Body-Mounted MR-Conditional Robot for Minimally Invasive Liver Intervention

MR-guided microwave ablation (MWA) has proven effective in treating hepatocellular carcinoma (HCC) with small-sized tumors, but the state-of-the-art technique suffers from sub-optimal workflow due to the limited accuracy provided by the manual needle insertions. This paper presents a compact body-mo...

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Bibliographic Details
Published in:Annals of biomedical engineering 2024-08, Vol.52 (8), p.2065-2075
Main Authors: Huang, Zhefeng, Gunderman, Anthony L., Wilcox, Samuel E., Sengupta, Saikat, Shah, Jay, Lu, Aiming, Woodrum, David, Chen, Yue
Format: Article
Language:English
Subjects:
Ablation
Bevel gears
Biochemistry
Biological and Medical Physics
Biomedical and Life Sciences
Biomedical Engineering and Bioengineering
Biomedicine
Biophysics
Classical Mechanics
Error analysis
Hepatocellular carcinoma
Insertion
Liver cancer
Optical fibers
Original Article
Robot control
Robotic surgery
Robots
Transmission lines
Turbines
Workflow
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Summary:MR-guided microwave ablation (MWA) has proven effective in treating hepatocellular carcinoma (HCC) with small-sized tumors, but the state-of-the-art technique suffers from sub-optimal workflow due to the limited accuracy provided by the manual needle insertions. This paper presents a compact body-mounted MR-conditional robot that can operate in closed-bore MR scanners for accurate needle guidance. The robotic platform consists of two stacked Cartesian XY stages, each with two degrees of freedom, that facilitate needle insertion pose control. The robot is actuated using 3D-printed pneumatic turbines with MR-conditional bevel gear transmission systems. Pneumatic valves and control mechatronics are located inside the MRI control room and are connected to the robot with pneumatic transmission lines and optical fibers. Free-space experiments indicated robot-assisted needle insertion error of 2.6 ± 1.3 mm at an insertion depth of 80 mm. The MR-guided phantom studies were conducted to verify the MR-conditionality and targeting performance of the robot. Future work will focus on the system optimization and validations in animal trials.
ISSN:0090-6964
1573-9686
1573-9686
DOI:10.1007/s10439-024-03503-2