An Integrated Robotic System for MRI-Guided Neuroablation: Preclinical Evaluation

Patel, Niravkumar; Nycz, Christopher J.; Carvalho, Paulo A.; Gandomi, Katie Y.; Gondokaryono, Radian; Li, Gang; Heffter, Tamas; Burdette, Everette C.; Pilitsis, Julie G.; Fischer, Gregory S.

doi:10.1109/tbme.2020.2974583

Cited by 15 publications

(9 citation statements)

References 40 publications

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“…A 4-degree-of-freedom (DOF) trapezoid MRI-compatible manipulator proposed by Eslami et al (2015) achieved millimeter level accuracy. Besides, researchers around the world also put efforts into studies on surgical robots for liver interventions (Gerboni et al, 2017; Song et al, 2013), neurosurgeries (Marzuq et al, 2019; Patel et al, 2020), bone biopsy (Alvara et al, 2018), and some other surgeries.…”

Section: Related Workmentioning

confidence: 99%

Penetration detection with intention recognition for cooperatively controlled robotic needle insertion

Wang

2022

Transactions of the Institute of Measurement and Control

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In lumbar puncture surgeries, force and position information throughout the insertion procedure is vital for needle tip localization, because it reflects different tissue properties. Especially in pediatric cases, the changes are always insignificant for surgeons to sense the crucial feeling of loss of resistance. In this study, a robot system is developed to tackle the major clinical difficulties. Four different control algorithms with intention recognition ability are applied on a novel lumbar puncture robot system for better human–robot cooperation. Specific penetration detection based on force and position derivatives captures the feeling of loss of resistance, which is deemed crucial for needle tip location. Kinematic and actuation modeling provides a clear description of the hardware setup. The control algorithm experiment compares the human–robot cooperation performance of proposed algorithms. The experiment also dictates the clear role of designed penetration detection criteria in capturing the penetration, improving the success rate, and ensuring operational safety.

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Section: Related Workmentioning

confidence: 99%

Penetration detection with intention recognition for cooperatively controlled robotic needle insertion

Wang

2022

Transactions of the Institute of Measurement and Control

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“…Initial experiments are predominantly performed in phantoms in an imaging environment, involving the use of fiducial markers for visualizing and registering the system in the imaging coordinates. A first planning scan is typically acquired for selecting the target locations in the phantom and calculating the insertion parameters 12–14 . Following targeting according to the estimated coordinates exported to a motor controller software, confirmation images are collected for assessing the accuracy of needle placement relative to the prescribed locations 12–14 .…”

Section: Introductionmentioning

confidence: 99%

“… 12 , 13 , 14 In a phantom study performed by Patel et al. 12 under real‐time MRI guidance, a needle‐based therapeutic ultrasound applicator was robotically inserted in a gelatine phantom in locations predefined in 3D slicer. The intended probe tip position was compared to the actual position as visualized in 3D‐fast field echo images.…”

Section: Introductionmentioning

confidence: 99%

“…A first planning scan is typically acquired for selecting the target locations in the phantom and calculating the insertion parameters. [12][13][14] Following targeting according to the estimated coordinates exported to a motor controller software, confirmation images are collected for assessing the accuracy of needle placement relative to the prescribed locations. [12][13][14] In a phantom study performed by Patel et al 12 under real-time MRI guidance, a needle-based therapeutic ultrasound applicator was robotically inserted in a gelatine phantom in locations predefined in 3D slicer.…”

mentioning

confidence: 99%

“…[12][13][14] Following targeting according to the estimated coordinates exported to a motor controller software, confirmation images are collected for assessing the accuracy of needle placement relative to the prescribed locations. [12][13][14] In a phantom study performed by Patel et al 12 under real-time MRI guidance, a needle-based therapeutic ultrasound applicator was robotically inserted in a gelatine phantom in locations predefined in 3D slicer. The intended probe tip position was compared to the actual position as visualized in 3D-fast field echo images.…”

mentioning

confidence: 99%

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Simple methods to test the accuracy of MRgFUS robotic systems

Antoniou

Drakos

Giannakou

et al. 2021

Robotics Computer Surgery

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Background Robotic‐assisted diagnostic and therapeutic modalities require a highly accurate performance to be certified for clinical application. In this paper, three simple methods for assessing the accuracy of motion of magnetic resonance‐guided focused ultrasound (MRgFUS) robotic systems are presented. Methods The accuracy of motion of a 4 degrees of freedom robotic system intended for preclinical use of MRgFUS was evaluated by calliper‐based and magnetic resonance imaging (MRI) methods, as well as visually by performing multiple ablations on a plastic film. Results The benchtop results confirmed a highly accurate motion in all axes of operation. The spatial positioning errors estimated by MRI evaluation were defined by the size of the imaging pixels. Lesions arrangement in discrete and overlapping patterns confirmed satisfactory alignment of motion trajectories. Conclusions We believe the methods presented here should serve as a standard for evaluating the accuracy of motion of MRgFUS robotic systems.

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Current State of Robotics in Interventional Radiology

Najafi

Kreiser

Abdelaziz

et al. 2023

Cardiovasc Intervent Radiol

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As a relatively new specialty with a minimally invasive nature, the field of interventional radiology is rapidly growing. Although the application of robotic systems in this field shows great promise, such as with increased precision, accuracy, and safety, as well as reduced radiation dose and potential for teleoperated procedures, the progression of these technologies has been slow. This is partly due to the complex equipment with complicated setup procedures, the disruption to theatre flow, the high costs, as well as some device limitations, such as lack of haptic feedback. To further assess these robotic technologies, more evidence of their performance and cost-effectiveness is needed before their widespread adoption within the field. In this review, we summarise the current progress of robotic systems that have been investigated for use in vascular and non-vascular interventions.

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An Integrated Robotic System for MRI-Guided Neuroablation: Preclinical Evaluation

Cited by 15 publications

References 40 publications

Penetration detection with intention recognition for cooperatively controlled robotic needle insertion

Penetration detection with intention recognition for cooperatively controlled robotic needle insertion

Simple methods to test the accuracy of MRgFUS robotic systems

Current State of Robotics in Interventional Radiology

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