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

Abstract

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.

Heart-surface reconstruction and ecg electrodes localization using fluoroscopy, epipolar geometry and stereovision: application to noninvasive imaging of cardiac electrical activity

“…Different from Hoffmann et al [ 28 ], [ 29 ] where a calibration object is imaged following acquisition of biplane images in a patient, here both the patient and calibration objects are imaged simultaneously eliminating possible errors due to sequential imaging. While the methods of Chen et al [ 30 ] and Hoffmann et al [ 31 ] do not use a calibration object to obtain the imaging geometry relating the two views of a biplane sequence, they do require a priori knowledge of the imaging system parameters including the source-to-image intensifier distance, the distance between the two focal points and/or the distance between two 3-D points in the scene.…”

“…However, this method requires the use of an a priori model of the imaged object whose location and orientation are iteratively modified to align the viewing lines with the measured single projection. In contrast to other methods [ 28 ]- [ 32 ] that use an iterative nonlinear optimization technique to reconstruct 3-D points in space, the method presented in this paper is linear and involves simple numerical algorithms. Other methods that reconstruct the 3-D structure and shape of smooth objects from their occluding contours [ 33 ]- [ 36 ] require the acquisition of multiple images from a camera rotating around the object.…”

Anatomy-based registration of CT-scan and intraoperative X-ray images for guiding a surgical robot

“…We are aware of two main approaches for calibrating such images: 1) correction of distortion [12]- [17] followed by determination of the parameters of the perspective projection [4], [18]- [20]; and 2) simultaneous distortion correction and determination of the projection parameters using multiplane methods [21]. In the first approach 1), all methods for correcting the distortion that we are aware of compare a known grid pattern with its X-ray image, and record the displacements of each relevant grid node caused by distortion.…”

Error analysis of marker‐based object localization using a single‐plane XRII

“…Threedimensional ͑3D͒ guidance or localization can be provided by optical or magnetic tracking systems, [7][8][9] more complex x-ray imaging systems, such as bi-plane x-ray systems, or systems that obtain stereoscopic visualization using a singledetector plane with dual x-ray sources. 10,11 Optical tracking, however, requires uninterrupted line-of-sight, which might not be available during intraoperative or dynamic procedures. Magnetic tracking systems are susceptible to interference from local metal objects, such as tools or implants.…”