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Bakhtiarinejad M, Gao C, Farvardin A, Zhu G, Wang Y, Oni JK, Taylor RH, Armand M. A Surgical Robotic System for Osteoporotic Hip Augmentation: System Development and Experimental Evaluation. IEEE TRANSACTIONS ON MEDICAL ROBOTICS AND BIONICS 2023; 5:18-29. [PMID: 37213937 PMCID: PMC10195101 DOI: 10.1109/tmrb.2023.3241589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/23/2023]
Abstract
Minimally-invasive Osteoporotic Hip Augmentation (OHA) by injecting bone cement is a potential treatment option to reduce the risk of hip fracture. This treatment can significantly benefit from computer-assisted planning and execution system to optimize the pattern of cement injection. We present a novel robotic system for the execution of OHA that consists of a 6-DOF robotic arm and integrated drilling and injection component. The minimally-invasive procedure is performed by registering the robot and preoperative images to the surgical scene using multiview image-based 2D/3D registration with no external fiducial attached to the body. The performance of the system is evaluated through experimental sawbone studies as well as cadaveric experiments with intact soft tissues. In the cadaver experiments, distance errors of 3.28mm and 2.64mm for entry and target points and orientation error of 2.30° are calculated. Moreover, the mean surface distance error of 2.13mm with translational error of 4.47mm is reported between injected and planned cement profiles. The experimental results demonstrate the first application of the proposed Robot-Assisted combined Drilling and Injection System (RADIS), incorporating biomechanical planning and intraoperative fiducial-less 2D/3D registration on human cadavers with intact soft tissues.
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Affiliation(s)
- Mahsan Bakhtiarinejad
- Laboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD 21218, USA; Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Cong Gao
- Laboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD 21218, USA; Department of Computer Science, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Amirhossein Farvardin
- Laboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD 21218, USA; Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Gang Zhu
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Yu Wang
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Julius K Oni
- Department of Orthopaedic Surgery, Johns Hopkins University, Baltimore, MD 21287, USA
| | - Russell H Taylor
- Laboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD 21218, USA; Department of Computer Science, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Mehran Armand
- Laboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD 21218, USA; Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA; Department of Computer Science, Johns Hopkins University, Baltimore, MD 21218, USA; Department of Orthopaedic Surgery, Johns Hopkins University, Baltimore, MD 21287, USA
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