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The Accuracy of Three-Dimensional CT Scan Software in Predicting Prosthetic Utilization in Total Shoulder
Keith M Baumgarten1, Logan Radtke
1From the Orthopedic Institute (Baumgarten), and the University of South Dakota Sanford School of Medicine, Sioux Falls, SD (Baumgarten and Radtke).
The Journal of the American Academy of Orthopaedic Surgeons
|October 6, 2021
Summary
Three-dimensional CT software accurately predicts shoulder arthroplasty type (97%) but shows lower accuracy for specific implant selection. This technology aids in optimizing surgical planning and supply chain logistics for prosthetic implants.
Area of Science:
- Orthopedic Surgery
- Medical Imaging
- Biomedical Engineering
Background:
- Innovations in shoulder arthroplasty include 3D CT software for predicting prosthetic implants.
- Accurate implant prediction can optimize supply chain logistics for all stakeholders.
- This study evaluates the predictive accuracy of 3D CT software in a single surgeon's experience.
Purpose of the Study:
- To determine the predictive accuracy of 3D CT software in identifying intraoperatively used prosthetic implants for shoulder arthroplasty.
- To assess the software's effectiveness in predicting both anatomic and reverse shoulder arthroplasty components.
Main Methods:
- Retrospective review of patients undergoing total shoulder arthroplasty (TSA) by a single surgeon.
- Inclusion of patients who had preoperative 3D CT planning software analysis.
- Chart review to compare preoperative plans with actual implanted prostheses.
Main Results:
- The study included 278 shoulders (151 anatomic TSA, 127 reverse TSA).
- The software accurately predicted arthroplasty type in 97% of cases.
- Accuracy for predicting all specific implants ranged from 20-28%, with higher accuracy for glenoid components (81-83%) and lower for humeral components (31-36%).
Conclusions:
- 3D CT software combined with surgeon's judgment offers high accuracy for predicting arthroplasty type.
- Predictive accuracy for specific glenoid implants is moderate, while accuracy for humeral implants and all components is low.
- The software shows potential for improving surgical planning but requires further refinement for precise implant prediction.
