Design and validation of a CT-guided robotic system for lung cancer brachytherapy

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Abstract

Purpose

Currently, lung brachytherapy in clinical setting is a complex procedure. Operation accuracy depends on accurate positioning of the template; however, it is difficult to guarantee the positioning accuracy manually. Application of robotic-assisted systems can simplify the procedure and improve the manual positioning accuracy. Therefore, a novel CT-guided robotic system was developed to assist the lung cancer brachytherapy.

Methods

A four degree-of-freedom (DOF) robot, controlled by a lung brachytherapy treatment planning system (TPS) software, was designed and manufactured to assist the template positioning. Target position of the template can be obtained from the treatment plan, thus the robot is driven to the target position automatically. The robotic system was validated in both the laboratory and the CT environment. In laboratory environment, a 3D laser tracker and an inertial measurement unit (IMU) were used to measure the mechanical accuracy in air, which includes positioning accuracy and position repeatability. Working reliability was also validated in this procedure by observing the response reliability and calculating the position repeatability. Imaging artifacts and accuracy of the robot registration were validated in the CT environment by using an artificial phantom with fiducial markers. CT images were obtained and used to test the image artifact and calculate the registration accuracy. Phantom experiments were conducted to test the accuracy of needle insertion by using a transparent hydrogel phantom with a high imitation artificial phantom. Also, the efficiency was validated in this procedure by comparing time costs in manual positioning with robotic positioning under the same experimental conditions.

Results

The robotic system achieved the positioning accuracy of 0.28 ± 0.25 mm and the position repeatability of 0.09 ± 0.11 mm. Experimental results showed that the robot was CT-compatible and responded reliably to the control commands. The mean registration accuracy of the robotic system was 0.49 ± 0.29 mm. Phantom experiments indicated that the accuracy of needle insertion was 1.5 ± 1.7 mm at a depth ranging from 30 to 80 mm. The time used to adjust the template to the target position was 12 min on average by robotic system automatically. An average of 30 min was saved compared with the manual positioning procedure in phantom experiments.

Conclusions

This paper describes the design and experimental validation of a novel CT-guided robotic system for lung cancer brachytherapy. The robotic system was validated in a number of aspects which prove that it was capable of locating the template with clinically acceptable accuracy in the CT environment. All experimental results indicated that the system is reliable and ready to be applied to further studies on animals.

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