Intravascular Ultrasound

Intravascular ultrasound (IVUS) is a cardiovascular imaging technology using a specially designed catheter with a miniaturized ultrasound probe for the assessment of vascular anatomy with detailed visualization of arterial layers. Over the past two decades, this technology has developed into an indispensable tool for research and clinical practice in cardiovascular medicine, offering the opportunity to gather diagnostic information about the process of atherosclerosis in vivo, and to directly observe the effects of various interventions on the plaque and arterial wall. This book aims to give a comprehensive overview of this rapidly evolving technique from basic principles and instrumentation to research and clinical applications with future perspectives

Understanding the role of hemodynamics in the initiation, progression, rupture, and treatment outcome of cerebral aneurysm from medical iamge-based computational studies

About a decade ago, the first image-based computational hemodynamic studies of cerebral aneurysms were presented. Their potential for clinical applications was the results of a right combination of medical image processing, vascular reconstruction, and grid generation techniques used to reconstruct personalziaed domains for computational fluid and solid dynamics solvers and data analysis and visualization techniques. A considerable number of studies have captivated the attention of clinicians, neurosurgeons, and neuroradiologists, who realized the ability of those tools to help in understanding the role played by hemodynamics in the natural history and management of intracranial aneurysms. This paper intends to summarize the most relevant results in the filed reported during the last years.Fil: Castro, Marcelo Adrian. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Intravascular ultrasound: a technique in evolution: methodological considerations

As the title of the thesis suggests, intravascular ultrasound has been, and continues to be, an imaging technique that is in active evolution. Image quality has improved dramatically from the crude, low resolution 'black and white' images of the first generation of intravascular ultrasound scanners and transducers are now small enough to image most arteries before intervention. Although intravascular ultrasound is increasingly seen as the most informative method of assessing the coronary arteries, there are outstanding problems that must be addressed and overcome before its full potential can be achieved.The aim of this thesis is to examine a number of these methodological shortcomings of intravascular ultrasound so that appropriate solutions can be found.After a general overview, provided in Chapter 1, the reproducibility of intravascular ultrasound quantitation is assessed in Chapter 2. For reasons elaborated above, ultrasound is seen as the best technique to study the acute and long term outcome of coronary interventions and the effect of plaque modifying agents. Without detailed data concerning its reproducibility, such studies are uninterpretable.Chapter 3 deals with the impact of catheter malfunction on the geometric integrity of intravascular ultrasound images. At present, the mechanical ultrasound devices are the most widely used systems. All mechanical systems are potentially subject to the problem of non -uniform rotation of the transducer, and to date its impact has been poorly characterised.The difficulty encountered in discriminating unstable coronary lesions is examined in Chapter 4. There is a widely held view that acute coronary lesions cannot be discriminated using intravascular ultrasound. Specific echographic markers are described that are found in the majority of unstable lesions. Close scrutiny of grey scale images allows identification of acute lesions and may allow discrimination of thrombus from underlying atheromatous plaque.In the last two chapters, methodological issues relating to the clinical application of intravascular ultrasound in guiding coronary stenting are explored. In chapter 5, the findings of an observational study confirm the potential of intravascular ultrasound to provide additional information in cases in which favourable angiographic appearances have been achieved. However, the choice of one particular 'expansion index' over another is seen to impact significantly on the proportion of lesions that are judged to be successful. Before ultrasound guidance based on the attainment of specific quantitative expansion criteria be advocated as a widely applied technique, the reproducibility of reference segment measurements must be known. This issue is studied in chapter 6.Separate studies are described in each of the data chapters. A similar layout is employed in each, consisting of the study aims, methods, findings, discussion and conclusion. At the risk of introducing a degree of repetition in the methods sections of each chapter, the ultrasound examination and image interpretation protocol are elaborated in each case, as important differences exist between the studies

Corevalve vs. Sapien 3 transcatheter aortic valve replacement: A finite element analysis study

Aim: to investigate the factors implied in the development of postoperative complications in both self-expandable and balloon-expandable transcatheter heart valves by means of finite element analysis (FEA). Materials and methods: FEA was integrated into CT scans to investigate two cases of postoperative device failure for valve thrombosis after the successful implantation of a CoreValve and a Sapien 3 valve. Data were then compared with two patients who had undergone uncomplicated transcatheter heart valve replacement (TAVR) with the same types of valves. Results: Computational biomechanical modeling showed calcifications persisting after device expansion, not visible on the CT scan. These calcifications determined geometrical distortion and elliptical deformation of the valve predisposing to hemodynamic disturbances and potential thrombosis. Increased regional stress was also identified in correspondence to the areas of distortion with the associated paravalvular leak. Conclusion: the use of FEA as an adjunct to preoperative imaging might assist patient selection and procedure planning as well as help in the detection and prevention of TAVR complications

Combinatorial optimisation for arterial image segmentation.

Cardiovascular disease is one of the leading causes of the mortality in the western world. Many imaging modalities have been used to diagnose cardiovascular diseases. However, each has different forms of noise and artifacts that make the medical image analysis field important and challenging. This thesis is concerned with developing fully automatic segmentation methods for cross-sectional coronary arterial imaging in particular, intra-vascular ultrasound and optical coherence tomography, by incorporating prior and tracking information without any user intervention, to effectively overcome various image artifacts and occlusions. Combinatorial optimisation methods are proposed to solve the segmentation problem in polynomial time. A node-weighted directed graph is constructed so that the vessel border delineation is considered as computing a minimum closed set. A set of complementary edge and texture features is extracted. Single and double interface segmentation methods are introduced. Novel optimisation of the boundary energy function is proposed based on a supervised classification method. Shape prior model is incorporated into the segmentation framework based on global and local information through the energy function design and graph construction. A combination of cross-sectional segmentation and longitudinal tracking is proposed using the Kalman filter and the hidden Markov model. The border is parameterised using the radial basis functions. The Kalman filter is used to adapt the inter-frame constraints between every two consecutive frames to obtain coherent temporal segmentation. An HMM-based border tracking method is also proposed in which the emission probability is derived from both the classification-based cost function and the shape prior model. The optimal sequence of the hidden states is computed using the Viterbi algorithm. Both qualitative and quantitative results on thousands of images show superior performance of the proposed methods compared to a number of state-of-the-art segmentation methods

Machine learning and reduced order modelling for the simulation of braided stent deployment

Endoluminal reconstruction using flow diverters represents a novel paradigm for the minimally invasive treatment of intracranial aneurysms. The configuration assumed by these very dense braided stents once deployed within the parent vessel is not easily predictable and medical volumetric images alone may be insufficient to plan the treatment satisfactorily. Therefore, here we propose a fast and accurate machine learning and reduced order modelling framework, based on finite element simulations, to assist practitioners in the planning and interventional stages. It consists of a first classification step to determine a priori whether a simulation will be successful (good conformity between stent and vessel) or not from a clinical perspective, followed by a regression step that provides an approximated solution of the deployed stent configuration. The latter is achieved using a non-intrusive reduced order modelling scheme that combines the proper orthogonal decomposition algorithm and Gaussian process regression. The workflow was validated on an idealised intracranial artery with a saccular aneurysm and the effect of six geometrical and surgical parameters on the outcome of stent deployment was studied. The two-step workflow allows the classification of deployment conditions with up to 95% accuracy and real-time prediction of the stent deployed configuration with an average prediction error never greater than the spatial resolution of 3D rotational angiography (0.15 mm). These results are promising as they demonstrate the ability of these techniques to achieve simulations within a few milliseconds while retaining the mechanical realism and predictability of the stent deployed configuration