Funktionelle Herzklappen-Stent Designs für zukünftige autologe, transkatheter Klappenprothesen in pulmonaler Position

Background Transcatheter pulmonary valve replacement (TPVR) has asserted its position as a cornerstone in cardiology and become a nonsurgical alternative for patients with a dysfunctional right ventricular outflow tract (RVOT), demonstrating excellent early and late clinical outcomes. Short- and long-term complications of TPVR include stent fracture and migration, coronary compression, and valve regurgitation. Objective The purpose of this study is to describe methodology for developing Nitinol stents by conducting a computational design and finite element analysis in conjunction with 3D reconstruction of animal cardiac CT for TPVR. Methods 3D cardiac CT reconstruction was achieved using 3D Slicer, from which the RVOT + pulmonary artery (PA) was exported for blood flow simulation and hoop force acquisition with the stents. Functional stents were designed using Autodesk Fusion 360 and divided into three morphological geometries: group 1–straight tubular stents, group 2–corollaceous stents, and group 3–corollaceous stents with an elliptic geometry. Stent simulations for stent life and radial force, and the hoop force of the stent during expansion with the RVOT+PA model were obtained in Ansys. The blood flow simulation of RVOT+PA was performed using Ansys with the velocity-based coupled solver. Results 3D cardiac CT reconstructions were obtained in STL format, from which the right ventricle (RV) +PA model was performed for the blood flow simulation and the hoop force was obtained with the stents. Twelve functional stents were successfully designed and exported in SAT and STP formats for simulation. All stent life (Times)/radial force (N) were achieved: Group 1 comprised the stents DGS 3 (3219.2/1.88E+05), DGS 5 (16406/1.94E+05), DGS 7 (1.00E+06/1.89E+05), DGS 8B (0/3.74E+05), DGS-10B (8370.1/2.41E+05), DGS 12D (1.00E+06/2.41E+08); Group 2 comprised the stents DGS 8A (0/3.60E+05), DGS 9A (0/3.60E+05), DGS 10A (46093/2.28E+05), DGS 12C (2.50E+005/1.69E+05); Group 3 comprised the stents DGS 12A (1.00E+06/2.38E+08), DGS 12B (54509/2.20E+05). Hoop force (N) was obtained from the 12 stents: Group 1–DGS 5 (57802), DGS 7 (54647), DGS 8B (53248), DGS 10B (56650), DGS 12D (46297). Group 2–DGS 8A (50490), DGS 9A (60393), DGS 10A (23639), DGS 12C (29802). Group 3–DGS 12A (16368), DGS 12B (16368). The RV+PA blood flow simulation demonstrated that the anterior part of the PA wall had the largest shear force. Conclusions DGS 12C, DGS 12D, DGS 10A, DGS 10B, DGS 7, and DGS 5 can be subsequently tested in vitro. Autologous pulmonary valves could be sutured onto the functional stents to maintain their original geometry prior to implantation. Pre-implantation 3D CT reconstruction and stent simulation can be performed for better evaluation and visualization. The RV+PA blood flow simulation may serve as a significant input for the design of stents and pulmonary valve to determine the shear force throughout the cardiac cycle.Hintergrund Der katheterbasierte Pulmonalklappenersatz ist ein Eckpfeiler der Kardiologie und bietet zudem eine nicht-chirurgische Alternative für die Behandlung funktionsgestörter rechtsventrikulärer Ausflusstrakte oder bioprothetischer Klappen mit hervorragenden frühen und späten klinischen Ergebnissen. Kurz- und langfristige Komplikationen von TPVR umfassen Stentfraktur/-migration, Komprimierung der Koronararterien und Klappeninsuffizienz. Ziel Ziel dieser Studie ist es, die Methodik und das Konzept für Nitinol-Stents mithilfe rechnerischer Entwürfe und Finite-Elemente-Analysen anhand von 3D-Rekonstruktionen kardialer CT-Untersuchungen in Tieren für die Anwendung von TPVR zu beschreiben. Methoden Die 3D-Rekonstruktion der CT-Untersuchungen erfolgte mit der Software 3D Slicer, aus der die RVOT und Pulmonalarterie (PA) in Verbindung mit den Stents für die Blutflusssimulation und die Umfangsspannung exportiert wurde. Die funktionellen Stents wurden mit Fusion 360 entworfen und danach in die Formate SAT und STP exportiert. Simulationen für die Lebensdauer und Radialkraft sowie für die Umfangsspannung der Stents bei der Freisetzung mit dem RVOT+PA-Modell wurden in Ansys berechnet. Die Blutflusssimulation von RVOT+PA wurde in Ansys mit dem geschwindigkeitsbasierten gekoppelten Solver durchgeführt. Ergebnisse Zwölf funktionelle Stents wurden mithilfe von Fusion 360 generiert. SAT- und STP-Dateien wurden zur Simulation in Ansys exportiert. 3D Kardio-CT-Rekonstruktionen wurden mithilfe im STL-Format kreiert, aus dem das RVOT+PA-Modell des Prä-CT ausgewählt wurde, um die Blutflusssimulation durchzuführen und die Ringkraft der Stents zu erhalten. Die Lebensdauer (Anzahl) und Radialkraft (N) der Stents wurden wie folgt berechnet: DGS-3 (3219.2/1.88E+05), DGS-5 (16406/1.94E+05), DGS-7 (1.00E+06/1.89E+05), DGS-8A (0/3.60E+05), DGS-8B (0/3.74E+05), DGS-9A (0/3.60E+05), DGS-10A (46093/2.28E+05), DGS-10B (8370.1/2.41E+05), DGS-12A (1.00E+06/2.38E+08), DGS-12B (54509/2.20E+05), DGS-12D (1.00E+06/2.41E+08), DGS-12C (2.50E+005/1.69E+05). Die jeweilige Umspannungskraft (N) wurde wie folgt berechnet: DGS-5 (57802), DGS-7 (54647), DGS-8A (50490), DGS-8B (53248), DGS-9A (60393), DGS-10A (23639), DGS-10B (56650), DGS-12A (16368), DGS-12B (16368), DGS-12C (29802), DGS-12D (46297). Die RV+PA-Blutflusssimulation zeigte, dass der vordere Teil der PA-Wand die größte Scherkraft aufwies. Schlussfolgerungen DGS-12C, DGS-12D, DGS-10A, DGS-10B, DGS-7 und DGS-5 können nachfolgend in vitro getestet werden. Autologe Pulmonalklappen können zur Erhaltung der ursprünglichen Geometrie vor der Implantation auf funktionelle Stents aufgenäht werden. Vor der Implantation können Kardio-CT 3D-Rekonstruktion und Stentsimulationen zur besseren Bewertung und Visualisierung durchgeführt werden. Die Blutflusssimulation von RVOT+PA kann einen bedeutsamen Beitrag zur Gestaltung von Stents und Pulmonalklappen leisten, um die Scherkraft während des gesamten Herzzyklus zu erhalten

Transcatheter Aortic Valve Therapies : Insights and Solutions for Clinical Complications and Future Perspectives

This thesis contemplates current challenges of transcatheter aortic valve implantation (TAVI) and focuses on three important entities. Conduction disorders remain a frequent issue. Daily ECG analysis after the procedure may help predict the fate of acquired conduction abnormalities at an earlier stage and identify the patients who would benefit from (early) permanent pacemaker implantation. Access site management relies on suture-based techniques and has inherent limitations. Collagen plug based closure is a different mechanism, may be easier to adopt and globally reduce vascular complications. Brain injury seems omnipresent after TAVI and is difficult to reconcile with the “primum non nocere” principle. Filter based embolic protection hold promise to mitigate the effects of cerebral embolization, especially if complete protection is achieved. TAVI has now matured into a simplified procedure under local anesthesia and the performance of the latest transcatheter valve iterations approach or even supersede what can be achieved with a surgical bioprosthesis. Bicuspid aortic disease, severe aortic regurgitation and moderate aortic stenosis in heart failure are potential new indications for TAVI. Furthermore, TAVI is attractive for treatment in patients at lower risk who are younger and have a longer life expectancy

Multiscale Modeling of the Ventricles: From Cellular Electrophysiology to Body Surface Electrocardiograms

This work is focused on different aspects within the loop of multiscale modeling: On the cellular level, effects of adrenergic regulation and the Long-QT syndrome have been investigated. On the organ level, a model for the excitation conduction system was developed and the role of electrophysiological heterogeneities was analyzed. On the torso level a dynamic model of a deforming heart was created and the effects of tissue conductivities on the solution of the forward problem were evaluated

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

Pacing with restoration of respiratory sinus arrhythmia improved cardiac contractility and the left ventricular output: a translational study

Introduction: Respiratory sinus arrhythmia (RSA) is a prognostic value for patients with heart failure and is defined as a beat-to-beat variation of the timing between the heart beats. Patients with heart failure or patients with permanent cardiac pacing might benefit from restoration of RSA. The aim of this translational, proof-of-principle study was to evaluate the effect of pacing with or without restored RSAon parameters of LV cardiac contractility and the cardiac output

Inverse estimation of the cardiac purkinje system from electroanatomical maps

Las enfermedades cardiovasculares son la primera causa de mortalidad en el mundo, con 17.7 millones de muertes cada año, aproximadamente el 31% de las muertes en todo el mundo (Organización Mundial de la Salud (OMS) 2018). Las arritmias ventriculares son una causa importante de muerte súbita, que representa aproximadamente la mitad de la mortalidad cardíaca. Algunas de esas arritmias se atribuyen a la red de Purkinje (PKN), que bajo ciertas condiciones puede generar ritmos focales automáticos, y su configuración de red puede sostener circuitos eléctricos reentrantes. Los ritmos focales originados desde la red de Purkinje pueden servir como puntos de inicio en casos de fibrilación ventricular en un amplio espectro de pacientes. El manejo de las enfermedades eléctricas cardíacas es un área clínica en expansión. Las nuevas tecnologías de imágenes y mapeo no invasivas, permiten adquirir imágenes clínicas de alta resolución (MRI, CT) que se pueden utilizar para localizar y caracterizar el tejido cardíaco patológico. Además, los sistemas de navegación electroanatómica (EAM) pueden ayudar al electrofisiólogo a encontrar las fuentes de actividad o circuitos arritmogénicos que mantienen la arritmia y eliminarlos mediante ablación por radiofrecuencia (RFA). A pesar de todos los avances técnicos, los tratamientos clínicos para esas enfermedades todavía se perciben como subóptimos, con tasas de éxito del tratamiento a largo plazo en el rango de 60 a 65%. Por lo tanto, existe una necesidad imperiosa de mejorar los resultados clínicos en beneficio de los pacientes y el sistema de salud. El área del modelado biofísico computacional ha comenzado a penetrar en entornos clínicos en unos pocos hospitales tecnológicamente avanzados y orientados a la investigación en el mundo. El objetivo principal de estas técnicas es el desarrollo de modelos 3D realistas de diferentes órganos, como el corazón, que incluyen, con un alto grado de detalle, características genéticas de las corrientes iónicas, sus mutaciones, las características electrofisiológicas de los diferentes tipos de células cardíacas, la estructura anatómica de los tejidos cardíacos y, en general, del cuerpo humano. A continuación, los modelos se utilizan para simular la función cardíaca, por ejemplo, electrofisiología, para tratar de estratificar a los pacientes o mejorar la planificación y ejecución de la terapia. Los enfoques por computador aún se enfrentan a varios desafíos que impiden su penetración completa en entornos clínicos. Podría decirse que uno de los obstáculos más importantes es el tiempo y la experiencia necesarios para construir un modelo del corazón personalizado a paciente, incluso si todos los datos clínicos necesarios están disponibles. En ese sentido, uno de los componentes del modelo que se ha mantenido elusivo a los modeladores ha sido la PKN, que es clave para la electrofisiología cardíaca. La razón principal es que debido a sus pequeñas dimensiones no existe una técnica clínica con resolución suficiente para permitir su visualización in vivo. El objetivo principal de esta tesis es desarrollar una metodología capaz de estimar inversamente un PKN reducido de paciente a partir de su EAM. Eso implica, primero encontrar en el EAM las fuentes de activación eléctrica, llamadas uniones de Purkinje-miocardio (PMJ), y seguir la estructura que interconecta esos PMJ y reproduce la secuencia de activación del paciente. En resumen, las principales contribuciones de esta tesis son: - Metodología para estimar los PMJ, o las fuentes de actividad eléctrica, sobre una representación 3D del endocardio ventricular, proporcionada por un EAM. El método desarrollado puede procesar directamente los datos adquiridos por un electrofisiólogo en el Cathlab, volver a anotar los tiempos en las muestras adquiridas y obtener las ubicaciones de los PMJs y los tiempos de activación, considerando explicitamente ruido en las muestras. - Metodología para estimar el PKN del paciente a partir de los PMJ estimados, que es capaz de reproducir la secuencia de activación eléctrica del paciente con un error mínimo. El método ha sido validado tanto en EAM sintéticos como en 28 EAM reales, mostrando errores de unos pocos milisegundos. Además, se ha utilizado un PKN estimado para simular el ECG virtual de un paciente, donse se observa coincidencia entre el ECG real y el simulado. En conclusión, he desarrollado y validado una metodología que permite la estimación de la PKN de un paciente con errores mínimos en la secuencia de activación, y que puede usarse para personalizar simulaciones biofísicas del corazón o ayudar al electrofisiólogo en la planificación de intervenciones de RFA.Cardiovascular disease is the number one cause of mortality in the world, accounting for 17.7 million deaths each year, an estimated 31% of all deaths worldwide (World Health Organization (WHO) 2018). Ventricular arrhythmias are a major cause of sudden death, which accounts for approximately half of cardiac mortality. Some of those arrhythmias are attributed to the Purkinje network (PKN), which under certain conditions can generate both automatic and triggered focal rhythms, and its network configuration can sustain re‑entrant circuits. Focal Purkinje triggers can serve as initial points of ventricular fibrillation in a wide spectrum of patients. The management of cardiac electrical diseases is an expanding clinical activity. New non-invasive imaging and mapping technologies, allow to acquire high resolution clinical images (MRI, CT) that can be used to localize and characterize pathological cardiac tissue. Furthermore, electroanatomical navigating (EAM) systems, can aid electrophysiologist to find the sources of arrhythmogenic activity or circuits maintaining arrhythmia, and eliminate them by radio-frequency ablation (RFA). Despite all the technical advances, overall clinical outcome for those diseases is still perceived as suboptimal, with long-term treatment success rates in the range of 60 to 65%. Therefore, there is a compelling need to improve clinical outcomes for the benefit of the patients and the healthcare system. The area of computational biophysical modeling has already started to penetrate in clinical environments in a few technologically advanced research oriented hospitals in the world. The main objective of these techniques is the development of realistic 3D models of different organs, such as the heart, that include, with a high degree of detail, genetic characteristics of the ionic currents, their mutations, the electrophysiological characteristics of the different cardiac cell types, the anatomical structure of cardiac tissues, and in general of the human body. Following, the models are used to simulate the heart function, e.g., electrophysiology, to try to stratify patients or improve therapy planning and delivery. Computer-based approaches are still facing several challenges that prevent their complete penetration into clinical environments. Arguably, one of the most important obstacles is the time and expertise required to build a patient-specific model of the heart, even if all necessary clinical data are available. In that sense, one of the model components that has remained largely elusive to modelers has been the PKN, which is key for cardiac electrophysiology. The main reason is that due to its small dimensions there is no clinical technique with enough resolution to allow its visualization in vivo. The main purpose of this thesis is to develop a methodology able to inversely estimate a reduced PKN of patient from his EAM. That involves, first, finding in the EAM the sources of electrical activation, so called Purkinje-myocardial junctions (PMJs), and, following, finding the structure that interconnects those PMJs and reproduces the patient sequence of activation. In summary, the main contributions of this thesis are: - Methodology to estimate the PMJs, or the sources of electrical activity, from a 3D representation of the ventricular endocardium provided by an EAM. The method developed can process directly the data acquired by an electrophysiologist in the Cathlab, re-annotate the time samples, and obtain the PMJ locations and activation times, explicitly considering noise in the samples. - Methodology to estimate the patient PKN from the estimated PMJs, that is able to reproduce the patient's sequence of electrical activation with a minimal error. The method has been validated on synthetic EAMs as well as in 28 real EAMs, showing errors of a few milliseconds. In addition, an estimated PKN has been used to simulate the virtual ECG of a patient, showing a good match with the clinical one. In conclusion, I have developed and validated a methodology that permits the estimation of a patient's PKN with small errors in the sequence of activation, that can be used to personalize biophysical simulations of the heart or aid electrophysiologist in the planning of RFA interventions