ABSTRACT
Augmented reality (AR) and 3D printing (3DP) are novel technologies in the orthopedic field. Over the past decade, enthusiasm for these new digital applications has driven new perspectives in improving diagnostic accuracy and sensitivity in the field of traumatology. Currently, however, it is still difficult to quantify their value and impact in the medical-scientific field, especially in the improvement of diagnostics in complex fractures. Acetabular fractures have always been a challenge in orthopedics, due to their volumetric complexity and low diagnostic reliability. Background/Objectives: The goal of this study was to determine whether these methods could improve the learning aspect and diagnostic accuracy of complex acetabular fractures compared to gold-standard CT (computed tomography). Methods: Orthopedic residents of our department were selected and divided into Junior (JUN) and Senior (SEN) groups. Associated fractures of acetabulum were included in the study, and details of these were provided as CT scans, 3DP models, and AR models displayed on a tablet screen. In a double-blind questionnaire, each resident classified every fracture. Diagnostic accuracy (DA), response time (RT), agreement (R), and confidence (C) were measured. Results: Twenty residents (JUN = 10, SEN = 10) classified five fractures. Overall DA was 26% (CT), 18% (3DP), and 29% (AR). AR-DA was superior to 3DP-DA (p = 0.048). DA means (JUN vs. SEN, respectively): CT-DA was 20% vs. 32% (p < 0.05), 3DP-DA was 12% vs. 24% (p = 0.08), and AR-DA was 28% vs. 30% (p = 0.80). Overall RT was 61.2 s (±24.6) for CT, 35.8 s (±20.1) for 3DP, and 46.7 s (±20.8) for AR. R was fairly poor between methods and groups. Overall, 3DPs had superior C (65%). Conclusions: AR had the same overall DA as CT, independent of experience, 3DP had minor differences in DA and R, but it was the fastest method and the one in which there was the most confidence. Intra- and inter-observer R between methods remained very poor in residents.
ABSTRACT
Background: Proximal humerus fractures (PHFs) are one of the most frequent fractures in the elderly and are the third most fractures after those of the hip and wrist. PHFs are assessed clinically through conventionally standard imaging (X-ray and computed tomography (CT) scans). The present study aims to conduct the diagnostic evaluation and therapeutic efficacy of the 3D-printed models (3DPMs) for the PHFs, compared with the standard imaging. Objectives: In terms of fracture classification and surgical indication, PHFs have poor interobserver agreement between orthopedic surgeons using traditional imaging such as X-rays and CT scan. Our objective is to compare interobserver reliability in diagnostic evaluation of PHFs using 3DPMs compared to traditional imaging. Methods: The inclusion criteria were elders aged >65 years, fracture classification AO/OTA 11 B and 11 C, and no pathological fractures or polytrauma. In addition, 9 PHFs were assessed by 6 evaluators through a questionnaire and double-blinded administered for each imaging (X-ray and CT scan) and 3DPMs for each fracture. The questionnaire for each method regarded Neer classification, Hertel classification, treatment indication (IT), and surgical technique (ST). Interobserver reliability was calculated through the intraclass correlation coefficient (ICC). Results: Nine patients with PHF were included in the study (66% female). The Neer and Hertel classifications between imaging types had similar ICC values between raters with no statistical differences. IT reliability using CT scan and 3DPMs (ICC = 1; (p=0.116)) assessed better agreement compared with X-rays IT. The ST reliability using 3DPMs (ICC = 0.755; p=0.002) was statistically superior to traditional imaging (ST-RX ICC = -0.004 (p=0.454); ST-CT ICC = 0.429 (p=0.116)). Conclusion: Classification systems like Neer and Hertel offer poor reliability between operators. The 3DPMs for evaluating diagnostics are comparable to CT images but superior to the surgical technique agreement. The application of 3DPMs is effective for preoperative fracture planning and the modeling of patient-specific hardware.
