We have developed an interactive geometric method for 3D reconstruction of the coronary arteries using multiple single-plane angiographic views with arbitrary orientations. Epipolar planes and epipolar lines are employed to trace corresponding vessel segments on these views. These points are utilized to reconstruct 3D vessel centerlines. The accuracy of the reconstruction is assessed using: (1) near-intersection distances of the rays that connect x-ray sources with projected points, (2) distances between traced and projected centerlines. These same two measures enter into a fitness function for a genetic search algorithm (GA) employed to orient the angiographic image planes automatically in 3D avoiding local minima in the search for optimized parameters. Furthermore, the GA utilizes traced vessel shapes (as opposed to isolated anchor points) to assist the optimization process. Differences between two-view and multiview reconstructions are evaluated. Vessel radii are measured and used to render the coronary tree in 3D as a surface. Reconstruction fidelity is demonstrated via (1) virtual phantom, (2) real phantom, and (3) patient data sets, the latter two of which utilize the GA. These simulated and measured angiograms illustrate that the vessel center-lines are reconstructed in 3D with accuracy below 1 mm. The reconstruction method is thus accurate compared to typical vessel dimensions of 1-3 mm. The methods presented should enable a combined interpretation of the severity of coronary artery stenoses and the hemodynamic impact on myocardial perfusion in patients with coronary artery disease.

We present a completely automated 2D-3D registration technique that accurately maps a patient-specific heart model, created from preoperative images, to the patient's orientation in the operating room. This mapping is based on the registration of preoperatively acquired 3D vascular data with intraoperatively acquired angiograms. Registration using both single and dual-plane angiograms is explored using simulated but realistic datasets that were created from clinical images. Heart deformations and cardiac phase mismatches are taken into account in our validation using a digital 4D human heart model. In an ideal situation where the pre- and intraoperative images were acquired at identical time points within the cardiac cycle, the single-plane and the dual-plane registrations resulted in 3D root-mean-square (rms) errors of 1.60 +/- 0.21 and 0.53 +/- 0.08 mm, respectively. When a 10% timing offset was added between the pre- and the intraoperative acquisitions, the single-plane registration approach resulted in inaccurate registrations in the out-of-plane axis, whereas the dual-plane registration exhibited a 98% success rate with a 3D rms error of 1.33 +/- 0.28 mm. When all potential sources of error were included, namely, the anatomical background, timing offset, and typical errors in the vascular tree reconstruction, the dual-plane registration performed at 94% with an accuracy of 2.19 +/- 0.77 mm.

A simulation environment has been developed to aid the development of three-dimensional (3D) angiographic imaging of the coronary arteries for use during minimally invasive robotic cardiac surgery. We have previously developed a dynamic model of the coronary arteries by non-linearly deforming a high-resolution 3D image of the coronaries of an excised human heart, based on motion information from cine bi-plane angiograms. The result was a sequence of volumetric images representing the motion of the coronary arteries throughout the cardiac cycle. To simulate different acquisition and gating strategies, we implemented an algorithm to forward project through the volume data sets. Thus, radiographic projections corresponding to any view-angle, can be produced for any time-point throughout the cardiac cycle. Combining re-projections from selected time-points and view angles enables the evaluation of various gating strategies. This approach will allow us to determine the optimum image acquisition parameters to produce 3D coronary angiograms for planning and guidance of minimally invasive robotic cardiac surgery.

A realistic numerical environment for simulating three-dimensional (3D) angiographic imaging of the coronary arteries has been developed. Through numerical simulation we propose to optimize acquisition and gating strategies, aiding in the design of 3D coronary imaging systems. We have previously developed a dynamic model of the coronary arteries, based on a high-resolution 3D image of an excised human heart, which was perfused with iodinated contrast agent. To mimic the motion of the arteries during the cardiac cycle, the motion of the vessel branch points was determined from cine bi-plane coronary angiograms of a patient with vessel anatomy similar to the excised heart. The static image was then non-linearly deformed to produce a sequence of volumetric images, with 0.4-mm isotropic resolution, representing the motion of the coronary arteries throughout the cardiac cycle. To simulate different acquisition strategies, we compute perspective radiographic projections of the volume data sets, over the geometry associated with the original acquisition. Thus, radiographic projections corresponding to any projection-angle can be produced for any time-point throughout the cardiac cycle. Combining re-projections from selected time-points and view angles enables the evaluation of various acquisition and gating strategies.

Conventional open-heart coronary bypass surgery requires a 30-cm long incision through the breast-bone and stopping the beating heart, which inflict great pain, trauma and lengthy recovery time to patients. Recently, a robot-assisted minimally invasive surgical technique has been introduced to coronary bypass to minimize incisions and avoid cardiac arrest in order to eliminate the medical complications associated with open-heart surgery. Despite its initial success, this innovation has its own limitations and problems. This paper discusses these limitations and proposes a framework that incorporates image-guidance techniques into MIRCAB surgery. We present two aspects of our preliminary work; 1) A Virtual Cardiac Surgical Planning system developed to visualize and manipulate simulated robotic surgical tools within the virtual patient. 2) Our work towards the extension of the static planning system to a dynamic situation that would model the position, orientation and dynamics of the heart, relative to the chest wall, during surgery.