Simulation-based training is increasingly used to support skill acquisition in endoscopic sinus surgery (ESS), although many existing simulators lack objective methods for performance evaluation. This study aimed to assess the face and construct validity of a patient-specific, multi-material 3D-printed sinonasal simulator for ESS using both structured technical scoring and postoperative radiological analysis. Fifteen surgeons with different levels of experience (novices, intermediates, and experts; n = 5 per group) performed a standardized sequence of ESS procedures on identical 3D-printed models, including dacryocystorhinostomy, uncinectomy, maxillary antrostomy, anterior and posterior ethmoidectomy, sphenoidotomy, and frontal sinusotomy (DRAF I). Surgical performance was evaluated on video recordings using a modified Objective Structured Assessment of Technical Skills (OSATS) score. After simulation, each model underwent computed tomography (CT) scanning and a dedicated radiological checklist was applied to assess the adequacy of surgical steps, dimensional parameters of enlarged sinus ostia, and potential procedural complications. Mean OSATS scores differed significantly among expertise levels, with experts achieving higher scores (48.0 +/- 1.9) than intermediates (39.4 +/- 3.4) and novices (28.4 +/- 3.8) (p < 0.01). CT analysis showed a significantly greater extent of ethmoidal cell removal in experts compared with novices (87.5% vs. 57.5%, p = 0.02) and a larger latero-lateral diameter of the frontoethmoidal recess compared with intermediates (p = 0.04). Questionnaire results indicated high perceived educational value, particularly among novices, despite some limitations in haptic realism. While the simulator appears to be a promising tool for ESS training, further studies are required to validate its effectiveness in improving surgical performance.

Spatial intelligence is critical for advancing computer-assisted technologies in Minimally Invasive Surgery (MIS). However, progress in this field has lagged behind other domains, primarily due to the limited availability of annotated data. To address this challenge, we propose a novel parallel adaptation technique that is both parameter- and memory-efficient, specifically designed to adapt depth foundation models for three-dimensional reconstruction and segmentation tasks. Our approach introduces parallel convolutional adapters for each task while keeping the underlying foundation model frozen. This design enables effective adaptation to the laparoscopic domain without compromising the learned geometric priors, which are essential for preserving sharp object boundaries. As a result, the proposed method facilitates the development of a comprehensive virtual measurement system. Extensive experiments on established benchmarks demonstrate the effectiveness and robustness of our approach. The implementation is available on GitHub .

STUDY OBJECTIVE:To evaluate the feasibility and surgical impact of static digital twin reconstructions in patients undergoing resection for complex pelvic or abdominal recurrences of gynecologic cancers. DESIGN:Prospective and observational feasibility study. SETTING:Academic tertiary care center with integrated biomedical engineering support. PATIENTS:Four patients with suspected oligometastatic recurrence of gynecologic malignancy involving vascular, urinary, nervous, or skeletal structures, deemed eligible for curative-intent surgery and 8 historical controls with recurrent leiomyosarcoma selected for exploratory comparison. INTERVENTIONS:Included patients underwent high-resolution cross-sectional imaging followed by semiautomated 3D segmentation and static digital twin reconstruction using Mimics Medical software (Materialise, Leuven, Belgium). Virtual models were co-reviewed by surgeons and engineers for surgical planning. During surgery, the digital twin was available for intraoperative navigation. Postoperative concordance between the model and intraoperative findings was evaluated by a multidisciplinary team (surgeon, radiologist, and clinical engineer) using an internally developed 1-5 rating scale. MEASUREMENTS AND MAIN RESULTS:All procedures were completed without intraoperative complications. The mean operative time was 191.5 minutes (range 120-270). In each case, the static digital twin allowed enhanced preoperative planning, identification of anatomical variants (e.g., duplicated ureter), and optimized team coordination. Surgical findings were highly concordant with the preoperative 3D models. No unplanned injuries or postoperative complications were observed. Intraoperative decision-making was positively influenced by the use of the model in all cases. CONCLUSION:Static digital twins are feasible and effective tools for surgical planning in complex gynecologic cancer recurrences. Their use supports anatomical understanding, interdisciplinary coordination, and intraoperative safety. Further research is needed to validate their impact on surgical outcomes and workflow efficiency.

Fibula free flaps are the gold standard for mandibular reconstruction, yet non-union remains a significant challenge. This study presents a patient-specific finite element and mechanobiological framework to evaluate early bone healing with reconstruction plates and miniplates. Postoperative CT-based models were subjected to clenching loads, and a mechano-regulation algorithm simulated callus differentiation based on strain stimuli. Both fixation strategies ensured mechanical stability, with stresses below material limits. However, under the simulated loading conditions, miniplates generated more uniform strain distributions, promoting earlier ossification and suggesting a more favorable mechanical environment for early bone healing.

To enhance laparoscopic rectal cancer surgery, we implemented Augmented Reality (AR). Magnetic resonance neurography and CT images were segmented to create 3D pelvic models, including rectum, nerves, vessels, and ureters. The use of Artificial intelligence with ConvNext U-Net binary segmentation architecture addressed real-time occlusion of surgical instruments in AR overlays. Anatomical landmarks such as the abdominal aorta bifurcation and the right iliac artery crossing the ureter were used to anchor the 3D model to the surgical view. Retroperitoneal structures were preferred for AR application due to their stability under pneumoperitoneum. Key high-risk points during anterior rectum resection were identified to focus AR use on the most critical surgical phases. Ten accurate and reproducible 3D pelvic models, including tumors, were developed. AR-assisted surgery was successfully conducted in two laparosopic rectal resection cases. During these procedures, surgeons' ability to identify essential pelvic structures—vessels, ureters, and nerves—was assessed. The study demonstrates the feasibility of AR in rectal surgery and suggests that it may enhance surgical precision and safety by improving intraoperative visualization of complex pelvic anatomy.

Preclinical assessment of patient-specific mandibular reconstruction plates relies on bench testing and computational modeling, yet existing setups are typically designed on practical grounds without a structured method to ensure their mechanical relevance to the intended clinical context of use (COU). This study proposes and demonstrates a methodology for constructing and assessing a validation domain with experimental and computational components for patient-specific fibula free flap mandibular reconstruction. A clinical reference finite element model (M-COU) representing the reconstructed mandible under physiological clenching conditions was used as an active design tool to derive the validation setup. Parameters were identified through analytical calibration of M-COU reaction forces and refined via a design-of-experiments procedure. The resulting setup was implemented as two coordinated components: a physical validation platform (R-VAL) enabling bench testing of the actual reconstruction plate, and a validation computational model (M-VAL) reproducing the same setting numerically. The resulting setup preserved the dominant mechanical features of the clinical scenario. In consistency analysis against M-COU, M-VAL achieved R2 = 0.75, substantially exceeding literature-based benchmark configurations (R2 = 0.27 and 0.40), and was the only configuration to preserve the clinically relevant stress distribution at the mandibular angle. Comparison between M-VAL and R-VAL showed close agreement in initial structural stiffness (0.6% difference) and local strain distribution (R2 = 0.93; RMSE = 10.9%). The proposed methodology provides a transferable framework for constructing validation domains that are simultaneously experimentally feasible, mechanically interpretable, and grounded in a defined clinical COU.

Binary surgical tool segmentation is a crucial component of Computer-Assisted Intervention (CAI) applications in minimally invasive surgery (MIS). Accurate segmentation is essential for instrument tracking, surgical scene understanding, and augmented reality overlays. However, a complete CAI system consists of multiple parallel processes, necessitating fast, accurate, and robust segmentation models with low computational cost and minimal memory footprint. In this study, a comprehensive benchmarking analysis of various backbone architectures and decoder topologies for binary surgical tool segmentation is conducted. The evaluation assesses memory efficiency, computational complexity, and generalization ability across unseen surgical datasets, including robotic, laparoscopic, and endoscopic procedures. The experimental results reveal the trade-offs between segmentation performance and resource constraints, offering valuable insights for selecting efficient models suitable for real-time surgical applications.

OBJECTIVE:Augmented reality (AR) has recently gained a reputation in surgical applications, providing real-time integration of virtual information into the surgeon's field of view. The aim of this paper was to describe the authors' clinical experience with AR using the Microsoft HoloLens 2 head-mounted display (HMD) in pediatric craniofacial surgery, particularly for correcting single-suture craniosynostosis. METHODS:In this study, the authors compared AR-guided osteotomies with those guided by a traditional neurosurgical navigation system in a cohort of 10 consecutive pediatric patients. Osteotomy lines drawn under both AR and standard neurosurgical navigator guidance were measured using computer-aided design/computer-aided manufacturing templates. Accuracy was evaluated at the ± 1.5-mm and ± 1.0-mm thresholds. RESULTS:The findings demonstrated a statistically significant superior accuracy using AR guidance at the ± 1.0-mm level, achieving an average accuracy of 34% compared to 16% with standard navigation (p = 0.044). CONCLUSIONS:The results indicate that AR performs similarly to traditional navigation methods in terms of accuracy. These findings suggest that AR-based HMDs hold significant potential to be a reliable method of intraoperative navigation. Further studies are recommended to implement the application of this technology and assess long-term outcomes.

Ossiculoplasty (OPL) aims to restore ossicular chain continuity to improve hearing in patients with conductive or mixed hearing loss, often performed during tympanoplasty. The current training methods, including cadaveric temporal bone models, face challenges such as limited availability, high costs, and biological risks, prompting the exploration of alternative models. This study introduces a novel training platform for OPL using 3D-printed temporal bones and incudes, including a magnified (3:1) model to enhance skill acquisition. Sixty medical students were divided into two groups: one trained on magnified models before transitioning to real-sized ones, and the other used only real-sized models. Training performance was quantitatively assessed using post-remodeling cone-beam CT imaging and mesh distance analysis. The results showed a significant improvement in performance for students with preliminary training on magnified models (87% acceptable results vs. 37%, p = 0.001). Qualitative feedback indicated higher confidence and skill ratings in the magnified model group. This study highlights the effectiveness of scalable, anatomically accurate synthetic models for complex surgical training. While further validation is required with experienced trainees and broader scenarios, the findings support the integration of 3D printing technologies into otologic education, offering a cost-effective, reproducible, and innovative approach to enhancing surgical preparedness.

OBJECTIVE:To develop and preliminarily validate a 3D-printed, multi-material, patient-specific simulator of the external and middle ear affected by stapes fixation. The simulator was designed for training in endoscopic stapes surgery (SS), addressing the lack of reliable training platforms for this technically challenging procedure. METHODS:Imaging data from a CT scan of a patient were used to create a virtual 3D model of significant ear structures. The simulator consisted of a multi-use temporal bone holder and a single-use middle ear box, printed with material Jetting 3D printing technology. Eight participants to a university ear surgery course used the simulator to perform endoscopic stapes surgery. The surgical performance was evaluated using modified Objective Structured Assessment of Technical Skills (OSATS) scoring, and participant feedback was gathered through qualitative questionnaires. RESULTS:Seven of the eight participants successfully completed the simulated SS, with a mean surgical time of 24 min. OSATS scores showed acceptable performance, with 75% of participants achieving a score above 20. The tactile feedback, particularly for the stapes fixation, was well received, although the chorda tympani was deemed too fragile. The simulator was highly valued for visuomotor coordination development. CONCLUSIONS:The 3D Stapes Trainer represents a promising platform for training in endoscopic SS. Despite its limitations, the model provided young surgeons with a valuable platform to gain confidence in the steps of endoscopic SS, offering a high-fidelity simulation that contributes to the development of the technical skills required in this demanding procedure. LEVEL OF EVIDENCE:N/A.

BACKGROUND:Margin control is a crucial prognostic factor in head and neck oncological surgery. This retrospective case-control study aims to assess the superiority of computer-assisted surgery compared to traditional surgery in achieving optimal resection margins in maxillofacial oncologic surgery. METHODS:Eighty patients with stage T3 or T4 oral squamous cell carcinoma were included, equally divided into computer-assisted surgery (CAS) and freehand groups. Negative, close, and positive margin rates were compared. Logistic regression with Firth's correction and multivariable Cox models for disease-free survival (DFS) and overall survival (OS) were applied, with tobacco and alcohol included as covariates. Sensitivity analyses used inverse probability of treatment weighting (IPTW)-weighted models. RESULTS:CAS was associated with a significantly lower risk of positive margins (OR 0.24; 95% CI: 0.06-0.78; p = 0.01), confirmed in the IPTW analysis. DFS was significantly improved with CAS in both multivariable and IPTW Cox models (HR 0.41 and 0.46, respectively), while OS showed no significant benefit. Nodal status emerged as the strongest prognostic factor. CONCLUSIONS:Despite its univocality, the CAS technology seems to offer significant advantages in achieving precise oncological margin control for oral squamous cell carcinomas.

Noninvasive ventilation (NIV) is a well-established technique for managing acute respiratory failure in various clinical settings. However, safety concerns in clinical NIV applications emerge due to the absence of robust monitoring and alarm systems, potentially leading to issues such as CO2 rebreathing during flow-block events. This work aims to enhance the safety and monitoring of NIV systems by studying the integration of two types of carbon dioxide (CO2) sensors within NIV helmets. The investigation encompasses two main analyses. The first analysis explores the impact of varying the fresh inlet gas flow rate on local CO2 concentrations within the helmet. The second analysis investigates the response of CO2 sensors during simulated flow-block events, a critical safety concern in NIV therapy. In both analyses the effect of the sensor positioning is also investigated. Results demonstrate that higher fresh gas flow rates enhance CO2 washout within the helmet, highlighting the importance of optimizing gas flow rates to mitigate CO2 rebreathing. The positioning of CO2 sensors within the helmet was also found to significantly influence measurements by affecting signal stability and response to flow-block events. Overall, this study demonstrated the potential of integrating CO2 sensors within NIV helmets to enhance patient safety and treatment effectiveness. The knowledge gained from this study can be used to guide the design and optimization of NIV systems.

Background: Augmented-reality (AR) navigation is emerging as a means of turning pre-operative cone-beam CT data into intuitive, in situ guidance for difficult tooth removal, yet the scattered evidence has never been consolidated nor illustrated with a full clinical workflow. Aims: This study aims to narratively synthesise AR applications limited to dental extractions and to illustrate a full AR-guided clinical workflow. Methods: We performed a PRISMA-informed narrative search (PubMed + Cochrane, January 2015–June 2025) focused exclusively on AR applications in dental extractions and found nine eligible studies. Results: These pilot reports—covering impacted third molars, supernumerary incisors, canines, and cyst-associated teeth—all used marker-less registration on natural dental surfaces and achieved mean target-registration errors below 1 mm with headset set-up times under three minutes; the only translational series (six molars) recorded a mean surgical duration of 21 ± 6 min and a System Usability Scale score of 79. To translate these findings into practice, we describe a case of AR-guided mandibular third-molar extraction. A QR-referenced 3D-printed splint, intra-oral scan, and CBCT were fused to create a colour-coded hologram rendered on a Magic Leap 2 headset. The procedure took 19 min and required only a conservative osteotomy and accurate odontotomy that ended without neurosensory disturbance (VAS pain 2/10 at one week). Conclusions: Collectively, the literature synthesis and clinical demonstration suggest that current AR platforms deliver sub-millimetre accuracy, minimal workflow overhead, and high user acceptance in high-risk extractions while highlighting the need for larger, controlled trials to prove tangible patient benefit.

This randomized trial aims to compare the efficacy of Patient Specific Implants in bimaxillary orthognathic surgery via maxilla-guided or mandible-guided technique, focusing on the accuracy of pre-operative planning transfer in the operating room.Twenty patients with dentoskeletal dysmorphism were enrolled and virtual surgical planning (VSP) was performed. Subsequently, they underwent bimaxillary orthognathic surgery using either a maxilla-guided or a mandible-guided approach, as determined via a blind randomization process. Post-operative CBCT scans were conducted one month after surgery to assess maxillo-mandibular positioning. Finally, a roto-translational rigid body analysis was conducted to compare the initial VSP and the post-operative results.Results revealed high reproducibility with both techniques, maxilla-guided approach demonstrating an increased accuracy in vertical, antero-posterior and total translational repositioning of the maxilla, and the antero-posterior repositioning of the mandible compared to the mandible-guided approach. However, the mandible-guided approach offered greater flexibility in controlling the vertical dimension. The two methods have proven to be largely comparable in terms of mandibular rami positioning. Both techniques exhibited clinically equivalent precision in reproducing the VSP, with no surgical complications observed.In conclusion, while the maxilla-guided approach exhibited generally lower discrepancies in the reproduction of the VSP, both techniques were deemed equally effective in bimaxillary orthognathic surgery.