Determining proper joint tension in reverse total shoulder arthroplasty (rTSA) can be a challenging task for shoulder surgeons. Often, this is a subjective metric learned by feel during fellowship training with no real quantitative measures of what proper tension encompasses. Tension too high can potentially lead to scapular stress fractures and limitation of range of motion (ROM), whereas tension too low may lead to instability. New technologies that detect joint load intraoperatively create the opportunity to observe rTSA joint reaction forces in a clinical setting for the first time. The purpose of this study was to observe the differences in rTSA loads in cases that utilized two different humeral liner sizes. Ten different surgeons performed a total of 37 rTSA cases with the same implant system. During the procedure, each surgeon reconstructed the rTSA implants to his or her own preferred tension. A wireless load sensing humeral liner trial (VERASENSE for Equinoxe, OrthoSensor, Dania Beach, FL) was used in lieu of a traditional plastic humeral liner trial to provide real-time load data to the operating surgeon during the procedure. Two humeral liner trial sizes were offered in 38mm and 42mm curvatures and were selected each case based on surgeon preference. To ensure consistent measurements between surgeons, a standardized ROM assessment consisting of four dynamic maneuvers (maximum internal to external rotation at 0°, 45°, and 90° of abduction, and a maximum flexion/extension maneuver) and three static maneuvers (arm overhead, across the body, and behind the back) was completed in each case. Deidentified load data in lbf was collected and sorted based on which size liner was selected. Differences in means for minimum and maximum load values for the four dynamic maneuvers and differences in means for the three static maneuvers were calculated using 2-tailed unpaired t-tests.INTRODUCTION
METHODS
Varus alignment in total knee replacement (TKR) results in a larger portion of the joint load carried by the medial compartment.[1] Increased burden on the medial compartment could negatively impact the implant fixation, especially for cementless TKR that requires bone ingrowth. Our aim was to quantify the effect varus alignment on the bone-implant interaction of cementless tibial baseplates. To this end, we evaluated the bone-implant micromotion and the amount of bone at risk of failure.[2,3] Finite element models (Fig.1) were developed from pre-operative CT scans of the tibiae of 11 female patients with osteoarthritis (age: 58–77 years). We sought to compare two loading conditions from Smith et al.;[1] these corresponded to a mechanically aligned knee and a knee with 4° of varus. Consequently, we virtually implanted each model with a two-peg cementless baseplate following two tibial alignment strategies: mechanical alignment (i.e., perpendicular to the tibial mechanical axis) and 2° tibial varus alignment (the femoral resection accounts for additional 2° varus). The baseplate was modeled as solid titanium (E=114.3 GPa; v=0.33). The pegs and a 1.2 mm layer on the bone-contact surface were modeled as 3D-printed porous titanium (E=1.1 GPa; v=0.3). Bone material properties were non-homogeneous, determined from the CT scans using relationships specific to the proximal tibia.[2,4] The bone-implant interface was modelled as frictional with friction coefficients for solid and porous titanium of 0.6 and 1.1, respectively. The tibia was fixed 77 mm distal to the resection. For mechanical alignment, instrumented TKR loads previously measured Introduction
Methods
Surgeons commonly resect additional distal femur during primary total knee arthroplasty (TKA) to correct a flexion contracture to restore range of motion and knee function. However, the effect of joint line elevation on the resulting TKA kinematics including frontal plane laxity is unclear. Thus, our goal was to quantify the effect of additional distal femoral resection on passive extension and mid-flexion laxity. Six computational knee models with capsular and collateral ligament properties specific to TKA were developed and implanted with a contemporary posterior-stabilized TKA. A 10° flexion contracture was modeled by imposing capsular contracture as determined by simulating a common clinical exam of knee extension and accounting for the length and weight of each limb segment from which the models were derived (Figure 1). Distal femoral resections of 2 mm and 4 mm were simulated for each model. The knees were then extended by applying the measured knee moments to quantify the amount of knee extension. The output data were compared with a previous cadaveric study using a two-sample two-tailed t-test (p<0.05) [1]. Subsequently, varus and valgus torques of ±10 Nm were applied as the knee was flexed from 0° to 90° at the baseline, and after distal resections of 2 mm, and 4 mm. Coronal laxity, defined as the sum of varus and valgus angulation in response to the applied varus and valgus torques, was measured at 30° and 45°of flexion, and the flexion angle was identified where the increase in laxity was the greatest with respect to baseline.Introduction
Methods
Total Elbow Arthroplasty (TEA) is recognized as an effective treatment solution for patients with rheumatoid arthritis or for traumatic conditions. Current total elbow devices can be divided into linked or unlinked design. The first design usually presents a linking element (i.e. an axle) to link together the ulnar and humeral components to stabilize the joint; the second one does not present any linkage and the stability is provided by both intrinsic design constraints and the soft tissues. Convertible modular solutions allow for an intraoperative decision to link or unlink the prosthesis; the modular connections introduce however additional risks in terms of both mechanical strength and potential fatigue and fretting phenomena that may arise not only due to low demand activities loads, but also high demand (HD) ones that could be even more detrimental. The aim of this study was to assess the strength of the modular connection between the axle and the ulnar component in a novel convertible elbow prosthesis design under simulated HD and activities of daily living (ADLs) loading. A novel convertible total elbow prosthesis (LimaCorporate, IT) comprising both ulnar and humeral components that can be linked together by means of an axle, was used. Both typical ADLs and HD torques to be applied to the axle were determined based on finite element analysis (FEA); the boundary load conditions for the FEA were determined based on kinematics analysis on real patients in previous studies. The FEA resultant moment acting on the axle junction during typical ADLs (i.e. feeding with 7.2lbs weight in hand) was 3.2Nm while for HD loads (i.e. sit to stand) was 5.7 Nm. In the experimental setup, 5 axle specimens coupled with 5 ulnar bodies through a tapered connection (5 Nm assembly torque) were fixed to a torque actuator (MTS Bionix) and submerged in a saline solution (9g/l). A moment of 3.2 Nm was applied to the axle for 5M cycles through a fixture to test it under ADLs loading. After 5M cycles, the axles were analyzed with regards to fretting behavior and then re-assembled to test them against HD loading by applying 5.7 Nm for 200K cycles (corresponding to 20 years function).Introduction
Methods
Proper ligament engagement is an important topic of discussion for total knee arthroplasty; however, its importance to total ankle arthroplasty (TAA) is uncertain. Ligaments are often lengthened or repaired in order to achieve balance in TAA without an understanding of changes in clinical outcomes. Unconstrained designs increase ankle laxity,1 but little is known about ligament changes with constrained designs or throughout functional activity. To better understand the importance of ligament engagement, we first investigated the changes in distance between ligament insertions throughout stance with different TAA designs. We hypothesize that the distance between ligaments spanning the ankle joint would increase in specimens following TAA throughout stance. A validated method of measuring individual bone kinematics was performed on pilot specimens pre- and post-TAA using a six-degree-of-freedom robotic simulator with extrinsic muscle actuators and motion capture cameras (Figure 1).2 Reflective markers attached to surgical pins and radiopaque beads were rigidly fixed to the tibia, fibula, talus, calcaneus, and navicular for each specimen. TAAs were performed by a fellowship-trained foot and ankle surgeon on two specimens with separate designs implanted (Cadence & Salto Talaris; Integra LifeSciences; Plainsboro, NJ). Each specimen was CT-scanned after robotic simulations of stance pre- and post-TAA. Specimens were then dissected before a 3D-coordinate measuring device was used to digitize the ligament insertions and beads. Ligament insertions were registered onto the bone geometries within CT images using the digitized beads. Individual bone kinematics measured from motion capture were then used to record the point-to-point distance between centers of the ligament insertions throughout stance.INTRODUCTION
METHODS
Acromial and scapular fractures are a rare but difficult complication with reverse total shoulder arthroplasty (rTSA), with an incidence rate reported from 1–10%. The risk factors associated with these fractures types is largely unknown. The goal of this study is to analyze the clinical outcomes, demographic and comorbidity data, and implant sizing and surgical technique information from 4125 patients who received a primary rTSA with one specific prosthesis (Equinoxe, Exactech, Inc) and were sorted based on the radiographic documentation of an acromial and/or scapula fracture (ASF) to identify factors associated with this complication. 4125 patients (2652F/1441M/32 unspecified; mean age: 72.5yrs) were treated with primary rTSA by 23 orthopaedic surgeons. Revision and fracture reverse arthroplasty cases were excluded. The radiographic presence of each fracture was documented and classified using the Levy classification method. 61 patients were identified as having ASF, 10 patients had fractures of the Type 1, 32 patients had Type 2, and 18 patients had Type 3 fractures according to Levy's classification. One fracture was not classifiable. Pre-op and post-op outcome scoring, ROM as well as demographic, comorbidity, implant, and surgical technique information were evaluated for these 61 patients and compared to the larger cohort of patients to identify any associations. A two-tailed, unpaired t-test identified differences (p<0.05).Introduction
Methods
Long term data on the survivorship of cemented total knee arthroplasty (TKA) has demonstrated excellent outcomes; however, with younger, more active patients, surgeons have a renewed interest in improved biologic fixation obtained from highly porous, cementless implants. Early designs of cementless total knees systems were fraught with high rates of failure for aseptic loosening, particularly on the tibial component. Prior studies have assessed the bone ingrowth extent for tibial tray designs reporting near 30% extent of bone ingrowth (1,2). While these analyses were performed on implants that demonstrated unacceptably high rates of clinical failure, a paucity of data exists on the extent on bone ingrowth in contemporary implant designs with newer methods for manufacturing the porous surfaces. We sought to evaluate the extent of attached bone on retrieved cementless tibial trays to determine if patient demographics, device factors, or radiographic results correlate to the extent of bone ingrowth in these contemporary designs. Using our IRB approved retrieval database, 17 porous tibial trays were identified and separated into groups based on manufactIntroduction
Methods
Machine learning is a relatively novel method to orthopaedics which can be used to evaluate complex associations and patterns in outcomes and healthcare data. The purpose of this study is to utilize 3 different supervised machine learning algorithms to evaluate outcomes from a multi-center international database of a single shoulder prosthesis to evaluate the accuracy of each model to predict post-operative outcomes of both aTSA and rTSA. Data from a multi-center international database consisting of 6485 patients who received primary total shoulder arthroplasty using a single shoulder prosthesis (Equinoxe, Exactech, Inc) were analyzed from 19,796 patient visits in this study. Specifically, demographic, comorbidity, implant type and implant size, surgical technique, pre-operative PROMs and ROM measures, post-operative PROMs and ROM measures, pre-operative and post-operative radiographic data, and also adverse event and complication data were obtained for 2367 primary aTSA patients from 8042 visits at an average follow-up of 22 months and 4118 primary rTSA from 11,754 visits at an average follow-up of 16 months were analyzed to create a predictive model using 3 different supervised machine learning techniques: 1) linear regression, 2) random forest, and 3) XGBoost. Each of these 3 different machine learning techniques evaluated the pre-operative parameters and created a predictive model which targeted the post-operative composite score, which was a 100 point score consisting of 50% post-operative composite outcome score (calculated from 33.3% ASES + 33.3% UCLA + 33.3% Constant) and 50% post-operative composite ROM score (calculated from S curves weighted by 70% active forward flexion + 15% internal rotation score + 15% active external rotation). 3 additional predictive models were created to control for the time required for patient improvement after surgery, to do this, each primary aTSA and primary rTSA cohort was subdivided to only include patient data follow-up visits >20 months after surgery, this yielded 1317 primary aTSA patients from 2962 visits at an average follow-up of 50 months and 1593 primary rTSA from 3144 visits at an average follow-up of 42 months. Each of these 6 predictive models were trained using a random selection of 80% of each cohort, then each model predicted the outcomes of the remaining 20% of the data based upon the demographic, comorbidity, implant type and implant size, surgical technique, pre-operative PROMs and ROM measures inputs of each 20% cohort. The error of all 6 predictive models was calculated from the root mean square error (RMSE) between the actual and predicted post-op composite score. The accuracy of each model was determined by subtracting the percent difference of each RMSE value from the average composite score associated with each cohort.Introduction
Methods
3D preoperative planning software for anatomic and reverse total shoulder arthroplasty (ATSA and RTSA) provides additional insight for surgeons regarding implant selection and placement. Interestingly, the advent of such software has brought previously unconsidered questions to light on the optimal way to plan a case. In this study, a survey of shoulder specialists from the American Shoulder and Elbow Society (ASES) was conducted to examine thought patterns in current glenoid implant selection and placement. 172 ASES members completed an 18-question survey on their thought process for how they select and place a glenoid implant for both ATSA and RTSA procedures. Data was collected using a custom online Survey Monkey survey. Surgeon answers were split into three cohorts based on their responses to usage of 3D preoperative planning software: high users, seldom users, and non-users. Data was analyzed for each cohort to examine differences in thought patterns, implant selection, and implant placement.INTRODUCTION
METHODS
The interaction between the mobile components of total elbow replacements (TER) provides additional constraint to the elbow motion. Semi-constrained TER depend on a mechanical linkage to avoid dislocation and have greater constraint than unconstrained TER that rely primarily in soft tissue for joint stability. Greater constraint increases the load transfer to the implant interfaces and the stresses in the polyethylene components. Both of these phenomena are detrimental to the longevity of TER, as they may result in implant loosening and increased damage to the polyethylene components, respectively[1]. The objective of this work was to compare the constraint profile in varus-valgus and internal-external rotation and the polyethylene stresses under loads from a common daily activity between two semi-constrained TER, Coonrad/Morrey (Zimmer-Biomet) and Discovery® (DJO), and an unconstrained TER, TEMA (LimaCorporate). We developed finite element (FE) models of the three TER mechanisms. To reduce computational cost, we did not include the humeral and ulnar stems. Materials were linear-elastic for the metallic components (ETi6Al4V=114.3 GPa, ECoCr=210 GPa, v=0.33) and linear elastic-plastic for the polyethylene components (E=618 MPa, v=0.46; SY=22 MPa; SU=230.6 MPa; εU=1.5 mm/mm). The models were meshed with linear tetrahedral elements of sizes 0.4–0.6 mm. We assumed a friction coefficient of 0.02 between metal and polyethylene. In all simulations, the ulnar component was fixed and the humeral component loaded. We computed the constraint profiles in full extension by simulating each mechanism from 8° varus to 8° valgus and from 8° internal to 8° external rotation. All other degrees-of-freedom except for flexion extension were unconstrained. Then, we identified the instant during feeding that generated the highest moments at the elbow[2], and we applied the joint forces and moments to each TER to evaluate the stresses in the polyethylene. To validate the FE results, we experimentally evaluated the constraint of the design with highest polyethylene stresses in pure internal-external rotation and compared the results against those from a FE model that reproduced the experimental setup (Fig.1-a).Introduction
Methods
The advent of CT based 3D preoperative planning software for reverse total shoulder arthroplasty (RTSA) provides surgeons with more data than ever before to prepare for a case. Interestingly, as the usage of such software has increased, further questions have appeared over the optimal way to plan and place a glenoid implant for RTSA. In this study, a survey of shoulder specialists from the American Shoulder and Elbow Society (ASES) was conducted to examine thought patterns in current RTSA implant selection and placement. 172 ASES members completed an 18-question survey on their thought process for how they select and place a RTSA glenoid implant. Data was collected using a custom online Survey Monkey survey. Surgeon answers were split into two cohorts based on number of arthroplasties performed per year: between 0–75 was considered low volume (LV), and between 75–200+ was considered high volume (HV). Data was analyzed for each cohort to examine differences in thought patterns, implant selection, and implant placement.INTRODUCTION
METHODS
3D preoperative planning software for anatomic total shoulder arthroplasty (ATSA) provides surgeons with increased ability to visualize complex joint relationships and deformities. Interestingly, the advent of such software has seemed to create less of a consensus on the optimal way to plan an ATSA rather than more. In this study, a survey of shoulder specialists from the American Shoulder and Elbow Society (ASES) was conducted to examine thought patterns in current ATSA implant selection and placement. 172 ASES members completed an 18-question survey on their thought process for how they select and place an ATSA glenoid implant. Data was collected using a custom online Survey Monkey survey. Surgeon answers were split into two cohorts based on number of arthroplasties performed per year: between 0–75 was considered low volume (LV), and between 75–200+ was considered high volume (HV). Data was analyzed for each cohort to examine differences in thought patterns, implant selection, and implant placement.INTRODUCTION
METHODS
Variability in placement of total shoulder arthroplasty (TSA) glenoid implants has led to the increased use of 3D CT preoperative planning software. Computer assisted surgery (CAS) offers the potential of improved accuracy in TSA while following a preoperative plan, as well as the flexibility for intraoperative adjustment during the procedure. This study compares the accuracy of implantation of reverse total shoulder arthroplasty (rTSA) glenoid implants using a CAS TSA system verses traditional non-navigated techniques in 30 cadaveric shoulders relative to a preoperative plan from 3D CT software. High resolution 1mm slice thickness CT scans were obtained on 30 cadaveric shoulders from 15 matched pair specimens. Each scan was segmented and the digital models were incorporated into a preoperative planning software. Five fellowship trained orthopedic shoulder specialists used this software to virtually place a rTSA glenoid implant as they deemed best fit in six cadavers each. The specimens were randomized with respect to side and split into a cohort utilizing the CAS system and a cohort utilizing conventional instrumentation, for a total of three shoulders per cohort per surgeon. A BaSO4 PEEK surrogate implant identical in geometry to the metal implant used in the preoperative plan was used in every specimen, to maintain high CT resolution while minimizing CT artifact. The surgeons were instructed to implant the rTSA implants as close to their preoperative plans as possible for both cohorts. In the CAS cohort, each surgeon used the system to register the native cadaveric bones to each respective CT, perform the TSA procedure, and implant the surrogate rTSA implant. The surgeons then performed the TSA procedure on the opposing side of the matched pair using conventional instrumentation. Postoperatively, CT scans were repeated on each specimen and segmented to extract the digital models. The pre- and postoperative scapulae models were aligned using a best fit match algorithm, and variance between the virtual planned position of the implant and the executed surgical position of the implant was calculated [Fig 1].INTRODUCTION
METHODS
Over the last decade, sensor technology has proven its benefits in total knee arthroplasty, allowing the quantitative assessment of tension in the medial and lateral compartment of the tibiofemoral joint through the range of motion (VERASENSE, OrthoSensor Inc, FL, USA). In reversal total shoulder arthroplasty, it is well understood that stability is primarily controlled by the active and passive structures surrounding the articulating surfaces. At current, assessing the tension in these stabilizing structures remains however highly subjective and relies on the surgeons’ feel and experience. In an attempt to quantify this feel and address instability as a dominant cause for revision surgery, this paper introduces an intra-articular load sensor for reverse total shoulder arthroplasty (RTSA). Using the capacitive load sensing technology embedded in instrumented tibial trays, a wireless, instrumented humeral trial has been developed. The wireless communication enables real-time display of the three-dimensional load vector and load magnitude in the glenohumeral joint during component trialing in RTSA. In an in-vitro setting, this sensor was used in two reverse total shoulder arthroplasties. The resulting load vectors were captured through the range of motion while the joint was artificially tightened by adding shims to the humeral tray.Introduction & Aims
Method
Preoperative planning software for anatomic total shoulder arthroplasty (ATSA) allows surgeons to virtually perform a reconstruction based off 3D models generated from CT scans of the glenohumeral joint. The purpose of this study was to examine the distribution of chosen glenoid implant as a function of glenoid wear severity, and to evaluate the inter-surgeon variability of optimal glenoid component placement in ATSA. CT scans from 45 patients with glenohumeral arthritis were planned by 8 fellowship trained shoulder arthroplasty specialists using a 3D preoperative planning software, planning each case for optimal implant selection and placement. The software provided three implant types: a standard non-augmented glenoid component, and an 8° and 16° posterior augment wedge glenoid component. The software interface allowed the surgeons to control version, inclination, rotation, depth, anterior- posterior and superior-inferior position of the glenoid components in 1mm and 1° increments, which were recorded and compared for final implant position in each case.INTRODUCTION
METHODS
Preoperative planning software for reverse total shoulder arthroplasty (RTSA) allows surgeons to virtually perform a reconstruction based off 3D models generated from CT scans of the glenohumeral joint. While anatomical studies have defined the range of normal values for glenoid version and inclination, there is no clear consensus on glenoid component selection and position for RTSA. The purpose of this study was to examine the distribution of chosen glenoid implant as a function of glenoid wear severity, and to evaluate the inter-surgeon variability of optimal glenoid component placement in RTSA. CT scans from 45 patients with glenohumeral arthritis were planned by 8 fellowship trained shoulder arthroplasty specialists using a 3D preoperative planning software, planning each case for optimal implant selection and placement. The software provided four glenoid baseplate implant types: a standard non-augmented component, an 8° posterior augment wedged component, a 10° superior augment wedged component, and a combined 8° posterior and 10° superior wedged augment component. The software interface allowed the surgeons to control version, inclination, rotation, depth, anterior-posterior and superior-inferior position of the glenoid components in 1mm and 1° increments, which were recorded and compared for final implant position in each case.INTRODUCTION
METHODS
Aseptic glenoid loosening is a common failure mode of reverse shoulder arthroplasty (rTSA). Achieving initial glenoid fixation can be a challenge for the orthopedic surgeon since rTSA is commonly used in elderly osteoporotic patients and is increasingly used in scapula with significant boney defects. Multiple rTSA baseplate designs are available in the marketplace, these prostheses offer between 2 and 6 screw options, with each screw hole accepting a locking and/or compression screw of varying lengths (between 15 to 50mm). Despite these multiple implant offerings, little guidance exists regarding the minimal screw length and/or minimum screw number necessary to achieve fixation. To this end, this study analyzes the effect of multiple screw lengths and multiple screw numbers on rTSA initial glenoid fixation when tested in a low density (15pcf) polyurethane bone substitute model. This rTSA glenoid loosening test was conducted according to ASTM F 2028–17; we quantified glenoid fixation of a 38mm reverse shoulder (Equinoxe, Exactech, Inc) in a 15 pcf low density polyurethane block (Pacific Research, Inc) before and after cyclic testing of 750N for 10k cycles. To evaluate the effect of both screw fixation and screw number, glenoid baseplates were constructed using 2 and 4, 4.5×18mm diameter poly-axial locking compression screws (both n = 5) and 2 and 4, 4.5×46mm diameter poly-axial locking compression screws (both n = 5). A two-tailed unpaired student's t-test (p < 0.05) compared prosthesis displacements to evaluate each screw length (18 vs 46mm) and each screw number (2 vs 4).Introduction
Methods
Musculoskeletal modeling techniques simulate reverse total shoulder arthroplasty (RTSA) shoulders and how implant placement affects muscle moment arms. Yet, studies have not taken into account how muscle-length changes affect force-generating capacity postoperatively. We develop a patient-specific model for RTSA patients to predict muscle activation. Patient-specific muscle parameters were estimated using an optimization scheme calibrating the model to isometric arm abduction data at 0°, 45°, and 90°. We compared predicted muscle activation to experimental electromyography recordings. A twelve-degree of freedom model with experimental measurements created patient-specific data estimating muscle parameters corresponding to strength. Optimization minimized the difference between measured and estimated joint moments and muscle activations, yielding parameters corresponding to subjects' strength that can predict muscle activation and lengths. Model calibration was performed on RTSA patients' arm abduction data. Predicted muscle activation ranged between 3% and 70% of maximum. The maximum joint moment produced was 10 Nm. The model replicated measured moments accurately (R2 > 0.99). The optimized muscle parameters produced feasible muscle moments and activations for dynamic arm abduction when using data from isometric force trials. A normalized correlation was found between predicted and experimental muscle activation for dynamic abduction (r > 0.9); the moment generation to lift the arm was tracked (R2 = 0.99). Statement of Clinical Significance: We developed a framework to predict patient-specific muscle parameters. Combined with patient-specific models incorporating joint configurations, kinematics, and bone anatomy, they can predict muscle activation in novel tasks and, e.g., predict how RTSA implant and surgical decisions may affect muscle function.
Reverse Total shoulder arthroplasty (RTSA) has become an increasingly used solution to treat osteoarthritis and cuff tear arthropathy. Though successful there are still 10 to 65% complication rates reported for RTSA. Complication rates range over different reverse shoulder designs but a clear understanding of implant design parameters that cause complications is still lacking within the literature. In efforts to reduce complication rates (Implant fixation, range of motion, joint stiffness, and fracture) and improve clinical/functional outcomes having to do with proper muscle performance we have employed a computational approach to assess the sensitivity of muscle performance to changes in RTSA implant geometry and surgical placement. The goal of this study was to assess how changes in RTSA joint configuration affect deltoid performance. An approach was developed from previous work to predict a patient's muscle performance. This approach was automated to assess changes in muscle performance over 1521 joint configurations for an RTSA subject. Patient-specific muscle moment arms, muscle lengths, muscle velocities, and muscle parameters served as inputs into the muscle prediction scheme. We systematically varied joint center locations over 1521 different perturbations from the Overall muscle normalized operating length varied over 1521 different implant configurations for the RTSA subject. Ideal muscle normalized operating length variations were found to be in all the fundamental directions that the joint was varied. The anterior deltoid normalized operating length was found to be most sensitive with joint configurations changes in the anterior/posterior medial/lateral direction. It lateral deltoid normalized operating length was found to be most sensitive with joint configurations changes in the medial/lateral direction. It posterior deltoid normalized operating length was found to be most sensitive with joint configurations changes in the medial/lateral direction. Reserve actuation for all samples remained below 1 Nm. The most optimal deltoid normalized operating length was implemented by changing the joint configuration in the superior/inferior and medial/lateral directions. Current shoulder models focus on predicting muscle moment arms. Although valuable it does not allow me for active understanding of how lengthening the muscle will affect its ability to generate force. Our study provides an understanding of how muscle lengthening will affect the force generating capacity of each of the heads of the deltoid. With this information improvements can be made to the surgical placement and design of RTSA to improve functional/clinical outcomes while minimizing complications. For any figures or tables, please contact the authors directly.
Variation in pelvic tilt during postural changes may affect functional alignment. The primary objective of this study was to quantify the changes in lumbo-pelvic-femoral alignment from sitting to standing in patients undergoing THA. 144 patients were enrolled. Standing and sitting radiographs using the EOS imaging system were analyzed preoperatively and 1-year postoperatively. Pelvic incidence (PI), lumbar lordosis (LL), sacral slope (SS), proximal femoral angle (PFA) and spine/femoroacetabular flexion were determined. 38 patients had multilevel DDD (26%). Following THA, patients sat with increased anterior pelvic tilt demonstrated by a significant increase in sitting lumbar lordosis (28° preop vs 35° postop; p<0.01) and sacral slope (18° vs 23°; p<0.01). Following THA, patients flexed less through their spines (preop 26° vs postop 19°; p<0.01) and more through their hips (femoroacetabular flexion) (preop 60° vs postop 67°; p<0.01) to achieve sitting position. Patients with multilevel DDD sat with less spine flexion (normal 22° vs spine 13°; p<0.01), less change in sacral slope (more relative anterior tilt) (17° vs 9°; p<0.01), and more femoroacetabular flexion (64° vs 71°; p<0.01). For the majority of patients after THA, a larger proportion of lumbo-pelvic-femoral flexion necessary to achieve a sitting position is derived from femoroacetabular flexion with an associated increase in anterior pelvic tilt and a decrease in lumbar spine flexion. These changes are more pronounced among patients with multilevel DDD. Surgeons may consider orienting the acetabular component with greater anteversion and inclination in patients identified preoperatively to have anterior pelvic tilt or significant DDD.
