A system for determination of 3D vessel tree centerlines from biplane images.

With the increasing number and complexity of therapeutic coronary interventions, there is an increasing need for accurate quantitative measurements. These interventions and measurements may be facilitated by accurate and reproducible magnifications and orientations of the vessel structures, specifically by accurate 3D vascular tree centerlines. A number of methods have been proposed to calculate 3D vascular tree centerlines from biplane images. In general, the calculated magnifications and orientations are accurate to within approximately 1-3% and 2-5 degrees, respectively. Here, we present a complete system for determination of the 3D vessel centerlines from biplane angiograms without the use of a calibration object. Subsequent to indication of the vessel centerlines, the imaging geometry and 3D centerlines are calculated automatically and within approximately 2 min. The system was evaluated in terms of the intra- and inter-user variations of the various calculated quantities. The reproducibilities obtained with this system are comparable to or better than the accuracies and reproducibilities quoted for other proposed methods. Based on these results and those reported in earlier studies, we believe that this system will provide accurate and reproducible vascular tree centerlines from biplane images while the patient is still on the table, and thereby will facilitate interventions and associated quantitative analyses of the vasculature.

Evaluation of imaging geometries calculated from biplane images.

A technique is developed that will calculate accurate and reliable imaging geometries and three-dimensional (3D) positions from biplane images of a calibration phantom. The calculated data provided by our technique will facilitate accurate 3D analysis in various clinical applications. Biplane images of a Lucite cube containing lead beads 1 mm in diameter were acquired. After identifying corresponding beads in both images and calculating their image positions, the 3D positions of the beads relative to each focal spot were determined. From these data, the transformation relating the 3D configurations were calculated to give the imaging geometry relating the biplane views. The 3D positions of objects were determined from the biplane images along with the corresponding imaging geometries. In addition, methods are developed to evaluate the quality of the calculated results on a case-by-case basis in the clinical setting. Methods are presented for evaluating the reproducibility of the calculated geometries and 3D positions, the accuracy of calculated object sizes, and the effects of errors due to time jitter, variation in user-indication, centering, and distortions on the calculated geometries and 3D reconstructions. The precision of the translation vectors and rotation matrices of the calculated geometries were within 1% and 1 degree, respectively, in phantom studies, with estimated accuracies of approximately 0.5% and 0.4 degree, respectively, in simulation studies. The precisions of the absolute 3D positions and orientations of the calculated 3D reconstructions were approximately 2 mm and 0.5 degree, respectively, in phantom studies, with estimated accuracies of approximately 1.5 mm and 0.4 degree, respectively, in simulation studies. This technique will provide accurate and precise imaging geometries as well as 3D positions from biplane images, thereby facilitating 3D analysis in various clinical applications. We believe that the study presented here is unique in that it represents the first steps toward understanding and evaluating the reliability of these 3D calculations in the clinical situation.

Determination of three-dimensional positions of known sparse objects from a single projection.

A new technique is developed for accurate determination of the three-dimensional position and orientation of known sparse objects, e.g., a configuration of points, from a single-perspective projection. In this technique, a computer model of the known object is translated and rotated so as to align it optimally in a least-squares sense with the projection lines connecting the image points with the focal spot by using a modification of the projection-Procrustes technique. The translational and rotational adjustments are repeated iteratively until the angular change between iterations is less than 0.25 degree. Simulations indicate that, for rms input image errors of 0.03 cm, the three-dimensional positions and orientations can be determined to within approximately 0.2 cm and 0.3 degree for a wide range of initially guessed positions and orientations, and positions can be determined with an accuracy of approximately 0.3 cm for objects having as few as four points. In phantom experiments, three-dimensional positions and orientations of a cube phantom were reproducibly determined to within 0.23 cm and 0.13 degree. The entire calculation requires only 10 s on a VAX 3500 to converge to the solution. The accuracy, precision, and speed of the technique indicate that it will be a useful tool for determination of three-dimensional positions and orientations of known sparse objects.

Determination of 3D positions of pacemaker leads from biplane angiographic sequences.

In vitro and in vivo analyses of stress on pacemaker leads and their components during the heart cycle have become especially important because of incidences of failure of some of these mechanical components. For stress analyses, the three-dimensional (3D) position, shape, and motion of the pacemaker leads must be known accurately at each time point during the cardiac cycle. We have developed a method for determination of the in vivo 3D positions of pacemaker leads during the entire heart cycle. Sequences of biplane images of patients with pacemakers were obtained at 30 frames/s for each projection. The sequences usually included at least two heart cycles. After patient imaging, biplane images of a calibration object were obtained from which the biplane imaging geometry was determined. The centerlines of the leads and unique, identifiable points on the attached electrodes were indicated manually for all acquired images. Temporal interpolation of the lead and electrode data was performed so that the temporal nonsynchronicity of the image acquisition was overcome. Epipolar lines, generated from the calculated geometry, were employed to identify corresponding points along the leads in the pairs of biplane images for each time point. The 3D positions of the lead and electrodes were calculated from the known geometry and from the identified corresponding points in the images. Using multiple image sets obtained with the calibration object at various orientations, the precision of the calculated rotation matrix and of the translation vector defining the imaging geometry was found to be approximately 0.7 degree and 1%, respectively. The 3D positions were reproducible to within 2 mm, with the error lying primarily along the axis between the focal spot and the imaging plane. Using data obtained by temporally downsampling to 15 frames/s, the interpolated data were found to lie within approximately 2 mm of the true position for most of the heart cycle. These results indicate that, with this technique, one can reliably determine pacemaker lead positions throughout the heart cycle, and thereby it will provide the basis for stress analysis on pacemaker leads.