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General Orthopaedics

NAVIGATED VERSUS NON-NAVIGATED RESULTS OF A CT-BASED COMPUTER-ASSISTED SHOULDER ARTHROPLASTY SYSTEM IN 30 CADAVERS

International Society for Technology in Arthroplasty (ISTA) 31st Annual Congress, London, England, October 2018. Part 2.



Abstract

INTRODUCTION

Variability in placement of total shoulder arthroplasty (TSA) glenoid implants has led to the increased use of 3D CT preoperative planning software. Computer assisted surgery (CAS) offers the potential of improved accuracy in TSA while following a preoperative plan, as well as the flexibility for intraoperative adjustment during the procedure. This study compares the accuracy of implantation of reverse total shoulder arthroplasty (rTSA) glenoid implants using a CAS TSA system verses traditional non-navigated techniques in 30 cadaveric shoulders relative to a preoperative plan from 3D CT software.

METHODS

High resolution 1mm slice thickness CT scans were obtained on 30 cadaveric shoulders from 15 matched pair specimens. Each scan was segmented and the digital models were incorporated into a preoperative planning software. Five fellowship trained orthopedic shoulder specialists used this software to virtually place a rTSA glenoid implant as they deemed best fit in six cadavers each. The specimens were randomized with respect to side and split into a cohort utilizing the CAS system and a cohort utilizing conventional instrumentation, for a total of three shoulders per cohort per surgeon. A BaSO4 PEEK surrogate implant identical in geometry to the metal implant used in the preoperative plan was used in every specimen, to maintain high CT resolution while minimizing CT artifact. The surgeons were instructed to implant the rTSA implants as close to their preoperative plans as possible for both cohorts. In the CAS cohort, each surgeon used the system to register the native cadaveric bones to each respective CT, perform the TSA procedure, and implant the surrogate rTSA implant. The surgeons then performed the TSA procedure on the opposing side of the matched pair using conventional instrumentation.

Postoperatively, CT scans were repeated on each specimen and segmented to extract the digital models. The pre- and postoperative scapulae models were aligned using a best fit match algorithm, and variance between the virtual planned position of the implant and the executed surgical position of the implant was calculated [Fig 1].

RESULTS

For version and inclination, implants in the CAS cohort showed significantly less deviation from preoperative plan than those in the non-navigated cohort (Version: 1.9 ± 1.9° vs 5.9 ± 3.5°; p < .001; Inclination: 2.4 ± 2.5° vs 6.3 ± 6.2°; p = .031). No significant difference was noted between the two cohorts regarding deviation from the preoperative plan in anterior-posterior and superior-inferior positioning on the glenoid face (1.5 ± 1.0mm CAS cohort, 2.4 ± 1.3mm non- navigated cohort; p = .055). No significant difference was found for deviation from preoperative plan for reaming depth (1.1

± 0.7mm CAS cohort, 1.3 ± 0.9mm non-navigated cohort; p =.397).

CONCLUSION

The results of this study demonstrate that this CAS navigation system facilitates a surgeon's ability to more accurately reproduce their intended glenoid implant version and inclination (with respect to their preoperative plan), compared to conventional non-navigated techniques. Future work will determine if more accurate and precise implant placement is associated with improved clinical outcomes.

For any figures or tables, please contact the authors directly.