CAOS 2025: Papers with Abstracts

Abstract. Objective: 3D bone shapes play a critical role in preclinical and clinical orthopedic applications. This study aimed to identify and evaluate 10 most relevant existing online CT databases to see if they meet requirements of biomedical experts.
Method: We performed a systematic search to identify relevant online CT databases for lower extremities. Additionally, a workshop with n=40 biomedical experts was held to gather insights on the benefits, challenges, and users for an online 3D bone shape database. This information was used to establish criteria to evaluate the identified databases.
Results: We found that currently available online databases inadequately address experts’ needs, particularly regarding inclusion of different shape formats, such as 3D meshes and CAD models, and inclusion of mechanical properties of bones.
Conclusion: These findings highlight a significant gap between databases’ offerings and users’ needs, underscoring the need for more comprehensive, accessible resources and advanced tools to support the field's progression.

Abstract. Background: Achieving optimal implant placement and gap balance is critical in total knee arthroplasty (TKA). Due to the limited precision of traditional instrumentation, technologies like computer-assisted surgery and robotic-assisted TKA have been developed. This experimental cadaveric study aimed to evaluate the accuracy and reproducibility of the Robin robotic system, a collaborative image-free technology, to support its clinical application.
Methods: Fifteen cadaveric specimens were treated by eight experienced TKA surgeons, all proficient in computer-assisted TKA but new to the Robin system. After receiving the same standardized training, surgeons used the robotic system, which positions and holds a universal cutting jig while they perform osteotomies. Registration repeatability was assessed by the alignment of cutting block positions with pre-existing pin placements. Bone resections, angles, and axes were analyzed by comparing preoperative planning values with the outcomes measured using a validated navigation system.
Results: There were no statistically significant differences between planned and measured resection angles, except for femoral and tibial orientation on the sagittal plane (0.6±0.8° and 0.6±1.0°). Similarly, resection thickness showed minimal deviations, with only the distal medial femoral cut differing by 0.8±0.7 mm. These results were consistent across all first-time users.
Conclusions: The Robin robotic system demonstrated high accuracy and reproducibility, closely matching preoperative plans for TKA. Its intuitive design allows surgeons to achieve their planned targets without altering surgical techniques, potentially improving efficiency and outcomes, even in complex cases.

Abstract. Restoring knee function to pre-diseased levels after arthroplasty remains challenging, as common surgical approaches do not easily account for the variability in joint-level function, leaving some patients with unmet functional expectations. Robotic-assisted knee arthroplasty (RAKA) enhances surgical precision and accuracy, but opportunities remain to better consider patient-specific morphological and anatomical variability and its influence on both passive and dynamic joint function in optimizing surgical decisions for the individual. This study examines the relationships between distal femur morphology, joint alignment, intraoperative passive knee kinematics, and active kinematics during walking to inform tailored knee arthroplasty surgical protocols.
Forty patients with end-stage knee osteoarthritis participated to date. Pre-operative gait kinematics were captured using markerless motion analysis. Passive kinematics were recorded intraoperatively under varus-valgus stress conditions with a robotic system. Morphological variables were measured on distal femurs modeled from computed tomography images to which principal component analysis was applied to reduce dimensionality and identify key morphometric shapes among this patient population.
PC1, characterized by wider femurs with elevated anterior condyles, was correlated with higher mean knee adduction angles during gait. PC2, reflecting longer femurs with flatter anterior condylar grooves, correlated with greater frontal plane variability during gait and higher passive angular movement under varus stress at 10° flexion.
These results highlight the influence of femoral morphology on knee mechanics and underscore the potential of integrating anatomical and morphometric variability into RAKA protocols to target functional outcomes. Continued exploration of these relationships could lead to improved post-arthroplasty functional outcomes tailored to individual patient needs.

Abstract. This study explores the integration of simulation-based augmented reality (AR) education in trauma care, focusing on digital twins and computer simulations for interactive learning. Traditional case discussions in fracture treatment rely on retrospective analysis. In contrast, this approach allows participants to experiment with treatment strategies and analyze their effects using predictive analytics, enhancing surgical outcomes.
The OSORA educational platform was deployed in trauma courses, utilizing the Ulm fracture healing model to simulate the bone tissue differentiation process. Participants could modify fracture management strategies and assess healing metrics such as interfragmentary movement and bone tissue formation. Interactive visualizations facilitated understanding of complex mechanobiological relationships, fostering a transition from passive to active learning.
Feedback from 109 participants and faculty members indicated positive reception of the concept. Course participants appreciated the clarity of learning objectives and the engaging nature of digital twins in case discussions. Faculty highlighted the potential of the platform to reduce preparation workload through improved usability and asynchronous formats. However, challenges such as technical requirements for 3D visualizations and the need for faculty onboarding were noted.
Future directions include extending the tool’s applications to cover the entire skeletal system, incorporating clinical planning software, and enhancing quality management through rigorous validation. Simulation-based education holds promise for improving trauma training, offering a risk-free environment to explore surgical outcomes and post-operative scenarios, ultimately bridging the gap between education and clinical practice.

Abstract. Purpose: The Young-Burgess pelvic ring classification system is commonly used for the classification of these fractures for treatment planning. In the emergency room, it is performed on a pelvic AP radiograph using general guidelines, whose results may vary between observers and may not be explainable. We aimed to validate a new rule-based regional anatomical system for systematic, explainable classification that is amenable to automation.
Methods: The rule-based pelvic regions system divides each pelvic radiograph into 11 distinct, partially overlapping pelvic regions. Each region is independently evaluated for radiographic findings – normal or injured. The Young-Burgess class is then determined with rules that combine the pelvic region evaluations.
Fifty pelvic radiographs were evaluated and classified into one of the Young-Burgess classes by three experienced orthopedic trauma surgeons. Each radiograph was assessed twice in separate sessions: once as a full image (Gestalt) and once with the pelvic regions only, presented in random locations to avoid providing spatial cues (Per-region). Inter-observer agreement was quantified with weighted kappa scores.
Results: The Gestalt and the Per-region evaluations had comparable inter-observer agreement, with mean weighted kappa scores of 0.46 and 0.47 (ranges 0.40-0.61 and 0.39-0.56), respectively. The Per-region approach had slightly more consistent scores across different observer pairs.
Conclusion: Performing Young-Burgess pelvic ring injury classification with a rule-based regional anatomical system yields observer agreement scores comparable to conventional whole-image evaluation. This suggests that machine learning methods using the new system may achieve results similar to human experts and provide more transparent and interpretable results than whole-image black box methods.

Abstract. Purpose: The Young-Burgess pelvic ring classification system is commonly used to support treatment planning. In the emergency room, it is performed on pelvic AP X-rays using general guidelines, whose results may vary between observers and may not be explainable. We aimed to validate a novel computerized method for the automatic Young-Burgess classification of traumatic pelvic ring fractures on pelvic AP X-rays using a rule-based regional anatomical system that provides systematic and explainable classifications.
Methods: The method inputs a pelvic AP X-ray. It extracts 11 pelvic regions using a pelvic regions atlas and a deep-learning model, classifies each pelvic region as normal/injured with another deep-learning network, and computes the Young-Burgess class with rules that combine the pelvic region classifications. The outputs are the Young-Burgess class and the pelvic AP X-ray with overlayed color-coded pelvic regions.
Evaluation was performed on 564 pelvic AP X-rays classified by a senior orthopedic trauma surgeon, on which 11 pelvic regions were delineated and classified as normal/injured. Two YOLOv8 deep-learning models were trained on 544 pelvic AP X-rays and tested on 20.
Results: Pelvic region computation yielded a mean F1-score of 0.99 (0.98-1.00). Pelvic region classification yielded a specificity of 1.00 and a mean sensitivity of 0.53 (0.20-1.00). The rule-based classification yielded a mean weighted kappa score of 0.47 and AUC score of 0.97.
Conclusion: Automatic Young-Burgess pelvic ring injury classification pelvic on AP X-rays with a rule-based regional anatomical system appears promising. Pelvic region computation is nearly perfect and rule-based classification is also excellent. Pelvic region classification requires further investigation.

Abstract. The hip joint center (HJC) does not only define the hip specific coordinate system in most definitions, but is also one of the most relevant functional parameters of the hip joint. Sphere fit of the femoral head is the most common method for HJC definition. In terms of preoperative planning for THA, many patients show deformities on the femoral heads and/or the acetabular region. Therefore, the approximation of the HJC via sphere fit has to be questioned. In our analysis, we studied different methods for automatic HJC definition and the influence of femoral head deformities on the location of the HJC for CT images of 201 THA patients. The different methods were ellipsoid fit on the femoral head, center of mass analysis of the femoral head, sphere fit on the acetabular region and geometric analysis based on ASIS location and pelvic width, height and depth. We compared the deviations between the sphere fit center and the different methods. We found best accordance with sphere fit for ellipsoid fit, followed by center of mass, acetabular sphere fit and geometric definition. The same tendency was found for the differences between sphere-like and deformed femoral heads, with deformed heads showing higher deviations for all methods. While no dynamic data was available, it has to be questioned, whether a sphere fit on the femoral head is the suitable for definition of HJC as center of rotation, especially for patients with deformed femoral heads. Further processing that takes different femur positions into account is recommended.

Abstract. Total hip arthroplasty (THA) is among the most common surgeries for hip osteoarthritis. Besides the conventional manual technique (mTHA), alternatives such as computer-assisted fluoroscopic navigation (cTHA) and robotic-assisted solutions (rTHA) are available for THA. We aimed to estimate the cost-utility of cTHA compared to rTHA and mTHA in patients undergoing THA from the US healthcare system perspective.
A Markov model was developed to compare costs and utilities of cTHA vs. mTHA, and cTHA vs. rTHA over a 1-year time horizon. Health states were defined based on the occurrence of readmissions with/without revisions due to fracture, dislocation, infection and hip pain. Utilities were presented in quality-adjusted life years (QALYs). Costs included length of stay, operative time and readmissions/revisions. The incremental cost-effectiveness ratio (ICER) was estimated as incremental cost per QALY change for each pairwise comparison. Inputs were drawn from published literature.
cTHA was associated with a slight QALY gain of 0.001, and estimated savings of $1,595 and $949 per patient compared to rTHA and mTHA, respectively. Results indicated that cTHA was the ‘dominant’ strategy, i.e. reducing costs and slightly increasing QALYs, compared to both alternatives. Probabilistic sensitivity analysis indicated that cTHA was cost saving in 100% of the 1,000 simulations compared to both rTHA and mTHA.
Using computer-assisted fluoroscopic navigation in THA showed cost savings and a slight improvement in quality of life compared to robotic-assisted and manual THA. Results suggest that computer-assisted fluoroscopic navigation is the preferred strategy for THA mainly due to downstream cost savings by reductions in OR time and readmissions/revisions rates.

Abstract. Mandibular reconstruction with bone grafts remains the gold standard for restoring masticatory function and facial aesthetics in patients with jaw defects. However, definitive guidelines for selecting plate types and fixation strategies remain lacking. This study evaluates different miniplate configurations to optimize bone union propensity (BUP) using physics-based simulation and finite element modeling. Various plate placements and screw configurations, covering a total of 10 cases, were tested to assess their impact on strain energy distribution and bone healing potential. The results indicate that miniplates with four screws provide superior stability and that higher placement enhances fixation. These findings contribute to refining patient-specific reconstruction strategies and improving surgical outcomes.

Abstract. Objective. Minimally invasive joint replacement offers benefits like little tissue damage, reduced pain, and fast recovery. Traditionally, the surgery has been adapted to the (size of the) implant limiting the true surgical potential. The aim of this study was to explore and conceptualize deployable implant spacer for minimally invasive surgery.
Methodology. Different deployment mechanisms have been researched and evaluated according to the suitability for joint implants. Origami, scissor, and sliding block were identified as most promising and integrated into a quadri-elliptical-shaped wrist implant spacer. The final designs were prototyped out of PLA using 3D printing and underwent compression testing of up to 1000 N in the lab.
Results. The deployment ratios were 140% for the origami, 150% for the scissor, and 160% for the sliding block. In the compression test, the origami prototype failed at 925 N, whereas scissor and sliding block survived the maximum load.
Conclusion. To the best of our knowledge, we explored for the first time a deployable implant spacer. Offering the highest deployment ratio and non-discrete height adaptation, the sliding block appeared to be most promising for in depth future research.

Abstract. The purpose of this descriptive study was to evaluate patient reported outcome at one year follow-up when performing TKA using a tibia 1st surgical workflow and a navigation system coupled to a ligament tensioning device, allowing taking knee laxities into consideration when doing the intraoperative femoral cut planning. Results suggest that the navigation allows more precision in bone cuts, saving the bone stock as much as possible, while intraoperative planning ensured medio-lateral gap balancing. Clinical results at one year were similar to those of equivalent studies, and patient satisfaction was very high.

Abstract. This study aims to retrospectively evaluate TSA planning patterns over an 8-year period, examining nearly 70,000 cases. For both aTSA and rTSA, over half of the planned cases are navigated, with most adhering to the planned procedure. Practitioners who plan both procedures are more likely to navigate the case, particularly in aTSA.
For aTSA, neutral inclination and slight retroversion are consistent targets. In rTSA, 0° inclination is the aim, with significant inferior corrections and greater version adjustments using posterior augments. Augmented implants help maintain planned residual angles while addressing severe deformities. No notable differences were observed between low- and high-volume surgeons.

Abstract. This study aims to retrospectively evaluate the intra-operative performance of computer-assisted navigation (CAN) total shoulder arthroplasty (TSA) over years, analyzing temporal performance evolution and influencing factors.

Abstract. External fixation is a therapy option for operative treatment of open fractures, especially in low-resource settings. Pins for the fixator need to penetrate cortical bone on both sides of the target bone to ensure mechanical stability, but without extensive protrusion. Evaluation of pin placement is challenging, since medical imaging like radiography may not be available in low-resource settings. To address this, we propose a device for ultrasound-assisted pin placement using a portable, robust and low-cost ultrasound probe. The device comprises a guiding sleeve and an arm that centers the probe on the opposite side in the pin axis. Penetration of the opposite cortical bone can thus be easily detected in the ultrasound image in real-time, without the need for manual probe placement. We evaluated our concept in small scale experimental feasibility study on porcine lower legs, where we used a prototype to place 4 pins. Afterwards, we assessed pin protrusion in the ultrasound images as well as manually on the dissected bone. Mean pin protrusion measured in the US images was 1.6 mm, compared to 1.4 mm for manual measurement, with a mean deviation between measurements of 0.5 mm. Pin penetration of the opposite cortical bone was easily detectable in the ultrasound images, and the device facilitated central pin placement. Moreover, our device allowed for use by a single operator. We have thus demonstrated the feasibility of our concept. Future studies will focus on further optimization of the device and evaluation in a cadaver study with medical experts.

Abstract. Patient-specific bone models are required for surgical planning of computer-assisted percutaneous scaphoid fracture fixation. 3D sonography may present an alternative to computed tomography (CT) or magnetic resonance imaging (MRI) for the acquisition of those bone models, but it requires a completion process to derive full models from partial sonographic surfaces. To date, methods based on statistical shape models (SSMs) represent the state-of-the-art for this completion process. However, we have shown feasibility of a deep learning (DL)-based method for scaphoid bone model completion in a previous study.
In this study, we compare our DL-based approach against three SSM-based completion methods: Active shape models (ASM), least squares optimization (LSO) and general-purpose optimization (GPO). 85 scaphoid bone models were used for training the DL-based AdaPoinTr as well as for building the SSM. All completion methods were evaluated on 20 additional test models, with partial input point clouds generated using a subsampling algorithm that mimics 3D sonography.
Evaluation in terms of symmetric surface distance between completed mesh and corresponding ground truth mesh showed 1.1 mm for ASM, 0.7 mm for GPO, 0.5 mm for LSO and 0.3 mm for AdaPoinTr. The assessment of suitability for screw planning showed 12 protruding screws for ASM, 4 protruding screws for GPO and LSO each, and no protrusion for AdaPoinTr. Also, AdaPoinTr was found to be at least one order of magnitude faster than all other methods. Nevertheless, SSM-based completion methods may be better suited for smaller datasets and if the generation of plausible shapes is to be ensured.

Abstract. This work describes the development and experimental evaluation of a software tool (OrthoGrasp) to predict the stability of patient specific guide (PSG) designs. The tool assists in the design of PSGs to ensure that they will provide the high level of stability required to achieve successful and accurate surgical drilling tasks. OrthoGrasps adapts robotic grasping theory to analyse potential PSG designs by treating each point of contact between the guide and the host bone as a force-torque wrench that can be used to calculate stability metrics. The efficacy of OrthoGrasp was evaluated in this study by conducting a series of force-to-dislocation experiments for a range of glenoid anatomies and associated PSG designs that were analysed using OrthoGrasp. The OrthoGrasp derived Least Resisted Wrench (LRW) and Volume Of the Polytope (VOP) metrics, adapted from the robotic grasping literature were then compared to the experimental results through the use of Spearman Rank Correlation analysis. The results demonstrated that the VOP metric was in good agreement with experimental results and thus could be used to predict the overall stability of a PSG design, but the LRW metric had poorer predictive value. In summary, this work demonstrated the potential of the OrthoGrasp pre-operative planning tool to objectively analyse and rank potential PSG designs to ensure that surgeons are provided with guides that stably fit their patients to assist in achieving optimal surgical accuracy.

Abstract. Introduction. In severe cases with lumbar lordosis loss > 25°, pedicle subtraction osteotomy is performed surgically to restore the sagittal malalignment. But it has severe limitations. So, we are developing a new Y-shaped pelvic osteotomy that targets the pelvis rather than the spine. This work presents a fixation system tailored to the Y-shaped pelvic osteotomy.
Methodology. Criteria for the fixation system were set: Offer compressed fixation on the posterior side (closed wedge), maintain a 15° wedge opening on the anterior side and use conventional fixation components. This resulted in combining a lag-screw posteriorly and a patient-specific osteosynthesis plate anteriorly. To assess feasibility, a basic finite element analysis (FEA) was performed using loads derived from a static free body analysis, and a preliminary test was performed on a Sawbones model to assess surgical usability and osteotomy accuracy.
Results. The load input to the FEA was determined to be 397 N in x-direction, 832 N in z-direction, and 18 Nm moment. The FEA showed that the width of the T-shape of the plate crossing the osteotomy should be at least 15 mm to remain below allowable material stress level.
The usability gave a score of 3.9 out of 7 for the fixation system. The Sawbone test showed obtained osteotomy angles of 16.6° and 19.5°, respectively compared to the set 15°. The bone contact area was 62% compared to the planned 61%.
Conclusion. The preliminary results indicate the feasibility of the Y-shaped pelvic osteotomy in combination with the new fixation system.

Abstract. Stemless TSA requires sufficient bone density to ensure appropriate implant stability, both of which can be impacted by surgical precision. While bone density surrounding a stemless humeral implant and implant size are the strongest predictors of implant stability, this study shows that implant positioning also impacts bone density and, hence, stability. The increased precision offered by robotic surgery relative to conventional surgery is shown here to reduce the variability in bone density around the implant, and may therefore improve the primary stability of stemless TSA.

Abstract. This comparative study evaluates functional outcomes in total knee arthroplasty (TKA) performed with a navigation system using femur-first measured resection (MR) or tibia-first gap balancing (GB) surgical workflows. A single surgeon at one center conducted all procedures using the same implant and navigation system. Data from 123 patients, including demographic information and Oxford Knee Scores (OKS) at preoperative, six weeks, one year, and two-year follow-ups, were analyzed. Results showed no significant differences in early postoperative outcomes between workflows. However, from one year onward, the GB group demonstrated superior functional results, with an OKS improvement of 5.8 points at two years, exceeding the MCID. The GB approach, which integrates joint laxity data into femoral planning, may offer better joint balance and antero-posterior stability over time.

Abstract. CT-based methods, such as robotic systems and patient-specific instrumentation (PSI), offer precise bone depiction, making them valuable for Total Knee Arthroplasty (TKA). However, they must be robust to the presence of cartilage, which is not easily visible on CT-scans. We present here a coupled bone and cartilage Statistical Shape Model (SSM) that predicts cartilage solely from bone shape. Four models were trained and tested for healthy and pathological patients, for both femur and tibia. Cartilage prediction results show good adaptability to the pathology as well as similar accuracy compared to the inter-observer MRI manual segmentation variability. This solution could be integrated in the planning of TKA surgeries to improve CT-based PSI and robotic systems.

Abstract. Unintended under- and overcorrections remain a significant challenge in medial open wedge High Tibial Osteotomy (owHTO). Achieving balanced load distribution is a central focus in HTO, yet most studies concentrate on the classical two-dimensional (2D) standing scenario rather than examining the complexities of three-dimensional (3D) load behavior during dynamic motions. This study aimed to investigate the biomechanical effects of key surgical parameters—wedge height, hinge axis, and osteotomy technique—on the position of the resultant force on the tibial plateau during knee flexion. A multibody simulation was conducted on 10 3D computer models of the tibia. The position of the center of pressure (CoP) on the tibial plateau was measured and compared across different surgical scenarios. Results indicate that increasing wedge height causes lateral CoP displacement, with the effect decreasing at higher flexion angles, while anteromedial axial rotation of the hinge axis led to posterior CoP shifts. A comparison of supratuberositary to infratuberositary osteotomies revealed a medial CoP displacement during late flexion (>5°).

Abstract. Predicting suitable implant sizes from 3D radiographic images of joint anatomy can be accomplished using templating methods. Automatic templating, which eliminates the need for manual intervention, is especially valuable for speeding up the creation of computer- or robot-assisted surgical plans. In our previous work, automatic templating for total knee arthroplasty was achieved through automatic bone segmentation, followed by matching a set of anatomical landmarks with corresponding points on candidate implants of various sizes. This paper introduces a novel approach that eliminates the reliance on point correspondences and matching, instead leveraging bone dimensions for implant size prediction. An experimental analysis on a dataset of 3261 knee cases demonstrates that the proposed method improves the performance of implant size prediction.

Abstract. Introduction. Complex proximal humerus fractures in elderly are preferably treated with reverse total shoulder arthroplasty (RTSA). We hypothesized that patients with proximal humerus fractures benefit from virtual surgical planning (VSP) to overcome complication. Therefore, the aim was to investigate clinical outcome of reverse total shoulder arthroplasty with preoperative virtual surgical planning compared to treatment without planning.
Methodology. A cohort study was performed comparing two groups: RTSA with VSP vs. RTSA without VSP. Patients were included if planned for only a RSTA for an acute fracture within 28 days after trauma. The primary outcome measure was the range of motion (ROM) assessed for abduction, forward elevation and external rotation. The secondary outcome measures were complication rate, Patient Reported Outcome Measures (PROMs), operating time (minutes), and stem height of the prosthesis (mm).
Results. Thirty-four patients were included with 27 in the RSTA with VSP group and 7 in the RSTA without VSP. No significant differences were found between the groups for ROM, complication rate, PROMs. Significant differences were found in favor of RSTA with VSP for operating time and stem height
Conclusion. Preliminary data show some benefits using VSP in RTSA, but full data collection is needed to confirm positive effect on clinical outcome.

Abstract. Surgical training integrates several years of didactic learning, simulation, mentorship, and hands-on experience. Challenges include stress, technical demands, and new technologies. Orthopedic education often uses static materials like books, images, and videos, lacking interactivity. This study compares a new interactive photorealistic 3D visualization to 2D videos for learning total hip arthroplasty. In a randomized controlled trial, participants (students and residents) were evaluated on spatial awareness, tool placement, and task times in a simulation. Results show that interactive photorealistic 3D visualization significantly improved scores, with residents and those with prior 3D experience performing better. These results emphasize the potential of the interactive photorealistic 3D visualization to enhance orthopedic training.

Abstract. Objectives: Physiotherapy is an established part of the post-operative protocol for total knee replacement (TKR). As length of hospital stay has decreased, rehabilitation has moved to the home setting with little direct supervision. The Slider, a smart exercise device utilises gamification to optimize patient engagement during self-directed physiotherapy. This pilot study aimed to evaluate whether the Slider device in addition to standard physiotherapy could improve outcomes following TKR.
Methods: 18 patients undergoing robotic primary TKR surgery at a single institution. Nine patients were allocated to the Slider group (device & standard physiotherapy) and nine patients to the standard physiotherapy group. Outcome measures included range of motion (ROM), Oxford Knee Score (OKS), EQ-5D-3L, and patient-reported outcome measures (PROMs) at six weeks postoperatively.
Results: Intraoperative and discharge ROM values were similar between groups (124 vs. 123, p=0.430; 76 vs. 78, p=0.624). Six-week postoperative ROM was superior in the Slider group (104 vs. 89, p=0.121). The Slider group had a shorter hospital stay and a similar number of inpatient physiotherapy sessions (2 vs. 3, p=0.332; and 4 vs. 4, p=0.999). The Slider group reported higher Likert scale satisfaction scores for post-op care (p=0.017). Both OKS and EQ-5D-3L were better in the Slider group, with OKS reaching statistical significance (39 vs. 33, p=0.045; 85 vs. 79, p=0.778).
Conclusion: The Slider device aids early patient rehabilitation after total knee replacement, improving OKS and satisfaction scores. This device shows promise in supporting home-based rehabilitation and will allow clinicians to supervise the process and identify struggling patients early.

Abstract. Introduction. Preformed osteosynthesis plates to treat zygomatic fractures could aid surgical outcome. The aim of this study was to develop a statistical shape model of the zygomatic maxillary complex (ZMC) to assist in the development of preformed 3D osteosynthesis plates.
Methodology. A statistical shape model (SSM) was built using 53 CT scans of patients sustained and surgically treated for a unilateral ZMC fracture. The unaffected side was used to build the SSM. The new element in the build was the development of a reference template of the bony area of interest that could be mapped to all individual meshes using initial correspondence mapping. After that only the region of interest, as set by the template, was used to capture the variation of the ZMC.
Results. The SSM performed sufficiently on accuracy (RMSE 0.3 mm) and compactness (14 principle components covered 90% of variance). The largest variations (up to 4,5 mm) occur in the teeth area, the zygomatic arch and the medical side of the inferior orbital rim; and smaller variations (<0.2 mm) occur in the zygomatic center area.
Conclusion. The SSM gives quantitative information for the design of preformed 3D osteosynthesis plates for the ZMC, and the methods could be applied for shape analysis of other bony regions that are less defined.

Abstract. The deltoid muscles play a crucial role in maintaining balanced arm function and enabling abduction following shoulder arthroplasty. Currently, pre-operative assessments of deltoid integrity rely primarily on visual inspection of medical images and subjective ratings. A recent work has shown accuracy of machine learning based pipeline to correctly segment and quantify characteristics of deltoid muscle in shoulder CT scans. In this paper, with the inputs from medical experts, we evaluated clinical acceptance and non-inferiority of the ML-based segmentations compared to the corrections provided by expert surgeons. The non-inferiority of the ML model was assessed by comparing model-generated masks to surgeons’ and inter-surgeon variations in metrics such as volume and fatty infiltration percentage. Expert validation showed 97% of masks to be clinically acceptable, with only 6% of ML generated masks requiring any major corrections. The median error in the volume and fatty infiltration measurements was <1% between the ML-generated masks and the masks corrected by surgeons. The non-inferiority analysis demonstrated no significant difference between the generated masks to surgeons’ and inter-surgeon variations (p<0.05).

Abstract. Despite the growing development of image-based machine-learning models, their integration into clinical practice remains limited. A significant barrier to adoption is the reliability of these models' predictions. This study demonstrates the use of uncertainty analysis to evaluate output of a CT-based model trained to segment deltoid muscles in shoulder arthroplasty patients. By quantifying uncertainty through metrics such as entropy, mutual information, and variance, we created 46 distinct image-level uncertainty scores for 108 good-quality and 100 low-quality segmentation outputs. In addition, these uncertainty scores were used to train a Gaussian Naïve Bayes model to identify low-quality cases, and the results were compared with those from single-metric thresholding. The results show that boundary 75 percentile entropy is the most predictive single uncertainly parameters (accuracy: 68%, recall: 68%, precision: 67%) while the trained model outperformed all single predictive metrics (accuracy: 78%, %, recall: 76%, precision: 78%). Our study indicates a uses case of utilizing uncertainty analysis to identify segmentation outputs that may require further manual correction, which will increase the trust, and potentially help for clinical adoption of ML segmentation models.

Abstract. Metal artifacts significantly degrade the image quality of cone-beam computed tomography (CBCT), particularly in spine surgeries involving pedicle screws, complicating the assessment of implant positioning and surrounding anatomy. This study introduces a novel Metal Artifact Avoidance (MAA) workflow that leverages deep learning for trajectory optimization to reduce artifacts during CBCT acquisition. The automated approach incorporates real-time user verification, enabling tailored C-arm adjustments based on a predictive artifact model.
The MAA workflow begins with scout views to detect metallic objects using a pretrained FasterRCNN model, followed by triangulation of their 3D positions. A physics-based artifact metric predicts the impact of various tilt angles, with the optimal trajectory suggested to the user through an intuitive visualization interface.
The method is demonstrated on cadaveric data with pedicle screws in the lumbar spine, comparing standard and MAA-guided tilted scans. Results show that MAA-guided scans visibly reduced artifacts and enhanced visualization of critical anatomical structures, such as cortical surfaces around screws, compared to standard scans. The improvements achieved were consistent, even in cases where post-processing techniques like fsMAR failed to effectively mitigate artifacts.
This study demonstrates that combining automated artifact prediction with user-verified trajectory adjustments provides a practical and reliable solution for artifact reduction. Future work will focus on validating the method on larger datasets and optimizing its integration into clinical workflows for broader adoption in spine surgery.

Abstract. Computer-Assisted Surgery (CAS) systems enhance joint replacement accuracy. Total ankle arthroplasty (TAA) is a viable alternative to ankle fusion, but achieving precise implant alignment remains challenging due to limited surgical exposure and reliance on fluoroscopy. This study aimed to compare the accuracy of a conventional TAA technique using fluoroscopy to a previously developed CAS system.
Twelve artificial ankle joints were used for the study. TAA was performed using conventional instrumentation and fluoroscopy. Bone resections were performed, and the resections were compared to the planned resections using 3D scanning and analysis software. Tibial and talar resections showed greater accuracy with the CAS system compared to the conventional technique. The conventional technique had larger deviations in tibial closed slope, tibial internal rotation, and talar slope. The conventional technique demonstrated acceptable accuracy, and was aligned with previous literature. However, the CAS system improved accuracy and precision, particularly by reducing outliers. Limitations of this study include the absence of soft tissues and limited surgeon variability with only one operator. Future studies should investigate surgeon variability, cadaveric models, and comparisons with patient-specific instrumentation (PSI) techniques. In conclusion, the conventional technique provides acceptable results, while the CAS system offers potential for enhanced accuracy and precision in TAA.

Abstract. The performance of deep learning algorithms is highly dependent on the quantity and diversity of the available training data. However, obtaining sufficiently large datasets represents a significant challenge, particularly in the field of medical imaging. This study underscores the potential of self-supervised training strategies in the development of deep learning models for medical imaging tasks. It is demonstrated that workflows can be significantly optimized by incorporating the feature content of a large collection of medical X-ray images from intraoperative C-arm scans into a so-called foundation model. This approach facilitates the efficient adaptation to a variety of concrete applications by fine-tuning a small task-specific head network on top of the pre-trained foundation model, thereby reducing both computational demands and training time.

Abstract. Introduction 3D bone models are increasingly adopted for leg alignment analysis, but there is substantial variability in the methods and underlying principles used to derive axes and joint orientations from 3D bone models. Therefore, the purpose was to reach consensus on a structured framework for standardized 3D leg alignment analysis based on 3D bone models.
Methodology A Delphi study was performed in four rounds. Rounds 1 and 2 involved a steering and rating group that developed 31 statements based on principles preserving the complexity of 3D anatomical structures, identified through a systematic review. These statements encompassed deriving joint centres and joint orientations, and defining coordinate systems using 3D bone models. In Rounds 3 and 4, an international panel of experts, evaluated these statements. Consensus was defined as ≥80% agreement.
Results Of the 31 statements, 26 achieved consensus in Round 3. Five statements were refined and subsequently all achieved consensus in Round 4. Experts agreed on utilising all available relevant surface data to define joint centres, joint orientations, and individual femoral and tibial coordinate systems alongside a combined leg coordinate system, and adopting central 3D axes for femoral version and tibial torsion.
Conclusion This international Delphi consensus study provides a structured framework for a standardized 3D leg alignment analysis based on 3D bone models. By utilizing all relevant surface data, this framework provides a more accurate representation of joint geometries compared to traditional landmark-based methods. Future research should focus on validating the methods adhering to these principles in diverse clinical settings.

Abstract. Cervical spine surgery, particularly for dorsal decompression and fusion in cervical myelopathy treatment, requires precise usage of surgical devices and instruments to achieve an optimal outcome. The surgery aims to decompress the spinal cord by removing any structures compressing the nerves.
While open networked central workstations have the potential to increase efficiency and safety, they can face workflow-driven conflicts, such as limited input resources, insufficient screen space for device or patient information, and inadequate control methods. Moreover, current standard operating procedures (SOP) lack detailed information about the inter-device communication requirements.
Preventing workflow-driven errors is already addressed in high-risk applications, such as airspace and nuclear power plant control rooms. This paper proposes a method to mitigate workflow-driven conflicts for open networked ISO IEEE 11073 SDC service-oriented device connectivity workstations. By extending clinical SOPs by specific device and instrument usage specifications (eSOP) especially related to human-machine-interaction (HMI) requirements, we could identify potential conflicts in a proposed central OR workstation solution before bringing devices into service. The eSOP has been discussed with spine surgery specialists from the University Hospital RWTH Aachen.

Abstract. C-arm fluoroscopy is commonly used in Computer-Assisted Surgery, enabling real-time imaging. Calibrating such images enable the use of 2D/3D registration or advanced reconstruction algorithms, making a well designed calibration approach is essential. Most prior work mainly focuses on the calibration methods, with limited attention given to the optimal design of C-arm calibration phantoms. This work introduces a stochastic optimization framework for designing sphere based calibration phantoms. Our approach optimizes sphere placement to satisfy key criteria: robustness to segmentation noise, visibility in clinically relevant views, and adherence to physical size constraints.
We model the calibration process using a pinhole camera representation, employing the Direct Linear Transform (DLT) algorithm employed to estimate extrinsic and intrinsic parameters from 2D-3D correspondences. Introducing normally distributed noise to the projected coordinates, we simulate realistic segmentation inaccuracies. We designed a tunable cost function incorporating components to minimize calibration errors under noisy conditions, penalize occlusions, and enforce visibility. This cost is optimized to define the 3D coordinates for the spheres of the calibration phantom using the stochastic optimizer Dual Annealing.
Results demonstrate that phantoms optimized using our method doubles the calibration accuracy of phantoms with randomly placed spheres in terms of both intrinsic and extrinsic parameters. In addition, occlusions are minimized, ensuring that the phantom can be well calibrated within all relevant images.
This method offers an automated solution for creating calibration phantoms aligning with specific clinical requirements, increasing the robustness and accuracy of existing calibration approaches.