ABSTRACT. Psoas syndrome after THA has received much attention in recent years. In some cases, the cause of pain cannot be found in a critical overhang of the implant cup, but is mainly unknown. We developed an approximation of modeling the medial part of the tendon of m. iliacus in 201 THA patients. We found length changes of the tendon of 7,73 mm ± 8,55 mm (range: -26,37 mm to 30,30 mm) and angular changes at the PSIS of 2,58 ° ± 1,72 ° (range: 0 to 7,91 °) and at the lesser trochanter of 10,53 ° ± 7,70 ° (range: 0,27 ° to 41,19 °). Furthermore, we identified 19 cases in whom the tendon wrapped over different bony structures than the acetabular region. Hence, we think that the m. iliacus tendon should be considered for analysis of risk factors in the preoperative planning process for THA.

ABSTRACT. INTRODUCTION: Up to 35% of total knee arthroplasty (TKA) patients experience short term anterior knee pain (AKP) and up to 20% of non-revised knees experience anterior knee pain in the long term. Patellofemoral pain is the primary cause of AKP and accounts for over 8% of revision TKA procedures in Australia. This study introduces a geometric patellofemoral ligament analysis model which was used to differentiate between patients with and without post-operative anterior knee pain.

METHODS: All patients received pre- and post-operative CT scans and lateral flexed radiograph. The CT scans were segmented and landmarked before being registered to the flexed radiographs. The antero-posterior (AP) of the medial and lateral patellar edge relative to the medial and lateral femoral epicondyles were measured pre-operatively, post-operatively as well as the difference between the two states. These measurements were analysed for their impacts on patient outcome using the Kujala score.

RESULTS: Both medial and lateral antero-posterior patellofemoral offsets had statistically significant, moderate inverse correlations with the overall Kujala score. However, no statistically significant relationship was observed between the post-operative Kujala score and the pre-operative AP offsets or the change in AP offset between the pre- and post-operative states.

DISCUSSION: The results suggest that a higher medial or lateral post-operative patellofemoral AP offset, potentially due to the overstuffing of the patellofemoral joint, may result in inferior patient outcomes and residual AKP. Overall, it is imperative to consider the possible causes of post-operative AKP and models should be developed to inform surgeons in a clinical setting.

ABSTRACT. Atrophy of thigh muscles significantly affects patients with hip diseases, thus quantifying the muscle volume can play an important role. Thigh circumference measurement has been used to predict thigh muscle volumes and atrophy. However, the validity of the measurement level, impact of error, and the relationship between each thigh muscle volumes at each measurement level remain not fully evaluated. In this study, we aimed to clarify the relationship between thigh circumference and the cross-sectional area (CSA) of each muscles using the deep learning model for automatic segmentation of the skin and muscles from CT images. Using 3D models, the thigh circumference and the CSAs of each muscle were measured at 0 cm to 20 cm above the superior aspect of the patella with 1 cm increment. evaluate the correlation between thigh circumference and CSAs. Thigh circumference tends to increase from distal to proximal, and for muscle’s CSA to increase as well. A strong correlation between muscle CSA and thigh circumference was observed above 5-10 cm, with a maximum correlation observed with the entire thigh muscle at 12 cm. Similar correlations were also observed around the level of maximum correlation. The correlation coefficients suggest that the measurement level should be adjusted for individual muscles. The correlation coefficients near the level of maximum correlation were almost equal, indicating that the influence of measurement level error is likely minimal.

ABSTRACT. One of the goals of total knee arthroplasty (TKA) is to restore of extend the range of motion of the knee joint. A small proportion of patients who are candidates for TKA exhibit fixed flexion contracture (FFC), a condition which prevents the knee from reaching full extension and can be associated with preoperative coronal deformity. In treating FFC, surgeons have two options, either through extensive soft tissue releases or through additional resections of bone on the proximal tibia and distal femur to increase the extension gap. Usually, FFC can be corrected with just soft tissue release, however, sometimes needs to be combined with additional bone resections, especially in cases with varus or valgus coronal deformity. However, additional bone resections beyond 11mm on the femoral side can be associated with knee instability. We therefore asked, is there a relationship between preoperative coronal deformity and intraoperative bone resections required to treat patients with extreme FFC? We analysed 3922 navigated TKA cases undertaken at our institution between March 2007 and October 2022. From this set, we identified 127 patients with extreme fixed flexion contracture (FFC) of greater than 15⁰ and with post-operative FFC less than 5⁰, indicating that the FFC had been resolved. Using simple linear regression and calculating the Pearson correlation coefficients, we related the preoperative coronal deformity to the maximum femoral and tibial resection depths between the medial and lateral sides. We then calculated the statistical significance and coefficient of determination. For the 127 cases, the coefficients of determination were calculated to be 0.19 for the proximal tibia and 0.22 for the distal femur (p < 0.025). The correlation coefficients for the relationship between coronal deformity and femoral or tibial resection depths were 0.47 (p< 0.025) and -0.43 (p< 0.025), respectively. In this study, we determined there was a moderate correlation (indicated as |0.40 – 0.59|) between the tibial and femoral bone resections required to treat extreme FFC in patients with varying degrees of preoperative coronal deformity. In planning to treat extreme FFC, surgeons should pay attention to the preoperative coronal deformity of patients as this will likely be an important factor in determining the required steps in successfully treating the FCC.

ABSTRACT. Soft tissue balancing is in vogue, but no quantitative numbers can be designated to it. The present study aimed to compare and quantify the soft tissue balance based femoral component rotation (FCR) with native trans epicondylar axis (TEA) during robot-assisted total knee arthroplasty using gap balancing. 81 patients underwent the procedure using the MAKO robot and the Stryker Triathlon knees. Preoperative deformity and intraoperative gaps were recorded and analysed. The results showed that intra operative measurements using the 3 D CT model showed that the mean external rotation of surgical TEA in relation to PCA was 2.9 degrees (range 0-7°, SD 1.7°). There was a significant difference between the preoperative TEA (mean 2.9°, SD 1.7°) and the soft tissue based gap balanced FCR (mean 1.3°, SD 2.1°) with a significant correlation between the two values (p<0.01, r=-0.38). The study found that 61% of cases showed the FCR was in external rotation compared to the TEA while the remaining 39% was internally rotated. The results demonstrate that the final femoral component rotation is determined by the soft tissue envelope. The MAKO robot with 3D modelling and digital soft tissue tension assessment can adjust both the coronal and sagittal plane alignment of TKA implants based on soft tissue tension and preoperative deformity. This study quantified the soft tissue relationship to bony landmark axes TEA and PCA.

ABSTRACT. This study investigated the variability of the manual localization of anatomical landmarks of the distal femur using 3 different methods: CT, Mesh, and 3D printed models. From a CT database of 50 knees, 3D meshes were automatically generated and 3D printed. The main author performed twice, for each case, a registration of 11 distal femoral landmarks. We investigated for each landmark and modality the: • mean distance per modality • averages distance between each modality • deviation of each modality from the barycentre • position of the new planes and axes relative to their starting position Finally, the study was carried out on 41 knees, 9 of which had to be excluded because of 3D printing issues. 2706 manual annotations were performed. Regarding the Intra-operator reproducibility, the average distances for each point and modality were between 1.49mm and 6.34mm. As for the analysis considering the barycenter no differences were found between the three modalities. However, some points showed more variability. But their impact on the 3 axes and the planes studied were found negligible. Mean angular variations for either axes or planes are all less than 0.5°. In summary, no differences were found between the three modalities but some points showed more variability.

ABSTRACT. INTRODUCTION: The Medial Proximal Tibial Angle (MPTA) is a key input for TKA alignment strategies and classification systems. The MPTA is most frequently measured using 2D antero-posterior (AP) radiographs, but technological advancements have allowed for 3D analysis techniques. This study compares different 3D MPTA analyses to the clinical standard of 2D measurements.

METHODS: Patients pre-operatively received a weightbearing AP EOS scan and a long-leg supine CT scan. 2D MPTA analysis was performed using the EOS. For 3D analyses, the CT scans were segmented and landmarked before a 3D landmarking technique and 3D geometric analyses were employed. The 3D geometric analyses investigated three regions and two combinations of multiple regions of the proximal tibial surface: Anterior (A), Centre (C), Posterior (P), anterior and centre (AC) and anterior, centre and posterior (ACP). Regression lines were created for each region and used to determine the MPTA.

RESULTS: A series of 209 knees were analysed and the mean 2D MPTA measurement was 86.3°±2.5°. The mean MPTA for the 3D landmark technique was 86.3°±2.9° and the five 3D geometric analyses (A, C, P, AC and ACP) were 89.5°±2.8°, 87.6°±2.6°, 86.9°±2.9°, 88.4°±2.5° and 87.8°±2.5°, respectively.

DISCUSSION: 2D radiograph or 3D landmark MPTA measurements techniques fail to consider the 3D topology of the tibial plateau. This can have clinical implications as MPTA measurements are utilised for surgical planning and execution. The 3D geometric analyses methodologies described in this study consider numerous points on the tibial plateau and were observed to be significantly different to the conventional techniques.

ABSTRACT. Implant overhang in total knee arthroplasty is associated with adverse effects with regard to postoperative pain and function, whereas implant underhang or bone undercoverage has been linked to increased risk of bleeding and osteolysis. To determine the suitability of different standard implant systems for a certain population, an automated analysis of overhang, underhang and coverage would be favorable. Therefore, we developed an automated framework for femoral implant interface fit evaluation. To evaluate this framework, we used surface models of 433 cadaver knees and of one specific femoral implant size. An analysis of the bone-implant interface fit was performed for all knees for which the available implant size was selected on the basis of the knee’s size. The analysis involved the orientation of bone and implant via reference points, the virtual resection of the bone, and the derivation and comparison of bone-implant interface contours. Implant over-/underhang was evaluated for the entire contour and in specific zones (defined in the literature). Bone coverage was calculated for the entire interface. A good agreement with the literature with regard to mean values and ranges of over-/underhang was found. Limitations include the restriction to one specific implant system and size. Future analyses should focus on different implant sizes and systems as well as on the assessment of the tibial component.

ABSTRACT. Objectives: A new ultrasound-based device is proposed to measure the standing position of the scapula position. The purpose of this study was to evaluate the accuracy of this device. Methods: Accuracy was assessed by making several measurements of scapula orientation in a reference space defined by the angle of the scapula plane with the axial, sagittal and coronal planes. The measurements were made with the ultrasonic device and compared to a reference measurement taken by an infrared tracking device. Error was defined as the difference in measurement between the angles measured by these two techniques. Results: The mean accuracy of the device was in the axial plane of 0.9° +/- 0.7°, in the coronal plane of 1.3° +/- 0.8° and for the sagittal plane 1.9° +/- 1.4°. Conclusions—This study presents a fair and faithful non-invasive device for measuring scapula orientation when standing. It offers relevant perspective to improve planning softwares for total shoulder arthroplasty.

ABSTRACT. Minimally invasive surgery (MIS) of the spine combined with navigation-assisted techniques has increased in recent years. The goal of this study is to present a case series and technical note of patients who underwent MIS of the transforaminal lumbar interbody fusion (MIS-TLIF) or percutaneous pedicle screw (PPS) fixation with C arm free O-arm navigation in various spine disease including degenerative spondylolisthesis and scoliosis correction patients. Navigation in spine surgery can decrease conventional misplacement rate of screw fixation. This study is one of the biggest single case series to our date. With our methods, we can increase the workflow rate of surgery without radiation exposure. This method could be used in all kinds of thoracolumbar disease, including any deformity situation or rotation spine morphology.

ABSTRACT. Introduction Bone mineral density (BMD) of the lumbar is usually measured in 2D by dual-energy X-ray absorptiometry (DXA-BMD). While the diagnosis of osteoporosis is based on the 2D measurements of BMD, previous reports that used CT images to measure lumbar BMD utilized the 3D measurements of BMD, which is different from the measurements in DXA. In this study, to bridge the gap between 2D and 3D BMD measurements, we aimed to develop a system that measures both 2D and 3D lumbar BMD from quantitative CT images and validated the accuracy of the system in diagnosing osteoporosis with regard to the DXA classification.

Materials and methods Fifty-nine pairs of spinal CT and DXA images were analyzed. First, the L1-L4 vertebrae were segmented from the CT images using deep learning to measure the 3D-BMD at the trabecular region of the L1-L4 vertebral bodies (CT-vBMD). Then, the segmented vertebrae were projected onto the coronal plane to measure the 2D-BMD (CT-aBMD). Each parameter was correlated with DXA-BMD, and the receiver operating characteristic (ROC) curve to diagnose osteoporosis was assessed.

Results The correlation coefficients of DXA-BMD with CT-vBMD and CT-aBMD were 0.456 and 0.911, respectively (both p<0.01). In the ROC curve analysis to diagnose osteoporosis, the area under the curve for CT-aBMD (0.941) was significantly higher than that for CT-vBMD (0.657) (p<0.01).

Conclusions Compared with CT-vBMD, CT-aBMD could accurately predict DXA-BMD and detect patients with osteoporosis. Given that our method can quantify BMD in both 2D and 3D, it could be used to screen for osteoporosis from quantitative CT images.

ABSTRACT. Fractures of the sacroiliac joint often require treatment through internal fixation. This procedure is typically guided by the use of intraoperative fluoroscopy, using an untracked C-arm device. However, this involves ionizing radiation exposure and the possibility of screw malplacement. We introduce the Navigated Orthopaedic Fixation using Ultrasound System (NOFUSS): an ultrasound (US) based end-to-end system for providing real-time navigation for iliosacral screw (ISS) insertions. Our system consists of an US imaging device and an optical tracking camera, together with computational algorithms for automatic processing of intraoperative data. In a cadaver trial of 6 specimens, we found that the ISS insertions performed using NOFUSS demonstrated accuracy comparable to conventional fluoroscopy guidance in the three specimens for which we could obtain good ultrasound images, reduced insertion time, and required no ionizing radiation.

ABSTRACT. Purpose: The aim of this study was (1) to compare the clinical and radiological outcomes of robotic and conventional total knee arthroplasty with a minimum follow-up of fifteen years, (2) to evaluate the survival rate, (3) and to estimate the accuracy of the two techniques by analyzing the outliers of the total knee arthroplasty (TKA) patients. Methods: We evaluated 172 patients, 101 patients undergoing robotic TKA, and 71 patients treated with conventional TKA with a mean follow-up of 18.0 years. HSS, KSS, WOMAC, and SF-12 questionnaires were used for clinical evaluation. Mechanical alignment, implant radiological measurements, and outliers were analyzed for radiological results. Kaplan-Meier survival analysis was performed for survival rate. Results: All clinical assessments showed excellent improvements in both groups (all p < 0.05), without any significant difference between the groups (p > 0.05). The conventional TKA group showed a significantly higher number of outliers compared with the robotic TKA group (0 < 0.05). The cumulative survival rate was 98.8% in the robotic TKA group and 98.5% in the conventional TKA group with excellent survival (p = 0.563). Conclusions: Our study showed excellent survival with both robotic and conventional TKA and similar clinical outcomes at long-term follow-up. And, in terms of radiological outcome, robotic TKA showed better accuracy and consistency with fewer outliers compared with conventional TKA. With longer follow-up and larger cohort, the accuracy and effectiveness of robotic TKA on implant survival rate can be elucidated in the future.

ABSTRACT. Purpose Radiographic parameters (RPs) provide objective support for effective decision making in determining clinical treatment of distal radius fractures (DRFs). Calculating the RPs manually in radiographs requires experience, is time consuming, and is subject to observer variability. Methods We present a novel automatic RP computation pipeline for computing the six anatomical RPs associated with DRFs in anteroposterior (AP) and lateral (LAT) forearm radiographs. The method consists of three main steps: 1) segmentation of the distal radius and ulna bones with six 2D Dynamic U-Net deep learning models; 2) landmark points detection and distal radius axis computation from the segmentations with geometric methods; 3) RP computation from the landmarks and generation of a quantitative DRF report and composite AP and LAT radiograph images. The pipeline is the first fully automatic method that accurately and robustly computes the RPs for a very wide variety of forearm radiographs from different sources, hand orientations, and with and without cast. Results The pipeline was evaluated on a dataset of 90 AP and 93 LAT radiographs. Ground truth distal radius and ulna segmentations and RP landmarks were manually obtained by an expert clinician. It achieves an accuracy of 94% and 86% on the AP and LAT RPs, within the observer variability and an RP measurement difference of 1.4±1.2° for the radial angle, 0.5±0.6mm for the radial length, 0.9±0.7mm for the radial shift, 0.7±0.5mm for the ulnar variance, 2.9±3.3° for the palmar tilt and 1.2±1.0mm for the dorsal shift. Conclusion Automated RP computation on clinical forearm radiographs may improve clinical decision making and increase the consistency and adherence to guidelines by providing accurate and reliable measurements for fracture severity.

ABSTRACT. To assess developmental dysplasia of the hip in infants, evaluations are currently conducted based on 2D ultrasound (US) images. Using 3D US has been shown to markedly reduce inter-rater variability, but 3D scanners are not widely available in pediatric practices. Here, we propose reconstructing 3D US volumes by using deep learning to estimate the spatial positions of 2D US image sequences. We extracted fan-shaped sets of slices from a database of 1403 3D US volumes and trained a previously proposed standard Convolutional Neural Network (CNN) as well as two variations of a deeper CNN (one augmented with optical flow (OF) information) to estimate the angular distances between separated slices. The deeper CNN most accurately predicted the inter-slice angular displacements (mean absolute error of 0.02˚) over a displacement of up to 3.0˚ (corresponding to a center-frame displacement of 5.3mm). OF did not appear to improve prediction accuracy in angle estimation. The deeper CNN also achieved a mean end-to-end sweep angle error of -0.8% ± 13.2%, compared with an error of 25.3% ± 14.7% for the previously proposed standard CNN. This relatively low error suggests that it may be feasible to accurately reconstruct a 3D representation of an infant hip using a 2D US video stream alone, without requiring additional probe-tracking devices.

ABSTRACT. Total Knee Arthroplasty is a frequently performed surgery. Patient specific planning and implants may improve surgical outcome. For this purpose, 3D models of the bones are required, which are typically generated by using computed tomography. A radiation free and cheaper alternative could be ultrasound. However, bone segmentation and a competitive method of creating a complete bone model are a challenge. In this work a fully-automatic bone reconstruction pipeline using ultrasound, which includes machine learning based image segmentation and an interpolation algorithm for missing areas using statistical shape models, is presented and evaluation results with free hand probe guidance are outlined. A mean surface distance error of 0.96 mm for femur bone reconstruction is achieved. Furthermore, a robotic scanning approach is presented to automate the entire process. Autonomous scanning of the anterior distal femur was successful for 4 out of 5 probands. On average, 54 % of the accessed bone surface could be reconstructed.

ABSTRACT. Surgical tool detection and localisation during robotic assisted surgery is of significant importance. The estimated 3D pose can be subsequently employed in different processes, such as optimising the interaction of tools with registered patient tissue or allowing for motion planning of a robotic end effector, thus avoiding collisions with external agents, and ensuring patient safety. Traditional tracking systems, namely robotic systems, or optical trackers, usually suffer from high costs and, especially in the case of trackers, the need for tool redesign to incorporate trackable markers. Therefore, recent research has focused on image-based, markerless detection and localisation techniques. This paper presents a network capable of both surgical tool detection and 3D pose estimation using a monocular system. For the purposes of training and testing of the network, a novel dataset of 5370 images of “off-the-shelf” surgical tools in action was produced, namely a scalpel, a pair of scissors, a pair of forceps, and an electric burr. Upon testing, the network obtained a mean DICE coefficient of 85.0% for detection. Furthermore, position and orientation in 3D were predicted, with the network achieving an average position error of 5.5mm and an average orientation error of 3.3̊. The presented network exhibits a high level of versatility compared to the state of the art, as it does not require any prior knowledge of the tool 3D structure, such as CAD information. Upon comparing the results with standard pose estimation techniques with the same dataset, most of the metrics exhibited lower errors when compared to their counterparts.

ABSTRACT. The follow-up of lower limb implants is routinely performed through the analysis of X-ray images to evaluate the characteristics of the implanted prosthesis and the limb alignment. This task is time-consuming and remains challenging for non-specialized physicians and junior surgeons. In this study, we present and evaluate a suite of deep learning algorithms. Our tool can automatically (1) perform quality control of X-rays to ensure their characteristics, (2) measure the prosthesis positioning on the knee close-up image and (3) determine the lower limb alignment angles on long-leg images. We collected a retrospective database of 103,360 X-rays belonging to 19,560 adult patients including both knee close-up and long-leg images. First, we cleaned our database to ensure its quality by defining 8 processing steps and training one convolutional neural network (CNN) for each of these steps. Secondly, we trained different neural networks to measure prosthesis positioning (i.e. angle between the prosthesis components and the bones’ axes) and limb alignment from manually labeled anatomical landmarks.

For the knee close-up, the algorithms obtained a mean error 1.71° (std 1.53°), close to the surgeons’ mean difference of 1.69° (std 1.52°) on a comparison subset. For the long-leg images, our pipeline reached a mean angle error of 2.59° (std 3.94°).

This study shows that innovative technologies can be integrated into the orthopedic surgeon’s routine. In particular artificial intelligence is well suited to assist in medical imaging analysis as it produces accurate and standardized measurements.

ABSTRACT. This study aims at comparing the nnU-Net, an open-source deep learning framework, with a previous customized U-Net model that we developed for the automatic segmentation of tibial and femoral bones from CT scans. The main purpose of our work is to develop a segmentation module that could be integrated into a surgical planning software for the design of customized Total Knee Prosthesis. The nnU-Net framework was chosen for its user-friendly design and features developed for medical imaging. The same dataset of 112 CT scans of lower limbs from 63 patients was used to train and test both our customized U-Net model and the nnU-Net model. All these data were manually annotated. The evaluation was done by computing the Average Symetric Surface Distance, the Dice Coefficient, the Hausdorff Distance, the precision, the recall and the Jaccard Index. Both models yielded similar results on these metrics, but the nnU-Net model is easier to setup. The performances of both models are also consistent with the literature, however, further tests on pathological data will be needed.

ABSTRACT. Hip osteoarthritis (HipOA) is an increasingly prevalent disease in today’s hyper-aged society. Its diagnosis is usually based on radiographs and requires the clinical expertise to grade the hip deformity and disease progression based on Kellgren and Lawrence (KL) and Crowe gradings. However, the diagnosis is subjective and depends on the surgeon, which may introduce inter– and intra– observer variabilities. Widely used deep learning models, including a recently proposed model (VisionTransformer (ViT)), were attempted in classification and regression settings. For validation, a database of 394 unilateral digitally- reconstructed radiographs (DRRs), generated from CT images of the hip region of 197 HipOA patients was used. The KL and Crowe grades were combined into a single label encoding one of seven combinations of the two, thus representing the disease severity. The grading accuracy was assessed using exact class accuracy (ECA) and one-neighbour class accuracy (ONCA). The largest ECA was obtained for ViT model with 0.656±0.015 for regression. By tolerating one-neighbor failure, ViT accuracy could increase to 0.962±0.011 for regression. Additionally, ViT produced the smallest mean error between the true and predicted labels in the regression (continuous label), which was 0.417 (IQR: 0.740). In general, DRRs of the normal to mild stages had higher accuracy compared with those of severe stages. Future work will focus on increasing training data of severe stages and analyze disease progression in large-scale databases.

ABSTRACT. Purpose Estimation of glenoid bone loss following shoulder dislocation in a CT scan is often required to determine the surgery needed to restore shoulder stability. However, quantifying glenoid bone loss is time-consuming, requires expertise, and is subject to observer variability. Methods We present a novel automatic method for glenoid bone loss quantification in CT scans. It consists of: 1) computation of an oblique plane in the CT scan that best matches the glenoid face orientation; 2) selection of the glenoid oblique CT slice; 3) computation of a glenoid best-fit circle; 4) quantification of the glenoid bone loss deficiency. The model-based method is the first to accurately compute the oblique slice, fit a circle, and compute the bone loss. Results The method was evaluated on a dataset of 50 shoulder CT scans from 42 patients. Ground truth oblique slice, circle, and bone loss measurements were obtained from three clinicians. It achieved a mean oblique CT slice selection difference of 1.42±1.32 slices and a mean slice selection accuracy of 0.93±0.06, above the intra-observer variability of 1.74±1.82 slices. The glenoid fit circle has a mean Average Symmetric Surface Distance of 1.32±0.52mm and a mean best-fit circle distance of 2.47±1.06mm. The glenoid bone loss measures have an Average Mean Error (MAE) Deficiency of 1.54±1.03mm, a MAE Diameter of 1.88±1.40mm, and a MAE Percentage Deficiency of 4.76±3.0%. These results indicate that the measures are within the desired accuracy and may be clinically valuable. Conclusion Automated quantitative analysis of glenoid bone loss in CT scans is practically viable and may assist orthopaedists in selecting and planning surgical shoulder re-stabilization procedures.

ABSTRACT. Morpho-functional analysis is a major aspect of preoperative planning for THA. This study aims to investigate whether pain or movement restrictions correlate with the morphofunctional parameters pelvic tilt, pelvic bend and pelvic rotation. Pre- and postoperative CT and EOS images, as well as score values of 201 Japanese patients were analyzed. No statistical relevant correlation between the score values and the parameters could be found (|rmax| = 0,38). However, the statistical power was found to be low for our data ((1-β ~ 0.10). Further research with larger data sets is desirable.

ABSTRACT. Background : The new trend of total knee arthroplasty surgery is encouraging in using Robotic assisted surgery not only more precision and accuracy of surgery but less soft tissue dissection. Ligament balancing plays an important role in prolonging longevity of TKA implant. Inadequate gap balancing produces pain and decreases longevity of implant. In Pre-Resection Balancing technique of robotic TKA, bone resection evaluated by paddle thickness, but unknown tension of gap. Aim of this study was to indicate the tension of gap resection in Robotic total knee arthroplasty Method and material : Seventy-three knees was performed by MAKO robotic assisted total knee arthroplasty. Patients received spinal block&adductor canal block anesthesia. After medial parapatellar approach was performed, deep MCL was released in varus knee, IT band was released in valgus knee. Gap tension was evaluated at extension and flexion position by paddle thickness. Femoral and tibial component position is adjusted to achieve even gap at flexion and extension. Proximal tibial was resected, gap tension was re-evaluated with tension device started from 100N in extension while increasing tension until the gap and planning gap are equal or the gap difference was less than 2 mm. We did the same technique in extension gap and flexion gap. Robotic TKA was performed as usual. Implant was installed with Cemented fixed- bearing TKA (Triathlon, Stryker) Result : The proper soft tissue balance that achieved from robotic assisted total knee arthroplasty was less than 2 mm difference in flexion and extension. Moreover, the difference of medial and lateral gap was less than 2 mm. We found that the mean soft tissue tension of medial extension gap was 165.83±33.81 N and 162.5±28.56 in lateral extension gap. The mean difference in extension gap was 3.33 N (p-value 0.571). The mean soft tissue tension of flexion gap was 166.67±39.77 N in medial side and was 190.83±39.59 N in lateral side. The mean difference in flexion gap was 24.17 N (p-value 0.001) Conclusion : Robotic assisted TKA,150-N was the median of tension in medial and lateral extension gap. However, in flexion gap the median of medial side was 150 N and lateral side was 200 N.

ABSTRACT. Introduction: Malalignment of the fibula after fixation of ankle fractures with syndesmostic instability was occurred 25 - 52 % of the cases in some studies. As malalaigment of fibula is difficult to detect with conventional fluoroscopy, some authors recommend an intraoperative control with 3D image. In this study, we present our experience with the intraoperative use of the 3D image (Cios Spin 3D, Siemens Healthineers, Erlangen, Germany) in the treatment of syndesmotic injuries, and compare the accuracy of intraoperative 3D imaging with postoperative CT.

Materials and methods: We treated 25 syndesmotic lesions by fixation using an intraoperative control with 3D image from April 2018. First, osteosynthesis is performed on the fracture sites of the fibula and tibia. Then, the tibio-fibular joint was reduced and temporally fixed by K-wire under conventional fluoroscopy technique. After this fixation, the position of the joint was controlled with a 3D image acquisition. The 3D image takes 100 low-dose shots while automatically rotating 200 degrees in about 1.5 minutes. If the tibio-fibular joint position was wrong, reduction was changed again before definitive fixation. Using intraoperative 3D image and postoperative CT scan, we evaluate about three-dimensional and rotational position of fibula.

Results: Eighteen patients (72%) showed a good reduction result intraoperative first reduction. The other nine patients (36%) needed a change in reduction of the tibio-fibular joint after intraoperative 3D imaging. Two was over 1.5mm shortening of fibular, three was 2mm ventral displace and the other four had over 10 degree rotational malposition. The postoperative CT scan showed 3 patients (12%) had 5~8 degree rotational malalignment.

Discussion: In this cohort, cases of malreduction decreased from 36% after initial reduction to 12% at the end. On the other hand, three cases (12%) of malposition are remained. We could not find it during surgery is caused that the malreduction of posterior maleollar fragment, the resolution of the 3D image is insufficient due to the metal artifacts, and the reduction position changes when the position screw is inserted after 3D image. This part is an issue in the future.

Conclusion: Although exposure to radiation will increase, it is more important to reduce the malreduction rate and reduce the reoperation rate in this study.

ABSTRACT. Background: Kinematic alignment technique has shown promising results, but there might be a risk of failure in the patient with extreme deformities. In order to prevent the risk of failure, modified Kinematic alignment (mKA) technique was proposed to achieve (safe) range of alignment by limiting the position of implant within 5° of femoral & tibial mechanical axis. Functional alignment (FA) technique is a relatively new concept to consider not only patient’s specific anatomy, but also to aim achieving balanced gap with respecting the native soft tissue envelope. The purpose of this study to compare the difference in the flexion and extension gap balance and bony resection depth between mKA and FA. Methods: 100 TKAs were preformed with an CT-based MAKO robot. Gap balancing was evaluated real-time during operation, mKA plan was considered to be successful when the medial-lateral gap difference within 2mm. When gap balancing was failed, implant position was changed within 5° of mechanical axis according to FA concepts until satisfactory gap balance was achieved. Bony resection depth, implant position, final tibio-femoral gap balance in extension and 90° flexion were compared with the mKA plan. Results: A mKA plan achieved successful gap balancing in 85% for the extension gap (18.33 ± 1.7mm) and 43% for the flexion gap (21.72 ± 2.3mm). After FA adjustment, gap balance was achieved in the extension gap (18.93 ± 1.2mm) and flexion gap (21.55 ± 1.4mm) in all cases. To achieve gap balancing, final femoral component position was more externally rotated relative to the posterior condylar axis (0° with mKA compared to 2.5° with FA, p=0.00), and more flexed relative to the sagittal plane (1.64° with mKA compared to 2.11° with FA, p=0.00). All bone resection depth were significantly less for FA compared to mKA. Conclusion: This study indicates that the use of FA significantly contributes to gap balance and less bone resection compared to mKA by more external rotation and flexion of the femoral component.

ABSTRACT. Purpose This study aimed to investigate whether acetabular cup positioning in robotic arm-assisted THA (rTHA) was accurate that than in computed tomography (CT) -based navigation THA (nTHA) performed through anterolateral approach. Methods This is a retrospective case-control study, which comprised of 19 patients who underwent rTHA and 16 patients who underwent nTHA. All procedures were performed by senior surgeons, using a modified Watson–Jones approach. Clinical data (surgical time, intraoperative blood loss, and total perioperative blood loss), and radiographic parameters, using pre and postoperative CT (inclination and anteversion angles) were statistically compared between the two groups. Result No significant differences were observed in surgical time, intraoperative blood loss, and total perioperative blood loss between the rTHA and nTHA groups. For rTHA group cup aligment, the mean RI was 39.0°±1.9° and the mean RA was 15.2° ±1.8°. With nTHA group, the mean RI was 40.8° ±2.6° and the mean RA 17.6° ±3.3°. For both measurements there was a significant heterogeneity of variances. The mean absolute difference was 1.5°±1.0° in RI and 1.4°±1.0° in RA in rTHA. That was 2.2°±2.0° in RI and 3.1°±3.5° in RA in nTHA. For both of RI and RA, rTHA was significantly smaller than nTHA. Conclusion The cup positioning through anterolateral approach was more accurate in robotic arm assisted THA than in CT-based navigation THA.

ABSTRACT. The computer-assisted technique for total knee arthroplasty (TKA) was initially employed to optimize the prosthetic alignment. However, under the computer-assisted TKA, bone cutting can be executed precisely in the extra-medullary way, thus diminishing the violation of the bone marrow cavity. Diminishing bone marrow insult is an additional benefit other than the optimization of prosthetic alignment. Our team has been dedicated in unravelling the biological impacts of intramedullary reaming, and this abstract tries to summarize our serial research findings in terms of the differential biological signatures between CAOS and conventional TKAs.

ABSTRACT. Adequate (femoral) implant sizing in total knee arthroplasty is of high relevance, as it is crucial for recreating both stability and pain-free mobility. Femoral size parameters include the anteroposterior (AP) height and mediolateral (ML) width. We aimed to optimize respective implant size parameters to maximize population coverage for a large database of 85,143 cases, which were provided with patient-specific implants (PSI). For a subset of 1,049 cases, the 3D surface information of the patients’ bones was available. We used this information to evaluate, whether the PSI size is representative of the bone size. The size optimization was conducted using the particle swarm optimization. Deviations between PSI and bone sizes were small and evaluated as clinically insignificant, hence the full database was used for the size optimization. The population coverage showed higher sensitivity regarding tolerated error bounds compared to the number of implant sizes. A population coverage of 84.67% was reached with an exemplary setup of 12 implant sizes and error bounds of +/- 1.5 mm for AP and +/- 3 mm for ML. Maximizing population coverage by increasing the number of implant sizes proved to be ineffective, as even with 30 implant sizes a full population coverage could not be reached. Remaining cases could instead be provided with a PSI.

ABSTRACT. Due to the complex anatomy of the pelvis, achieving adequate surgical margins and performing limb-sparing resections of pelvic tumors can often be challenging. Marginal resections have a high local recurrence rate, up to 70%, therefore, achieving adequate margins is of paramount importance. We performed CATS for pelvic tumors and selected extremity tumors. We initiated CATS in November 2018 and present here the retrospective analysis of our prospectively maintained database from November 2018 to November 2022. We evaluated the intraoperative feasibility, margin status, and complications in this cohort. A total of 78 cases were planned for CATS during the study period, of which 49 underwent CATS (Navigation group) and 29 were operated without CATS (Non-navigation group). Navigation was successfully executed in 46 cases and failed in three cases. The majority of the cases in the navigation group were of Ewing's sarcoma. The mean time taken for navigation was 25.12 minutes. The average registration error was 1.08mm (range of 0.6 to 1.8mm). There were no margin-positive cases in the navigated group, while in the non-navigated pelvic and sacral tumors, six patients had margin positivity. Intraoperative complications were 18.3% in the navigation group compared to 13.7% in the non-navigated group. Navigation was used to save the sacral roots, save the acetabular roof, and for hemi-cortical excisions. Our early experience suggests that there is a learning curve with the use of navigation. With an increase in experience, the time taken for planning and intraoperative execution decreases considerably. It helps in protecting vital structures like sacral roots while providing adequate margins. There was no increase in intraoperative or postoperative complications observed with the use of CATS, even with prolonged surgical procedures. CATS is an incredible academic tool for teaching complex surgical anatomy and resections.

ABSTRACT. Background: The use of robotics in TKA has been shown to minimize human error, as well as improve the accuracy and precision of component implantation and mechanical axis alignment. Dr LCT (CT based full active, 7 axis arm robotic system) was newly developed in 2021. The present study aimed to demonstrate that robot-assisted TKA using Dr LCT is safe and capable of producing a consistent and accurate postoperative mechanical axis.

Methods: This is prospective randomized controlled study. From June 2021 to September 2021, 50 osteoarthritis patients (average age: 69.7, male: 7, female: 43) was preformed bilateral TKA with mechanically alignment. The operations were performed one Knee with conventional ROBODOC & ORTHODOC and the other knee with Dr LCT, same times or in a week. The radiological evaluations included mechanical axis, implant position (α,β,γ,δ angle) according to the system of American Knee Society. Clinical outcomes and motion were measured preoperatively, 6 weeks, 3 months, 6 months and 1 year postoperatively.

Results: There was no difference in the postoperative α, β, γ angle and mechanical axis between two groups (p<0.05). In group ROBODOC, mechanical axis angle changed from preoperative varus 8.5 to postoperative varus 0.3° with 1 outlier. In group Dr LCT, mechanical axis angle changed from varus 7.8° to varus 0.2° with 1outliers. In group ROBODOC, the mean α, β, γ, δ angle were 96.2°, 89.9°, 1.5°, 84.3° and 96.2°, 90.2°, 1.4°, 83.4° in group Dr LCT. There was no difference of clinical results between two groups. Mean knee society score was improved in both group, (pain score; from 46.3(preoperative) to 83.4(postoperative) in ROBODOC, from 50.3 to 85.0 in Dr LCT, function score: from 43.2 to 86.7 in ROBODOC, from 39.1 to 86.7 in Fr LCT). WOMAC score showed similar results; 68.1 to 15.6 in ROBODOC, 69.6 to 15.70 in Dr LCT). There was significant difference in surgery times between two groups (Match times (minutes): 7.9 in ROBODOC, 2.8 in Dr LCT, Cut time: 23.5 in ROBODOC, 8.2 in Dr LCT).

Conclusion: On the basis of our results, TKA with ROBODOC and TKA with Dr LCT showed good radiological & clinical results without difference, whereas operative time and cutting time were founded to be less in TKA with Dr LCT. We think that Dr LCT system has clinically safety and effectiveness, comparable to ROBODOC system. However, a long term follow up evaluation will be necessary in Dr LCT system.