ArticleInternational journal of computer assisted radiology and surgery2023
Comparative verification of control methodology for robotic interventional neuroradiology procedures.
Article in International journal of computer assisted radiology and surgery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed.
- A Position Statement on Endovascular Models and Effectiveness Metrics for Mechanical Thrombectomy Navigation, on Behalf of the Stakeholder Taskforce for Artificial Intelligence-Assisted Robotic Thrombectomy (START).Journal of the American Heart Association · 2026Article
- Reinforcement learning for safe autonomous two-device navigation of cerebral vessels in mechanical thrombectomy.International journal of computer assisted radiology and surgery · 2025Article
- Benchmarking reinforcement learning algorithms for autonomous mechanical thrombectomy.International journal of computer assisted radiology and surgery · 2025Article
- Autonomous navigation of catheters and guidewires in mechanical thrombectomy using inverse reinforcement learning.International journal of computer assisted radiology and surgery · 2024Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
purposeThe use of robotics is emerging for performing interventional radiology procedures. Robots in interventional radiology are typically controlled using button presses and joystick movements. This study identified how different human-robot interfaces affect endovascular surgical performance using interventional radiology simulations.
methodsNine participants performed a navigation task on an interventional radiology simulator with three different human-computer interfaces. Using Simulation Open Framework Architecture we developed a simulation profile of vessels, catheters and guidewires. We designed and manufactured a bespoke haptic interventional radiology controller for robotic systems to control the simulation. Metrics including time taken for navigation, number of incorrect catheterisations, number of catheter and guidewire prolapses and forces applied to vessel walls were measured and used to characterise the interfaces. Finally, participants responded to a questionnaire to evaluate the perception of the controllers.
resultsTime taken for navigation, number of incorrect catheterisations and the number of catheter and guidewire prolapses, showed that the device-mimicking controller is better suited for controlling interventional neuroradiology procedures over joystick control approaches. Qualitative metrics also showed that interventional radiologists prefer a device-mimicking controller approach over a joystick approach.
conclusionOf the four metrics used to compare and contrast the human-robot interfaces, three conclusively showed that a device-mimicking controller was better suited for controlling interventional neuroradiology robotics.
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Registered trials
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