Aditya Koolwal

An Ultrasound-based Localization Algorithm for Catheter Ablation Guidance in the Left Atrium

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.

Design and Fabrication of Tubular Shape Memory Alloy Actuators for Active Catheters

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

An Incremental Method for Registering Electroanatomic Mapping Data to Surface Mesh Models of the Left Atrium

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 catheters pose with respect to anatomy. After considering less than a minutes 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.

A probabilistic framework for freehand 3D ultrasound reconstruction applied to catheter ablation guidance in the left atrium

IntroductionThe 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.MethodsUsing 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.ResultsOur 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.

Catheter localization in the left atrium using an outdated anatomic reference for guidance

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.

A microfabricated intravascular ultrasound scanner for intravascular interventions

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.

An Image-Based Localization Algorithm for Catheter Navigation in the Left Atrium

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.