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Biomedical subjects

Terry Peters

Publications and source records attributed to Terry Peters.

6 recordsLinked to original sources

Image-guided laser projection for port placement in minimally invasive surgery.

We present an application of an augmented reality laser projection system in which procedure-specific optimal incision sites, computed from pre-operative image acquisition, are superimposed on a patient to guide port placement in minimally invasive surgery. Tests were conducted to evaluate the fidelity of computed and measured port configurations, and to validate the accuracy with which a surgical tool-tip can be placed at an identified virtual target. A high resolution volumetric image of a thorax phantom was acquired using helical computed tomography imaging. Oriented within the thorax, a phantom organ with marked targets was visualized in a virtual environment. A graphical interface enabled marking the locations of target anatomy, and calculation of a grid of potential port locations along the intercostal rib lines. Optimal configurations of port positions and tool orientations were determined by an objective measure reflecting image-based indices of surgical dexterity, hand-eye alignment, and collision detection. Intra-operative registration of the computed virtual model and the phantom anatomy was performed using an optical tracking system. Initial trials demonstrated that computed and projected port placement provided direct access to target anatomy with an accuracy of 2 mm.

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2D-3D registration of coronary angiograms for cardiac procedure planning and guidance.

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.

Algorithms↗

Validation of dynamic heart models obtained using non-linear registration for virtual reality training, planning, and guidance of minimally invasive cardiac surgeries.

Current minimally invasive techniques for beating heart surgery are associated with three major limitations: the shortage of realistic and safe training methods, the process of selecting port locations for optimal target coverage from X-rays and angiograms, and the sole use of the endoscope for instrument navigation in a dynamic and confined 3D environment. To supplement the current surgery training, planning and guidance methods, we continue to develop our Virtual Cardiac Surgery Planning environment (VCSP) -- a virtual reality, patient-specific, thoracic cavity model derived from 3D pre-procedural images. In this work, we create and validate dynamic models of the heart and its components. A static model is first generated by segmenting one of the image frames in a given 4D data set. The dynamics of this model are then extracted from the remaining image frames using a non-linear, intensity-based registration algorithm with a choice of six different similarity metrics. The algorithm is validated on an artificial CT image set created using an excised porcine heart, on CT images of canine subjects, and on MR images of human volunteers. We found that with the appropriate choice of similarity metric, our algorithm extracts the motion of the epicardial surface in CT images, or of the myocardium, right atrium, right ventricle, aorta, left atrium, pulmonary arteries, vena cava and epicardial surface in MR images, with a root mean square error in the 1 mm range. These results indicate that our method of modeling the motion of the heart is easily adaptable and sufficiently accurate to meet the requirements for reliable cardiac surgery training, planning, and guidance.

Algorithms↗

Augmented reality laser projection device for surgery.

We have developed an augmented reality system capable of projecting preoperative plans directly onto a patient using rapidly scanned laser beams. Projected contours can typically represent cut paths, tumors or delineate boundaries of interest. The system can be used as part of, or a replacement for, conventional robotic Telesurgery systems. Because the graphics are projected, there is no degradation in surgeon's view due to optical components interposed between the surgeon's eye and the patient. This system has been designed to work with a common infrared 3D camera system used in image-guided surgery, and projects both visible and infrared beams. The IR beam enables surface digitization functions to be carried out using the camera. The clinical accuracy is in the range required by CAS procedures, around 1-2mm. The device will be particularly useful for executing precise preoperative plans and for teleconsultation applications, where planned or live consultations can be efficiently communicated to a less skilled local caregiver.

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