Background: The recent development of three-dimensional (3D) technologies introduces a novel set of opportunities to the medical field in general, and specifically to surgery. The preoperative phase has proven to be a critical factor in surgical success. Utilization of 3D technologies has the potential to improve preoperative planning and overall surgical outcomes. In this narrative review article, the authors describe existing clinical data pertaining to the current use of 3D printing, virtual reality, and augmented reality in the preoperative phase of bone surgery. Methods: The methodology included keyword-based literature search in PubMed and Google Scholar for original articles published between 2014 and 2022. After excluding studies performed in nonbone surgery disciplines, data from 61 studies of five different surgical disciplines were processed to be included in this narrative review. Results: Among the mentioned technologies, 3D printing is currently the most advanced in terms of clinical use, predominantly creating anatomical models and patient-specific instruments that provide high-quality operative preparation. Virtual reality allows to set a surgical plan and to further simulate the procedure via a 2D screen or head mounted display. Augmented reality is found to be useful for surgical simulation upon 3D printed anatomical models or virtual phantoms. Conclusions: Overall, 3D technologies are gradually becoming an integral part of a surgeon’s preoperative toolbox, allowing for increased surgical accuracy and reduction of operation time, mainly in complex and unique surgical cases. This may eventually lead to improved surgical outcomes, thereby optimizing the personalized surgical approach.

Background: The use of electric scooters (e-scooters) has dramatically increased as they become an attractive alternative for public transportation in busy metropolitan areas worldwide. Despite their benefits, e-scooters challenge the health-care system with poorly understood forms of injuries, mainly orthopaedic fractures. To our knowledge, this study is the first to investigate e-scooter-related orthopaedic fracture patterns, mechanisms of injury, and management. Methods: Data on 3,331 e-scooter-related admissions were retrospectively collected between May 2017 and February 2020 in a level-I trauma center. These admissions were analyzed for demographic variables, orthopaedic fracture diagnosis (using the AO/OTA classification), associated injuries, and surgical treatment. Results: During the study period, a total of 716 fractures were diagnosed in 563 patients, with 46.4% of the patients requiring hospitalization. Of 492 upper-limb fractures, 89.2% occurred in a rider fall mechanism; and of 210 lower-limb fractures, 15.7% occurred in rider-vehicle collisions. Fifty-nine percent of long bone fractures were complex fragmentary and/or intra-articular fractures. Orthopaedic surgeons recommended that 225 fractures undergo surgical treatment. The most common upper-limb fracture was AO/OTA class 2R1A, with open reduction and internal fixation of the distal part of the radius being the most common upper-limb procedure (n = 58). The most common lower-limb fracture was AO/OTA class 41C, with open reduction and internal fixation of the proximal part of the tibia being the most common procedure (n = 28). A total of 22 patients (3.9%) required reoperation within 1 year. Conclusions: This investigation provides unique information on demographic characteristics, patterns, and treatment of orthopaedic fractures secondary to the high-energy mechanism of e-scooter injuries. These new in-depth data are important, first, for health-care system preparedness with regard to management and resource allocation to treat these challenging injuries and, second, for legislators promoting safety and injury prevention strategies.

Background: this pilot study aimed at determining whether the application of a novel new method of generating pulsed electromagnetic field (PEMF), the Fracture Healing Patch (FHP), accelerates the healing of acute distal radius fractures (DRF) when compared to a sham treatment. Methods: 41 patients with DRFs treated with cast immobilization were included. Patients were allocated to a PEMF group (n = 20) or a control (sham) group (n = 21). All patients were assessed with regard to functional and radiological outcomes (X-rays and CT scans) at 2, 4, 6 and 12 weeks. Results: fractures treated with active PEMF demonstrated significantly higher extent of union at 4 weeks as assessed by CT (76% vs. 58%, p = 0.02). SF12 mean physical score was significantly higher in PEMF treated group (47 vs. 36, p = 0.005). Time to cast removal was significantly shorter in PEMF treated patients, 33 ± 5.9 days in PEMF vs. 39.8 ± 7.4 days in sham group (p = 0.002). Conclusion: early addition of PEMF treatment may accelerate bone healing which could lead to a shorter cast immobilization, thus allowing an earlier return to daily life activities and work. There were no complications related to the PEMF device (FHP).

Objectives: To examine the clinical feasibility and results of a multidisciplinary workflow, employing rapid three-dimensional (3D) scanning and modeling software along with a high-speed printer, for in-hospital production of patient-specific 3D-printed casts, for the treatment of non-displaced wrist and hand fractures. Methods: Consenting adult patients admitted to the emergency department (ED) due to wrist or hand fractures between January and February 2021 were prospectively enrolled. The study participants underwent conversion of the standard plaster of Paris cast to a 3D-printed cast one week after the ED visit, and follow-up examinations were performed around two, six, and twelve weeks later. The primary objective was to examine the clinical feasibility in terms of complexity and length of the overall procedure. Secondary outcomes were patient-reported impressions and radiological results. Results: Twenty patients (16 males, mean age 37 ± 13.1 years) were included. The entire printing workflow took a mean of 161 ± 8 min. All patients demonstrated clinical improvement and fracture union at final follow-up, with no pressure sores or loss of reduction. Patient-reported comfort and satisfaction rates were excellent. The mean Visual Analog Scale was 0.9 ± 1.1 and 0.6 ± 1, and the mean Disabilities of the Arm, Shoulder, and Hand score was 18.7 ± 9.5 and 7.6 ± 7.6 at 2 and 6 weeks after application of the 3D-printed cast, respectively. Conclusion: The in-hospital workflow was feasible and efficient, with excellent clinical and radiographic results and high patient satisfaction and comfort rates. Our medical center now routinely provides this cast option for non-displaced wrist and hand fractures. Level of evidence: IV, Therapeutic Study

Background: As advanced technology continues to evolve, incorporating robotics into surgical procedures has become imperative for precision and accuracy in preoperative planning. Nevertheless, the integration of three-dimensional (3D) imaging into these processes presents both financial considerations and potential patient safety concerns. This study aims to assess the accuracy of a novel 2D-to-3D knee reconstruction solution, RSIP XPlan.ai™ (RSIP Vision, Jerusalem, Israel), on preoperative total knee arthroplasty (TKA) patient anatomies. Methods: Accuracy was calculated by measuring the Root Mean Square Error (RMSE) between X-ray-based 3D bone models generated by the algorithm and corresponding CT bone segmentations (distances of each mesh vertex to the closest vertex in the second mesh). The RMSE was computed globally for each bone, locally for eight clinically relevant bony landmark regions, and along simulated bone cut contours. In addition, the accuracies of three anatomical axes were assessed by comparing angular deviations to inter- and intra-observer baseline values. Results: The global RMSE was 0.93 ± 0.25 mm for the femur and 0.88 ± 0.14 mm for the tibia. Local RMSE values for bony landmark regions were 0.51 ± 0.33 mm for the five femoral landmarks and 0.47 ± 0.17 mm for the three tibial landmarks. The RMSE along simulated cut contours was 0.75 ± 0.35 mm for the distal femur cut and 0.63 ± 0.27 mm for the proximal tibial cut. Anatomical axial average angular deviations were 1.89° for the trans epicondylar axis (with an inter- and intra-observer baseline of 1.43°), 1.78° for the posterior condylar axis (with a baseline of 1.71°), and 2.82° (with a baseline of 2.56°) for the medial–lateral transverse axis. Conclusions: The study findings demonstrate promising results regarding the accuracy of XPlan.ai™ in reconstructing 3D bone models from plain-film X-rays. The observed accuracy on real-world TKA patient anatomies in anatomically relevant regions, including bony landmarks, cut contours, and axes, suggests the potential utility of this method in various clinical scenarios. Further validation studies on larger cohorts are warranted to fully assess the reliability and generalizability of our results. Nonetheless, our findings lay the groundwork for potential advancements in future robotic arthroplasty technologies, with XPlan.ai™ offering a promising alternative to conventional CT scans in certain clinical contexts.