Robotic stage for head motion correction in stereotactic radiosurgery

Liu, Xinmin; Belcher, AH; Grelewicz, Z; Wiersma, R

doi:10.1109/acc.2015.7172244

Cited by 5 publications

(3 citation statements)

References 17 publications

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“…They reported the head mold and open face mask system could restrict head motions to within 0.6 • ± 0.3 • with the time spent on in-situ motion corrections limited to 2.7 ± 1.0 min. Correction-based Systems: In [9], a 4-DOF motion correction system was used in a real-time motion compensation of a phantom and in human trials. An optical sensing system tracked the pose of the head and a decoupling control law regulated the xyz-translational and pitch motions of the head.…”

Section: Related Workmentioning

confidence: 99%

Soft-NeuroAdapt: A 3-DOF neuro-adaptive patient pose correction system for frameless and maskless cancer radiotherapy

Ogunmolu

Kulkarni

Tadesse

et al. 2017

2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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Abstract-Precise patient positioning is fundamental to successful removal of malignant tumors during treatment of head and neck cancers. Errors in patient positioning have been known to damage critical organs and cause complications. To better address issues of patient positioning and motion, we introduce a 3-DOF neuro-adaptive soft-robot, called SoftNeuroAdapt to correct deviations along 3 axes. The robot consists of inflatable air bladders that adaptively control head deviations from target while ensuring patient safety and comfort. The adaptive-neuro controller combines a state feedback component, a feedforward regulator, and a neural network that ensures correct adaptation. States are measured by a 3D vision system. We validate Soft-NeuroAdapt on a 3D printed head-and-neck dummy, and demonstrate that the controller provides adaptive actuation that compensates for intrafractional deviations in patient positioning.

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Section: Related Workmentioning

confidence: 99%

Soft-NeuroAdapt: A 3-DOF neuro-adaptive patient pose correction system for frameless and maskless cancer radiotherapy

Ogunmolu

Kulkarni

Tadesse

et al. 2017

2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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“…To maintain dynamic behavior of systems in the face of perturbations and other uncertainties, a robust control for parallel robotic platforms was investigated and compared with a widely used PID approach using extensive computer simulations [29]. For robotic SRS based head motion with angular stabilization, a decoupling control method for a 4D (xyz+pitch) robot was investigated [30,31].…”

Section: Introductionmentioning

confidence: 99%

Trajectory planning optimization for real-time 6DOF robotic patient motion compensation

Wiersma¹,

Liu²

2018

Preprint

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Purpose: Robotic stabilization of a therapeutic radiation beam with respect to a dynamically moving tumor target can be accomplished either by moving the radiation source, the patient, or both. As the treatment beam is on during this process, the primary goal is to minimize exposure of normal tissue to radiation as much as possible when moving the target back to the desired position. Due to the complex mechanical structure of 6 degree-of-freedom (6DoF) robots, it is not intuitive as to what 6 dimensional (6D) correction trajectory is optimal in balancing the shortest trajectory with the fastest trajectory. With proportional-integrative-derivative (PID) and other controls, potential exists that the controller may chose a trajectory that is highly curved, slow, or less optimal in that it leads to unnecessary exposure of healthy tissue to radiation. This work investigates a novel feedback planning method that takes into account a robot's mechanical joint structure, patient safety tolerances, and other system constraints, and performs real-time optimization to search the entire 6D trajectory space in each time cycle so it can respond with the most optimal 6D correction trajectory.Methods: Computer simulations were created for two 6DoF robotic patient support systems: a Stewart-Gough plaform for moving a patient's head in frameless maskless stereotactic radiosurgery, and a linear accelerator treatment table for moving a patient in prostate cancer radiation therapy. The motion planning problem was formulated as an optimization problem and solved at real-time speeds using the L-BFGS algorithm. Three planning methods were investigated, moving the platform as fast as possible (platform-D), moving the target along a straight-line (target-S), and moving the target based on the fastest decent of position error (target-D). Both synthetic motion and prior recorded human motion were used as input data and output results were analyzed.Results: For randomly generated 6D step-like and sinusoidal synthetic input motion, target-D planning demonstrated the smallest net trajectory error in all cases. On average, optimal planning was found to have a 45% smaller target trajectory error than platform-D control, and a 44% smaller target trajectory error than target-S planning. For patient head motion compensation, only target-D planning was able to maintain a ≤0.5mm and ≤0.5deg clinical tolerance objective for 100% of the treatment time. For prostate motion, both target-S planning and target-D planning outperformed platform-D control.Conclusions: A general 6D target trajectory optimization framework for robotic patient motion compensation systems was investigated. The method was found to be flexible as it allows control over various performance requirements such as mechanical limits, velocities, acceleration, or other system control objectives.

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“…To our knowledge, no commercial option to mechanically perform this type of correction yet exists. Early attempts at independent head positioning systems have relied on conventional robotic construction, utilizing metal structural components and fully integrated stepper motors to achieve precise motion (Belcher and Wiersma 2012, Wiersma et al 2013, Liu et al 2015. However, x-ray interactions in metals contraindicate their candidacy as primary materials in radiation therapy applications.…”

Section: Introductionmentioning

confidence: 99%

An electromechanical, patient positioning system for head and neck radiotherapy

et al. 2017

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In cancer treatment with radiation, accurate patient setup is critical for proper dose delivery. Improper arrangement can lead to disease recurrence, permanent organ damage, or lack of disease control. While current immobilization equipment often helps for patient positioning, manual adjustment is required, involving iterative, time-consuming steps. Here, we present an electromechanical robotic system for improving patient setup in radiotherapy, specifically targeting head and neck cancer. This positioning system offers six degrees of freedom for a variety of applications in radiation oncology. An analytical calculation of inverse kinematics serves as fundamental criteria to design the system. Computational mechanical modeling and experimental study of radiotherapy compatibility and x-ray-based imaging demonstrates the device feasibility and reliability to be used in radiotherapy. An absolute positioning accuracy test in a clinical treatment room supports the clinical feasibility of the system.

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Robotic stage for head motion correction in stereotactic radiosurgery

Cited by 5 publications

References 17 publications

Soft-NeuroAdapt: A 3-DOF neuro-adaptive patient pose correction system for frameless and maskless cancer radiotherapy

Soft-NeuroAdapt: A 3-DOF neuro-adaptive patient pose correction system for frameless and maskless cancer radiotherapy

Trajectory planning optimization for real-time 6DOF robotic patient motion compensation

An electromechanical, patient positioning system for head and neck radiotherapy

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