Analysis of Left Atrial Respiratory and Cardiac Motion for Cardiac Ablation Therapy.

Cardiac ablation therapy is often guided by models built from preoperative computed tomography (CT) or magnetic resonance imaging (MRI) scans. One of the challenges in guiding a procedure from a preoperative model is properly synching the preoperative models with cardiac and respiratory motion through computational motion models. In this paper, we describe a methodology for evaluating cardiac and respiratory motion in the left atrium and pulmonary veins of a beating canine heart. Cardiac catheters were used to place metal clips within and near the pulmonary veins and left atrial appendage under fluoroscopic and ultrasound guidance and a contrast-enhanced, 64-slice multidetector CT scan was collected with the clips in place. Each clip was segmented from the CT scan at each of the five phases of the cardiac cycle at both end-inspiration and end-expiration. The centroid of each segmented clip was computed and used to evaluate both cardiac and respiratory motion of the left atrium. A total of three canine studies were completed, with 4 clips analyzed in the first study, 5 clips in the second study, and 2 clips in the third study. Mean respiratory displacement was 0.2±1.8 mm in the medial/lateral direction, 4.7±4.4 mm in the anterior/posterior direction (moving anterior on inspiration), and 9.0±5.0 mm superior/inferior (moving inferior with inspiration). At end inspiration, the mean left atrial cardiac motion at the clip locations was 1.5±1.3 mm in the medial/lateral direction, and 2.1±2.0 mm in the anterior/posterior and 1.3±1.2 mm superior/inferior directions. At end expiration, the mean left atrial cardiac motion at the clip locations was 2.0±1.5 mm in the medial/lateral direction, 3.0±1.8 mm in the anterior/posterior direction, and 1.5±1.5 mm in the superior/inferior directions.

Toward Standardized Mapping for Left Atrial Analysis and Cardiac Ablation Guidance.

In catheter-based cardiac ablation, the pulmonary vein ostia are important landmarks for guiding the ablation procedure, and for this reason, have been the focus of many studies quantifying their size, structure, and variability. Analysis of pulmonary vein structure, however, has been limited by the lack of a standardized reference space for population based studies. Standardized maps are important tools for characterizing anatomic variability across subjects with the goal of separating normal inter-subject variability from abnormal variability associated with disease. In this work, we describe a novel technique for computing flat maps of left atrial anatomy in a standardized space. A flat map of left atrial anatomy is created by casting a single ray through the volume and systematically rotating the camera viewpoint to obtain the entire field of view. The technique is validated by assessing preservation of relative surface areas and distances between the original 3D geometry and the flat map geometry. The proposed methodology is demonstrated on 10 subjects which are subsequently combined to form a probabilistic map of anatomic location for each of the pulmonary vein ostia and the boundary of the left atrial appendage. The probabilistic map demonstrates that the location of the inferior ostia have higher variability than the superior ostia and the variability of the left atrial appendage is similar to the superior pulmonary veins. This technique could also have potential application in mapping electrophysiology data, radio-frequency ablation burns, or treatment planning in cardiac ablation therapy.

An event-driven distributed processing architecture for image-guided cardiac ablation therapy.

Medical imaging data is becoming increasing valuable in interventional medicine, not only for preoperative planning, but also for real-time guidance during clinical procedures. Three key components necessary for image-guided intervention are real-time tracking of the surgical instrument, aligning the real-world patient space with image-space, and creating a meaningful display that integrates the tracked instrument and patient data. Issues to consider when developing image-guided intervention systems include the communication scheme, the ability to distribute CPU intensive tasks, and flexibility to allow for new technologies. In this work, we have designed a communication architecture for use in image-guided catheter ablation therapy. Communication between the system components is through a database which contains an event queue and auxiliary data tables. The communication scheme is unique in that each system component is responsible for querying and responding to relevant events from the centralized database queue. An advantage of the architecture is the flexibility to add new system components without affecting existing software code. In addition, the architecture is intrinsically distributed, in that components can run on different CPU boxes, and even different operating systems. We refer to this Framework for Image-Guided Navigation using a Distributed Event-Driven Database in Real-Time as the FINDER architecture. This architecture has been implemented for the specific application of image-guided cardiac ablation therapy. We describe our prototype image-guidance system and demonstrate its functionality by emulating a cardiac ablation procedure with a patient-specific phantom. The proposed architecture, designed to be modular, flexible, and intuitive, is a key step towards our goal of developing a complete system for visualization and targeting in image-guided cardiac ablation procedures.

Patient specific physical anatomy models.

The advent of small footprint stereo-lithographic printers and the ready availability of segmentation and surface modeling software provide a unique opportunity to create patient-specific physical models of anatomy, validation of image guided intervention applications against phantoms that exhibit naturally occurring anatomic variation. Because these models can incorporate all structures relevant to a procedure, this allows validation to occur under realistic conditions using the same or similar techniques as would be used in a clinical application. This in turn reduces the number of trials and time spent performing in-vivo validation experiments. In this paper, we describe our general approach for the creation of both non-tissue and tissue-mimicking patient-specific models as part of a general-purpose patient emulation system used to validate image guided intervention applications.

An integrated system for real-time image guided cardiac catheter ablation.

Minimally invasive cardiac catheter ablation procedures require effective visualization of the relevant heart anatomy and electrophysiology (EP). In a typical ablation procedure, the visualization tools available to the cardiologist include bi-plane fluoroscopy, real-time ultrasound, and a coarse 3D model which gives a rough representation of cardiac anatomy and electrical activity. Recently, there has been increased interest in incorporating detailed, patient specific anatomical data into the cardiac ablation procedure. We are currently developing a prototype system which both integrates a patient specific, preoperative data model into the procedure as well as fuses the various visualization modalities (i.e. fluoroscopy, ultrasound, EP) into a single display. In this paper, we focus on two aspects of the prototype system. First, we describe the framework for integrating the various system components, including an efficient communication protocol. Second, using a simple two-chamber phantom of the heart, we demonstrate the ability to integrate preoperative data into the ablation procedure. This involves the registration and visualization of tracked catheter points within the cardiac chambers of the preoperative model.

Reconstruction of the human cerebral cortex from magnetic resonance images.

Reconstructing the geometry of the human cerebral cortex from MR images is an important step in both brain mapping and surgical path planning applications. Difficulties with imaging noise, partial volume averaging, image intensity inhomogeneities, convoluted cortical structures, and the requirement to preserve anatomical topology make the development of accurate automated algorithms particularly challenging. In this paper we address each of these problems and describe a systematic method for obtaining a surface representation of the geometric central layer of the human cerebral cortex. Using fuzzy segmentation, an isosurface algorithm, and a deformable surface model, the method reconstructs the entire cortex with the correct topology, including deep convoluted sulci and gyri. The method is largely automated and its results are robust to imaging noise, partial volume averaging, and image intensity inhomogeneities. The performance of this method is demonstrated, both qualitatively and quantitatively, and the results of its application to six subjects and one simulated MR brain volume are presented.