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

Authors

  • Turgeon Guy-Anne,

    1. Imaging Research Laboratories, Robarts Research Institute, London, Ontario, Canada and Biomedical Engineering Program, The University of Western Ontario, London, Ontario, Canada
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  • Lehmann Glen,

    1. Department of Medical Biophysics, The University of Western Ontario, London, Ontario, Canada
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  • Guiraudon Gerard,

    1. Canadian Surgical Technologies and Advanced Robotics (C-STAR), London Health Sciences Centre, London, Ontario, Canada
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  • Drangova Maria,

    1. Imaging Research Laboratories, Robarts Research Institute, London, Ontario, Canada Department of Medical Biophysics, The University of Western Ontario, London, Ontario, Canada and Department of Diagnostic Radiology and Nuclear Medicine, The University of Western Ontario, London, Ontario, Canada
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  • Holdsworth David,

    1. Imaging Research Laboratories, Robarts Research Institute, London, Ontario, Canada Department of Diagnostic Radiology and Nuclear Medicine, The University of Western Ontario, London, Ontario, Canada and Department of Medical Biophysics, The University of Western Ontario, London, Ontario, Canada
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  • Peters Terry

    1. Imaging Research Laboratories, Robarts Research Institute, London, Ontario, Canada Department of Diagnostic Radiology and Nuclear Medicine, The University of Western Ontario, London, Ontario, Canada Department of Medical Biophysics, The University of Western Ontario, London, Ontario, Canada and Biomedical Engineering Program, The University of Western Ontario, London, Ontario, Canada
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Abstract

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±0.08mm, 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±0.28mm. 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±0.77mm.

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