Ergonomic RFID tag placement on surgical instruments - a preliminary user study.

OBJECTIVES: RFID tags on surgical instruments allow tracking of individual instruments. However, the tags on the instruments can restrict the handling, potentially increasing patient risks. Previous studies analyzed hand contact areas to identify potential locations for tags. However, the studies did not conduct interaction tests using instruments equipped with RFID tags, potentially neglecting the influence of haptic perception. In addition, previous studies required time-consuming evaluations by clinicians. METHODS: Therefore, the present study aims to verify the previous findings in interaction-centered tests with clinicians using real RFID tags on the instruments. Additionally, we had instrument design experts rate RFID tag positions and examined whether they could predict the clinician's preferred tag positions. RESULTS: We found that nearly all RFID tag positions decreased the user satisfaction of clinicians compared to a reference instrument. Compared to previous studies, our study shows that the RFID tag influences the orientations in which an instrument can be comfortably held, which was criticized by clinicians. Instrument design experts could only predict the clinician's preferred tag positions for some instruments. CONCLUSIONS: Therefore, we recommend investigating further changes to instrument design, for what the "ideal" positions proposed by the clinicians in this study can provide initial pointers.

Ultrasound-based 3D bone modelling in computer assisted orthopedic surgery - a review and future challenges.

Computer-assisted orthopedic surgery requires precise representations of bone surfaces. To date, computed tomography constitutes the gold standard, but comes with a number of limitations, including costs, radiation and availability. Ultrasound has potential to become an alternative to computed tomography, yet suffers from low image quality and limited field-of-view. These shortcomings may be addressed by a fully automatic segmentation and model-based completion of 3D bone surfaces from ultrasound images. This survey summarizes the state-of-the-art in this field by introducing employed algorithms, and determining challenges and trends. For segmentation, a clear trend toward machine learning-based algorithms can be observed. For 3D bone model completion however, none of the published methods involve machine learning. Furthermore, data sets and metrics are identified as weak spots in current research, preventing development and evaluation of models that generalize well.

Ultrasound-Based Registration for the Computer-Assisted Navigated Percutaneous Scaphoid Fixation.

An ultrasound (US)-based computer-assisted approach has the potential to improve the accuracy and precision of screw placement for the percutaneous fixation of scaphoid fractures and also reduce the radiation dose for patient and clinical staff. Therefore, a surgical plan based on preoperative diagnostic computed tomography (CT) is registered with intraoperative US images, enabling a navigated percutaneous fracture fixation. However, approaches published so far rely on semimanual methods for intraoperative registration and are limited by long computation times. To address these challenges, we propose the employment of deep learning-based methods for US segmentation and registration in order to achieve a fast and fully automated yet robust registration process. For validation of the proposed US-based approach, we first provide a comparison of methods for segmentation and registration, assess their contribution to the overall error throughout our pipeline, and, finally, evaluate navigated screw placement in an in vitro study on 3-D printed carpal phantoms. Successful screw placement has been achieved for all ten screws, with deviations from the planned axis of 1.0 ± 0.6 and 0.7 ± 0.3 mm at the distal and proximal pole, respectively. The complete automation and total duration of about 12 s also allow seamless integration of our approach into the surgical workflow.

Accuracy of on-site teleoperated milling with haptic assistance.

PURPOSE: In bone surgery specialties, like orthopedics, neurosurgery, and oral and maxillofacial surgery patient safety and treatment success depends on the accurate implementation of computer-based surgical plans. Unintentional plan deviations can result in long-term functional damage to the patient. With on-site teleoperation, the surgeon operates a slave robot with a physically-decoupled master device, while being directly present at the operation site. This allows the surgeon to perform surgical tasks with robotic accuracy, while always remaining in the control loop. METHODS: In this study the master- and slave-side accuracy of an on-site teleoperated miniature cooperative robot (minaroHD) is evaluated. Master-side accuracy is investigated in a user study regarding scale factor, target feed rate, movement direction and haptic guidance stiffness. Scale factors are chosen to correspond to primarily finger, hand, and arm movements. Slave-side accuracy is investigated in autonomous milling trials regarding stepover, feed rate, movement direction, and material density. RESULTS: Master-side user input errors increase with increasing target feed rate and scale factor, and decrease with increasing haptic guidance stiffness. Resulting slave-side errors decrease with increasing scale factor and are < 0.07 mm for optimal guidance parameters. Slave-side robot position errors correlate with the feed rate but show little correlation with stepover distance. For optimal milling parameters, the 95th percentile of tracked slave-side position error is 0.086 mm with a maximal error of 0.16 mm. CONCLUSION: For optimal guidance and milling parameters, the combined error of 0.23 mm is in the range of the dura mater thickness (< 0.27 mm) or mandibular canal wall (~ 0.85 mm). This corresponds to safety margins in high-demand surgical procedures like craniotomies, laminectomies, or decortication of the jaw. However, for further clinical translation, the performance and usability of on-site teleoperated milling must be further evaluated for real-life clinical application examples with consideration of all error sources in a computer-assisted surgery workflow.

Knee Bone Models From Ultrasound.

The number of total knee arthroplasties performed worldwide is on the rise. Patient-specific planning and implants may improve surgical outcomes but require 3-D models of the bones involved. Ultrasound (US) may become a cheap and nonharmful imaging modality if the shortcomings of segmentation techniques in terms of automation, accuracy, and robustness are overcome; furthermore, any kind of US-based bone reconstruction must involve some kind of model completion to handle occluded areas, for example, the frontal femur. A fully automatic and robust processing pipeline is proposed, generating full bone models from 3-D freehand US scanning. A convolutional neural network (CNN) is combined with a statistical shape model (SSM) to segment and extrapolate the bone surface. We evaluate the method in vivo on ten subjects, comparing the US-based model to a magnetic resonance imaging (MRI) reference. The partial freehand 3-D record of the femur and tibia bones deviate by 0.7-0.8 mm from the MRI reference. After completion, the full bone model shows an average submillimetric error in the case of the femur and 1.24 mm in the case of the tibia. Processing of the images is performed in real time, and the final model fitting step is computed in less than a minute. It took an average of 22 min for a full record per subject.

Parameter-based patient-specific restoration of physiological knee morphology for optimized implant design and matching.

Total knee arthroplasty (TKA) patients may present with genetic deformities, such as trochlear dysplasia, or deformities related to osteoarthritis. This pathologic morphology should be corrected by TKA to compensate for related functional deficiencies. Hence, a reconstruction of an equivalent physiological knee morphology would be favorable for detailed preoperative planning and the patient-specific implant selection or design process. A parametric database of 673 knees, each described by 36 femoral parameter values, was used. Each knee was classified as pathological or physiological based on cut-off values from literature. A clinical and a mathematical classification approach were developed to distinguish between affected and unaffected parameters. Three different prediction methods were used for the restoration of physiological parameter values: regression, nearest neighbor search and artificial neural networks. Several variants of the respective prediction model were considered, such as different network architectures. Regarding all methods, the model variant chosen resulted in a prediction error below the parameters' standard deviation, while the regression yielded the lowest errors. Future analyses should consider other deformities, also of tibia and patella. Furthermore, the functional consequences of the parameter changes should be analyzed.

Integration of a surgical robotic arm to the connected operating room via ISO IEEE 11073 SDC.

PURPOSE: Since 2019, intraoperative networking with ISO IEEE 11073 SDC has, for the first time, enabled standardized multi-vendor data exchange between medical devices. For seamless plug-and-play integration of devices without previous configuration, further specifications for device profiles ("device specializations") on top of the existing core standards must be developed. These generic interfaces are then incorporated into the standardization process. METHODS: An existing classification scheme of robotic assistance functions is being adopted and used as a baseline to derive functional requirements for a universal interface for modular robot arms. Additionally, the robot system requires machine-machine interfaces (MMI) to a surgical navigation system and a surgical planning software in order to carry out its function. Further technical requirements are derived from these MMI. The functional and technical requirements motivate the design of an SDC-compatible device profile. The device profile is then assessed for feasibility. RESULTS: We present a new modeling of a device profile for surgical robotic arms intended for neurosurgery and orthopedic surgery. The modeling in SDC succeeds for the most part. However, some details of the proposed model cannot yet be realized within the framework of the existing SDC standards. Some aspects can already be realized, but could be better supported in the future by the nomenclature system. These improvements are being presented as well. CONCLUSION: The proposed device profile presents a first step toward a uniform technical description model for modular surgical robot systems. The current SDC core standards lack some functionality to fully support the proposed device profile. These could be defined in future work and then included in standardization efforts.

Potential for femoral size optimization for off-the-shelf implants: A CT derived implant database analysis.

In total knee arthroplasty, the femoral implant size is chosen mainly based on the femoral anteroposterior (AP) height and mediolateral (ML) width. This choice often is a compromise, due to limited size availability. Inadequate AP fit is expected to alter flexion laxity and thus knee function. Inadequate ML fit entails underhang or overhang, which is linked to worse clinical outcomes. Hence, we aimed to find implant size distributions, which maximize population coverage, and to evaluate the sensitivity regarding error bounds and the number of implant sizes for a database of 85,143 cases. All patients in the database have been provided with a patient-specific implant in the past. For a subset of 1049 cases, three-dimensional preoperative bone surface models were available. These were used to validate whether the implant dimensions were representative of the bone dimensions. Particle Swarm Optimization was used for optimizing the implant size distribution. The deviations between implant and bone measures in the subset were found to be clinically irrelevant. Therefore, the full database of 85,143 cases was used for further analyses. A higher sensitivity of the population coverage regarding the error bounds compared to the number of implant sizes was found. For an exemplary setup of 12 optimized implant sizes and error bounds of ±1.5 mm for AP and ±3 mm for ML, a population coverage of almost 85% was achieved. In contrast, even with 30 implant sizes, a full population coverage could not be reached. Hence, remaining cases should be provided with patient-specific implants.

Safe design of surgical robots - a systematic approach to comprehensive hazard identification.

OBJECTIVES: Since the 1980s, robotic arms have been transferred from industrial applications to orthopaedic surgical robotics. Adverse events are frequent and often associated with the adopted powerful and oversized anthropomorphic arms. The FDA's 510(k) pathway encourages building on such systems, leading to the adoption of hazards, which is known as "predicate creep". Additionally, the methodology of hazard identification for medical device development needs improvement. METHODS: We present an approach to enhance general hazard identification and prevent hazards of predicate creep by using the integrative, scenario-based and multi-perspective Point-of-View (PoV) approach. We also present the Catalogue of Hazards (CoH) as an approach for collecting and systematising hazards for future risk analysis and robot development. RESULTS: We applied seven predefined PoVs to the use case of robotic laminectomy and identified 133 hazards, mainly coming from HMI analysis and literature. By analysing the MAUDE and recalls databases of the FDA, we were able to classify historical hazards and adopt them into the use case. CONCLUSIONS: The combination of PoV approach and CoH is suitable for integrating multiple established hazard identification methods, increasing comprehensiveness, and supporting the systematic and hazard-based development of surgical robots.

Implications of the uncertainty of postoperative functional parameters for the preoperative planning of total hip arthroplasty.

The functional parameters pelvic tilt (PT) and hip joint force (HJF) are required to calculate patient-specific target zones based on the range of motion (ROM) and implant loading for preoperative planning of total hip arthroplasty (THA). Both functional parameters may change after THA. The preoperative prediction of the postoperative PT and HJF is associated with a specific amount of uncertainty. The prediction uncertainty has to be considered in the preoperative planning process to avoid a suboptimal implantation. So far, very little attention has been paid to the necessary reduction of patient-specific target zones by the prediction uncertainties of postoperative functional parameters. Prediction models for the postoperative PT in standing position and for the HJF during one-leg stance as a surrogate for the peak force phase during level walking were used to quantify the reduction of the ROM- and load-based target zones of 196 Japanese THA patients. The prediction uncertainty was about 14° for the postoperative standing PT and ranged from 17% body weight to 37% body weight for the components of the HJF. On average, the prosthetic ROM-based target zone had to be significantly reduced by 43% and the load-based target zone by 39%. This led to a median reduction of the combined prosthetic ROM- and load-based target zone of 96%. The study sharpens the awareness for the substantial reduction of ROM- and load-based target zones by prediction uncertainties of the postoperative PT and HJF and highlights the importance of further research to improve prediction models for both functional parameters.

Investigation of morphotypes of the knee using cluster analysis.

BACKGROUND: Objects that manifest in several characteristic shapes, or morphotypes, are typically caused by some hidden variable. For example, the gender of a person influences the width of their pelvis. This is important when reconstructing natural shapes, e.g., in knee implant design. The aim of this study was to identify such morphotypes. METHODS: This work investigated the shapes of roughly 1000 knee joints acquired from computed tomography, including the distal femur and proximal tibia. Two comprehensive feature sets were utilized to describe the bone shapes, one based on morphological measurements and the other on statistical shape model (SSM) weights. We normalized the data by size and performed a cluster analysis with different algorithms, namely k-means and high dimensional data clustering. The clusters were evaluated using several metrics. RESULTS: The data showed a low tendency to form clusters. Only one of 12 experiments slightly exceeded the thresholds for actual clusters suggested by the literature. k-Means outperformed high dimensional data clustering in all cases. CONCLUSION: After anisotropic normalization by size, which removes size and aspect ratio related differences, the data exhibited no morphotypes. This showed that there are no relevant hidden variables, e.g., gender, body type or ethnicity, which influence the shape of the knee joint. Instead, knee shape is highly individual. Investigating the three-dimensional shape, variations occur for a wide range of different shape parameters, not just for anterior-posterior and mediolateral size.

Effect of the underlying cadaver data and patient-specific adaptation of the femur and pelvis on the prediction of the hip joint force estimated using static models.

The prediction of the hip joint force (HJF) is a fundamental factor for the prevention of edge loading in total hip arthroplasty. Naturally, the loading of the liner of the acetabular component depends on the HJF acting on the artificial joint. In contrast to dynamic musculoskeletal models, static models for HJF prediction do not require motion analysis of the patient. However, patient-specific adaptability and validity of static models have to be scrutinized. In this study, a modular framework for HJF prediction using static models is introduced to compare the results of different cadaver templates that are the basis of most static and dynamic models, and different scaling laws for the patient-specific adaptation with in vivo HJF of ten patients for one-leg stance and level walking. The results revealed the significant effect of the underlying cadaver template used for the prediction of the HJF (p < 0.01). A higher degree of patient-specific scaling of the cadaver template often did not significantly reduce the prediction error. Three static models with the lowest prediction errors were compared to results of dynamic models from literature. The prediction error of the peak HJF of the static models (median absolute errors below 15% body weight in magnitude and below 5° in direction) was similar in magnitude and even smaller in direction compared to dynamic models. The necessary reduction of a load-based target zone for the prevention of edge loading due to the uncertainty of the HJF prediction has to be considered in the preoperative planning. The framework for HJF prediction is openly accessible at https://github.com/RWTHmediTEC/HipJointForceModel.

The Patient-Specific Combined Target Zone for Morpho-Functional Planning of Total Hip Arthroplasty.

Background Relevant criteria for total hip arthroplasty (THA) planning have been introduced in the literature which include the hip range of motion, bony coverage, anterior cup overhang, leg length discrepancy, edge loading risk, and wear. The optimal implant design and alignment depends on the patient's anatomy and patient-specific functional parameters such as the pelvic tilt. The approaches proposed in literature often consider one or more criteria for THA planning. but to the best of our knowledge none of them follow an integrated approach including all criteria for the definition of a patient-specific combined target zone (PSCTZ). Questions/purposes (1) How can we calculate suitable THA implant and implantation parameters for a specific patient considering all relevant criteria? (2) Are the resulting target zones in the range of conventional safe zones? (3) Do patients who fulfil these combined criteria have a better outcome score? Methods A method is presented that calculates individual target zones based on the morphology, range of motion and load acting on the hip joint and merges them into the PSCTZ. In a retrospective analysis of 198 THA patients, it was calculated whether the patients were inside or outside the Lewinnek safe zone, Dorr combined anteversion range and PSCTZ. The postoperative Harris Hip Scores (HHS) between insiders and outsiders were compared. Results 11 patients were inside the PSCTZ. Patients inside and outside the PSCTZ showed no significant difference in the HHS. However, a significant higher HHS was observed for the insiders of two of the three sub-target zones incorporated in the PSCTZ. By combining the sub-target zones in the PSCTZ, all PSCTZ insiders except one had an HHS higher than 90. Conclusions The results might suggest that, for a prosthesis implanted in the PSCTZ a low outcome score of the patient is less likely than using the conventional safe zones by Lewinnek and Dorr. For future studies, a larger cohort of patients inside the PSCTZ is needed which can only be achieved if the cases are planned prospectively with the method introduced in this paper. Clinical Relevance The method presented in this paper could help the surgeon combining multiple different criteria during THA planning and find the suitable implant design and alignment for a specific patient.

Variation of the Three-Dimensional Femoral J-Curve in the Native Knee.

The native femoral J-Curve is known to be a relevant determinant of knee biomechanics. Similarly, after total knee arthroplasty, the J-Curve of the femoral implant component is reported to have a high impact on knee kinematics. The shape of the native femoral J-Curve has previously been analyzed in 2D, however, the knee motion is not planar. In this study, we investigated the J-Curve in 3D by principal component analysis (PCA) and the resulting mean shapes and modes by geometric parameter analysis. Surface models of 90 cadaveric femora were available, 56 male, 32 female and two without respective information. After the translation to a bone-specific coordinate system, relevant contours of the femoral condyles were derived using virtual rotating cutting planes. For each derived contour, an extremum search was performed. The extremum points were used to define the 3D J-Curve of each condyle. Afterwards a PCA and a geometric parameter analysis were performed on the medial and lateral 3D J-Curves. The normalized measures of the mean shapes and the aspects of shape variation of the male and female 3D J-Curves were found to be similar. When considering both female and male J-Curves in a combined analysis, the first mode of the PCA primarily consisted of changes in size, highlighting size differences between female and male femora. Apart from changes in size, variation regarding aspect ratio, arc lengths, orientation, circularity, as well as regarding relative location of the 3D J-Curves was found. The results of this study are in agreement with those of previous 2D analyses on shape and shape variation of the femoral J-Curves. The presented 3D analysis highlights new aspects of shape variability, e.g., regarding curvature and relative location in the transversal plane. Finally, the analysis presented may support the design of (patient-specific) femoral implant components for TKA.

Evaluation of a novel stair-climbing transportation aid for emergency medical services.

Acute and planned transportations of patients are major tasks for emergency medical services (EMS) and often result in substantial physical strains with a major impact on the workers' health, because current transportation aids cannot provide sufficient support, especially on stairs. A new stair-climbing and self-balancing approach (SEBARES) has been developed and its usability is evaluated in the context of this paper. Twelve participants operated a prototype in a transportation scenario and user forces, user joint angles and the perceived usability were evaluated. Results show that user forces were within long-term acceptable ergonomic limits for over 90% of the transportation time and a mainly healthy upright posture of the back could be maintained. This resulted in a healthy working posture for 85% of the time, according to the OWAS method, and a good perceived usability. A comparison to the most ergonomic aid according to literature, a caterpillar stair chair, reveals that similar upright postures are assumed, while the operation of SEBARES required only 47% of the forces to operate the caterpillar stair chair. A comparison to a previous field study indicates a reduction of strenuous working postures by a factor of three, which further confirms the ergonomic advantages of this concept.

Relationship between the form and function of implant design in total knee replacement.

The implant design in total knee replacement affects postoperative functionality greatly, therefore, its optimization is of major concern. However, little is known about how implant design parameters affect active knee kinematics. Comprehensive in silico and in vitro sensitivity analyses were performed, based on one patient-specific, physical knee implant set and corresponding bone and knee implant surface geometry data. The implant surfaces were parametrized and varied systematically, resulting in 85 different knee implant surface models. In addition, four variations of extensor mechanism parameters, being the muscular attachment points defining the Q-Angle, were investigated. The variations were evaluated in a patient-specific multibody simulation model and an experimental testing rig and contributions of different implant designs and extensor mechanism parameters on kinematics were analysed. The results of the in silico and in vitro analyses showed good qualitative agreement. The highest deviations from the implant's reference kinematics were found for parameter variations of the femoral sagittal radii, the lateral trochlear elevation, the tibial sagittal slopes, the mediolateral position of the patellar ridge and the mediolateral position of the tuberositas tibiae. The implant design parameters identified with the highest functional relevance should be focused on in implant design. As the tuberositas tibiae's position constituted a main impact factor, it should also be considered during implant design and preoperative planning. Due to the competing influence of implant design parameters on active kinematics, respective parameters should be designed which are compatible to each other to avoid adverse constraints and associated functional limitations.

MINARO HD: control and evaluation of a handheld, highly dynamic surgical robot.

PURPOSE: Current surgical robotic systems are either large serial arms, resulting in higher risks due to their high inertia and no inherent limitations of the working space, or they are bone-mounted, adding substantial additional task steps to the surgical workflow. The robot presented in this paper has a handy and lightweight design and can be easily held by the surgeon. No rigid fixation to the bone or a cart is necessary. A high-speed tracking camera together with a fast control system ensures the accurate positioning of a burring tool. METHODS: The capabilities of the robotic system to dynamically compensate for unintended motion, either of the robot itself or the patient, was evaluated. Therefore, the step response was analyzed as well as the capability to follow a moving target. RESULTS: The step response show that the robot can compensate for undesired motions up to 12 Hz in any direction. While following a moving target, a maximum positioning error of 0.5 mm can be obtained with a target motion of up to 18 mm/s. CONCLUSION: The requirements regarding dynamic motion compensation, accuracy, and machining speed of unicompartmental knee arthroplasties, for which the robot was optimized, are achieved with the presented robotic system. In particular, the step response results show that the robot is able to compensate for human tremor.

Usability of cooperative surgical telemanipulation for bone milling tasks.

PURPOSE: Cooperative surgical systems enable humans and machines to combine their individual strengths and collaborate to improve the surgical outcome. Cooperative telemanipulated systems offer the widest spectrum of cooperative functionalities, because motion scaling is possible. Haptic guidance can be used to assist surgeons and haptic feedback makes acting forces at the slave side transparent to the operator, however, overlapping and masking of forces needs to be avoided. This study evaluates the usability of a cooperative surgical telemanipulator in a laboratory setting. METHODS: Three experiments were designed and conducted for characteristic surgical task scenarios derived from field studies in orthopedics and neurosurgery to address bone tissue differentiation, guided milling and depth sensitive milling. Interaction modes were designed to ensure that no overlapping or masking of haptic guidance and haptic feedback occurs when allocating information to the haptic channel. Twenty participants were recruited to compare teleoperated modes, direct manual execution and an exemplary automated milling with respect to usability. RESULTS: Participants were able to differentiate compact and cancellous bone, both directly manually and teleoperatively. Both telemanipulated modes increased effectiveness measured by the mean absolute depth and contour error for guided and depth sensitive millings. Efficiency is decreased if solely a boundary constraint is used in hard material, while a trajectory guidance and manual milling perform similarly. With respect to subjective user satisfaction trajectory guidance is rated best for guided millings followed by boundary constraints and the direct manual interaction. Haptic feedback only improved subjective user satisfaction. CONCLUSION: A cooperative surgical telemanipulator can improve effectiveness and efficiency close to an automated execution and enhance user satisfaction compared to direct manual interaction. At the same time, the surgeon remains part of the control loop and is able to adjust the surgical plan according to the intraoperative situation and his/her expertise at any time.

A robust method for automatic identification of femoral landmarks, axes, planes and bone coordinate systems using surface models.

The identification of femoral landmarks is a common procedure in multiple academic fields. Femoral bone coordinate systems are used particularly in orthopedics and biomechanics, and are defined by landmarks, axes and planes. A fully automatic detection overcomes the drawbacks of a labor-intensive manual identification. In this paper, a new automatic atlas- and a priori knowledge-based approach that processes femoral surface models, called the A&A method, was evaluated. The A&A method is divided in two stages. Firstly, a single atlas-based registration maps landmarks and areas from a template surface to the subject. In the second stage, landmarks, axes and planes that are used to construct several femoral bone coordinate systems are refined using a priori knowledge. Three common femoral coordinate systems are defined by the landmarks detected. The A&A method proved to be very robust against a variation of the spatial alignment of the surface models. The results of the A&A method and a manual identification were compared. No significant rotational differences existed for the bone coordinate system recommended by the International Society of Biomechanics. Minor significant differences of maximally 0.5° were observed for the two other coordinate systems. This might be clinically irrelevant, depending on the context of use and should, therefore, be evaluated by the potential user regarding the specific application. The entire source code of the A&A method and the data used in the study is open source and can be accessed via https://github.com/RWTHmediTEC/FemoralCoordinateSystem .

Preoperative factors improving the prediction of the postoperative sagittal orientation of the pelvis in standing position after total hip arthroplasty.

The aims of this study were to investigate if the sagittal orientation of the pelvis (SOP) in the standing position changes after total hip arthroplasty (THA) and evaluate what preoperative factors may improve the prediction of the postoperative standing SOP in the context of a patient-specific functional cup orientation. 196 primary THA patients from Japan were retrospectively selected for this study. Computed tomography imaging of the pelvis, EOS imaging of the lower body and lateral radiographs of the lumbar spine in the standing position were taken preoperatively. Common biometrics and preoperative Harris Hip Score were recorded. The EOS imaging in the standing position was repeated three months following THA. A 3D/2.5D registration process was used to determine the standing SOP. Thirty-three preoperative biometric, morphological and functional parameters were measured. Important preoperative parameters were identified that significantly improve the prediction of the postoperative standing SOP by using multiple linear LASSO regression. On average, the SOP changed significantly (p < 0.001) between the preoperative and postoperative standing position three months after THA by 3° ± 4° in the posterior direction. The age, standing lumbar lordosis angle (LLA) and preoperative supine and standing SOP significantly (p < 0.001) improve the prediction of the postoperative standing SOP. The linear regression model for the prediction of the postoperative standing SOP is significantly (p < 0.001) improved by adding the parameters preoperative standing SOP and LLA, in addition to the preoperative supine SOP, reducing the root mean square error derived from a leave-one-out cross-validation by more than 1°. The mean standing SOP in Japanese patients changes already three months after THA in comparison to the preoperative value. The preoperative factors age, LLA, supine and standing SOP can significantly improve the prediction of the postoperative standing SOP and should be considered within the preoperative planning process of a patient-specific functional cup orientation.