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.

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.

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.

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.