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Minimally Invasive Neurosurgical Robot for MRI-Guided Intratumoral Therapeutic Delivery
Saeed Rezaeian1, Hengjie Chen2, Chandan Sidhu1
1Department of Mechanical Engineering, University of California Riverside, Riverside, CA 92521 USA.
A novel magnetic resonance-conditional steerable neurosurgical robot enables precise, minimally invasive intratumoral delivery of immunotherapy agents, improving brain tumor treatment efficiency and coverage.
Area of Science:
- Neurosurgery
- Robotics
- Biomedical Engineering
Background:
- Immunotherapy faces challenges in brain tumor treatment due to poor drug trafficking with systemic infusions, especially in large tumors.
- Effective delivery of therapeutic agents directly within the tumor volume is crucial for improving treatment efficacy.
Purpose of the Study:
- To design, model, and assess the feasibility of a magnetic resonance (MR)-conditional steerable neurosurgical robot for minimally invasive intratumoral delivery of therapeutic agents.
- To overcome the limitations of systemic drug delivery in brain tumors by enabling targeted delivery throughout the entire tumor volume.
Main Methods:
- Development of a robotic system with a steerable inner tube for 3D navigation and a non-magnetic actuation system.
- Integration of a custom injection mechanism for precise delivery of therapeutic agents.
- Control experiments for curvature and tip tracking accuracy, phantom studies for tumor coverage, and MRI-guided manipulation studies.
Main Results:
- High accuracy in robot control with a curvature control error of 2.6 ± 1.8% and a relative tip tracking error of 4.2 ± 3.9%.
- Significantly improved tumor coverage ratio (73% vs. 29%) compared to a straight needle in phantom studies.
- Acceptable signal-to-noise ratio decrease (up to 1.41%) during MRI-guided manipulation.
Conclusions:
- The developed MR-conditional steerable neurosurgical robot is feasible for accurate, MRI-guided therapeutic delivery within brain tumors.
- This robotic approach has the potential to enhance drug trafficking and treatment efficiency for brain tumors.
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