Linear programming approach to optimize 3D data obtained from multiple view angiograms

Three-dimensional (3D) vessel data from CTA or MRA are not always available prior to or during endovascular interventional procedures, whereas multiple 2D projection angiograms often are. Unfortunately, patient movement, table movement, and gantry sag during angiographic procedures can lead to large errors in gantry-based imaging geometries and thereby incorrect 3D. Therefore, we are developing methods for combining vessel data from multiple 2D angiographic views obtained during interventional procedures to provide 3D vessel data during these procedures. Multiple 2D projection views of carotid vessels are obtained, and the vessel centerlines are indicated. For each pair of views, endpoints of the 3D centerlines are reconstructed using triangulation based on the provided gantry geometry. Previous investigations indicated that translation errors were the primary source of error in the reconstructed 3D. Therefore, the errors in the translations relating the imaging systems are corrected by minimizing the L1 distance between the reconstructed endpoints, after which the 3D centerlines are reconstructed using epipolar constraints for every pair of views. Evaluations were performed using simulations, phantom data, and clinical cases. In simulation and phantom studies, the RMS error decreased from 6.0 mm obtained with biplane approaches to 0.5 mm with our technique. Centerlines in clinical cases are smoother and more consistent than those calculated from individual biplane pairs. The 3D centerlines are calculated in about 2 seconds. These results indicate that reliable 3D vessel data can be generated for treatment planning or revision during interventional procedures.

[1]  S A MacKay,et al.  Methods for evaluating cardiac wall motion in three dimensions using bifurcation points of the coronary arterial tree. , 1983, Investigative radiology.

[2]  J S Whiting,et al.  Automatic correction of biplane projection imaging geometry. , 1996, Medical physics.

[3]  K R Hoffmann,et al.  Determination of 3D imaging geometry and object configurations from two biplane views: an enhancement of the Metz-Fencil technique. , 1995, Medical physics.

[4]  Kenneth R Hoffmann,et al.  Optimization of three-dimensional angiographic data obtained by self-calibration of multiview imaging. , 2006, Medical physics.

[5]  Jinhui Xu,et al.  Efficient Algorithms for Determining 3-D Bi-Plane Imaging Geometry , 2005, J. Comb. Optim..

[6]  S Rudin,et al.  Super-global distortion correction for a rotational C-arm x-ray image intensifier. , 1999, Medical physics.

[7]  Andreas Wahle.  Präzise dreidimensionale Rekonstruktion von Gefässsystemen aus biplanen angiographischen Projektionen und deren klinische Anwendung , 1997 .

[8]  Dennis L. Parker,et al.  FLOW MEASUREMENTS FROM 3D RECONSTRUCTION OF MOVING ARTERIAL BEDS FROM DIGITAL SUBTRACTION ANGIOGRAPHY. , 1987 .

[9]  C. Metz,et al.  Determination of three-dimensional structure in biplane radiography without prior knowledge of the relationship between the two views: theory. , 1989, Medical physics.

[10]  K Doi,et al.  Automated tracking and computer reproduction of vessels in DSA images. , 1990, Investigative radiology.

[11]  Peter B. Noël,et al.  3D reconstruction of the carotid artery from two views using a single centerline , 2004, CARS.

[12]  Fernando Vilariño,et al.  Predictive (un)distortion model and 3-D reconstruction by biplane snakes , 2002, IEEE Transactions on Medical Imaging.

[13]  Andreas Wahle,et al.  Assessment of diffuse coronary artery disease by quantitative analysis of coronary morphology based upon 3-D reconstruction from biplane angiograms , 1995, IEEE Trans. Medical Imaging.

[14]  S. Y. Chen,et al.  Improved determination of biplane imaging geometry from two projection images and its application to three-dimensional reconstruction of coronary arterial trees. , 1997, Medical physics.

[15]  S. L. Murphy,et al.  Deaths: final data for 2002. , 2004, National vital statistics reports : from the Centers for Disease Control and Prevention, National Center for Health Statistics, National Vital Statistics System.

[16]  C J Henri,et al.  Three-dimensional reconstruction of vascular trees. Theory and methodology. , 1996, Medical physics.

[17]  Maria Drangova,et al.  Coronary x-ray angiographic reconstruction and image orientation. , 2006, Medical physics.

[18]  Jun Chen,et al.  Three-dimensional reconstruction of intracranial vessels from biplane projection views , 1996, Journal of Neuroscience Methods.