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Li Z, Manzionna E, Monizzi G, Mastrangelo A, Mancini ME, Andreini D, Dankelman J, De Momi E. Position-based dynamics simulator of vessel deformations for path planning in robotic endovascular catheterization. Med Eng Phys 2022; 110:103920. [PMID: 36564143 DOI: 10.1016/j.medengphy.2022.103920] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 09/14/2022] [Accepted: 11/03/2022] [Indexed: 11/08/2022]
Abstract
A major challenge during autonomous navigation in endovascular interventions is the complexity of operating in a deformable but constrained workspace with an instrument. Simulation of deformations for it can provide a cost-effective training platform for path planning. Aim of this study is to develop a realistic, auto-adaptive, and visually plausible simulator to predict vessels' global deformation induced by the robotic catheter's contact and cyclic heartbeat motion. Based on a Position-based Dynamics (PBD) approach for vessel modeling, Particle Swarm Optimization (PSO) algorithm is employed for an auto-adaptive calibration of PBD deformation parameters and of the vessels movement due to a heartbeat. In-vitro experiments were conducted and compared with in-silico results. The end-user evaluation results were reported through quantitative performance metrics and a 5-Point Likert Scale questionnaire. Compared with literature, this simulator has an error of 0.23±0.13% for deformation and 0.30±0.85mm for the aortic root displacement. In-vitro experiments show an error of 1.35±1.38mm for deformation prediction. The end-user evaluation results show that novices are more accustomed to using joystick controllers, and cardiologists are more satisfied with the visual authenticity. The real-time and accurate performance of the simulator make this framework suitable for creating a dynamic environment for autonomous navigation of robotic catheters.
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Affiliation(s)
- Zhen Li
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Piazza Leonardo da Vinci 32, Milan 20133, Italy; Department of Biomechanical Engineering, Delft University of Technology, Mekelweg 2, CD Delft 2628, Netherlands.
| | - Enrico Manzionna
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Piazza Leonardo da Vinci 32, Milan 20133, Italy
| | | | | | | | - Daniele Andreini
- Centro Cardiologico Monzino, IRCCS, Milan, Italy; Department of Clinical Sciences and Community Health, University of Milan, Milan, Italy
| | - Jenny Dankelman
- Department of Biomechanical Engineering, Delft University of Technology, Mekelweg 2, CD Delft 2628, Netherlands
| | - Elena De Momi
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Piazza Leonardo da Vinci 32, Milan 20133, Italy
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Brouwer J, Gheorghe L, Rensing BJ, Swaans MJ. First use of 3D-TEE model-based fully automatic fusion of 3D-MSCT and fluoroscopy during transcatheter aortic valve implantation. EUROINTERVENTION 2019; 15:900-901. [DOI: 10.4244/eij-d-19-00261] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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