Both global and local intensity statistics are utilised in the energy functional calculation, which allows for dealing with non-uniform brightness conditions, while evolving the contour towards to the desired boundaries without being trapped in local minima. To suppress kissing vessel artifacts, a slice-by-slice correction scheme, based on multiple regions competition, is proposed to identify and track the kissing vessels throughout the transaxial images of the CTA data. Based on the resulting segmentation, we then present a dedicated algorithm to estimate the geometric parameters of the extracted arteries, with focus on vessel bifurcations. In particular, the centreline and associated reference surface of the coronary arteries, in the vicinity of arterial bifurcations, are determined by registering an elliptical cross sectional tube to the desired constituent branch. The registration problem is solved by a hybrid optimisation method, combining local greedy search and dynamic programming, which ensures the global optimality of the solution and permits the incorporation of any hard constraints posed to the tube model within a natural and direct framework. In contrast with conventional volume domain methods, this technique works directly on the mesh domain, thus alleviating the need for image upsampling. The performance of the proposed framework, in terms of efficiency and accuracy, is demonstrated on both synthetic and clinical image data. Experimental results have shown that our techniques are capable of extracting the major branches of the coronary arteries and estimating the related geometric parameters (i.e., the centreline and the reference surface) with a high degree of agreement to those obtained through manual delineation. Particularly, all of the major branches of coronary arteries are successfully detected by the proposed technique, with a voxel-wise error at 0.73 voxels to the manually delineated ground truth data. Through the application of the slice-by-slice correction scheme, the false positive metric, for those coronary segments affected by kissing vessel artifacts, reduces from 294% to 22.5%. In terms of the capability of the presented framework in defining the location of centrelines across vessel bifurcations, the mean square errors (MSE) of the resulting centreline, with respect to the ground truth data, is reduced by an average of 62.3%, when compared with initial estimation obtained using a topological thinning based algorithm

Multislice computerized tomography coronary angiography can be a comparable tool to intravascular ultrasound in evaluating “true” coronary artery bifurcations

AimCoronary bifurcation atherosclerosis depends on its angles, flow, and extensive branching. We investigate the ability of CT coronary angiography (CTCA) to determine atherosclerotic plaque characteristics of “true” bifurcation compared with intravascular ultrasound (IVUS) and the influence on side branch (SB) fate after percutaneous coronary intervention (PCI).Methods and resultsThe study included 70 patients with 72 “true” bifurcations. Most of the bifurcations were in the left anterior descending—diagonal (Dg) territory [50 out of 72 (69.4%)]. Longitudinal plaque evaluation at the polygon of confluence [carina and 5 mm proximal and distal in the main branch (MB)] showed that carina side MB and SB plaque had occurred with the lowest incidence with fibro-lipid structure (115 ± 63 HU and 89 ± 73 HU, p < 0.001 for all). Bland–Altman analysis showed a discrepancy in measuring mainly the lumen area between CTCA and IVUS in proximal MB [lumen 5.10, 95% CI (95% confidence interval, 4.53–5.68) mm2, p < 0.001; vessel −1.42, 95% CI (−2.63 to −0.21) mm2, p = 0.023], carina MB [lumen 3.74, 95% CI (3.37–4.10) mm2, p < 0.001; vessel −0.48, 95% CI (−1.45 to 0.48) mm2, p = 0.322], and distal MB [lumen 4.72, 95% CI (4.27–5.18) mm2, p < 0.001; vessel 0.62, 95% CI (−0.53 to 1.77) mm2, p = 0.283]. A significant correlation existed between average plaque density on CTCA with a percentage of calcified plaque on IVUS tissue characterization (proximal r = 0.307/p = 0.024, carina 0.469/0.008, distal 0.339/0.024, minimal lumen diameter 0.318/0.020). Circumferential plaque in the proximal MB segment remained an independent predictor of SB compromise [OR 3.962 (95% CI 1.170–13.418)].ConclusionDetection and characterization of atherosclerotic plaque by CTCA in non-left main “true” coronary bifurcations can provide useful information about bifurcation anatomy and plaque distribution that can predict outcomes after provisional stenting, thus guiding the interventional strategy to bifurcation PCI

Automatic centerline extraction of coronary arteries in coronary computed tomographic angiography

Coronary computed tomographic angiography (CCTA) is a non-invasive imaging modality for the visualization of the heart and coronary arteries. To fully exploit the potential of the CCTA datasets and apply it in clinical practice, an automated coronary artery extraction approach is needed. The purpose of this paper is to present and validate a fully automatic centerline extraction algorithm for coronary arteries in CCTA images. The algorithm is based on an improved version of Frangi’s vesselness filter which removes unwanted step-edge responses at the boundaries of the cardiac chambers. Building upon this new vesselness filter, the coronary artery extraction pipeline extracts the centerlines of main branches as well as side-branches automatically. This algorithm was first evaluated with a standardized evaluation framework named Rotterdam Coronary Artery Algorithm Evaluation Framework used in the MICCAI Coronary Artery Tracking challenge 2008 (CAT08). It includes 128 reference centerlines which were manually delineated. The average overlap and accuracy measures of our method were 93.7% and 0.30 mm, respectively, which ranked at the 1st and 3rd place compared to five other automatic methods presented in the CAT08. Secondly, in 50 clinical datasets, a total of 100 reference centerlines were generated from lumen contours in the transversal planes which were manually corrected by an expert from the cardiology department. In this evaluation, the average overlap and accuracy were 96.1% and 0.33 mm, respectively. The entire processing time for one dataset is less than 2 min on a standard desktop computer. In conclusion, our newly developed automatic approach can extract coronary arteries in CCTA images with excellent performances in extraction ability and accuracy

Blood vessel segmentation and shape analysis for quantification of coronary artery stenosis in CT angiography

This thesis presents an automated framework for quantitative vascular shape analysis of the coronary arteries, which constitutes an important and fundamental component of an automated image-based diagnostic system. Firstly, an automated vessel segmentation algorithm is developed to extract the coronary arteries based on the framework of active contours. Both global and local intensity statistics are utilised in the energy functional calculation, which allows for dealing with non-uniform brightness conditions, while evolving the contour towards to the desired boundaries without being trapped in local minima. To suppress kissing vessel artifacts, a slice-by-slice correction scheme, based on multiple regions competition, is proposed to identify and track the kissing vessels throughout the transaxial images of the CTA data. Based on the resulting segmentation, we then present a dedicated algorithm to estimate the geometric parameters of the extracted arteries, with focus on vessel bifurcations. In particular, the centreline and associated reference surface of the coronary arteries, in the vicinity of arterial bifurcations, are determined by registering an elliptical cross sectional tube to the desired constituent branch. The registration problem is solved by a hybrid optimisation method, combining local greedy search and dynamic programming, which ensures the global optimality of the solution and permits the incorporation of any hard constraints posed to the tube model within a natural and direct framework. In contrast with conventional volume domain methods, this technique works directly on the mesh domain, thus alleviating the need for image upsampling. The performance of the proposed framework, in terms of efficiency and accuracy, is demonstrated on both synthetic and clinical image data. Experimental results have shown that our techniques are capable of extracting the major branches of the coronary arteries and estimating the related geometric parameters (i.e., the centreline and the reference surface) with a high degree of agreement to those obtained through manual delineation. Particularly, all of the major branches of coronary arteries are successfully detected by the proposed technique, with a voxel-wise error at 0.73 voxels to the manually delineated ground truth data. Through the application of the slice-by-slice correction scheme, the false positive metric, for those coronary segments affected by kissing vessel artifacts, reduces from 294% to 22.5%. In terms of the capability of the presented framework in defining the location of centrelines across vessel bifurcations, the mean square errors (MSE) of the resulting centreline, with respect to the ground truth data, is reduced by an average of 62.3%, when compared with initial estimation obtained using a topological thinning based algorithm.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Coronary Artery Segmentation and Motion Modelling

Conventional coronary artery bypass surgery requires invasive sternotomy and the use of a cardiopulmonary bypass, which leads to long recovery period and has high infectious potential. Totally endoscopic coronary artery bypass (TECAB) surgery based on image guided robotic surgical approaches have been developed to allow the clinicians to conduct the bypass surgery off-pump with only three pin holes incisions in the chest cavity, through which two robotic arms and one stereo endoscopic camera are inserted. However, the restricted field of view of the stereo endoscopic images leads to possible vessel misidentification and coronary artery mis-localization. This results in 20-30% conversion rates from TECAB surgery to the conventional approach. We have constructed patient-specific 3D + time coronary artery and left ventricle motion models from preoperative 4D Computed Tomography Angiography (CTA) scans. Through temporally and spatially aligning this model with the intraoperative endoscopic views of the patient's beating heart, this work assists the surgeon to identify and locate the correct coronaries during the TECAB precedures. Thus this work has the prospect of reducing the conversion rate from TECAB to conventional coronary bypass procedures. This thesis mainly focus on designing segmentation and motion tracking methods of the coronary arteries in order to build pre-operative patient-specific motion models. Various vessel centreline extraction and lumen segmentation algorithms are presented, including intensity based approaches, geometric model matching method and morphology-based method. A probabilistic atlas of the coronary arteries is formed from a group of subjects to facilitate the vascular segmentation and registration procedures. Non-rigid registration framework based on a free-form deformation model and multi-level multi-channel large deformation diffeomorphic metric mapping are proposed to track the coronary motion. The methods are applied to 4D CTA images acquired from various groups of patients and quantitatively evaluated

Improved modelling of the human cerebral vasculature

Ph.DDOCTOR OF PHILOSOPH

Reconstruction of coronary arteries from X-ray angiography: A review.

Despite continuous progress in X-ray angiography systems, X-ray coronary angiography is fundamentally limited by its 2D representation of moving coronary arterial trees, which can negatively impact assessment of coronary artery disease and guidance of percutaneous coronary intervention. To provide clinicians with 3D/3D+time information of coronary arteries, methods computing reconstructions of coronary arteries from X-ray angiography are required. Because of several aspects (e.g. cardiac and respiratory motion, type of X-ray system), reconstruction from X-ray coronary angiography has led to vast amount of research and it still remains as a challenging and dynamic research area. In this paper, we review the state-of-the-art approaches on reconstruction of high-contrast coronary arteries from X-ray angiography. We mainly focus on the theoretical features in model-based (modelling) and tomographic reconstruction of coronary arteries, and discuss the evaluation strategies. We also discuss the potential role of reconstructions in clinical decision making and interventional guidance, and highlight areas for future research

Angiographic Applications for Modern Percutaneous Coronary Intervention

This thesis sought to explore contemporary applications of invasive coronary angiography in the era of advanced percutaneous coronary intervention. Firstly, it describes the development and validation of dedicated bifurcation quantitative coronary angiography algorithms, in order to facilitate their analysis in a harmonized, reliable and reproducible manner. Then it presents the use of bifurcation quantitative coronary angiography algorithms in clinical studies, in the context of large registries and randomized trials, and discusses the clinical relevance of angiographic measures. Finally, it explores the prognostic value of angiographic scoring sys