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. 2023 Feb;19(1):e2465.
doi: 10.1002/rcs.2465. Epub 2022 Oct 6.

Optimisation and validation of a co-manipulated robot for brachytherapy procedure

Aziza Ben Halima  1 , Julien Bert  1 , Jean-François Clément  1 , Dimitris Visvikis  1
Affiliations

Optimisation and validation of a co-manipulated robot for brachytherapy procedure

Aziza Ben Halima et al. Int J Med Robot. 2023 Feb.

Abstract

Background: Low-dose rate brachytherapy is the referent treatment for early-stage prostate cancer and consists in manually inserting radioactive seeds within the organ to destroy tumorous cells. This treatment is inaccurate leading to side effects. Researchers developed robots to improve this technique. Despite ameliorating accuracy, they cannot be clinically used because of size and acceptability. Therefore, a 6-DOF parallel and co-manipulated robot is proposed to meet these requirements.

Methods: To fulfil the application requirements, a compact design was modelled. The robot's optimal dimensions were defined by establishing kinematics and implementing genetic algorithm. The robot's relevance was evaluated by measuring workspace and needle placement errors.

Results: The robot fits into a cube of 300 × 300 × 300 mm3 and provides a free-singularity workspace of 55 × 55 × 150 mm3 with a possible end-effector rotation of 15° and a needle placement error <3 mm.

Conclusion: The results are promising and prove that our robot fulfils the application requirements and presents a beneficial alternative to the manual procedure.

Keywords: co-manipulation; medical robotics; prostate brachytherapy.

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Conflict of interest statement

All authors declared that they have no conflict of interests.

Figures

FIGURE 1
FIGURE 1
Schematic description of the proposed robotic structure in place during the low‐dose rate brachytherapy
FIGURE 2
FIGURE 2
Robot nomenclature representing the geometric parameters and the different coordinate systems used to get the kinematics of the robot: (A) front view, (B) left view
FIGURE 3
FIGURE 3
Identification of the positioning points of the needle
FIGURE 4
FIGURE 4
Optimisation process applied to our proposed robotic solution to determine the optimal design parameters
FIGURE 5
FIGURE 5
Experimental bench installed in our laboratory
FIGURE 6
FIGURE 6
Results of the experimental measurements of the workspace before (blue zone) and after (grey zone) the addition of the ultrasound probe. The dotted shape corresponds to the volume required by the medical application. (A) xz plane, (B) xy plane
FIGURE 7
FIGURE 7
Positioning errors measured using the visualisation software between the target positions (points in blue) already predefined on the phantom surface and the poses determined by the calculation of the robot kinematics (circles in green)
FIGURE 8
FIGURE 8
Insertion errors measured using the visualisation software, for point A, between the already predefined target positions (blue points) and the poses determined by the electromagnetic tracker (green stars) and by the calculation of kinematics (red squares)
See this image and copyright information in PMC

References

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