We present a method for real-time, freehand 3D ultrasound (3D-US) reconstruction of moving anatomy, with specific application towards guiding the catheter ablation procedure in the left atrium. Using an intracardiac echo (ICE) catheter with a pose (position/orientation) sensor mounted to its tip, we continually mosaic 2D-ICE images of a left atrium phantom model to form a 3D-US volume. Our mosaicing strategy employs a probabilistic framework based on simultaneous localization and mapping (SLAM), a technique commonly used in mobile robotics for creating maps of unexplored environments. The measured ICE catheter tip pose provides an initial estimate for compounding 2D-ICE image data into the 3D-US volume. However, we simultaneously consider the overlap-consistency shared between 2D-ICE images and the 3D-US volume, computing a "corrected" tip pose if need be to ensure spatially-consistent reconstruction. This allows us to compensate for anatomic movement and sensor drift that would otherwise cause motion artifacts in the 3D-US volume. Our approach incorporates 2D-ICE data immediately after acquisition, allowing us to continuously update the registration parameters linking sensor coordinates to 3D-US coordinates. This, in turn, enables real-time localization and display of sensorized therapeutic catheters within the 3D-US volume for facilitating procedural guidance.

To successfully perform minimally invasive surgical procedures, physicians must be able to visualize their instruments inside the anatomy. Unfortunately, guidance facilities for several such procedures are limited; this is especially true in the cardiac setting. The two imaging modalities which provide the most-detailed views of the anatomy—computed tomography (CT) and magnetic resonance (MR)—are presently not well-suited for guiding cardiac interventions. Ultrasound, by contrast, provides real-time imaging without radiation exposure, but its field-of-view and ability to discriminate between tissues are limited. This dissertation presents a set of novel registration algorithms that fuse intracardiac ultrasound, pre-operative CT/MR, and electromagnetic position sensing data to create a "virtual surgical environment," allowing physicians to visualize their instruments inside a detailed surface mesh model of the anatomy. These algorithms are based on principles taken from robotic localization and mapping—a well-developed set of techniques used to locate mobile robots within and construct maps of their environment. Here, the mobile robot is an ultrasound imaging probe tracked by a position sensing system, and its environment is the heart. By localizing the ultrasound probe inside the heart, other instruments tracked by the position sensing system are localized as well. The ultrasound probe is then used to maintain localization for the duration of the procedure. We evaluate the performance of these algorithms in three clinically-relevant scenarios. First, we assume that an anatomic surface mesh whose shape matches that of the intraoperative anatomy can be obtained by segmenting pre-operative CT/MR; the surface mesh is then used as a "reference map" while the ultrasound probe "navigates" inside the heart. Localization within the reference map is equated to localization within the anatomy because of their assumed identical structure. Next, we relax our assumption that the pre-operative surface mesh and intra-operative anatomy are identically-shaped. This scenario is more realistic because pre-operative image data is typically "out-of-date" at the start of the procedure. We localize the ultrasound probe within the outdated reference map, and use acquired ultrasound data to either construct a new map, or update the outdated map. Finally, we assume that pre-operative CT/MR was not acquired. A reference map must be created from scratch during the procedure while simultaneously localizing the ultrasound probe within the map. Our algorithms are fast, automatic, and accurate, ensuring that tissue contact in the anatomy is properly indicated inside the virtual model. Furthermore, ultrasound probe localization is updated continuously to compensate for dynamic phenomena that occur during the procedure, including patient motion. In achieving the above, we have created a catheter guidance system that enables cardiologists to operate in an accurate virtual surgical environment which is created rapidly, robust to real world perturbations, and equally easy-to-visualize as three-dimensional CT and MR.

We present a method for catheter localization in the left atrium based on the unscented particle filter (UPF), a Monte Carlo method employed in stochastic state estimation. Using an intracardiac echo (ICE) ultrasound catheter, we acquire ultrasound images of the atrium from multiple configurations and iteratively determine the catheter’s pose with respect to anatomy. At each time step, the catheter’s change in pose is determined using either a six-degree-of-freedom electromagnetic pose sensor or a robotic guide catheter whose kinematics serve as a pseudo-pose measurement. Sensor and kinematic model uncertainties are explicitly considered when computing the localization estimate. Acquired ultrasound images are compared with simulated ultrasound images based on segmented computed tomography (CT) or magnetic resonance (MR) data of the left atrium. The results of these comparisons are used to refine the localization estimate. After considering less than 30 seconds’ worth of ICE data, our algorithm converges to an accurate pose estimate. Furthermore, our algorithm is robust to sensor drift and kinematic model errors, as well as gradual, unmodeled movements in the anatomy. Such problems typically complicate traditional image-based localization.

Introduction The catheter ablation procedure is a minimally invasive surgery used to treat atrial fibrillation. Difficulty visualizing the catheter inside the left atrium anatomy has led to lengthy procedure times and limited success rates. In this paper, we present a set of algorithms for reconstructing 3D ultrasound data of the left atrium in real-time, with an emphasis on automatic tissue classification for improved clarity surrounding regions of interest.Methods Using an intracardiac echo (ICE) ultrasound catheter, we collect 2D-ICE images of a left atrium phantom from multiple configurations and iteratively compound the acquired data into a 3D-ICE volume. We introduce two new methods for compounding overlapping US data-occupancy-likelihood and response-grid compounding-which automatically classify voxels as "occupied" or "clear," and mitigate reconstruction artifacts caused by signal dropout. Finally, we use the results of an ICE-to-CT registration algorithm to devise a response-likelihood weighting scheme, which assigns weights to US signals based on the likelihood that they correspond to tissue-reflections.Results Our algorithms successfully reconstruct a 3D-ICE volume of the left atrium with voxels classified as "occupied" or " clear," even within difficult-to-image regions like the pulmonary vein openings. We are robust to dropout artifact that plagues a subset of the 2D-ICE images, and our weighting scheme assists in filtering out spurious data attributed to ghost-signals from multi-path reflections. By automatically classifying tissue, our algorithm precludes the need for thresholding, a process that is difficult to automate without subjective input. Our hope is to use this result towards developing 3D ultrasound segmentation algorithms in the future.

We present a method for registering real-time ultrasound of the left atrium to an outdated, anatomic surface mesh model, whose shape differs from that of the anatomy. Using an intracardiac echo (ICE) catheter with mounted 6DOF electromagnetic position/orientation sensor (EPS), we acquire images of the left atrium and determine where the ICE catheter must be positioned relative to the surface mesh to generate similar, "virtual" ICE images. Further, we use an affine warping model to infer how the shape of the surface mesh differs from that of the atrium. Our registration and warping algorithm allows us to display EPS-sensorized catheters inside the surface mesh, facilitating guidance for left atrial procedures. By solving for the atrium-to-mesh warping parameters, we ensure that tissue contact in the anatomy is properly displayed as tissue contact in the mesh. After considering less than thirty seconds worth of ICE data, we are able to accurately localize EPS measurements within the surface mesh, despite surface mesh warpings of up to +/-20% along and about the principal axes of the left atrium. Further, because our estimation framework is iterative and continuous, our accuracy improves as new data is acquired.

We present a sensorless method for localizing a, robotic catheter inside the left atrium using intracardiac echo (ICE) ultrasound. As the robotic catheter navigates inside the anatomy, its kinematics provide a rough estimate of change in pose. At the same time, an ICE catheter inserted through the robotic catheter's lumen acquires images to refine this estimate.Our algorithm is based on the Unscented Particle Filter (UPF) for stochastic state estimation. We iteratively determine the catheter's pose by comparing newly acquired ICE images to segmented Computed Tomography (CT) images of the left atrium. After considering less than fifteen second's worth of ICE data, the algorithm converges to an accurate pose estimate despite significant deviations from the kinematic model, and unmodeled movements in the anatomy.

We present a method for registering position and orientation data collected from an electroanatomic mapping system (EMS) to a surface mesh based on segmented Computed Tomography (CT) or Magnetic Resonance (MR) images of the left atrium. Our algorithm is based on the Unscented Particle Filter (UPF) for stochastic state estimation. Using an intracardiac echo (ICE) ultrasound catheter with mounted mapping sensor, we acquire ultrasound images of the atrium from multiple configurations and iteratively determine the catheter's pose with respect to anatomy. After considering less than a minute's worth of ICE data, the algorithm converges to an accurate pose estimate which, in turn, yields the registration parameters transforming EMS coordinates to mesh coordinates. The iterative framework of the UPF allows us to be robust to unmodeled EMS noise and drift, problems which complicate traditional registration methods assuming regularity in image data structure.

There is a growing trend in medicine toward minimally invasive surgery, and. with it comes an increasing need for precise miniature instruments to achieve accurate positioning for complex procedures. Catheter-based surgeries in particular suffer from a lack of active steering of the interventional device. We present a new actuator made by laser machining shape memory alloy (SMA) tubes for use in an active steerable catheter. Using finite element analysis and experimental verification, we have designed an SMA actuator cut from 1.27 mm diameter NiTi tubing that exhibits good fatigue properties and can produce forces up to 2 N at 20% elongation. In this paper, we describe the design and testing of the actuator, as well as its characterization to verify its mechanical properties.

In this paper we discuss a novel shape memory alloy (SMA) actuator for minimally invasive robotic surgery (MIRS). Initial characterizations of this actuator reveal that it is well-suited for MIRS, capable of generating relatively large forces (up to 500 mN) over substantial distances (up to 500mum). We focus our attention on the position control of two actuators in an antagonistic configuration. In particular, we report our developments toward a switching control architecture that minimizes energy consumption and heating of the actuators, in an attempt to extend their useful life. A variable switching control architecture drives a pair of SMA actuators, alternately turning "on" one actuator based on the sign of the position error signal. While such control is robust to model and environment uncertainties, large current amplitudes may increase temperatures excessively and result in limit cycle behavior. To counter these effects, the amplitudes are modulated over distinct error regions. The resulting amplitude-modulating switching control algorithm allows for smooth and robust position control without knowledge of underlying models of the SMA actuator

Minimally invasive medical therapy can reduce both healthcare costs and patient suffering. The development of submillimeter scale instruments falls in a gap of manufacturing technologies between traditional machining and microfabrication techniques. To address this need we have developed a fabrication technique based upon laser machining of tubular structures combined with shaped-memory alloy actuators to create compliant devices for minimally invasive interventions.The initial application of this approach has been to develop a forward viewing intravascular ultrasound scanner for use in guiding intravascular interventions in situations where traditional angiography and intravascular ultrasound are unable to provide adequate guidance. The ultrasound device is less than 1.5 mm in diameter and provides imaging at 20 frames per second. Imaging currently is performed with a 20 MHz 800 micron diameter transducer producing axial resolutions of approximately 150 microns. Device optimization has resulted in peak strains of less than 1% within the compliant structure resulting in device life greater than 200,000 cycles providing usable times greater than twice the anticipated procedure length.The design concepts embodied in this initial implementation will serve as a platform for a variety of self actuated minimally invasive tools.

Major histocompatibility complex (MHC) class I molecules found on antigen-presenting cells present peptides derived from cytoplasmic proteins to T cells. In contrast, peptides from exogenous proteins are mostly presented by class II molecules. It has been well established that liposomes can serve as an efficient delivery system for entry of exogenous protein antigens into the MHC class I pathway. Our previous studies utilizing fluorophore-labeled proteins encapsulated in liposomes demonstrated that after phagocytosis of the liposomes by bone marrow-derived macrophages (BMs), the processed peptides were subsequently visualized in the trans-Golgi, while free conalbumin was excluded from the trans-Golgi area. In the present study, we investigated whether liposomal lipids follow the same intracellular route as the liposomal proteins after phagocytosis by BMs. Multilamellar liposomes with different lipid compositions that also contained fluorescent phospholipids (empty liposomes) were incubated with murine BMs. Our results indicate that although empty liposomes were avidly phagocytosed by macrophages, the fluorescent liposomal lipids did not localize to any particular area of the cell but were distributed throughout the cell. In contrast, when a protein was encapsulated in the liposomes, the liposomal lipids were no longer dispersed throughout the cell, but were concentrated and localized in the trans-Golgi area. Furthermore, when the liposomes contained a fluorescent-labeled protein, the fluorescent peptides also localized to the trans-Golgi. These results demonstrate that the combination of both liposomal lipids and liposomal protein is required for Golgi-specific targeting of liposomal antigens. Transport of both liposomal lipids and liposomal proteins to the Golgi complex, a major subcellular organelle in the passage of MHC class I molecules, might explain why antigens encapsulated in liposomes readily induce cytotoxic T lymphocytes.