Optimal orthopaedic implant placement is a major contributing factor to the long term success of all common joint arthroplasty procedures. Devices such as three-dimensional (3D) printed, bespoke guides and orthopaedic robots are extensively described in the literature and have been shown to enhance prosthesis placement accuracy. These technologies, however, have significant drawbacks, such as logistical and temporal inefficiency, high cost, cumbersome nature and difficult theatre integration. A new technology for the rapid intraoperative production of patient-specific instrumentation, which overcomes many of the disadvantages of existing technologies, is presented here. The technology comprises a reusable table side machine, bespoke software and a disposable element comprising a region of standard geometry and a body of moldable material. Anatomical data from computed tomography (CT) scans of 10 human scapulae was collected and, in each case, the optimal glenoid guidewire position was digitally planned and recorded. The achieved accuracy compared to the pre-operative bespoke plan was measured in all glenoids, from both a conventional group and a guided group (GG). The technology was successfully able to intraoperatively produce sterile, patient-specific guides according to a pre-operative plan in 5min, with no additional manufacturing required prior to surgery. Additionally, the average guidewire placement accuracy was $1.58$ $1.58$ mm and 6.82 $^{\circ}$ $^{\circ}$ in the manual group, and $0.55$ $0.55$ mm and $1.7 6^{\circ}$ $1.7 6^{\circ}$ in the guided group, also demonstrating a statistically significant improvement.

This paper was recommended for publication in its revised form by Editors J. Marc Simard and Peter Berkelman.

NOTICE: Prior to using any material contained in this paper, the users are advised to consult with the individual paper author(s) regarding the material contained in this paper, including but not limited to, their specific design(s) and recommendation(s).

Keywords:

References

1. S. Krishnan, A. Dawood, R. Richards, J. Henckel and A. Hart, A review of rapid prototyped surgical guides for patient-specific total Knee replacement, J. Bone Joint Surg. Br. 94B (2012) 1457–1461. Crossref, Google Scholar
2. P. F. Choong, M. M. Dowsey and J. D. Stoney, Does accurate anatomical alignment result in better function and quality of life? comparing conventional and computer-assisted total knee arthroplasty, J. Arthroplasty 24 (4) (2009) 560–569. Crossref, Google Scholar
3. R. De Haan, P. A. Campbell, E. P. Su and K. A. De Smet, Revision of metal-on-metal resurfacing arthroplasty of the hip: the influence of malpositioning of the components, J. Bone Joint Surg. Br. 90-B (9) (2008) 1158–1163. Crossref, Google Scholar
4. A. P. Skirving, Total shoulder arthroplasty current problems and possible solutions, J. Orthop. Sci. 4 (1) (1999) 42–53. Crossref, Google Scholar
5. H. H. Malik, A. R. Darwood, S. Shaunak, P. Kulatilake, A. A. El-Hilly, O. Mulki and A. Baskaradas, Three-dimensional printing in surgery: a review of current surgical applications, J. Surg. Res. 199 (2) (2015) 512–522. Crossref, Google Scholar
6. M. Jakopec, F. R. y Baena, S. Harris, P. Gomes, J. Cobb and B. L. Davies, The hands-on orthopaedic robot “acrobot”: early clinical trials of total knee replacement surgery, IEEE Trans. Robot. Autom. 19 (2003) 902–911. Crossref, Google Scholar
7. J. Cobb, J. Henckel, P. Gomes, S. Harris, M. Jakopec, F. Rodriguez, A. Barrett and B. Davies, Hands-on robotic unicompartmental knee replacement: a prospective, randomized controlled study of the acrobot system, J. Bone Joint Surg. Br. 88-B (2) (2006) 188–197. Crossref, Google Scholar
8. J. E. Lang, S. Mannava, A. J. Floyd, M. S. Goddard, B. P. Smith, A. Mofidi, T. M. Seyler and R. H. Jinnah, Robotic systems in orthopaedic surgery, J. Bone Joint Surg. Br. 93-B (10) (2011) 1296–1299. Crossref, Google Scholar
9. D. C. Beringer, J. J. Patel and K. J. Bozic, An overview of economic issues in computer-assisted total joint arthroplasty, Clin. Orthop. Relat. Res. 463 (2007) 26–30. Crossref, Google Scholar
10. V. Salvi, Identifit: a silicone mold used to intraoperatively construct a cementless femoral stem, Chir. Organi Mov. 77 (4) (1992) 443–445. Google Scholar
11. J. D. Slover, H. E. Rubash, H. Malchau and J. A. Bosco, Cost-effectiveness analysis of custom total knee cutting blocks, J. Arthroplasty 27 (2) (2012) 180–185. Crossref, Google Scholar
12. E. Thienpont, F. Paternostre and C. van Wymeersch, The indirect cost of patient-specific instruments, Acta Orthop. Belg. 81 (3) (2015) 462–470. Google Scholar
13. M. Abderrahim and A. Whittaker, Kinematic model identification of industrial manipulators, Robot. Comput. Integr. Manuf. 16 (1) (2000) 1–8. Crossref, Google Scholar
14. P. Besl and N. D. McKay, A method for registration of 3-d shapes, IEEE Trans. Pattern Anal. Mach. Intell. 14 (1992) 239–256. Crossref, Google Scholar
15. B. K. P. Horn, Closed-form solution of absolute orientation using unit quaternions, J. Opt. Soc. Am. A 4 (4) (1987) 629–642. Crossref, Google Scholar
16. P. I. Corke, Robotics, Vision and Control: Fundamental Algorithms in MATLAB (Springer, 2011). Crossref, Google Scholar
17. G. Guennebaus et al., Eigen v3. http://eigen.tuxfamily.org (2010). Google Scholar