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

A Platform for Robot-Assisted Intracardiac Catheter Navigation

Steerable catheters are routinely deployed in the treatment of cardiac arrhythmias. During invasive electrophysiology studies, the catheter handle is manipulated by an interventionalist to guide the catheter's distal section toward endocardium for pacing and ablation. Catheter manipulation requires dexterity and experience, and exposes the interventionalist to ionizing radiation. Through the course of this research, a platform was developed to assist and enhance the navigation of the catheter inside the cardiac chambers. This robotic platform replaces the interventionalist's hand in catheter manipulation and provides the option to force the catheter tip in arbitrary directions using a 3D input device or to automatically navigate the catheter to desired positions within a cardiac chamber by commanding the software to do so. To accomplish catheter navigation, the catheter was modeled as a continuum manipulator, and utilizing robot kinematics, catheter tip position control was designed and implemented. An electromagnetic tracking system was utilized to measure the position and orientation of two key points in catheter model, for position feedback to the control system. A software platform was developed to implement the navigation and control strategies and to interface with the robot, the 3D input device and the tracking system. The catheter modeling was validated through in-vitro experiments with a static phantom, and in-vivo experiments on three live swines. The feasibility of automatic navigation was also veri ed by navigating to three landmarks in the beating heart of swine subjects, and comparing their performance with that of an experienced interventionalist using quasi biplane fluoroscopy. The platform realizes automatic, assisted, and motorized navigation under the interventionalist's control, thus reducing the dependence of successful navigation on the dexterity and manipulation skills of the interventionalist, and providing a means to reduce the exposure to X-ray radiation. Upon further development, the platform could be adopted for human deployment

Autonomous robotic intracardiac catheter navigation using haptic vision

International audienceWhile all minimally invasive procedures involve navigating from a small incision in the skin to the site of the intervention, it has not been previously demonstrated how this can be done 10 autonomously. To show that autonomous navigation is possible, we investigated it in the hardest place to do it-inside the beating heart. We created a robotic catheter that can navigate through the blood-filled heart using wall-following algorithms inspired by positively thigmotactic animals. The catheter employs haptic vision, a hybrid sense using imaging for both touch-based surface identification and force sensing, to accomplish wall following inside the blood-filled heart. 15 Through in vivo animal experiments, we demonstrate that the performance of an autonomously-controlled robotic catheter rivals that of an experienced clinician. Autonomous navigation is a fundamental capability on which more sophisticated levels of autonomy can be built, e.g., to perform a procedure. Similar to the role of automation in fighter aircraft, such capabilities can free the clinician to focus on the most critical aspects of the procedure while providing precise and 20 repeatable tool motions independent of operator experience and fatigue

Learning Analysis-by-Synthesis for 6D Pose Estimation in RGB-D Images

Analysis-by-synthesis has been a successful approach for many tasks in computer vision, such as 6D pose estimation of an object in an RGB-D image which is the topic of this work. The idea is to compare the observation with the output of a forward process, such as a rendered image of the object of interest in a particular pose. Due to occlusion or complicated sensor noise, it can be difficult to perform this comparison in a meaningful way. We propose an approach that "learns to compare", while taking these difficulties into account. This is done by describing the posterior density of a particular object pose with a convolutional neural network (CNN) that compares an observed and rendered image. The network is trained with the maximum likelihood paradigm. We observe empirically that the CNN does not specialize to the geometry or appearance of specific objects, and it can be used with objects of vastly different shapes and appearances, and in different backgrounds. Compared to state-of-the-art, we demonstrate a significant improvement on two different datasets which include a total of eleven objects, cluttered background, and heavy occlusion.Comment: 16 pages, 8 figure

Virtual and Augmented Reality Techniques for Minimally Invasive Cardiac Interventions: Concept, Design, Evaluation and Pre-clinical Implementation

While less invasive techniques have been employed for some procedures, most intracardiac interventions are still performed under cardiopulmonary bypass, on the drained, arrested heart. The progress toward off-pump intracardiac interventions has been hampered by the lack of adequate visualization inside the beating heart. This thesis describes the development, assessment, and pre-clinical implementation of a mixed reality environment that integrates pre-operative imaging and modeling with surgical tracking technologies and real-time ultrasound imaging. The intra-operative echo images are augmented with pre-operative representations of the cardiac anatomy and virtual models of the delivery instruments tracked in real time using magnetic tracking technologies. As a result, the otherwise context-less images can now be interpreted within the anatomical context provided by the anatomical models. The virtual models assist the user with the tool-to-target navigation, while real-time ultrasound ensures accurate positioning of the tool on target, providing the surgeon with sufficient information to ``see\u27\u27 and manipulate instruments in absence of direct vision. Several pre-clinical acute evaluation studies have been conducted in vivo on swine models to assess the feasibility of the proposed environment in a clinical context. Following direct access inside the beating heart using the UCI, the proposed mixed reality environment was used to provide the necessary visualization and navigation to position a prosthetic mitral valve on the the native annulus, or to place a repair patch on a created septal defect in vivo in porcine models. Following further development and seamless integration into the clinical workflow, we hope that the proposed mixed reality guidance environment may become a significant milestone toward enabling minimally invasive therapy on the beating heart

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

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