ABSTRACT
Hybrid imaging systems, consisting of fluoroscopy and echocardiography, are increasingly selected for intra-operative support of minimally invasive cardiac interventions. Intracardiac echocardiograpy (ICE) is an emerging modality with the promise of removing sedation or general anesthesia associated with transesophageal echocardiography (TEE). We introduce a novel 6 degrees of freedom (DoF) pose estimation approach for catheters (equipped with radiopaque ball markers) in single X-Ray fluoroscopy projection and investigate the method's application to a prototype ICE catheter. Machine learning based catheter detection is implemented in a Bayesian hypothesis fusion framework, followed by refinement of ball marker locations through template matching. Marker correspondence and 3D pose estimation are solved through iterative optimization. The method registers the ICE volume to the C-arm coordinate system. Experiments are performed on synthetic and porcine in-vivo data. Target registration error (TRE), defined in the echo cone, is the basis of our preliminary evaluation. The method reached 8.06 ± 7.2 mm TRE on 703 cases. Potential uses of our hybrid system include structural heart disease interventions and electrophysiologycal mapping or catheter ablation procedures.
Subject(s)
Cardiac Catheterization/instrumentation , Cardiac Catheters , Echocardiography/instrumentation , Fiducial Markers , Imaging, Three-Dimensional/instrumentation , Imaging, Three-Dimensional/methods , Ultrasonography, Interventional/instrumentation , Artificial Intelligence , Cardiac Catheterization/methods , Echocardiography/methods , Equipment Design , Equipment Failure Analysis , Humans , Image Enhancement/instrumentation , Image Enhancement/methods , Image Interpretation, Computer-Assisted/instrumentation , Image Interpretation, Computer-Assisted/methods , Phantoms, Imaging , Reproducibility of Results , Sensitivity and Specificity , Ultrasonography, Interventional/methodsABSTRACT
This paper describes a novel method for improving the navigation and guidance of devices and catheters in electrophysiology and interventional cardiology procedures using volumetric data fusion. The clinical workflow includes the acquisition and reconstruction of CT data from a C-arm X-ray angiographic system and the real-time acquisition of volumetric ultrasound datasets with a new intracardiac real-time 3D ultrasound catheter. Mono- and multi-modal volumetric registration methods, as well as visualization modes, that are suitable for real-time fusion are described, which are the key components of this work. Evaluation on phantom and in-vivo animal data shows that it is feasible to register and track the motion of real-time 3D intracardiac ultrasound in C-arm CT.
