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Proceedings Paper

MRI robot for prostate focal laser ablation: a phantom study
Author(s): Reza Seifabadi; Ming Li; Sheng Xu; Ayele H. Negussie; Zion Tsz Ho Tse; Bradford J. Wood
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Paper Abstract

Purpose: A new version of a grid-template-mimicking MR-compatible robot is developed to assist during in-gantry MRI-guided focal laser ablation of prostate cancer. This robot replaces the grid template and provides higher positioning resolution, and allows autonomous needle alignment directly from the targeting and navigation software, with the needle insertion manually performed for safety. Method: A substantially more compact solution is designed and prototyped to allow comfortable accommodation between the patient’s legs while in MRI bore. The controller software was reconfigured and embedded into the custom navigation and multi-focal ablation software, OncoNav (NIH). OncoNav performs robot-to-image registration, target planning, controlling the robot, ablation planning, and 3D temperature analysis for monitoring. For free space accuracy study, 5 targets were selected across the workspace and the robot was commanded 5 times to each target. Then, a thermochromic phantom study was designed consisting of acrylamide gel and color changing ink for testing the overall workflow. 4 spherical metal fiducials were embedded in the phantom at different locations. After each targeting, laser ablation was applied in two of the targets. Finally, the phantom was sliced for gross observation of guidance and treatment accuracy. Results: in-the-air accuracy was 0.38±0.27 mm. The overall targeting accuracy including robot, registration, and insertion error was 2.17±0.47 mm in phantom. Ablation successfully covered ellipsoids around the targets. The workflow was acceptably smooth. Conclusions: The new robot can accurately assist in targeting small targets followed by focal laser ablation. Sterility and regulatory hurdles will be addressed with specific design approaches as the next step.

Paper Details

Date Published: 8 March 2019
PDF: 9 pages
Proc. SPIE 10951, Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling, 109510N (8 March 2019); doi: 10.1117/12.2511999
Show Author Affiliations
Reza Seifabadi, National Institutes of Health (United States)
Ming Li, National Institutes of Health (United States)
Sheng Xu, National Institutes of Health (United States)
Ayele H. Negussie, National Institutes of Health (United States)
Zion Tsz Ho Tse, The Univ. of Georgia (United States)
Bradford J. Wood, National Institutes of Health (United States)

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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