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Controlling virtual views in navigated breast conserving surgery
Author(s): Shaun Lund; Thomas Vaughan; Tamas Ungi; Andras Lasso; Mark Asselin; Caitlin Yeo; C. Jay Engel; Gabor Fichtinger
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Paper Abstract

PURPOSE: Lumpectomy is the resection of a tumor in the breast while retaining as much healthy tissue as possible. Navigated lumpectomy seeks to improve on the traditional technique by employing computer guidance to achieve the complete excision of the cancer with optimal retention of healthy tissue. Setting up navigation in the OR relies on the manual interactions of a trained technician to align three-dimensional virtual views to the patient’s physical position and maintain their alignment throughout surgery. This work develops automatic alignment tools to improve the operability of navigation software for lumpectomies. METHODS: Preset view buttons were developed to refine view setup to a single interaction. These buttons were tested by measuring the reduction in setup time and the number of manual interactions avoided through their use. An auto-center feature was created to ensure that three-dimensional models of anatomy and instruments were in the center of view throughout surgery. Recorded data from 32 lumpectomy cases were replayed and the number of auto-center view shifts was counted from the first cautery incision until the completion of the excision of cancerous tissue. RESULTS: View setup can now be performed in a single interaction compared to an average of 13 interactions (taking 83 seconds) when performed manually. The auto-center feature was activated an average of 33 times in the cases studied (n=32). CONCLUSION: The auto-center feature enhances the operability of the surgical navigation system, reducing the number of manual interactions required by a technician during the surgery. This feature along with preset camera view options are instrumental in the shift towards a completely surgeon-operable navigated lumpectomy system.

Paper Details

Date Published: 8 March 2019
PDF: 6 pages
Proc. SPIE 10951, Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling, 1095114 (8 March 2019); doi: 10.1117/12.2512632
Show Author Affiliations
Shaun Lund, Lab. for Percutaneous Surgery, Queen's Univ. (Canada)
Thomas Vaughan, Lab. for Percutaneous Surgery, Queen's Univ. (Canada)
Tamas Ungi, Lab. for Percutaneous Surgery, Queen's Univ. (Canada)
School of Medicine, Queen's Univ. (Canada)
Andras Lasso, Lab. for Percutaneous Surgery, Queen's Univ. (Canada)
Mark Asselin, Lab. for Percutaneous Surgery, Queen's Univ. (Canada)
Caitlin Yeo, School of Medicine, Queen's Univ. (Canada)
C. Jay Engel, School of Medicine, Queen's Univ. (Canada)
Gabor Fichtinger, Lab. for Percutaneous Surgery, Queen's Univ. (Canada)
School of Medicine, Queen's Univ. (Canada)


Published in SPIE Proceedings Vol. 10951:
Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling
Baowei Fei; Cristian A. Linte, Editor(s)

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