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Real-time 3D image fusion system for valvular interventions based on echocardiography and biplane x-ray fluoroscopy
Author(s): Martin G. Wagner; Lindsay E. Bodart; Amish N. Raval; Michael A. Speidel
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Paper Abstract

Fluoroscopic imaging provides good visibility of prosthetic valve stent frames during transcatheter aortic valve replacement (TAVR) procedures. Recently, efforts have been made to perform 3D tracking of valve frames based on biplane fluoroscopic imaging; however, x-ray-based imaging lacks contrast in the soft tissue structures of the heart. The purpose of this work was to develop a system for real-time 3D visualization of transcatheter prosthetic valve frames and cardiac soft tissue anatomy using the fusion of biplane fluoroscopy and echocardiography. The system is a workstation that accepts real-time image streams from commercial biplane x-ray and echocardiography systems. The image datasets can be registered based on an x-ray visible fiducial apparatus attached to the echocardiography probe, or alternatively, manually registered. During the procedure, a real-time display shows the 3D valve representation together with adjustable cut-planes through the real time 3D ultrasound data. To validate the system, a phantom with cylindrical cavities was created using an agar-graphite mixture. Dual-modality fiducials were attached to the phantom for manual registration and evaluation of registration error. At maximum speed, the frame rate of the fusion system was 24.6 fps. The fiducial registration error between the ultrasound and x-ray imaging systems was 1.3 mm. The target registration error between the 3D prosthetic valve model reconstructed from biplane x-ray and a reference CT acquisition was 1.2 mm. The proposed system works with commercially available angiography and ultrasound systems and provides a novel 3D visualization of the prosthetic valve within the ultrasound image space in real-time.

Paper Details

Date Published: 8 March 2019
PDF: 8 pages
Proc. SPIE 10951, Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling, 1095121 (8 March 2019); doi: 10.1117/12.2512793
Show Author Affiliations
Martin G. Wagner, Univ. of Wisconsin-Madison (United States)
Lindsay E. Bodart, Univ. of Wisconsin-Madison (United States)
Amish N. Raval, Univ. of Wisconsin-Madison (United States)
Michael A. Speidel, Univ. of Wisconsin-Madison (United States)


Published in SPIE Proceedings Vol. 10951:
Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling
Baowei Fei; Cristian A. Linte, Editor(s)

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