title: An event-driven distributed processing architecture for image-guided cardiac ablation therapy.
abstract: 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.
authors.affiliation: Biomedical Imaging Resource, Mayo Clinic College of Medicine, Rochester, MN, USA.
authors.forename: M E
authors.initials: ME
authors.lastname: Rettmann
authors.forename: D R
authors.initials: DR
authors.lastname: Holmes
authors.forename: B M
authors.initials: BM
authors.lastname: Cameron
authors.forename: R A
authors.initials: RA
authors.lastname: Robb
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D017115:Catheter Ablation / Q000379:methods*; D003195:Computer Communication Networks; D003628:Database Management Systems; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D011873:Radiology Information Systems; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012984:Software; D013382:Subtraction Technique; D025321:Surgery, Computer-Assisted / Q000379:methods*