Computer Vision Techniques for Transcatheter Intervention

Minimally invasive transcatheter technologies have demonstrated substantial promise for the diagnosis and treatment of cardiovascular diseases. For example, TAVI is an alternative to AVR for the treatment of severe aortic stenosis and TAFA is widely used for the treatment and cure of atrial fibrillation. In addition, catheter-based IVUS and OCT imaging of coronary arteries provides important information about the coronary lumen, wall and plaque characteristics. Qualitative and quantitative analysis of these cross-sectional image data will be beneficial for the evaluation and treatment of coronary artery diseases such as atherosclerosis. In all the phases (preoperative, intraoperative, and postoperative) during the transcatheter intervention procedure, computer vision techniques (e.g., image segmentation, motion tracking) have been largely applied in the field to accomplish tasks like annulus measurement, valve selection, catheter placement control, and vessel centerline extraction. This provides beneficial guidance for the clinicians in surgical planning, disease diagnosis, and treatment assessment. In this paper, we present a systematical review on these state-of-the-art methods.We aim to give a comprehensive overview for researchers in the area of computer vision on the subject of transcatheter intervention. Research in medical computing is multi-disciplinary due to its nature, and hence it is important to understand the application domain, clinical background, and imaging modality so that methods and quantitative measurements derived from analyzing the imaging data are appropriate and meaningful. We thus provide an overview on background information of transcatheter intervention procedures, as well as a review of the computer vision techniques and methodologies applied in this area

Interventional techniques in the management of persistent atrial fibrillation

Atrial fibrillation (AF) is a common cardiac rhythm problem experienced by patients and comprises an increasing demand on healthcare systems. AF is characterised by advanced neurohormonal remodelling in the atria resulting in dilation and variable degree of atrial fibrosis that can be measured by imaging techniques with difficulty in developing methods of identifying and quantifying left atrial (LA) fibrosis. LA fibrosis can be estimated by measuring LA scar using non-invasive imaging methods such as strain imaging in advanced echocardiography and in cardiac magnetic resonance (CMR) imaging. Achieving rhythm control strategy utilising catheter ablation (CA) has shown to be advantageous in improving quality of life (QOL) in patients with paroxysmal AF. The most effective method in management of AF has remained elusive in non-paroxysmal AF. Thoracoscopic surgical ablation (TSA) has been developed over the last decade by experienced surgeons with some promising early results but has not been investigated in long-standing persistent AF (LSPAF). I have attempted to answer some of the relevant questions that have remained in management of LSPAF by conducting a multicentre randomised control trial comparing efficacy between CA and TSA (CASA-AF RCT) and improvements in quality of life indices. In a sub-study, I measured LA volumes using echocardiography and CMR to determine reverse remodelling and LA function using tissue Doppler imaging and strain imaging to predict AF recurrence. In a CMR sub-study, a novel automatic LA segmentation algorithm was used to quantify LA fibrosis before and after ablation. I was able to quantify the response of the autonomic nervous system to targeted ganglionic plexi (GP) ablation as part of TSA compared to CA by measuring heart rate variability. I am hopeful that the knowledge gained from this thesis will help with an appropriate selection that will improve the management of patients with LSPAF.Open Acces

Personalized Multi-Scale Modeling of the Atria: Heterogeneities, Fiber Architecture, Hemodialysis and Ablation Therapy

This book targets three fields of computational multi-scale cardiac modeling. First, advanced models of the cellular atrial electrophysiology and fiber orientation are introduced. Second, novel methods to create patient-specific models of the atria are described. Third, applications of personalized models in basic research and clinical practice are presented. The results mark an important step towards the patient-specific model-based atrial fibrillation diagnosis, understanding and treatment

Characterization and modeling of the human left atrium using optical coherence tomography

With current needs to better understand the interaction between atrial tissue microstructure and atrial fibrillation dynamics, micrometer scale imaging with optical coherence tomography has significant potential to provide further insight on arrhythmia mechanisms and improve treatment guidance. However, optical coherence tomography imaging of cardiac tissue in humans is largely unexplored, and the ability of optical coherence tomography to identify the structural substrate of atrial fibrillation has not yet been investigated. Therefore, the objective of this thesis was to develop an optical coherence tomography imaging atlas of the human heart, study the utility of optical coherence tomography in providing useful features of human left atrial tissues, and develop a framework for optical coherence tomography-informed cardiac modeling that could be used to probe dynamics between electrophysiology and tissue structure. Human left atrial tissues were comprehensively imaged by optical coherence tomography for the first time, providing an imaging atlas that can guide identification of left atrial tissue features from optical coherence tomography imaging. Optical coherence tomography image features corresponding to myofiber and collagen fiber orientation, adipose tissue, endocardial thickness and composition, and venous media were established. Varying collagen fiber distributions in the myocardial sleeves were identified within the pulmonary veins. A scheme for mapping optical coherence tomography data of dissected left atrial tissues to a three-dimensional, anatomical model of the human left atrium was also developed, enabling the mapping of distributions of imaged adipose tissue and fiber orientation to the whole left atrial geometry. These results inform future applications of structural substrate mapping in the human left atrium using optical coherence tomography-integrated catheters, as well as potential directions of ex vivo optical coherence tomography atrial imaging studies. Additionally, we developed a workflow for creating optical mapping models of atrial tissue as informed by optical coherence tomography. Tissue geometry, fiber orientation, ablation lesion geometry, and heterogeneous tissue types were extracted from optical coherence tomography images and incorporated into tissue-specific meshes. Electrophysiological propagation was simulated and combined with photon scattering simulations to evaluate the influence of tissue-specific structure on electrical and optical mapping signals. Through tissue-specific modeling of myofiber orientation, ablation lesions, and heterogeneous tissue types, the influence of myofiber orientation on transmural activation, the relationship between fluorescent signals and lesion geometry, and the blurring of optical mapping signals in the presence of heterogeneous tissue types were investigated. By providing a comprehensive optical coherence tomography image database of the human left atrium and a workflow for developing optical coherence tomography-informed cardiac tissue models, this work establishes the foundation for utilizing optical coherence tomography to improve the structural substrate characterization of atrial fibrillation. Future developments include analysis of optical coherence tomography imaged tissue structure with respect to clinical presentation, development of automated processing to better leverage the large amount of imaging data, enhancements and validation of the modeling scheme, and in vivo evaluation of the left atrial structural substrate through optical coherence tomography-integrated catheter