Automatic aortic root landmark detection in CTA images for preprocedural planning of transcatheter aortic valve implantation

Transcatheter aortic valve implantation is currently a well-established minimal invasive treatment option for patients with severe aortic valve stenosis. CT Angiography is used for the pre-operative planning and sizing of the prosthesis. To reduce the inconsistency in sizing due to interobserver variability, we introduce and evaluate an automatic aortic root landmarks detection method to determine the sizing parameters. The proposed algorithm detects the sinotubular junction, two coronary ostia, and three valvular hinge points on a segmented aortic root surface. Using these aortic root landmarks, the automated method determines annulus radius, annulus orientation, and distance from annulus plane to right and left coronary ostia. Validation is performed by the comparison with manual measurements of two observers for 40 CTA image datasets. Detection of landmarks showed high accuracy where the mean distance between the automatically detected and reference landmarks was 2.81 ± 2.08 mm, comparable to the interobserver variation of 2.67 ± 2.52 mm. The mean annulus to coronary ostium distance was 16.9 ± 3.3 and 17.1 ± 3.3 mm for the automated and the reference manual measurements, respectively, with a mean paired difference of 1.89 ± 1.71 mm and interobserver mean paired difference of 1.38 ± 1.52 mm. Automated detection of aortic root landmarks enables automated sizing with good agreement with manual measurements, which suggests applicability of the presented method in current clinical practic

Deep learning method for aortic root detection

Background: Computed tomography angiography (CTA) is a preferred imaging technique for a wide range of vascular diseases. However, extensive manual analysis is required to detect and identify several anatomical landmarks for clinical application. This study demonstrates the feasibility of a fully automatic method for detecting the aortic root, which is a key anatomical landmark in this type of procedure. The approach is based on the use of deep learning techniques that attempt to mimic expert behavior. Methods: A total of 69 CTA scans (39 for training and 30 for validation) with different pathology types were selected to train the network. Furthermore, a total of 71 CTA scans were selected independently and applied as the test set to assess their performance. Results: The accuracy was evaluated by comparing the locations marked by the method with benchmark locations (which were manually marked by two experts). The interobserver error was 4.6 ± 2.3 mm. On an average, the differences between the locations marked by the two experts and those detected by the computer were 6.6 ± 3.0 mm and 6.8 ± 3.3 mm, respectively, when calculated using the test set. Conclusions: From an analysis of these results, we can conclude that the proposed method based on pre-trained CNN models can accurately detect the aortic root in CTA images without prior segmentationThis work was partially financed by Consellería de Cultura, Educación e Universidade (reference 2019–2021, ED431C 2018/19)S

Artificial intelligence and automation in valvular heart diseases

Artificial intelligence (AI) is gradually changing every aspect of social life, and healthcare is no exception. The clinical procedures that were supposed to, and could previously only be handled by human experts can now be carried out by machines in a more accurate and efficient way. The coming era of big data and the advent of supercomputers provides great opportunities to the development of AI technology for the enhancement of diagnosis and clinical decision-making. This review provides an introduction to AI and highlights its applications in the clinical flow of diagnosing and treating valvular heart diseases (VHDs). More specifically, this review first introduces some key concepts and subareas in AI. Secondly, it discusses the application of AI in heart sound auscultation and medical image analysis for assistance in diagnosing VHDs. Thirdly, it introduces using AI algorithms to identify risk factors and predict mortality of cardiac surgery. This review also describes the state-of-the-art autonomous surgical robots and their roles in cardiac surgery and intervention

Fully Automatic 3D-TEE Segmentation for the Planning of Transcatheter Aortic Valve Implantation

A novel fully automatic framework for aortic valve (AV) trunk segmentation in three-dimensional (3-D) transesophageal echocardiography (TEE) datasets is proposed. The methodology combines a previously presented semiautomatic segmentation strategy by using shape-based B-spline Explicit Active Surfaces with two novel algorithms to automate the quantification of relevant AV measures. The first combines a fast rotation-invariant 3-D generalized Hough transform with a vessel-like dark tube detector to initialize the segmentation. After segmenting the AV wall, the second algorithm focuses on aligning this surface with the reference ones in order to estimate the short-axis (SAx) planes (at the left ventricular outflow tract, annulus, sinuses of Valsalva, and sinotubular junction) in which to perform the measurements. The framework has been tested in 20 3-D-TEE datasets with both stenotic and nonstenotic AVs. The initialization algorithm presented a median error of around 3 mm for the AV axis endpoints, with an overall feasibility of 90%. In its turn, the SAx detection algorithm showed to be highly reproducible, with indistinguishable results compared with the variability found between the experts' defined planes. Automatically extracted measures at the four levels showed a good agreement with the experts' ones, with limits of agreement similar to the interobserver variability. Moreover, a validation set of 20 additional stenotic AV datasets corroborated the method's applicability and accuracy. The proposed approach mitigates the variability associated with the manual quantification while significantly reducing the required analysis time (12 s versus 5 to 10 min), which shows its appeal for automatic dimensioning of the AV morphology in 3-D-TEE for the planning of transcatheter AV implantation.This work was supported by the project "ON.2 SR&TD Integrated Program (Norte-07-0124-FEDER-000017)" cofunded by the Programa Operacional Regional do Norte (ON.2- O Novo Norte), Quadro de Referencia Estrategico Nacional, through Fundo Europeu de Desenvolvimento Regional. The work of S. Queiros and P. Morais was supported by the FCT-Fundacao para a Ciencia e a Tecnologia and the European Social Found through the Programa Operacional Capital Humano in the scope of the Ph.D. Grants SFRH/BD/93443/2013 and SFRH/BD/95438/2013, respectively. J. L. Vilaca and J. D'hooge are joint last authors. Asterisk indicates corresponding author.info:eu-repo/semantics/publishedVersio

Die Anwendung der 4D-Segmentierung der Herz-CT für den prä- und postoperativen Transkatheter-Lungenklappenersatz

Background: Transcatheter pulmonary valve replacement (TPVR) has become an alternative therapeutic option for patients with right ventricular outflow tract (RVOT) dysfunction. Cardiac CT angiography (CTA) is crucial for TPVR pre- and post-operative assessment of the landing zone from RVOT to pulmonary artery (PA). However, three-dimension (3D) CT is still inadequate to assess the full dynamic variation of landing zone and spatial relationships between structures over the cardiac cycle accurately. Methods: The objective of this present study was to simulate the dynamic variation of the landing zone from RVOT to PA in vivo for TPVR by four-dimension (4D) CTA segmentation and evaluate the feasibility and accuracy of the 4D straightened model. The straightened model was created by adding centerline to the right heart model, then the anatomical right heart model was straightened. The 4D conventional anatomical model and straightened model were reconstructed at 10 cardiac cycle phases in 14 cardiac CTA datasets of seven sheep underwent TPVR. The cross-sectional area, circumference, and diameter deformations over the cardiac cycle were measured at five planes of the landing zone from pre- and post-operative 4D CTA. In addition, the correlation analysis between the anatomical model and straightened model was also conducted by means of Pearson correlation and Bland-Altman analysis. Results: The clear structure of each section from RVOT to PA were observed on straightened model. Significant variations of cross-sectional area and circumference measurements showed at the RVOT plane throughout the cardiac cycle for both pre- and post-operative 4D CTA. Nevertheless, nearly no deformation of area and circumference was observed at the valvular sinuses level (Plane 3a) and the sino-tubular junction plane (Plane 4a) from pre-operative CT; the middle plane of the stent level (Plane 3b) and the top plane of the stent level (Plane 4b) from the post-operative CT. The straightened model was highly correlated with the anatomical model. The Pearson correlation coefficient between straightened model and anatomical model for cross-sectional area, circumference, minimum diameter, and maximum diameter ranged from 0.77 to 0.99 (P < 0.0001) and the limits of agreement from Bland-Altman analysis were within a good range, which further confirmed the great agreement between straightened model and anatomical model. Conclusions: The 4D CT anatomical model can be used to demonstrate the deformation of RVOT to PA dynamics over the cardiac cycle. The straightened model can show the changes in the landing area, accurately measure these data, and clearly show the structure of the various sections.Hintergrund: Der Transkatheter-Pulmonalklappenersatz (TPVR) hat sich zu einer alternativen Therapieoption für Patienten mit einer Funktionsstörung des rechtsventrikulären Ausflusstrakts (RVOT) entwickelt. Die kardiale CT-Angiographie (CTA) ist von entscheidender Bedeutung für die prä- und postoperative Beurteilung der Landezone vom RVOT zur Pulmonalarterie (PA) bei der TPVR. Die dreidimensionale (3D) CT ist jedoch noch immer unzureichend, um die vollständige dynamische Veränderung der Landezone und die räumlichen Beziehungen zwischen den Strukturen während des Herzzyklus genau zu beurteilen. Methoden: Ziel dieser Studie war es, die dynamische Veränderung der Landezone vom RVOT zur PA in vivo für die TPVR durch vierdimensionale (4D) CTA-Segmentierung zu simulieren und die Durchführbarkeit und Genauigkeit des begradigten 4D-Modells zu bewerten. Das begradigte Modell wurde durch Hinzufügen einer Mittellinie zum Rechtsherzmodell erstellt, anschließend wurde das anatomische Rechtsherzmodell begradigt. Das konventionelle anatomische 4D-Modell und das begradigte Modell wurden in 10 Herzzyklusphasen in 14 kardialen CTA-Datensätzen von sieben Schafen rekonstruiert, die eine TPVR aufwiesen. Die Querschnittsfläche, der Umfang und die Durchmesserverformungen über den Herzzyklus wurden in fünf Ebenen der Landezone aus der prä- und postoperativen 4D-CTA gemessen. Darüber hinaus wurde die Korrelationsanalyse zwischen dem anatomischen Modell und dem begradigten Modell mittels Pearson-Korrelation und Bland-Altman-Analyse durchgeführt. Ergebnisse: Die klare Struktur jedes Abschnitts vom RVOT bis zur PA wurde am begradigten Modell beobachtet. Sowohl bei der prä- als auch bei der postoperativen 4D-CTA zeigten sich in der RVOT-Ebene während des Herzzyklus signifikante Schwankungen der Querschnittsfläche und des Umfangs. Dennoch wurde auf der Ebene der Klappenhöhlen (Ebene 3a) und der Ebene der sino-tubulären Verbindung (Ebene 4a) im präoperativen CT nahezu keine Verformung der Fläche und des Umfangs beobachtet, genauso wie auf der mittleren Ebene der Stent-Ebene (Ebene 3b) und der oberen Ebene der Stent-Ebene (Ebene 4b) im postoperativen CT. Das begradigte Modell wies eine hohe Korrelation mit dem anatomischen Modell auf. Der Pearson-Korrelationskoeffizient zwischen dem begradigten Modell und dem anatomischen Modell für die Querschnittsfläche, den Umfang, den minimalen Durchmesser und den maximalen Durchmesser lag zwischen 0,77 und 0,99 (P < 0,0001). Die Grenzen der Übereinstimmung aus der Bland-Altman-Analyse lagen in einem guten Bereich, was die große Übereinstimmung zwischen dem begradigten Modell und dem anatomischen Modell weiter bestätigt. Schlussfolgerungen: Das anatomische 4D-CT-Modell kann verwendet werden, um die Verformung der Dynamik zwischen RVOT und PA während des Herzzyklus zu demonstrieren. Das begradigte Modell kann die Veränderungen im Landebereich zeigen, diese Daten genau messen und die Struktur der verschiedenen Abschnitte deutlich darstellen

NOVEL STRATEGIES FOR THE MORPHOLOGICAL AND BIOMECHANICAL ANALYSIS OF THE CARDIAC VALVES BASED ON VOLUMETRIC CLINICAL IMAGES

This work was focused on the morphological and biomechanical analysis of the heart valves exploiting the volumetric data. Novel methods were implemented to perform cardiac valve structure and sub-structure segmentation by defining long axis planes evenly rotated around the long axis of the valve. These methods were exploited to successfully reconstruct the 3D geometry of the mitral, tricuspid and aortic valve structures. Firstly, the reconstructed models were used for the morphological analysis providing a detailed description of the geometry of the valve structures, also computing novel indexes that could improve the description of the valvular apparatus and help their clinical assessment. Additionally, the models obtained for the mitral valve complex were adopted for the development of a novel biomechanical approach to simulate the systolic closure of the valve, relying on highly-efficient mass-spring models thus obtaining a good trade-off between the accuracy and the computational cost of the numerical simulations. In specific: \u2022 First, an innovative and semi-automated method was implemented to generate the 3D model of the aortic valve and of its calcifications, to quantitively describe its 3D morphology and to compute the anatomical aortic valve area (AVA) based on multi-detector computed tomography images. The comparison of the obtained results vs. effective AVA measurements showed a good correlation. Additionally, these methods accounted for asymmetries or anatomical derangements, which would be difficult to correctly capture through either effective AVA or planimetric AVA. \u2022 Second, a tool to quantitively assess the geometry of the tricuspid valve during the cardiac cycle using multidetector CT was developed, in particular focusing on the 3D spatial relationship between the tricuspid annulus and the right coronary artery. The morphological analysis of the annulus and leaflets confirmed data reported in literature. The qualitative and quantitative analysis of the spatial relationship could standardize the analysis protocol and be pivotal in the procedure planning of the percutaneous device implantation that interact with the tricuspid annulus. \u2022 Third, we simulated the systolic closure of three patient specific mitral valve models, derived from CMR datasets, by means of the mass spring model approach. The comparison of the obtained results vs. finite element analyses (considered as the gold-standard) was performed tuning the parameters of the mass spring model, so to obtain the best trade-off between computational expense and accuracy of the results. A configuration mismatch between the two models lower than two times the in-plane resolution of starting imaging data was yielded using a mass spring model set-up that requires, on average, only ten minutes to simulate the valve closure. \u2022 Finally, in the last chapter, we performed a comprehensive analysis which aimed at exploring the morphological and mechanical changes induced by the myxomatous pathologies in the mitral valve tissue. The analysis of mitral valve thickness confirmed the data and patterns reported in literature, while the mechanical test accurately described the behavior of the pathological tissue. A preliminary implementation of this data into finite element simulations suggested that the use of more reliable patient-specific and pathology-specific characterization of the model could improve the realism and the accuracy of the biomechanical simulations

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

Computertomographie-basierte Bestimmung von Aortenklappenkalk und seine Assoziation mit Komplikationen nach interventioneller Aortenklappenimplantation (TAVI)

Background: Severe aortic valve calcification (AVC) has generally been recognized as a key factor in the occurrence of adverse events after transcatheter aortic valve implantation (TAVI). To date, however, a consensus on a standardized calcium detection threshold for aortic valve calcium quantification in contrast-enhanced computed tomography angiography (CTA) is still lacking. The present thesis aimed at comparing two different approaches for quantifying AVC in CTA scans based on their predictive power for adverse events and survival after a TAVI procedure.   Methods: The extensive dataset of this study included 198 characteristics for each of the 965 prospectively included patients who had undergone TAVI between November 2012 and December 2019 at the German Heart Center Berlin (DHZB). AVC quantification in CTA scans was performed at a fixed Hounsfield Unit (HU) threshold of 850 HU (HU 850 approach) and at a patient-specific threshold, where the HU threshold was set by multiplying the mean luminal attenuation of the ascending aorta by 2 (+100 % HUAorta approach). The primary endpoint of this study consisted of a combination of post-TAVI outcomes (paravalvular leak ≥ mild, implant-related conduction disturbances, 30-day mortality, post-procedural stroke, annulus rupture, and device migration). The Akaike information criterion was used to select variables for the multivariable regression model. Multivariable analysis was carried out to determine the predictive power of the investigated approaches.   Results: Multivariable analyses showed that a fixed threshold of 850 HU (calcium volume cut-off 146 mm3) was unable to predict the composite clinical endpoint post-TAVI (OR=1.13, 95 % CI 0.87 to 1.48, p=0.35). In contrast, the +100 % HUAorta approach (calcium volume cut-off 1421 mm3) enabled independent prediction of the composite clinical endpoint post-TAVI (OR=2, 95 % CI 1.52 to 2.64, p=9.2x10-7). No significant difference in the Kaplan-Meier survival analysis was observed for either of the approaches.   Conclusions: The patient-specific calcium detection threshold +100 % HUAorta is more predictive of post-TAVI adverse events included in the combined clinical endpoint than the fixed HU 850 approach. For the +100 % HUAorta approach, a calcium volume cut-off of 1421 mm3 of the aortic valve had the highest predictive value.Hintergrund: Ein wichtiger Auslöser von Komplikationen nach einer Transkatheter-Aortenklappen-Implantation (TAVI) sind ausgeprägte Kalkablagerung an der Aortenklappe. Dennoch erfolgte bisher keine Einigung auf ein standardisiertes Messverfahren zur Quantifizierung der Kalklast der Aortenklappe in einer kontrastverstärkten dynamischen computertomographischen Angiographie (CTA). Die vorliegende Dissertation untersucht, inwieweit die Wahl des Analyseverfahrens zur Quantifizierung von Kalkablagerungen in der Aortenklappe die Prognose von Komplikationen und der Überlebensdauer nach einer TAVI beeinflusst.   Methodik: Der Untersuchung liegt ein umfangreicher Datensatz von 965 Patienten mit 198 Merkmalen pro Patienten zugrunde, welche sich zwischen 2012 und 2019 am Deutschen Herzzentrum Berlin einer TAVI unterzogen haben. Die Quantifizierung der Kalkablagerung an der Aortenklappe mittels CTA wurde einerseits mit einem starren Grenzwert von 850 Hounsfield Einheiten (HU) (HU 850 Verfahren) und andererseits anhand eines individuellen Grenzwertes bemessen. Letzterer ergibt sich aus der HU-Dämpfung in dem Lumen der Aorta ascendens multipliziert mit 2 (+100 % HUAorta Verfahren). Der primäre klinische Endpunkt dieser Dissertation besteht aus einem aus sechs Variablen zusammengesetzten klinischen Endpunkt, welcher ungewünschte Ereignisse nach einer TAVI abbildet (paravalvuläre Leckage ≥mild, Herzrhythmusstörungen nach einer TAVI, Tod innerhalb von 30 Tagen, post-TAVI Schlaganfall, Ruptur des Annulus und Prothesendislokation). Mögliche Störfaktoren, die auf das Eintreten der Komplikationen nach TAVI Einfluss haben, wurden durch den Einsatz des Akaike Informationskriterium ermittelt. Um die Vorhersagekraft von Komplikationen nach einer TAVI durch beide Verfahren zu ermitteln, wurde eine multivariate Regressionsanalyse durchgeführt.   Ergebnisse: Die multivariaten logistischen Regressionen zeigen, dass die Messung der Kalkablagerungen anhand der HU 850 Messung (Kalklast Grenzwert von 146 mm3) die Komplikationen und die Überlebensdauer nicht vorhersagen konnten (OR=1.13, 95 % CI 0.87 bis 1.48, p=0.35). Die nach dem +100 % HUAorta Verfahren (Kalklast Grenzwert von 1421 mm3) individualisierte Kalkmessung erwies sich hingegen als sehr aussagekräftig, da hiermit Komplikationen nach einer TAVI signifikant vorhergesagt werden konnten (OR=2, 95 % CI 1.52 bis 2.64, p=9.2x10-7). In Hinblick auf die postoperative Kaplan-Meier Überlebenszeitanalyse kann auch mit dem +100 % HUAorta Verfahren keine Vorhersage getroffen werden.   Fazit: Aus der Dissertation ergibt sich die Empfehlung, die Messung von Kalkablagerungen nach dem +100 % HUAorta Verfahren vorzunehmen, da Komplikationen wesentlich besser und zuverlässiger als nach der gängigen HU 850 Messmethode vorhergesagt werden können. Für das +100 % HUAorta Verfahren lag der optimale Kalklast Grenzwert bei 1421 mm3

The Role of Visualization, Force Feedback, and Augmented Reality in Minimally Invasive Heart Valve Repair

New cardiovascular techniques have been developed to address the unique requirements of high risk, elderly, surgical patients with heart valve disease by avoiding both sternotomy and cardiopulmonary bypass. However, these technologies pose new challenges in visualization, force application, and intracardiac navigation. Force feedback and augmented reality (AR) can be applied to minimally invasive mitral valve repair and transcatheter aortic valve implantation (TAVI) techniques to potentially surmount these challenges. Our study demonstrated shorter operative times with three dimensional (3D) visualization compared to two dimensional (2D) visualization; however, both experts and novices applied significantly more force to cardiac tissue during 3D robotics-assisted mitral valve annuloplasty than during conventional open mitral valve annuloplasty. This finding suggests that 3D visualization does not fully compensate for the absence of haptic feedback in robotics-assisted cardiac surgery. Subsequently, using an innovative robotics-assisted surgical system design, we determined that direct haptic feedback may improve both expert and trainee performance using robotics-assisted techniques. We determined that during robotics-assisted mitral valve annuloplasty the use of either visual or direct force feedback resulted in a significant decrease in forces applied to cardiac tissue when compared to robotics-assisted mitral valve annuloplasty without force feedback. We presented NeoNav, an AR-enhanced echocardiograpy intracardiac guidance system for NeoChord off-pump mitral valve repair. Our study demonstrated superior tool navigation accuracy, significantly shorter navigation times, and reduced potential for injury with AR enhanced intracardiac navigation for off-pump transapical mitral valve repair with neochordae implantation. In addition, we applied the NeoNav system as a safe and inexpensive alternative imaging modality for TAVI guidance. We found that our proposed AR guidance system may achieve similar or better results than the current standard of care, contrast enhanced fluoroscopy, while eliminating the use of nephrotoxic contrast and ionizing radiation. These results suggest that the addition of both force feedback and augmented reality image guidance can improve both surgical performance and safety during minimally invasive robotics assisted and beating heart valve surgery, respectively