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Mechanically assisted 3D ultrasound with geometrically variable imaging for minimally invasive focal liver tumor therapy
Author(s): Derek J. Gillies; Jeffrey Bax; Kevin Barker; Lori Gardi; David Tessier; Nirmal Kakani; Aaron Fenster
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Paper Abstract

Liver cancer is the second and sixth most frequent cause of cancer mortality worldwide in men and women, respectively, with high prevalence in under developed and developing countries. Minimally invasive focal ablation of liver tumors is an alternative technique to resection and transplantation for early-stage cancer and is focused on reducing patient complications and recovery times. Although promising, the therapeutic benefits are currently present with high local cancer recurrence. One potential source of error arises when performing therapy applicator guidance with 2D ultrasound (US) since the field-of-view is limited and requires the physician to build a mental image of the anatomy. Our solution to this limitation has been the development of a novel mechanically assisted 3D US imaging and guidance system capable of providing geometrically variable images. A three-motor mechanical mover was designed to provide linear, tilt, and hybrid geometries with adjustable ranges of motion for variable 3D US fields-of-view. This mover can manipulate any clinically available 2D US transducer via transducer-specific 3D-printed holders to guide applicator insertions intraoperatively. This mover is held by a counterbalanced mechanical “arm and wrist”, which contain electromagnetic brakes and five encoders to track the position of the transducer. This mechanical support is mounted on a portable cart with coarse adjustable height to accommodate gross differences in patient sizes. This work represents the design, construction, software implementation, preliminary 3D volume reconstruction evaluation, and the first qualitative human volunteer scans. Geometric errors performed on a grid phantom were <3% and human volunteer images were clinically applicable.

Paper Details

Date Published: 8 March 2019
PDF: 6 pages
Proc. SPIE 10951, Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling, 109510Y (8 March 2019); doi: 10.1117/12.2512875
Show Author Affiliations
Derek J. Gillies, Western Univ. (Canada)
Robarts Research Institute (Canada)
Jeffrey Bax, Robarts Research Institute (Canada)
Kevin Barker, Robarts Research Institute (Canada)
Lori Gardi, Robarts Research Institute (Canada)
David Tessier, Robarts Research Institute (Canada)
Nirmal Kakani, Manchester Royal Infirmary (United Kingdom)
Aaron Fenster, Western Univ. (Canada)
Robarts Research Institute (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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