Daniel R. Elgort

Augmenting CT cardiac roadmaps with segmented streaming ultrasound

Static X-ray computed tomography (CT) volumes are often used as anatomic roadmaps during catheter-based cardiac interventions performed under X-ray fluoroscopy guidance. These CT volumes provide a high-resolution depiction of soft-tissue structures, but at only a single point within the cardiac and respiratory cycles. Augmenting these static CT roadmaps with segmented myocardial borders extracted from live ultrasound (US) provides intra-operative access to real-time dynamic information about the cardiac anatomy. In this work, using a customized segmentation method based on a 3D active mesh, endocardial borders of the left ventricle were extracted from US image streams (4D data sets) at a frame rate of approximately 5 frames per second. The coordinate systems for CT and US modalities were registered using rigid body registration based on manually selected landmarks, and the segmented endocardial surfaces were overlaid onto the CT volume. The root-mean squared fiducial registration error was 3.80 mm. The accuracy of the segmentation was quantitatively evaluated in phantom and human volunteer studies via comparison with manual tracings on 9 randomly selected frames using a finite-element model (the US image resolutions of the phantom and volunteer data were 1.3 x 1.1 x 1.3 mm and 0.70 x 0.82 x 0.77 mm, respectively). This comparison yielded 3.70±2.5 mm (approximately 3 pixels) root-mean squared error (RMSE) in a phantom study and 2.58±1.58 mm (approximately 3 pixels) RMSE in a clinical study. The combination of static anatomical roadmap volumes and dynamic intra-operative anatomic information will enable better guidance and feedback for image-guided minimally invasive cardiac interventions.

Multimodality image guidance system integrating X-ray fluoroscopy and ultrasound image streams with electromagnetic tracking

This work presents an integrated system for multimodality image guidance of minimally invasive medical procedures. This software and hardware system offers real-time integration and registration of multiple image streams with localization data from navigation systems. All system components communicate over a local area Ethernet network, enabling rapid and flexible deployment configurations. As a representative configuration, we use X-ray fluoroscopy (XF) and ultrasound (US) imaging. The XF imaging system serves as the world coordinate system, with gantry geometry derived from the imaging system, and patient table position tracked with a custom-built measurement device using linear encoders. An electromagnetic (EM) tracking system is registered to the XF space using a custom imaging phantom that is also tracked by the EM system. The RMS fiducial registration error for the EM to X-ray registration was 2.19 mm, and the RMS target registration error measured with an EM-tracked catheter was 8.81 mm. The US image stream is subsequently registered to the XF coordinate system using EM tracking of the probe, following a calibration of the US image within the EM coordinate system. We present qualitative results of the system in operation, demonstrating the integration of live ultrasound imaging spatially registered to X-ray fluoroscopy with catheter localization using electromagnetic tracking.