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

Exploiting Temporal Image Information in Minimally Invasive Surgery

Minimally invasive procedures rely on medical imaging instead of the surgeons direct vision. While preoperative images can be used for surgical planning and navigation, once the surgeon arrives at the target site real-time intraoperative imaging is needed. However, acquiring and interpreting these images can be challenging and much of the rich temporal information present in these images is not visible. The goal of this thesis is to improve image guidance for minimally invasive surgery in two main areas. First, by showing how high-quality ultrasound video can be obtained by integrating an ultrasound transducer directly into delivery devices for beating heart valve surgery. Secondly, by extracting hidden temporal information through video processing methods to help the surgeon localize important anatomical structures. Prototypes of delivery tools, with integrated ultrasound imaging, were developed for both transcatheter aortic valve implantation and mitral valve repair. These tools provided an on-site view that shows the tool-tissue interactions during valve repair. Additionally, augmented reality environments were used to add more anatomical context that aids in navigation and in interpreting the on-site video. Other procedures can be improved by extracting hidden temporal information from the intraoperative video. In ultrasound guided epidural injections, dural pulsation provides a cue in finding a clear trajectory to the epidural space. By processing the video using extended Kalman filtering, subtle pulsations were automatically detected and visualized in real-time. A statistical framework for analyzing periodicity was developed based on dynamic linear modelling. In addition to detecting dural pulsation in lumbar spine ultrasound, this approach was used to image tissue perfusion in natural video and generate ventilation maps from free-breathing magnetic resonance imaging. A second statistical method, based on spectral analysis of pixel intensity values, allowed blood flow to be detected directly from high-frequency B-mode ultrasound video. Finally, pulsatile cues in endoscopic video were enhanced through Eulerian video magnification to help localize critical vasculature. This approach shows particular promise in identifying the basilar artery in endoscopic third ventriculostomy and the prostatic artery in nerve-sparing prostatectomy. A real-time implementation was developed which processed full-resolution stereoscopic video on the da Vinci Surgical System

Augmented Image-Guidance for Transcatheter Aortic Valve Implantation

The introduction of transcatheter aortic valve implantation (TAVI), an innovative stent-based technique for delivery of a bioprosthetic valve, has resulted in a paradigm shift in treatment options for elderly patients with aortic stenosis. While there have been major advancements in valve design and access routes, TAVI still relies largely on single-plane fluoroscopy for intraoperative navigation and guidance, which provides only gross imaging of anatomical structures. Inadequate imaging leading to suboptimal valve positioning contributes to many of the early complications experienced by TAVI patients, including valve embolism, coronary ostia obstruction, paravalvular leak, heart block, and secondary nephrotoxicity from contrast use. A potential method of providing improved image-guidance for TAVI is to combine the information derived from intra-operative fluoroscopy and TEE with pre-operative CT data. This would allow the 3D anatomy of the aortic root to be visualized along with real-time information about valve and prosthesis motion. The combined information can be visualized as a `merged\u27 image where the different imaging modalities are overlaid upon each other, or as an `augmented\u27 image, where the location of key target features identified on one image are displayed on a different imaging modality. This research develops image registration techniques to bring fluoroscopy, TEE, and CT models into a common coordinate frame with an image processing workflow that is compatible with the TAVI procedure. The techniques are designed to be fast enough to allow for real-time image fusion and visualization during the procedure, with an intra-procedural set-up requiring only a few minutes. TEE to fluoroscopy registration was achieved using a single-perspective TEE probe pose estimation technique. The alignment of CT and TEE images was achieved using custom-designed algorithms to extract aortic root contours from XPlane TEE images, and matching the shape of these contours to a CT-derived surface model. Registration accuracy was assessed on porcine and human images by identifying targets (such as guidewires or coronary ostia) on the different imaging modalities and measuring the correspondence of these targets after registration. The merged images demonstrated good visual alignment of aortic root structures, and quantitative assessment measured an accuracy of less than 1.5mm error for TEE-fluoroscopy registration and less than 6mm error for CT-TEE registration. These results suggest that the image processing techniques presented have potential for development into a clinical tool to guide TAVI. Such a tool could potentially reduce TAVI complications, reducing morbidity and mortality and allowing for a safer procedure

3D Printing and Engineering Tools Relevant to Plan a Transcatheter Procedure

Advance cardiac imaging techniques such as three-dimensional (3D) printing technology and engineering tools have experienced a rapid development over the last decade in many surgical and interventional settings. In presence of complex cardiac and extra-cardiac anatomies, the creation of a physical, patient-specific model is useful to better understand the anatomical spatial relationships and formulate the best surgical or interventional plan. Although many case reports and small series have been published over this topic, at the present time, there is still a lack of strong scientific evidence of the benefit of 3D models and advance engineering tools, including virtual and augmented reality, in clinical practice and only qualitative evaluation of the models has been used to investigate their clinical use. Patient-specific 3D models can be printed in many different materials including rigid, flexible and transparent materials, depending on their application. To plan interventional procedure, transparent materials may be preferred in order to better evaluate the device or stent landing zone. 3D models can also be used as an input for augmented and virtual reality application and advance fluido-dynamic simulation, which aim to support the interventional cardiologist before entering the cath lab. The aim of this chapter is to present an overview on how 3D printing, extended reality platforms and the most common computational engineering methodologies"finite element and computational fluid dynamics"are currently used to support percutaneous procedures in congenital heart disease (CHD), with examples from the scientific literature

Dynamic Image Processing for Guidance of Off-pump Beating Heart Mitral Valve Repair

Compared to conventional open heart procedures, minimally invasive off-pump beating heart mitral valve repair aims to deliver equivalent treatment for mitral regurgitation with reduced trauma and side effects. However, minimally invasive approaches are often limited by the lack of a direct view to surgical targets and/or tools, a challenge that is compounded by potential movement of the target during the cardiac cycle. For this reason, sophisticated image guidance systems are required in achieving procedural efficiency and therapeutic success. The development of such guidance systems is associated with many challenges. For example, the system should be able to provide high quality visualization of both cardiac anatomy and motion, as well as augmenting it with virtual models of tracked tools and targets. It should have the capability of integrating pre-operative images to the intra-operative scenario through registration techniques. The computation speed must be sufficiently fast to capture the rapid cardiac motion. Meanwhile, the system should be cost effective and easily integrated into standard clinical workflow. This thesis develops image processing techniques to address these challenges, aiming to achieve a safe and efficient guidance system for off-pump beating heart mitral valve repair. These techniques can be divided into two categories, using 3D and 2D image data respectively. When 3D images are accessible, a rapid multi-modal registration approach is proposed to link the pre-operative CT images to the intra-operative ultrasound images. The ultrasound images are used to display the real time cardiac motion, enhanced by CT data serving as high quality 3D context with annotated features. I also developed a method to generate synthetic dynamic CT images, aiming to replace real dynamic CT data in such a guidance system to reduce the radiation dose applied to the patients. When only 2D images are available, an approach is developed to track the feature of interest, i.e. the mitral annulus, based on bi-plane ultrasound images and a magnetic tracking system. The concept of modern GPU-based parallel computing is employed in most of these approaches to accelerate the computation in order to capture the rapid cardiac motion with desired accuracy. Validation experiments were performed on phantom, animal and human data. The overall accuracy of registration and feature tracking with respect to the mitral annulus was about 2-3mm with computation time of 60-400ms per frame, sufficient for one update per cardiac cycle. It was also demonstrated in the results that the synthetic CT images can provide very similar anatomical representations and registration accuracy compared to that of the real dynamic CT images. These results suggest that the approaches developed in the thesis have good potential for a safer and more effective guidance system for off-pump beating heart mitral valve repair

Development of a Surgical Assistance System for Guiding Transcatheter Aortic Valve Implantation

Development of image-guided interventional systems is growing up rapidly in the recent years. These new systems become an essential part of the modern minimally invasive surgical procedures, especially for the cardiac surgery. Transcatheter aortic valve implantation (TAVI) is a recently developed surgical technique to treat severe aortic valve stenosis in elderly and high-risk patients. The placement of stented aortic valve prosthesis is crucial and typically performed under live 2D fluoroscopy guidance. To assist the placement of the prosthesis during the surgical procedure, a new fluoroscopy-based TAVI assistance system has been developed. The developed assistance system integrates a 3D geometrical aortic mesh model and anatomical valve landmarks with live 2D fluoroscopic images. The 3D aortic mesh model and landmarks are reconstructed from interventional angiographic and fluoroscopic C-arm CT system, and a target area of valve implantation is automatically estimated using these aortic mesh models. Based on template-based tracking approach, the overlay of visualized 3D aortic mesh model, landmarks and target area of implantation onto fluoroscopic images is updated by approximating the aortic root motion from a pigtail catheter motion without contrast agent. A rigid intensity-based registration method is also used to track continuously the aortic root motion in the presence of contrast agent. Moreover, the aortic valve prosthesis is tracked in fluoroscopic images to guide the surgeon to perform the appropriate placement of prosthesis into the estimated target area of implantation. An interactive graphical user interface for the surgeon is developed to initialize the system algorithms, control the visualization view of the guidance results, and correct manually overlay errors if needed. Retrospective experiments were carried out on several patient datasets from the clinical routine of the TAVI in a hybrid operating room. The maximum displacement errors were small for both the dynamic overlay of aortic mesh models and tracking the prosthesis, and within the clinically accepted ranges. High success rates of the developed assistance system were obtained for all tested patient datasets. The results show that the developed surgical assistance system provides a helpful tool for the surgeon by automatically defining the desired placement position of the prosthesis during the surgical procedure of the TAVI.Die Entwicklung bildgeführter interventioneller Systeme wächst rasant in den letzten Jahren. Diese neuen Systeme werden zunehmend ein wesentlicher Bestandteil der technischen Ausstattung bei modernen minimal-invasiven chirurgischen Eingriffen. Diese Entwicklung gilt besonders für die Herzchirurgie. Transkatheter Aortenklappen-Implantation (TAKI) ist eine neue entwickelte Operationstechnik zur Behandlung der schweren Aortenklappen-Stenose bei alten und Hochrisiko-Patienten. Die Platzierung der Aortenklappenprothese ist entscheidend und wird in der Regel unter live-2D-fluoroskopischen Bildgebung durchgeführt. Zur Unterstützung der Platzierung der Prothese während des chirurgischen Eingriffs wurde in dieser Arbeit ein neues Fluoroskopie-basiertes TAKI Assistenzsystem entwickelt. Das entwickelte Assistenzsystem überlagert eine 3D-Geometrie des Aorten-Netzmodells und anatomischen Landmarken auf live-2D-fluoroskopische Bilder. Das 3D-Aorten-Netzmodell und die Landmarken werden auf Basis der interventionellen Angiographie und Fluoroskopie mittels eines C-Arm-CT-Systems rekonstruiert. Unter Verwendung dieser Aorten-Netzmodelle wird das Zielgebiet der Klappen-Implantation automatisch geschätzt. Mit Hilfe eines auf Template Matching basierenden Tracking-Ansatzes wird die Überlagerung des visualisierten 3D-Aorten-Netzmodells, der berechneten Landmarken und der Zielbereich der Implantation auf fluoroskopischen Bildern korrekt überlagert. Eine kompensation der Aortenwurzelbewegung erfolgt durch Bewegungsverfolgung eines Pigtail-Katheters in Bildsequenzen ohne Kontrastmittel. Eine starrere Intensitätsbasierte Registrierungsmethode wurde verwendet, um kontinuierlich die Aortenwurzelbewegung in Bildsequenzen mit Kontrastmittelgabe zu detektieren. Die Aortenklappenprothese wird in die fluoroskopischen Bilder eingeblendet und dient dem Chirurg als Leitfaden für die richtige Platzierung der realen Prothese. Eine interaktive Benutzerschnittstelle für den Chirurg wurde zur Initialisierung der Systemsalgorithmen, zur Steuerung der Visualisierung und für manuelle Korrektur eventueller Überlagerungsfehler entwickelt. Retrospektive Experimente wurden an mehreren Patienten-Datensätze aus der klinischen Routine der TAKI in einem Hybrid-OP durchgeführt. Hohe Erfolgsraten des entwickelten Assistenzsystems wurden für alle getesteten Patienten-Datensätze erzielt. Die Ergebnisse zeigen, dass das entwickelte chirurgische Assistenzsystem ein hilfreiches Werkzeug für den Chirurg bei der Platzierung Position der Prothese während des chirurgischen Eingriffs der TAKI bietet

Towards fluoro-free interventions: Using radial intracardiac ultrasound for vascular navigation

Transcatheter cardio-vascular interventions have the advantage of patient safety,reduced surgery time, and minimal trauma to the patient\u27s body. Transcathetherinterventions, which are performed percutaneously, suffer from the lack of direct line-of-sight with the surgical tools and the patient anatomy. Therefore, such interventionalprocedures rely heavily on image guidance for navigating towards and deliveringtherapy at the target site. Vascular navigation via the inferior vena cava (IVC), from thegroin to the heart, is an imperative part of most transcatheter cardiovascularinterventions such as valve repair surgeries and ablation therapy. Traditionally, the IVCis navigated using fluoroscopic techniques such as angiography or CT venography.These X-ray based techniques can have detrimental effects on the patient as well asthe surgical team, causing increased radiation exposure, increased risk of cancer, fetaldefects, eye cataracts. The use of heavy lead apron has also been reported to causeback pain and spine issues thus leading to interventionalist’s disc disease. We proposethe use of a catheter-based ultrasound augmented with electromagnetic (EM) trackingtechnology to generate a vascular roadmap in real-time and perform navigation withoutharmful radiation. In this pilot study, we use intracardiac echocardiography (ICE) and tracking technology to reconstruct a vessel from a phantom in a 3D virtual space. Thispaper presents a pilot phantom study on ICE-based vessel reconstruction anddemonstrates how the proposed ultrasound-based navigation will appear in a virtualspace, by navigating a tracked guidewire within the vessels in the phantom without anyradiation-based imaging. The geometric accuracy is assessed using a CT scan of thephantom, with a Dice coefficient of 0.79. The average distance between the surface ofthe two models comes out to be 1.7 ± 1.12mm

Artificial Intelligence, Computational Simulations, and Extended Reality in Cardiovascular Interventions

Artificial intelligence, computational simulations, and extended reality, among other 21st century computational technologies, are changing the health care system. To collectively highlight the most recent advances and benefits of artificial intelligence, computational simulations, and extended reality in cardiovascular therapies, we coined the abbreviation AISER. The review particularly focuses on the following applications of AISER: 1) preprocedural planning and clinical decision making; 2) virtual clinical trials, and cardiovascular device research, development, and regulatory approval; and 3) education and training of interventional health care professionals and medical technology innovators. We also discuss the obstacles and constraints associated with the application of AISER technologies, as well as the proposed solutions. Interventional health care professionals, computer scientists, biomedical engineers, experts in bioinformatics and visualization, the device industry, ethics committees, and regulatory agencies are expected to streamline the use of AISER technologies in cardiovascular interventions and medicine in general

Semiautonomous Robotic Manipulator for Minimally Invasive Aortic Valve Replacement

Aortic valve surgery is the preferred procedure for replacing a damaged valve with an artificial one. The ValveTech robotic platform comprises a flexible articulated manipulator and surgical interface supporting the effective delivery of an artificial valve by teleoperation and endoscopic vision. This article presents our recent work on force-perceptive, safe, semiautonomous navigation of the ValveTech platform prior to valve implantation. First, we present a force observer that transfers forces from the manipulator body and tip to a haptic interface. Second, we demonstrate how hybrid forward/inverse mechanics, together with endoscopic visual servoing, lead to autonomous valve positioning. Benchtop experiments and an artificial phantom quantify the performance of the developed robot controller and navigator. Valves can be autonomously delivered with a 2.0±0.5 mm position error and a minimal misalignment of 3.4±0.9°. The hybrid force/shape observer (FSO) algorithm was able to predict distributed external forces on the articulated manipulator body with an average error of 0.09 N. FSO can also estimate loads on the tip with an average accuracy of 3.3%. The presented system can lead to better patient care, delivery outcome, and surgeon comfort during aortic valve surgery, without requiring sensorization of the robot tip, and therefore obviating miniaturization constraints.</p