1
|
Gao C, Farvardin A, Grupp RB, Bakhtiarinejad M, Ma L, Thies M, Unberath M, Taylor RH, Armand M. Fiducial-Free 2D/3D Registration for Robot-Assisted Femoroplasty. ACTA ACUST UNITED AC 2020; 2:437-446. [PMID: 33763632 DOI: 10.1109/tmrb.2020.3012460] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Femoroplasty is a proposed alternative therapeutic method for preventing osteoporotic hip fractures in the elderly. Previously developed navigation system for femoroplasty required the attachment of an external X-ray fiducial to the femur. We propose a fiducial-free 2D/3D registration pipeline using fluoroscopic images for robot-assisted femoroplasty. Intraoperative fluoroscopic images are taken from multiple views to perform registration of the femur and drilling/injection device. The proposed method was tested through comprehensive simulation and cadaveric studies. Performance was evaluated on the registration error of the femur and the drilling/injection device. In simulations, the proposed approach achieved a mean accuracy of 1.26±0.74 mm for the relative planned injection entry point; 0.63±0.21° and 0.17±0.19° for the femur injection path direction and device guide direction, respectively. In the cadaver studies, a mean error of 2.64 ± 1.10 mm was achieved between the planned entry point and the device guide tip. The biomechanical analysis showed that even with a 4 mm translational deviation from the optimal injection path, the yield load prior to fracture increased by 40.7%. This result suggests that the fiducial-less 2D/3D registration is sufficiently accurate to guide robot assisted femoroplasty.
Collapse
Affiliation(s)
- Cong Gao
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA 21211
| | - Amirhossein Farvardin
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, USA 21211
| | - Robert B Grupp
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA 21211
| | - Mahsan Bakhtiarinejad
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, USA 21211
| | - Liuhong Ma
- Department of Cranio-maxillo-facial Surgery Center, Plastic Surgery Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, CHN,100144
| | - Mareike Thies
- Pattern Recognition Lab, Friedrich-Alexander-Universitt Erlangen-Nrnberg, Erlangen, Germany 91058
| | - Mathias Unberath
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA 21211
| | - Russell H Taylor
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA 21211
| | - Mehran Armand
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, USA 21211; Department of Orthopaedic Surgery and Johns Hopkins Applied Physics Laboratory, Baltimore, MD, USA 21224
| |
Collapse
|
2
|
Kumar R. Robotic Assistance and Intervention in Spine Surgery. SPINAL IMAGING AND IMAGE ANALYSIS 2015. [DOI: 10.1007/978-3-319-12508-4_16] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/10/2023]
|
3
|
|