A novel multi-DoF surgical robotic system for brachytherapy on liver tumor: Design and control

Phantom study of a fully automatic radioactive seed placement robot for the treatment of skull base tumours

BACKGROUND

Interstitial brachytherapy is a form of intensive local irradiation that facilitates the effective protection of surrounding structures and the preservation of organ functions, resulting in a favourable therapeutic response. As surgical robots can perform needle placement with a high level of accuracy, our team developed a fully automatic radioactive seed placement robot, and this study aimed to evaluate the accuracy and feasibility of fully automatic radioactive seed placement for the treatment of tumours in the skull base.

METHODS

A fully automatic radioactive seed placement robot was established, and 4 phantoms of skull base tumours were built for experimental validation. All the phantoms were subjected to computed tomography (CT) scans. Then, the CT data were imported into the Remebot software to design the preoperative seed placement plan. After the phantoms were fixed in place, navigation registration of the Remebot was carried out, and the automatic seed placement device was controlled to complete the needle insertion and particle placement operations. After all of the seeds were implanted in the 4 phantoms, postoperative image scanning was performed, and the results were verified via image fusion.

RESULTS

A total of 120 seeds were implanted in 4 phantoms. The average error of seed placement was (2.51 ± 1.44) mm.

CONCLUSION

This study presents an innovative, fully automated radioactive particle implantation system utilizing the Remebot device, which can successfully complete automated localization, needle insertion, and radioactive particle implantation procedures for skull base tumours. The phantom experiments showed the robotic system to be reliable, stable, efficient and safe. However, further research on the needle-soft tissue interaction and deformation mechanism of needle puncture is still needed.

Robust stochastic optimization of needle configurations for robotic HDR prostate brachytherapy

BACKGROUND

Ideally, inverse planning for HDR brachytherapy (BT) should include the pose of the needles which define the trajectory of the source. This would be particularly interesting when considering the additional freedom and accuracy in needle pose which robotic needle placement enables. However, needle insertion typically leads to tissue deformation, resulting in uncertainty regarding the actual pose of the needles with respect to the tissue.

PURPOSE

To efficiently address uncertainty during inverse planning for HDR BT in order to robustly optimize the pose of the needles before insertion, that is, to facilitate path planning for robotic needle placement.

METHODS

We use a form of stochastic linear programming to model the inverse treatment planning problem. To account for uncertainty, we consider random tissue displacements at the needle tip to simulate tissue deformation. Conventionally for stochastic linear programming, each simulated deformation is reflected by an addition to the linear programming problem which increases problem size and computational complexity substantially and leads to impractical runtime. We propose two efficient approaches for stochastic linear programming. First, we consider averaging dose coefficients to reduce the problem size. Second, we study weighting of the slack variables of an adjusted linear problem to approximate the full stochastic linear program. We compare different approaches to optimize the needle configurations and evaluate their robustness with respect to different amounts of tissue deformation.

RESULTS

Our results illustrate that stochastic planning can improve the robustness of the treatment with respect to deformation. The proposed approaches approximating stochastic linear programming better conform to the tissue deformation compared to conventional linear programming. They show good correlation with the plans computed after deformation while reducing the runtime by two orders of magnitude compared to the complete stochastic linear program. Robust optimization of needle configurations takes on average 59.42 s. Skew needle configurations lead to mean coverage improvements compared to parallel needles from 0.39 to 2.94 percentage points, when 8 mm tissue deformation is considered. Considering tissue deformations from 4  to 10 mm during planning with weighted stochastic optimization and skew needles generally results in improved mean coverage from 1.77 to 4.21 percentage points.

CONCLUSIONS

We show that efficient stochastic optimization allows selecting needle configurations which are more robust with respect to potentially negative effects of target deformation and displacement on the achievable prescription dose coverage. The approach facilitates robust path planning for robotic needle placement.

Design and Experimental Setup of a Robotic Medical Instrument for Brachytherapy in Non-Resectable Liver Tumors

This paper presents a study regarding the design and the experimental setup of a medical robotic system for brachytherapy using tribology analysis. The robotic system is composed of a collaborative robotic arm and a multi-needle brachytherapy instrument controlled using a unified control system embedding a haptic device and force-feedback. This work is oriented towards identifying the technical characteristics of the system components to determine the accuracy of the procedure, as well as using different scenarios for needle insertion in ex vivo porcine liver tissue in order to determine the forces required for insertion and extraction of the needle and the friction coefficient that accompanies the previously mentioned forces. Subsequent to the computation of the friction forces, the normal forces and the wear during the needle insertion are determined with the scope of predicting the lifecycle of some components of the medical device.