A fast slam approach to freehand 3-d ultrasound reconstruction for catheter ablation guidance in the left atrium.

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.

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

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.

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.

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 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.

Flexible robotic retrograde renoscopy: description of novel robotic device and preliminary laboratory experience.

OBJECTIVES: To describe a novel flexible robotic system for performing retrograde intrarenal surgery. METHODS: Remote robotic flexible ureterorenoscopy was performed bilaterally in 5 acute swine (10 kidneys). A novel 14F robotic catheter system, which manipulated a passive optical fiberscope mounted on a remote catheter manipulator was used. The technical feasibility, efficiency, and reproducibility of accessing all calices were assessed. Additionally, laser lithotripsy of calculi and laser ablation of renal papillae were performed. RESULTS: The robotic catheter system could be introduced de novo in eight ureters; two ureters required balloon dilation. The ureteroscope could be successfully manipulated remotely into 83 (98%) of the 85 calices. The time required to inspect all calices within a given kidney decreased with experience from 15 minutes in the first kidney to 49 seconds in the last (mean 4.6 minutes). On a visual analog scale (1, worst to 10, best), the reproducibility of caliceal access was rated at 8, and instrument tip stability was rated at 10. A renal pelvic perforation constituted the solitary complication. Histologic examination of the ureter showed changes consistent with acute dilation without areas of necrosis. CONCLUSIONS: A novel robotic catheter system is described for performing retrograde ureterorenoscopy. The potential advantages compared with conventional manual flexible ureterorenoscopy include an increased range of motion, instrument stability, and improved ergonomics. Ongoing refinement is likely to expand the role of this technology in retrograde intrarenal surgery in the near future.

Providing metrics and performance feedback in a surgical simulator.

One of the most important advantages of computer simulators for surgical training is the opportunity they afford for independent learning. However, if the simulator does not provide useful instructional feedback to the user, this advantage is significantly blunted by the need for an instructor to supervise and tutor the trainee while using the simulator. Thus, the incorporation of relevant, intuitive metrics is essential to the development of efficient simulators. Equally as important is the presentation of such metrics to the user in such a way so as to provide constructive feedback that facilitates independent learning and improvement. This paper presents a number of novel metrics for the automated evaluation of surgical technique. The general approach was to take criteria that are intuitive to surgeons and develop ways to quantify them in a simulator. Although many of the concepts behind these metrics have wide application throughout surgery, they have been implemented specifically in the context of a simulation of mastoidectomy. First, the visuohaptic simulator itself is described, followed by the details of a wide variety of metrics designed to assess the user's performance. We present mechanisms for presenting visualizations and other feedback based on these metrics during a virtual procedure. We further describe a novel performance evaluation console that displays metric-based information during an automated debriefing session. Finally, the results of several user studies are reported, providing some preliminary validation of the simulator, the metrics, and the feedback mechanisms. Several machine learning algorithms, including Hidden Markov Models and a Naïve Bayes Classifier, are applied to our simulator data to automatically differentiate users' expertise levels.

Validating metrics for a mastoidectomy simulator.

One of the primary barriers to the acceptance of surgical simulators is that most simulators still require a significant amount of an instructing surgeon's time to evaluate and provide feedback to the students using them. Thus, an important area of research in this field is the development of metrics that can enable a simulator to be an essentially self-contained teaching tool, capable of identifying and explaining the user's weaknesses. However, it is essential that these metrics be validated in able to ensure that the evaluations provided by the "virtual instructor" match those that the real instructor would provide were he/she present. We have previously proposed a number of algorithms for providing automated feedback in the context of a mastoidectomy simulator. In this paper, we present the results of a user study in which we attempted to establish construct validity (with inter-rater reliability) for our simulator itself and to validate our metrics. Fifteen subjects (8 experts, 7 novices) were asked to perform two virtual mastoidectomies. Each virtual procedure was recorded, and two experienced instructing surgeons assigned global scores that were correlated with subjects' experience levels. We then validated our metrics by correlating the scores generated by our algorithms with the instructors' global ratings, as well as with metric-specific sub-scores assigned by one of the instructors.

Evaluating drilling and suctioning technique in a mastoidectomy simulator.

This paper presents several new metrics related to bone removal and suctioning technique in the context of a mastoidectomy simulator. The expertise with which decisions as to which regions of bone to remove and which to leave intact is evaluated by building a Naïve Bayes classifier using training data from known experts and novices. Since the bone voxel mesh is very large, and many voxels are always either removed or not removed regardless of expertise, the mutual information was calculated for each voxel and only the most informative voxels used for the classifier. Leave-out-one cross validation showed a high correlation of calculated expert probabilities with scores assigned by instructors. Additional metrics described in this paper include those for assessing smoothness of drill strokes, proper drill burr selection, sufficiency of suctioning, two-handed tool coordination, and application of appropriate force and velocity magnitudes as functions of distance from critical structures.

Visuohaptic simulation of bone surgery for training and evaluation.

Visual and haptic simulation of bone surgery can support and extend current surgical training techniques. The authors present a system for simulating surgeries involving bone manipulation, such as temporal bone surgery and mandibular surgery, and discuss the automatic computation of surgical performance metrics. Experimental results confirm the system's construct validity.

Virtual 3D planning and guidance of mandibular distraction osteogenesis.

We present a system for 3D planning and pre-operative rehearsal of mandibular distraction osteogenesis procedures. Two primary architectural components are described: a planning system that allows geometric bone manipulation to rapidly explore various modifications and configurations, and a visuohaptic simulator that allows both general-purpose training and preoperative, patient-specific procedure rehearsal. We provide relevant clinical background, then describe the underlying simulation algorithms and their application to craniofacial procedures.

Achieving proper exposure in surgical simulation.

One important technique common throughout surgery is achieving proper exposure of critical anatomic structures so that their shapes, which may vary somewhat among patients, can be confidently established and avoided. In this paper, we present an algorithm for determining which regions of selected structures are properly exposed in the context of a mastoidectomy simulation. Furthermore, our algorithm then finds and displays all other points along the surface of the structure that lie along a sufficiently short and straight path from an exposed portion such that their locations can be safely inferred. Finally, we present an algorithm for providing realistic visual cues about underlying structures with view-dependent shading of the bone.

An interactive simulation environment for craniofacial surgical procedures.

Recent advances in medical imaging and surgical techniques have made possible the correction of severe facial deformities and fractures. Surgical correction techniques often involve the direct manipulation - both relocation and surgical fracture - of the underlying facial bone. The work presented here introduces an environment for interactive, visuohaptic simulation of craniofacial surgical procedures, with an emphasis on both mandibular distraction procedures and traditional orthognathic surgeries. The simulator is intended both for instruction and for procedure-specific rehearsal, and can thus load canonical training cases or patient-specific image data into the interactive environment. A network module allows remote demonstration of procedure technique, a form of 'haptic tutoring'. This paper discusses the simulation, haptic feedback, and graphic rendering techniques used to drive the environment. Particular emphasis is placed on techniques for fracture and subsequent rigid manipulation of bone structures, a key component of the relevant procedures.

Quantifying risky behavior in surgical simulation.

Evaluating a trainee's performance on a simulated procedure involves determining whether a specified objective was met while avoiding certain "injurious" actions that damage vulnerable structures. However, it is also important to teach the stylistic behaviors that minimize overall risk to the patient, even though these criteria may be more difficult to explicitly specify and detect. In this paper, we address the development of metrics that evaluate the risk in a trainee's behavior while performing a simulated mastoidectomy. Specifically, we measure the trainee's ability to maintain an appropriate field of view so as to avoid drilling bone that is hidden from view, as well as to consistently apply appropriate forces and velocities. Models of the maximum safe force and velocity magnitudes as functions of distances from key vulnerable structures are learned from model procedures performed by an expert surgeon on the simulator. In addition to quantitatively scoring the trainee's performance, these metrics allow for interactive 3D visualization of the performance by distinctive coloring of regions in which excessive forces or velocities were applied or insufficient visibility was maintained, enabling the trainee to pinpoint his/her mistakes and how to correct them. Although these risky behaviors relate to a mastoidectomy simulator, the objectives of maintaining visibility and applying safe forces and velocities are common in surgery, so it may be possible to extend much of this methodology to other procedures.