OBJECTIVE: Learning surgical skills is an essential part of neurosurgical training. Ideally, these skills are acquired to a sufficient extent in an ex vivo setting. The authors previously described an in vitro brain tumor model, consisting of a cadaveric animal brain injected with fluorescent agar-agar, for acquiring a wide range of basic neuro-oncological skills. This model focused on haptic skills such as safe tissue ablation technique and the training of fluorescence-based resection. As important didactical technologies such as mixed reality and 3D printing become more readily available, the authors developed a readily available training model that integrates the haptic aspects into a mixed reality setup. METHODS: The anatomical structures of a brain tumor patient were segmented from medical imaging data to create a digital twin of the case. Bony structures were 3D printed and combined with the in vitro brain tumor model. The segmented structures were visualized in mixed reality headsets, and the congruence of the printed and the virtual objects allowed them to be spatially superimposed. In this way, users of the system were able to train on the entire treatment process from surgery planning to instrument preparation and execution of the surgery. RESULTS: Mixed reality visualization in the joint model facilitated model (patient) positioning as well as craniotomy and the extent of resection planning respecting case-dependent specifications. The advanced physical model allowed brain tumor surgery training including skin incision; craniotomy; dural opening; fluorescence-guided tumor resection; and dura, bone, and skin closure. CONCLUSIONS: Combining mixed reality visualization with the corresponding 3D printed physical hands-on model allowed advanced training of sequential brain tumor resection skills. Three-dimensional printing technology facilitates the production of a precise, reproducible, and worldwide accessible brain tumor surgery model. The described model for brain tumor resection advanced regarding important aspects of skills training for neurosurgical residents (e.g., locating the lesion, head position planning, skull trepanation, dura opening, tissue ablation techniques, fluorescence-guided resection, and closure). Mixed reality enriches the model with important structures that are difficult to model (e.g., vessels and fiber tracts) and advanced interaction concepts (e.g., craniotomy simulations). Finally, this concept demonstrates a bridging technology toward intraoperative application of mixed reality.

Background/Objectives: In reverse shoulder arthroplasty (RSA), precise K-wire positioning of the glenoid component is critical to prevent complications such as glenoid loosening or instability as well as premature implant failure. Optimal component placement must adhere to individualized preoperative plans to account for patient-specific anatomical conditions. Conventional methods often fail to achieve this level of accuracy, undermining the need for personalized medicine. Intraoperative navigation systems are growing in use to improve accuracy in orthopedic surgery. This study aimed to compare the accuracy of K-wire positioning in a 3D-printed model of the scapula using conventional versus navigated methods. Methods: We recruited 20 participants: 10 experienced surgeons and 10 inexperienced medical students. Each participant performed four K-wire drillings—two with conventional instruments and two with an intraoperative navigation system. A novel target system, BoneTrack3D, was used to measure accuracy. We assessed the absolute deviation of the entry and exit points as well as the three-dimensional drilling angle. Results: The navigated method was significantly more accurate for all measured parameters at a family-wise significance level of α = 0.05. The median absolute deviation for the entry point was 1.6 mm with navigation versus 3.0 mm with the conventional method (p < 0.001). Similarly, the exit point deviation was 1.8 mm with navigation versus 6.7 mm conventionally (p < 0.001). The drilling angle deviation also showed significant improvement with navigation, at 2.6° compared to 8.9° conventionally (p < 0.001). However, the navigated method took longer, with a median drilling time of 100.0 s compared to 55.0 s for the conventional method (p < 0.001). The navigated method provided consistent and superior results regardless of a participant’s surgical experience. Conclusions: Navigated techniques for K-wire positioning in RSA demonstrate enhanced accuracy in a 3D-printed model, effectively executing a precise, patient-specific preoperative plan. This could be a direct contribution to personalized medicine, ensuring the final implant alignment is tailored to the individual’s anatomy. Furthermore, intraoperative navigation may contribute to a flatter learning curve, thereby increasing accessibility for surgeons with varying levels of experience. Although navigation introduces additional costs and longer initial procedure times, these drawbacks could be offset by improved technical outcomes and a reduced risk of complications. Future studies, including randomized clinical trials and cost-effectiveness analyses, should seek to validate these results in clinical settings with longer follow-up periods and larger patient cohorts to define long-term value and utility of navigation systems in reverse shoulder arthroplasty.