Intersurgeon and intrasurgeon variability in preoperative planning of anatomic total shoulder arthroplasty: a quantitative comparison of 49 cases planned by 9 surgeons

The Value of Computed Tomography-Based Planning in Shoulder Arthroplasty Compared to Intra-/Interobserver Reliability of X-ray Planning

Background: Reversed total shoulder arthroplasty (RTSA) is an established surgery for many pathologies of the shoulder and the demand continues to rise with an aging population. Preoperative planning is mandatory to support the surgeon's understanding of the patient's individual anatomy and, therefore, is crucial for the patient's outcome. Methods: In this observational study, we identified 30 patients who underwent RTSA with two- and three-dimensional preoperative planning. Each patient underwent new two-dimensional planning from a medical student and an orthopedic resident as well as through a mid-volume and high-volume shoulder surgeon, which was repeated after a minimum of 4 weeks. The intra- and interobserver reliability was then analyzed and compared to the 3D planning and the implanted prosthesis. The evaluated parameters were the size of the pegged glenoid baseplate, glenosphere, and humeral short stem. Results: The inter-rater reliability showed higher deviations in all four raters compared to the 3D planning of the base plate, glenosphere, and shaft. The intra-rater reliability showed a better correlation in more experienced raters, especially in the planning of the shaft. Conclusions: Our study shows that 3D planning is more accurate than traditional planning on plain X-rays, despite experienced shoulder surgeons showing better results in 2D planning than inexperienced ones.

Preoperative planning with three-dimensional CT vs. three-dimensional magnetic resonance imaging does not change surgical management for shoulder instability

Background

This study aims to determine the effect of time and imaging modality (three-dimensional (3D) CT vs. 3D magnetic resonance imaging (MRI)) on the surgical procedure indicated for shoulder instability. The hypothesis is there will be no clinical difference in procedure selection between time and imaging modality.

Methods

Eleven shoulder surgeons were surveyed with the same ten shoulder instability clinical scenarios at three time points. All time points included history of present illness, musculoskeletal exam, radiographs, and standard two-dimensional MRI. To assess the effect of imaging modality, survey 1 included 3D MRI while survey 2 included a two-dimensional and 3D CT scan. To assess the effect of time, a retest was performed with survey 3 which was identical to survey 2. The outcome measured was whether surgeons made a "major" or "minor" surgical change between surveys.

Results

The average major change rate was 14.1% (standard deviation: 7.6%). The average minor change rate was 12.6% (standard deviation: 7.5%). Between survey 1 to the survey 2, the major change rate was 15.2%, compared to 13.1% when going from the second to the third survey (P = .68). The minior change rate between the first and second surveys was 12.1% and between the second to third interview was 13.1% (P = .8).

Discussion

The findings suggest that the major factor related to procedural changes was time between reviewing patient information. Furthermore, this study demonstrates that there remains significant intrasurgeon variability in selecting surgical procedures for shoulder instability. Lastly, the findings in this study suggest that 3D MRI is clinically equivalent to 3D CT in guiding shoulder instability surgical management.

Conclusion

This study demonstrates that there is significant variability in surgical procedure selection driven by time alone in shoulder instability. Surgical decision making with 3D MRI was similar to 3D CT scans and may be used by surgeons for preoperative planning.

Impact of Deltoid Computer Tomography Image Data on the Accuracy of Machine Learning Predictions of Clinical Outcomes after Anatomic and Reverse Total Shoulder Arthroplasty

Background: Despite the importance of the deltoid to shoulder biomechanics, very few studies have quantified the three-dimensional shape, size, or quality of the deltoid muscle, and no studies have correlated these measurements to clinical outcomes after anatomic (aTSA) and/or reverse (rTSA) total shoulder arthroplasty in any statistically/scientifically relevant manner. Methods: Preoperative computer tomography (CT) images from 1057 patients (585 female, 469 male; 799 primary rTSA and 258 primary aTSA) of a single platform shoulder arthroplasty prosthesis (Equinoxe; Exactech, Inc., Gainesville, FL) were analyzed in this study. A machine learning (ML) framework was used to segment the deltoid muscle for 1057 patients and quantify 15 different muscle characteristics, including volumetric (size, shape, etc.) and intensity-based Hounsfield (HU) measurements. These deltoid measurements were correlated to postoperative clinical outcomes and utilized as inputs to train/test ML algorithms used to predict postoperative outcomes at multiple postoperative timepoints (1 year, 2-3 years, and 3-5 years) for aTSA and rTSA. Results: Numerous deltoid muscle measurements were demonstrated to significantly vary with age, gender, prosthesis type, and CT image kernel; notably, normalized deltoid volume and deltoid fatty infiltration were demonstrated to be relevant to preoperative and postoperative clinical outcomes after aTSA and rTSA. Incorporating deltoid image data into the ML models improved clinical outcome prediction accuracy relative to ML algorithms without image data, particularly for the prediction of abduction and forward elevation after aTSA and rTSA. Analyzing ML feature importance facilitated rank-ordering of the deltoid image measurements relevant to aTSA and rTSA clinical outcomes. Specifically, we identified that deltoid shape flatness, normalized deltoid volume, deltoid voxel skewness, and deltoid shape sphericity were the most predictive image-based features used to predict clinical outcomes after aTSA and rTSA. Many of these deltoid measurements were found to be more predictive of aTSA and rTSA postoperative outcomes than patient demographic data, comorbidity data, and diagnosis data. Conclusions: While future work is required to further refine the ML models, which include additional shoulder muscles, like the rotator cuff, our results show promise that the developed ML framework can be used to evolve traditional CT-based preoperative planning software into an evidence-based ML clinical decision support tool.

Two-year clinical outcomes and complication rates in anatomic and reverse shoulder arthroplasty implanted with Exactech GPS intraoperative navigation

INTRODUCTION

We compared the 2-year clinical outcomes of both anatomic and reverse total shoulder arthroplasty (ATSA and RTSA) using intraoperative navigation compared to traditional positioning techniques. We also examined the effect of glenoid implant retroversion on clinical outcomes.

HYPOTHESIS

In both ATSA and RTSA, computer navigation would be associated with equal or better outcomes with fewer complications. Final glenoid version and degree of correction would not show outcome differences.

MATERIAL AND METHODS

A total of 216 ATSAs and 533 RTSAs were performed using preoperative planning and intraoperative navigation with a minimum of 2-year follow-up. Matched cohorts (2:1) for age, gender, and follow-up for cases without intraoperative navigation were compared using all standard shoulder arthroplasty clinical outcome metrics. Two subanalyses were performed on navigated cases comparing glenoids positioned greater or less than 10° of retroversion and glenoids corrected more or less than 15°.

RESULTS

For ASTA, no statistical differences were found between the navigated and non-navigated cohorts for postoperative complications, glenoid implant loosening, or revision rate. No significant differences were seen in any of the ATSA outcome metrics besides higher internal and external rotation in the navigated cohort. For RTSA, the navigated cohort showed an ARR of 1.7% (95% CI 0%, 3.4%) for postoperative complications and 0.7% (95% CI 0.1%, 1.2%) for dislocations. No difference was found in the revision rate, glenoid implant loosening, acromial stress fracture rates, or scapular notching. Navigated RTSA patients demonstrated significant improvements over non-navigated patients in internal rotation, external rotation, maximum lifting weight, the Simple Shoulder Test (SST), Constant, and Shoulder Arthroplasty Smart (SAS) scores. For the navigated subcohorts, ATSA cases with a higher degree of final retroversion showed significant improvement in pain, Constant, American Shoulder and Elbow Surgeons Standardized Shoulder Assessment Form (ASES), SST, University of California-Los Angeles shoulder score (UCLA), and Shoulder Pain and Disability Index (SPADI) scores. No significant differences were found in the RTSA subcohort. Higher degrees of version correction showed improvement in external rotation, SST, and Constant scores for ATSA and forward elevation, internal rotation, pain, SST, Constant, ASES, UCLA, SPADI, and SAS scores for RTSA.

CONCLUSION

The use of intraoperative navigation shoulder arthroplasty is safe, produces at least equally good outcomes at 2 years as standard instrumentation does without any increased risk of complications. The effect of final implant position above or below 10° of glenoid retroversion and correction more or less than 15° does not negatively impact outcomes.

Accuracy and Reliability of Computerized Surgical Planning Software in Anatomic Total Shoulder Arthroplasty

PURPOSE

The primary purpose of this study was to assess the concordance between preoperatively determined implant parameters using CT-based planning software and surgically implanted prostheses. Secondarily, we sought to evaluate the agreement between preoperative plans performed by surgeons at different levels of training.

METHODS

Patients with primary glenohumeral osteoarthritis who underwent anatomic total shoulder arthroplasty (aTSA) and had a preoperative CT scan according to Blueprint (Stryker, Mahwah, NJ) protocol to be used for preoperative planning were included. A cohort of short-stemmed (SS) and stemless cases performed between October 2017 and December 2018 was randomly selected from an institutional database for the study. Planning was performed separately by four observers at different levels of orthopedic training at a minimum of six months following the actual surgery. Concordance between the surgical decisions during planning and the actually utilized implants was calculated. Additionally, inter-rater agreement was analyzed using the intra-class correlation coefficient (ICC). Implant parameters assessed were glenoid size, backside radius of curvature, and the need for posterior augment, in addition to humeral stem/nucleus size, head size, head height, and head eccentricity.

RESULTS

Twenty-one patients were included (10 stemmed and 11 stemless) with a cohort comprising 12 (57%) females with a median age of 62 years (IQR 59.5,67). There was a total of 544 decision possibilities based on the above parameters. The total number of decisions that matched surgical data was 333 (61.2%). Prediction of glenoid component augmentation need and size was the variable that matched most with surgical data (83.3%), whereas nucleus/stem size was the worst (42.9%). Interobserver agreement was excellent in one variable, good in three variables, moderate in one, and poor in two. The best interobserver agreement was with regard to head height.

CONCLUSION

Preoperative planning using CT-based software may be more accurate for the glenoid component when compared to humeral-sided parameters. Specifically, planning may be most helpful in determining the need and the size of glenoid component augmentation. Utilizing computerized software demonstrates high reliability, even among surgeons early in their orthopedic training.