770 research outputs found

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

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    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

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

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    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

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

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    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

    Exploiting Temporal Image Information in Minimally Invasive Surgery

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    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

    3D Localization of Vena Contracta using Doppler ICE Imaging in Tricuspid Valve Interventions

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    PURPOSE: Tricuspid valve (TV) interventions face the challenge of imaging the anatomy and tools because of the ‘TEE-unfriendly’ nature of the TV. In edge-to-edge TV repair, a core step is to position the clip perpendicular to the coaptation gap. In this study, we provide a semi-automated method to localize the VC from Doppler intracardiac echo (ICE) imaging in a tracked 3D space, thus providing a pre-mapped location of the coaptation gap to assist device positioning. METHODS: A magnetically tracked ICE probe with Doppler imaging capabilities is employed in this study for imaging three patient-specific TVs placed in a pulsatile heart phantom. For each of the valves, the ICE probe is positioned to image the maximum regurgitant flow for five cardiac cycles. An algorithm then extracts the regurgitation imaging and computes the exact location of the vena contracta on the image. RESULTS: Across the three pathological, patient-specific valves, the average distance error between the detected VC and the ground truth model is [Formula: see text] mm. For each of the valves, one case represented the outlier where the algorithm misidentified the vena contracta to be near the annulus. In such cases, it is recommended to retake the five-second imaging data. CONCLUSION: This study presented a method for ultrasound-based localization of vena contracta in 3D space. Mapping such anatomical landmarks has the potential to assist with device positioning and to simplify tricuspid valve interventions by providing more contextual information to the interventionalists, thus enhancing their spatial awareness. Additionally, ICE can be used to provide live US and Doppler imaging of the complex TV anatomy throughout the procedure

    INTERFACE DESIGN FOR A VIRTUAL REALITY-ENHANCED IMAGE-GUIDED SURGERY PLATFORM USING SURGEON-CONTROLLED VIEWING TECHNIQUES

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    Initiative has been taken to develop a VR-guided cardiac interface that will display and deliver information without affecting the surgeons’ natural workflow while yielding better accuracy and task completion time than the existing setup. This paper discusses the design process, the development of comparable user interface prototypes as well as an evaluation methodology that can measure user performance and workload for each of the suggested display concepts. User-based studies and expert recommendations are used in conjunction to es­ tablish design guidelines for our VR-guided surgical platform. As a result, a better understanding of autonomous view control, depth display, and use of virtual context, is attained. In addition, three proposed interfaces have been developed to allow a surgeon to control the view of the virtual environment intra-operatively. Comparative evaluation of the three implemented interface prototypes in a simulated surgical task scenario, revealed performance advantages for stereoscopic and monoscopic biplanar display conditions, as well as the differences between three types of control modalities. One particular interface prototype demonstrated significant improvement in task performance. Design recommendations are made for this interface as well as the others as we prepare for prospective development iterations

    Investigation and Validation of Imaging Techniques for Mitral Valve Disease Diagnosis and Intervention

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    Mitral Valve Disease (MVD) describes a variety of pathologies that result in regurgitation of blood during the systolic phase of the cardiac cycle. Decisions in valvular disease management rely heavily on non-invasive imaging. Transesophageal echocardiography (TEE) is widely recognized as the key evaluation technique where backflow of high velocity blood can be visualized under Doppler. In most cases, TEE imaging is adequate for identifying mitral valve pathology, though the modality is often limited from signal dropout, artifacts and a restricted field of view. Quantitative analysis is an integral part of the overall assessment of valve morphology and gives objective evidence for both classification and guiding intervention of regurgitation. In addition, patient-specific models derived from diagnostic TEE images allow clinicians to gain insight into uniquely intricate anatomy prior to surgery. However, the heavy reliance on TEE segmentation for diagnosis and modelling has necessitated an evaluation of the accuracy of the oft-used mitral valve imaging modality. Dynamic cardiac 4D-Computed Tomography (4D-CT) is emerging as a valuable tool for diagnosis, quantification and assessment of cardiac diseases. This modality has the potential to provide a high quality rendering of the mitral valve and subvalvular apparatus, to provide a more complete picture of the underlying morphology. However, application of dynamic CT to mitral valve imaging is especially challenging due to the large and rapid motion of the valve leaflets. It is therefore necessary to investigate the accuracy and level of precision by which dynamic CT captures mitral valve motion throughout the cardiac cycle. To do this, we design and construct a silicone and bovine quasi-static mitral valve phantom which can simulate a range of ECG-gated heart rates and reproduce physiologic valve motion over the cardiac cycle. In this study, we discovered that the dynamic CT accurately captures the underlying valve movement, but with a higher prevalence of image artifacts as leaflet and chordae motion increases due to elevated heart rates. In a subsequent study, we acquire simultaneous CT and TEE images of both a silicone mitral valve phantom and an iodine-stained bovine mitral valve. We propose a pipeline to use CT as the ground truth to study the relationship between TEE intensities and the underlying valve morphology. Preliminary results demonstrate that with an optimized threshold selection based solely on TEE pixel intensities, only 40\% of pixels are correctly classified as part of the valve. In addition, we have shown that emphasizing the centre-line rather than the boundaries of high intensity TEE image regions provides a better representation and segmentation of the valve morphology. This work has the potential to inform and augment the use of TEE for diagnosis and modelling of the mitral valve in the clinical workflow for MVD
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