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Proceedings Paper

Assessment of therapy applicator targeting with a mechanically assisted 3D ultrasound system 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

Minimally invasive focal ablation of liver cancer is an alternative technique to conventional methods for early-stage tumors. Sufficient therapy is provided when ablation applicators are placed at their intended target locations, but current practices are occasionally unable to achieve the required degree of accuracy, as observed by local cancer recurrence rates. We have developed a mechanically assisted 3D ultrasound (US) imaging and guidance system capable of providing geometrically variable images to increase intraoperative spatial information and propose a new method for placing therapeutic applicators during focal liver tumor ablations. A three-motor mechanical mover was designed to provide linear, tilt, and combined hybrid geometries for user-defined 3D US fields-of-view. This mover can manipulate any clinically available 2D US transducer mounted in a transducer-specific 3D-printed holders and is held by a counterbalanced mechanical guidance system, which contains electromagnetic brakes and encoders to track the position of the transducer. Fabrication of a transducer-specific needle guide allowed for information from 3D US images and targets to be overlaid with live 2D US to perform an image-guided workflow. End-to-end testing from 3D US acquisition to needle insertion was performed with a mock phantom procedure to assess overall needle placement accuracy and a potential clinical workflow. Mean applicator placement error was 3.8 ± 1.9 mm for all trials and demonstrated that our 3D US image-guided system may be a feasible approach for guiding ablation applicators accurately during focal liver tumor ablation procedures.

Paper Details

Date Published: 16 March 2020
PDF: 6 pages
Proc. SPIE 11315, Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling, 113152K (16 March 2020); doi: 10.1117/12.2549841
Show Author Affiliations
Derek J. Gillies, Western Univ. (Canada)
Jeffrey Bax, Western Univ. (Canada)
Kevin Barker, Western Univ. (Canada)
Lori Gardi, Western Univ. (Canada)
David Tessier, Western Univ. (Canada)
Nirmal Kakani, Manchester Royal Infirmary (United Kingdom)
Aaron Fenster, Western Univ. (Canada)

Published in SPIE Proceedings Vol. 11315:
Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling
Baowei Fei; Cristian A. Linte, Editor(s)

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