Dome versus single-cut osteotomies for correction of long bone deformities-technical considerations.

Corrective osteotomy allows to improve joint loading, pain and function. In complex deformities, the biggest challenge is to define the optimal surgical solution, while considering anatomical, technical and biomechanical factors. While the single-cut osteotomy (SCOT) and focal dome osteotomy (FDO) are well-established treatment options, their mathematical relationship remain largely unclear. The aim of the study was (1) to describe the close mathematical relationship between the SCOT and FDO and (2) to analyze and introduce a novel technique-the stepped FDO-as a modification of the classic FDO. The mathematical background and relationship of SCOT and FDO are described for the example of a femoral deformity correction and visualized using a 3D surface model taking into account the benefits for the clinical application. The novel modifications of the stepped FDO are introduced and its technical and clinical feasibility demonstrated. Both, SCOT and FDO, rely on the same deformity axis that defines the rotation axis k for a 3D deformity correction. To achieve the desired correction using a SCOT, the resulting cutting plane is perpendicular to k, while using a FDO will result in a cylindrical cut with a central axis parallel to k. The SCOT and FDO demonstrate a strong mathematical relation, as both methods rely on the same deformity axis, however, resulting in different cutting planes. These characteristics enable a complementary use when defining the optimal type of osteotomy. This understanding enables a more versatile planning approach when considering factors as the surgical approach, biomechanical characteristics of fixation or soft tissue conditions. The newly introduced stepped FDO facilitates an exact reduction of the bone fragments and potentially expands the clinical applicability of the FDO.

Deep-learning based 3D reconstruction of lower limb bones from biplanar radiographs for preoperative osteotomy planning.

PURPOSE: Three-dimensional (3D) preoperative planning has become the gold standard for orthopedic surgeries, primarily relying on CT-reconstructed 3D models. However, in contrast to standing radiographs, a CT scan is not part of the standard protocol but is usually acquired for preoperative planning purposes only. Additionally, it is costly, exposes the patients to high doses of radiation and is acquired in a non-weight-bearing position. METHODS: In this study, we develop a deep-learning based pipeline to facilitate 3D preoperative planning for high tibial osteotomies, based on 3D models reconstructed from low-dose biplanar standing EOS radiographs. Using digitally reconstructed radiographs, we train networks to localize the clinically required landmarks, separate the two legs in the sagittal radiograph and finally reconstruct the 3D bone model. Finally, we evaluate the accuracy of the reconstructed 3D models for the particular application case of preoperative planning, with the aim of eliminating the need for a CT scan in specific cases, such as high tibial osteotomies. RESULTS: The mean Dice coefficients for the tibial reconstructions were 0.92 and 0.89 for the right and left tibia, respectively. The reconstructed models were successfully used for clinical-grade preoperative planning in a real patient series of 52 cases. The mean differences to ground truth values for mechanical axis and tibial slope were 0.52° and 4.33°, respectively. CONCLUSIONS: We contribute a novel framework for the 2D-3D reconstruction of bone models from biplanar standing EOS radiographs and successfully use them in automated clinical-grade preoperative planning of high tibial osteotomies. However, achieving precise reconstruction and automated measurement of tibial slope remains a significant challenge.

Validation of a Three-Dimensional Weight-Bearing Measurement Protocol for Medial Open-Wedge High Tibial Osteotomy.

Three-dimensional (3D) deformity assessment and leg realignment planning is emerging. The aim of this study was to (1) validate a novel 3D planning modality that incorporates the weight-bearing (WB) state (3D WB) by comparing it to existing modalities (3D non-weight-bearing (NWB), 2D WB) and (2) evaluate the influence of the modality (2D vs. 3D) and the WB condition on the measurements. Three different planning and deformity measurement protocols were analyzed in 19 legs that underwent medial open-wedge high tibial osteotomy (HTO): (1) a 3D WB protocol, after 2D/3D registration of 3D CT models onto the long-leg radiograph (LLR) (3D WB), (2) a 3D NWB protocol based on the 3D surface models obtained in the supine position (3D NWB), and (3) a 2D WB protocol based on the LLR (2D WB). The hip-knee-ankle angle (HKA), joint line convergence angle (JLCA), and the achieved surgical correction were measured for each modality and patient. All the measurement protocols demonstrated excellent intermodal agreement for the achieved surgical correction, with an ICC of 0.90 (95% CI: 0.76-0.96)) (p < 0.001). Surgical correction had a higher mean absolute difference compared to the 3D opening angle (OA) when measured with the WB protocols (3D WB: 2.7 ± 1.8°, 3D NWB: 1.9 ± 1.3°, 2D WB: 2.2 ± 1.3°), but it did not show statistical significance. The novel planning modality (3D WB) demonstrated excellent agreement when measuring the surgical correction after HTO compared to existing modalities.

Reducing residual forces in spinal fusion using a custom-built rod bending machine.

BACKGROUND AND OBJECTIVE: As part of spinal fusion surgery, shaping the rod implant to align with the anatomy is a tedious, error-prone, and time-consuming manual process. Inadequately contoured rod implants introduce stress on the screw-bone interface of the pedicle screws, potentially leading to screw loosening or even pull-out. METHODS: We propose the first fully automated solution to the rod bending problem by leveraging the advantages of augmented reality and robotics. Augmented reality not only enables the surgeons to intraoperatively digitize the screw positions but also provides a human-computer interface to the wirelessly integrated custom-built rod bending machine. Furthermore, we introduce custom-built test rigs to quantify per screw absolute tensile/compressive residual forces on the screw-bone interface. Besides residual forces, we have evaluated the required bending times and reducer engagements, and compared our method to the freehand gold standard. RESULTS: We achieved a significant reduction of the average absolute residual forces from for the freehand gold standard to (p=0.0015) using the bending machine. Moreover, our bending machine reduced the average time to instrumentation per screw from to . Reducer engagements per rod were significantly decreased from an average of 1.00±1.14 to 0.11±0.32 (p=0.0037). CONCLUSION: The combination of augmented reality and robotics has the potential to improve surgical outcomes while minimizing the dependency on individual surgeon skill and dexterity.

The influence of the weight-bearing state on three-dimensional (3D) planning in lower extremity realignment - analysis of novel vs. state-of-the-art planning approaches.

BACKGROUND: The use of 3D planning to guide corrective osteotomies of the lower extremity is increasing in clinical practice. The use of computer-tomography (CT) data acquired in supine position neglects the weight-bearing (WB) state and the gold standard in 3D planning involves the manual adaption of the surgical plan after considering the WB state in long-leg radiographs (LLR). However, this process is subjective and dependent on the surgeons experience. A more standardized and automated method could reduce variability and decrease costs. PURPOSE: The aim of the study was (1) to compare three different three-dimensional (3D) planning modalities for medial open-wedge high tibial osteotomy (MOWHTO) and (2) to describe the current practice of adapting NWB CT data after considering the WB state in LLR. The purpose of this study is to validate a new, standardized approach to include the WB state into the 3D planning and to compare this method against the current gold standard of 3D planning. Our hypothesis is that the correction is comparable to the gold standard, but shows less variability due compared to the more subjective hybrid approach. METHODS: Three surgical planning modalities were retrospectively analyzed in 43 legs scheduled for MOWHTO between 2015 and 2019. The planning modalities included: (1) 3D hybrid (3D non-weight-bearing (NWB) CT models after manual adaption of the opening angle considering the WB state in LLR, (2) 3D NWB (3D NWB CT models) and (3) 3D WB (2D/3D registration of 3D NWB CT models onto LLR to simulate the WB state). The pre- and postoperative hip-knee-ankle angle (HKA) and the planned opening angle (°) were assessed and differences among modalities reported. The relationship between the reported differences and BMI, preoperative HKA (LLR), medial meniscus extrusion, Outerbridge osteoarthritis grade and joint line convergence angle (JLCA) was analyzed. RESULTS: The mean (std) planned opening angle of 3D hybrid did not differ between 3D hybrid and 3D WB (0.4 ± 2.1°) (n.s.) but was higher in 3D hybrid compared to 3D NWB (1.1° ± 1.1°) (p = 0.039). 3D WB demonstrated increased preoperative varus deformity compared to 3D NWB: 6.7 ± 3.8° vs. 5.6 ± 2.7° (p = 0.029). Patients with an increased varus deformity in 3D WB compared to 3D NWB (> 2 °) demonstrated more extensive varus alignment in LLR (p = 0.009) and a higher JLCA (p = 0.013). CONCLUSION: Small intermodal differences between the current practice of the reported 3D hybrid planning modality and a 3D WB approach using a 2D/3D registration algorithm were reported. In contrast, neglecting the WB state underestimates preoperative varus deformity and results in a smaller planned opening angle. This leads to potential under correction in MOWHTO, especially in patients with extensive varus deformities or JLCA. CLINICAL RELEVANCE: Incorporating the WB state in 3D planning modalities has the potential to increase accuracy and lead to a more consistent and reliable planning in MOWHTO. The inclusion of the WB state in automatized surgical planning algorithms has the potential to reduce costs and time in the future.

Augmented reality-guided pelvic osteotomy of Ganz: feasibility in cadavers.

INTRODUCTION: The periacetabular osteotomy is a technically demanding procedure with the goal to improve the osseous containment of the femoral head. The options for controlled execution of the osteotomies and verification of the acetabular reorientation are limited. With the assistance of augmented reality, new possibilities are emerging to guide this intervention. However, the scientific knowledge regarding AR navigation for PAO is sparse. METHODS: In this cadaveric study, we wanted to find out, if the execution of this complex procedure is feasible with AR guidance, quantify the accuracy of the execution of the three-dimensional plan, and find out what has to be done to proceed to real surgery. Therefore, an AR guidance for the PAO was developed and applied on 14 human hip cadavers. The guidance included performance of the four osteotomies and reorientation of the acetabular fragment. The osteotomy starting points, the orientation of the osteotomy planes, as well as the reorientation of the acetabular fragment were compared to the 3D planning. RESULTS: The mean 3D distance between planned and performed starting points was between 9 and 17 mm. The mean angle between planned and performed osteotomies was between 6° and 7°. The mean reorientation error between the planned and performed rotation of the acetabular fragment was between 2° and 11°. CONCLUSION: The planned correction can be achieved with promising accuracy and without serious errors. Further steps for a translation from the cadaver to the patient have been identified and must be addressed in future work.

Automatic registration with continuous pose updates for marker-less surgical navigation in spine surgery.

Established surgical navigation systems for pedicle screw placement have been proven to be accurate, but still reveal limitations in registration or surgical guidance. Registration of preoperative data to the intraoperative anatomy remains a time-consuming, error-prone task that includes exposure to harmful radiation. Surgical guidance through conventional displays has well-known drawbacks, as information cannot be presented in-situ and from the surgeon's perspective. Consequently, radiation-free and more automatic registration methods with subsequent surgeon-centric navigation feedback are desirable. In this work, we present a marker-less approach that automatically solves the registration problem for lumbar spinal fusion surgery in a radiation-free manner. A deep neural network was trained to segment the lumbar spine and simultaneously predict its orientation, yielding an initial pose for preoperative models, which then is refined for each vertebra individually and updated in real-time with GPU acceleration while handling surgeon occlusions. An intuitive surgical guidance is provided thanks to the integration into an augmented reality based navigation system. The registration method was verified on a public dataset with a median of 100% successful registrations, a median target registration error of 2.7 mm, a median screw trajectory error of 1.6°and a median screw entry point error of 2.3 mm. Additionally, the whole pipeline was validated in an ex-vivo surgery, yielding a 100% screw accuracy and a median target registration error of 1.0 mm. Our results meet clinical demands and emphasize the potential of RGB-D data for fully automatic registration approaches in combination with augmented reality guidance.

Development and evaluation of robot-assisted ultrasound navigation system for pedicle screw placement: An ex-vivo animal validation.

PURPOSE: Spinal instrumentation with pedicle screw placement (PSP) is an important surgical technique for spinal diseases. Accurate screw trajectory is a prerequisite for PSP. Ultrasound (US) imaging with robot-assisted system forms a non-radiative alternative to provide precise screw trajectory. This study reports on the development and assessment of US navigation for this application. METHODS: A robot-assisted US reconstruction was proposed and an automatic CT-to-US registration algorithm was investigated, allowing the registration of screw trajectories. Experiments were conducted on ex-vivo lamb spines to evaluate system performance. RESULTS: In total, 72 screw trajectories are measured, displaying an average position accuracy of 2.80 ± 1.14 mm and orientation accuracy of 1.38 ± 0.61°. CONCLUSION: The experimental results demonstrate the feasibility of proposed US system. This work, although restricted to laboratory settings, encourages further exploration of the potential of this technology in clinical practice.

Automatic breach detection during spine pedicle drilling based on vibroacoustic sensing.

Pedicle drilling is a complex and critical spinal surgery task. Detecting breach or penetration of the surgical tool to the cortical wall during pilot-hole drilling is essential to avoid damage to vital anatomical structures adjacent to the pedicle, such as the spinal cord, blood vessels, and nerves. Currently, the guidance of pedicle drilling is done using image-guided methods that are radiation intensive and limited to the preoperative information. This work proposes a new radiation-free breach detection algorithm leveraging a non-visual sensor setup in combination with deep learning approach. Multiple vibroacoustic sensors, such as a contact microphone, a free-field microphone, a tri-axial accelerometer, a uni-axial accelerometer, and an optical tracking system were integrated into the setup. Data were collected on four cadaveric human spines, ranging from L5 to T10. An experienced spine surgeon drilled the pedicles relying on optical navigation. A new automatic labeling method based on the tracking data was introduced. Labeled data was subsequently fed to the network in mel-spectrograms, classifying the data into breach and non-breach. Different sensor types, sensor positioning, and their combinations were evaluated. The best results in breach recall for individual sensors could be achieved using contact microphones attached to the dorsal skin (85.8%) and uni-axial accelerometers clamped to the spinous process of the drilled vertebra (81.0%). The best-performing data fusion model combined the latter two sensors with a breach recall of 98%. The proposed method shows the great potential of non-visual sensor fusion for avoiding screw misplacement and accidental bone breaches during pedicle drilling and could be extended to further surgical applications.

State-of-the-Art of Non-Radiative, Non-Visual Spine Sensing with a Focus on Sensing Forces, Vibrations and Bioelectrical Properties: A Systematic Review.

In the research field of robotic spine surgery, there is a big upcoming momentum for surgeon-like autonomous behaviour and surgical accuracy in robotics which goes beyond the standard engineering notions such as geometric precision. The objective of this review is to present an overview of the state of the art in non-visual, non-radiative spine sensing for the enhancement of surgical techniques in robotic automation. It provides a vantage point that facilitates experimentation and guides new research projects to what has not been investigated or integrated in surgical robotics. Studies were identified, selected and processed according to the PRISMA guidelines. Relevant study characteristics that were searched for include the sensor type and measured feature, the surgical action, the tested sample, the method for data analysis and the system's accuracy of state identification. The 6DOF f/t sensor, the microphone and the electromyography probe were the most commonly used sensors in each category, respectively. The performance of the electromyography probe is unsatisfactory in terms of preventing nerve damage as it can only signal after the nerve is disturbed. Feature thresholding and artificial neural networks were the most common decision algorithms for state identification. The fusion of different sensor data in the decision algorithm improved the accuracy of state identification.

Automatic 3D Postoperative Evaluation of Complex Orthopaedic Interventions.

In clinical practice, image-based postoperative evaluation is still performed without state-of-the-art computer methods, as these are not sufficiently automated. In this study we propose a fully automatic 3D postoperative outcome quantification method for the relevant steps of orthopaedic interventions on the example of Periacetabular Osteotomy of Ganz (PAO). A typical orthopaedic intervention involves cutting bone, anatomy manipulation and repositioning as well as implant placement. Our method includes a segmentation based deep learning approach for detection and quantification of the cuts. Furthermore, anatomy repositioning was quantified through a multi-step registration method, which entailed a coarse alignment of the pre- and postoperative CT images followed by a fine fragment alignment of the repositioned anatomy. Implant (i.e., screw) position was identified by 3D Hough transform for line detection combined with fast voxel traversal based on ray tracing. The feasibility of our approach was investigated on 27 interventions and compared against manually performed 3D outcome evaluations. The results show that our method can accurately assess the quality and accuracy of the surgery. Our evaluation of the fragment repositioning showed a cumulative error for the coarse and fine alignment of 2.1 mm. Our evaluation of screw placement accuracy resulted in a distance error of 1.32 mm for screw head location and an angular deviation of 1.1° for screw axis. As a next step we will explore generalisation capabilities by applying the method to different interventions.

Factors affecting augmented reality head-mounted device performance in real OR.

PURPOSE: Over the last years, interest and efforts to implement augmented reality (AR) in orthopedic surgery through head-mounted devices (HMD) have increased. However, the majority of experiments were preclinical and within a controlled laboratory environment. The operating room (OR) is a more challenging environment with various confounding factors potentially affecting the performance of an AR-HMD. The aim of this study was to assess the performance of an AR-HMD in a real-life OR setting. METHODS: An established AR application using the HoloLens 2 HMD was tested in an OR and in a laboratory by two users. The accuracy of the hologram overlay, the time to complete the trial, the number of rejected registration attempts, the delay in live overlay of the hologram, and the number of completely failed runs were recorded. Further, different OR setting parameters (light condition, setting up partitions, movement of personnel, and anchor placement) were modified and compared. RESULTS: Time for full registration was higher with 48 s (IQR 24 s) in the OR versus 33 s (IQR 10 s) in the laboratory setting (p < 0.001). The other investigated parameters didn't differ significantly if an optimal OR setting was used. Within the OR, the strongest influence on performance of the AR-HMD was different light conditions with direct light illumination on the situs being the least favorable. CONCLUSION: AR-HMDs are affected by different OR setups. Standardization measures for better AR-HMD performance include avoiding direct light illumination on the situs, setting up partitions, and minimizing the movement of personnel.

Synthetic white balancing for intra-operative hyperspectral imaging.

Purpose: Hyperspectral imaging shows promise for surgical applications to non-invasively provide spatially resolved, spectral information. For calibration purposes, a white reference image of a highly reflective Lambertian surface should be obtained under the same imaging conditions. Standard white references are not sterilizable and so are unsuitable for surgical environments. We demonstrate the necessity for in situ white references and address this by proposing a novel, sterile, synthetic reference construction algorithm. Approach: The use of references obtained at different distances and lighting conditions to the subject were examined. Spectral and color reconstructions were compared with standard measurements qualitatively and quantitatively, using ΔE and normalized RMSE, respectively. The algorithm forms a composite image from a video of a standard sterile ruler, whose imperfect reflectivity is compensated for. The reference is modeled as the product of independent spatial and spectral components, and a scalar factor accounting for gain, exposure, and light intensity. Evaluation of synthetic references against ideal but non-sterile references is performed using the same metrics alongside pixel-by-pixel errors. Finally, intraoperative integration is assessed though cadaveric experiments. Results: Improper white balancing leads to increases in all quantitative and qualitative errors. Synthetic references achieve median pixel-by-pixel errors lower than 6.5% and produce similar reconstructions and errors to an ideal reference. The algorithm integrated well into surgical workflow, achieving median pixel-by-pixel errors of 4.77% while maintaining good spectral and color reconstruction. Conclusions: We demonstrate the importance of in situ white referencing and present a novel synthetic referencing algorithm. This algorithm is suitable for surgery while maintaining the quality of classical data reconstruction.

Robot-assisted ultrasound reconstruction for spine surgery: from bench-top to pre-clinical study.

PURPOSE: Robot-assisted ultrasound (rUS) systems have already been used to provide non-radiative three-dimensional (3D) reconstructions that form the basis for guiding spine surgical procedures. Despite promising studies on this technology, there are few studies that offer insight into the robustness and generality of the approach by verifying performance in various testing scenarios. Therefore, this study aims at providing an assessment of a rUS system, with technical details from experiments starting at the bench-top to the pre-clinical study. METHODS: A semi-automatic control strategy was proposed to ensure continuous and smooth robotic scanning. Next, a U-Net-based segmentation approach was developed to automatically process the anatomic features and derive a high-quality 3D US reconstruction. Experiments were conducted on synthetic phantoms and human cadavers to validate the proposed approach. RESULTS: Average deviations of scanning force were found to be 2.84±0.45 N on synthetic phantoms and to be 5.64±1.10 N on human cadavers. The anatomic features could be reliably reconstructed at mean accuracy of 1.28±0.87 mm for the synthetic phantoms and of 1.74±0.89 mm for the human cadavers. CONCLUSION: The results and experiments demonstrate the feasibility of the proposed system in a pre-clinical setting. This work is complementary to previous work, encouraging further exploration of the potential of this technology in in vivo studies.

An automated optimization pipeline for clinical-grade computer-assisted planning of high tibial osteotomies under consideration of weight-bearing.

3D preoperative planning for high tibial osteotomies (HTO) has increasingly replaced 2D planning but is complex, time-consuming and therefore expensive. Several interdependent clinical objectives and constraints have to be considered, which often requires multiple rounds of revisions between surgeons and biomedical engineers. We therefore developed an automated preoperative planning pipeline, which takes imaging data as an input to generate a ready-to-use, patient-specific planning solution. Deep-learning based segmentation and landmark localization was used to enable the fully automated 3D lower limb deformity assessment. A 2D-3D registration algorithm allowed the transformation of the 3D bone models into the weight-bearing state. Finally, an optimization framework was implemented to generate ready-to use preoperative plannings in a fully automated fashion, using a genetic algorithm to solve the multi-objective optimization (MOO) problem based on several clinical requirements and constraints. The entire pipeline was evaluated on a large clinical dataset of 53 patient cases who previously underwent a medial opening-wedge HTO. The pipeline was used to automatically generate preoperative solutions for these patients. Five experts blindly compared the automatically generated solutions to the previously generated manual plannings. The overall mean rating for the algorithm-generated solutions was better than for the manual solutions. In 90% of all comparisons, they were considered to be equally good or better than the manual solution. The combined use of deep learning approaches, registration methods and MOO can reliably produce ready-to-use preoperative solutions that significantly reduce human workload and related health costs.

Sonification as a reliable alternative to conventional visual surgical navigation.

Despite the undeniable advantages of image-guided surgical assistance systems in terms of accuracy, such systems have not yet fully met surgeons' needs or expectations regarding usability, time efficiency, and their integration into the surgical workflow. On the other hand, perceptual studies have shown that presenting independent but causally correlated information via multimodal feedback involving different sensory modalities can improve task performance. This article investigates an alternative method for computer-assisted surgical navigation, introduces a novel four-DOF sonification methodology for navigated pedicle screw placement, and discusses advanced solutions based on multisensory feedback. The proposed method comprises a novel four-DOF sonification solution for alignment tasks in four degrees of freedom based on frequency modulation synthesis. We compared the resulting accuracy and execution time of the proposed sonification method with visual navigation, which is currently considered the state of the art. We conducted a phantom study in which 17 surgeons executed the pedicle screw placement task in the lumbar spine, guided by either the proposed sonification-based or the traditional visual navigation method. The results demonstrated that the proposed method is as accurate as the state of the art while decreasing the surgeon's need to focus on visual navigation displays instead of the natural focus on surgical tools and targeted anatomy during task execution.

Three-dimensional analysis of functional femoral antetorsion and the position of the greater trochanter in high-grade patellofemoral dysplastic knees.

BACKGROUND: The relationship between functional femoral antetorsion, the greater trochanter (GT) position and anatomical antetorsion has been demonstrated in patients with a primary hip pathology. However, the functional antetorsion and GT position have not been analyzed in patellofemoral dysplastic knees. The aim of this study was to develop a three-dimensional (3D) measurement to quantify the functional femoral antetorsion and position of the GT and to analyze these measurements in a cohort of high-grade patellofemoral dysplastic knees. METHOD: A 3D measurement was developed to analyze functional antetorsion and the axial position of the GT and assessed in 100 cadaveric femora. For validity and repeatability testing, inter- and intra-observer reliability were determined using intraclass correlation coefficients (ICCs). These measurements were then evaluated in a cohort of 19 high-grade patellofemoral dysplastic knees (Dejour type C, D). The relationship between anatomical antetorsion, functional antetorsion and GT position were reported. RESULTS: Inter- and intra-reader reliability for 3D functional antetorsion and axial position of the GT demonstrated a minimum ICC of 0.96 (P < 0.001). Anatomical and functional antetorsion demonstrated a highly linear relationship (R2 = 0.878; P < 0.001) in high-grade patellofemoral dysplastic knees. The mean difference between anatomical and functional antetorsion decreased with increasing anatomical antetorsion (R2 = 0.25; P = 0.031, indicating a more anterior position of the GT relative to the femoral neck axis. CONCLUSION: In high-grade patellofemoral dysplastic knees, the GT is located more anteriorly, relative to the femoral neck axis, with increasing anatomical antetorsion and correction osteotomy may result in an excessively anterior position of the GT.

How different augmented reality visualizations for drilling affect trajectory deviation, visual attention, and user experience.

PURPOSE: Previous work has demonstrated the high accuracy of augmented reality (AR) head-mounted displays for pedicle screw placement in spinal fusion surgery. An important question that remains unanswered is how pedicle screw trajectories should be visualized in AR to best assist the surgeon. METHODOLOGY: We compared five AR visualizations displaying the drill trajectory via Microsoft HoloLens 2 with different configurations of abstraction level (abstract or anatomical), position (overlay or small offset), and dimensionality (2D or 3D) against standard navigation on an external screen. We tested these visualizations in a study with 4 expert surgeons and 10 novices (residents in orthopedic surgery) on lumbar spine models covered by Plasticine. We assessed trajectory deviations ([Formula: see text]) from the preoperative plan, dwell times (%) on areas of interest, and the user experience. RESULTS: Two AR visualizations resulted in significantly lower trajectory deviations (mixed-effects ANOVA, p<0.0001 and p<0.05) compared to standard navigation, whereas no significant differences were found between participant groups. The best ratings for ease of use and cognitive load were obtained with an abstract visualization displayed peripherally around the entry point and with a 3D anatomical visualization displayed with some offset. For visualizations displayed with some offset, participants spent on average only 20% of their time examining the entry point area. CONCLUSION: Our results show that real-time feedback provided by navigation can level task performance between experts and novices, and that the design of a visualization has a significant impact on task performance, visual attention, and user experience. Both abstract and anatomical visualizations can be suitable for navigation when not directly occluding the execution area. Our results shed light on how AR visualizations guide visual attention and the benefits of anchoring information in the peripheral field around the entry point.

Translation of Medical AR Research into Clinical Practice.

Translational research is aimed at turning discoveries from basic science into results that advance patient treatment. The translation of technical solutions into clinical use is a complex, iterative process that involves different stages of design, development, and validation, such as the identification of unmet clinical needs, technical conception, development, verification and validation, regulatory matters, and ethics. For this reason, many promising technical developments at the interface of technology, informatics, and medicine remain research prototypes without finding their way into clinical practice. Augmented reality is a technology that is now making its breakthrough into patient care, even though it has been available for decades. In this work, we explain the translational process for Medical AR devices and present associated challenges and opportunities. To the best knowledge of the authors, this concept paper is the first to present a guideline for the translation of medical AR research into clinical practice.

Augmented reality through head-mounted display for navigation of baseplate component placement in reverse total shoulder arthroplasty: a cadaveric study.

BACKGROUND: To achieve an optimal clinical outcome in reverse total shoulder arthroplasty (RSA), accurate placement of the components is essential. The recently introduced navigation technology of augmented reality (AR) through head-mounted displays (HMD) offers a promising new approach to visualize the anatomy and navigate component positioning in various orthopedic surgeries. We hypothesized that AR through HMD is feasible, reliable, and accurate for guidewire placement in RSA baseplate positioning. METHODS: Twelve human cadaver shoulders were scanned with computed tomography (CT) and RSA baseplate positioning was 3-D planned using dedicated software. The shoulders were prepared through a deltopectoral approach and an augmented reality hologram was superimposed using the HMD Microsoft HoloLense. The central guidewire was then navigated through the HMD to achieve the planned entry point and trajectory. Postoperatively, the shoulders were CT-scanned a second time and the deviation from the planning was calculated. RESULTS: The mean deviation of the entry point was 3.5 mm ± 1.7 mm (95% CI 2.4 mm; 4.6 mm). The mean deviation of the planned trajectory was 3.8° ± 1.7° (95% CI 2.6°; 4.9°). CONCLUSION: Augmented reality seems feasible and reliable for baseplate guidewire positioning in reverse total shoulder arthroplasty. The achieved values were accurate.