Telemetric knee implants have provided invaluable insight into the forces occurring in the knee during various activities. However, due to the high amount of cost involved only a few of them have been developed. Mathematical modeling of the knee provides an alternative that can be easily applied to study high number of patients. However, in order to ensure accuracy these models need to be validated with in vivo force data. Previously, mathematical models have been developed and validated to study only specific activities. Therefore, the objective of this study was compare the knee force predictions from the same model with that obtained using telemetry for multiple activities. Kinematics of a telemetric patient was collected using fluoroscopy and 2D to 3D image registration for gait, deep knee bend (DKB), chair rise, step up and step down activities. Along with telemetric forces obtained from the implant, synchronized ground reaction forces (GRF) were also collected from a force plate. The relevant kinematics and the GRF were input into an inverse dynamic model of the human leg starting from the foot and ending at the pelvis (Figure 1). All major ligaments and muscles affecting the knee joint were included in the model. The pelvis and the foot were incorporated into the system so as to provide realistic boundary conditions at the hip and the ankle and also to provide reference geometry for the attachment sites of relevant muscles. The muscle redundancy problem was solved using the pseudo-inverse technique which has been shown to automatically optimize muscle forces based on the Crowninshield-Brand cost function. The same model, without any additional changes, was applied for all activities and the predicted knee force results were compared with the data obtained from telemetry. Comparison of the model predictions for the tibiofemoral contact forces with the telemetric implant data revealed a high degree of correlation both in the nature of variation of forces and the magnitudes of the forces obtained. Interestingly, the model predicted forces with a high level of accuracy for activities in which the flexion of the knee do not vary monotonically (increases and decreases or vice-versa) with the activity cycle (gait, step up and step down). During these activities, the difference between the model predictions with the telemetric data was less than 5% (Figure 2). For activities where flexion varies monotonically (either increases or decreases) with activity (DKB and chair rise) the difference between the forces was less than 10% (Figure 3). The results from this study show that inverse dynamic computational models of the knee can be robust enough to predict forces occurring at the knee with a high amount of accuracy for multiple activities. While this study was conducted only on one patient with a telemetric implant, the required inputs to the model are generic enough so that it is applicable for any TKA patient with the mobility to conduct the desired activity. This allows kinetic data to be provided for the improvement of implant design and surgical techniques accessibly and relatively inexpensively

Introduction. Current methodologies for designing and validating existing THA systems can be expensive and time-consuming. A validated mathematical model provides an alternative solution with immediate predictions of contact mechanics and an understanding of potential adverse effects. The objective of this study is to demonstrate the value of a validated forward solution mathematical model of the hip that can offer kinematic results similar to fluoroscopy and forces similar to telemetric implants. Methods. This model is a forward solution dynamic model of the hip that incorporates the muscles at the hip, the hip capsule, and the ability to modify implant position, orientation, and surgical technique. Muscle forces are simulated to drive the motion, and a unique contact detection algorithm allows for virtual implantation of components in any orientation. Patient-specific data was input into the model for a telemetric subject and for a fluoroscopic subject. Results. For both stance and swing phase, the model predicted similar patterns and magnitudes compared to telemetry (forces) and fluoroscopy (kinematics). During stance phase, the model predicts 2.5 xBW of maximum hip force while telemetry predicts 2.3 xBW, yielding 8.7% error (Figure 1a). During swing phase, the model predicts 1.1 xBW maximum hip force, similar to telemetry (Figure 1b). During stance phase, the model predicts 1.3mm of hip separation (sliding) compared to 1.6mm for fluoroscopy, yielding 18.8% error (Figure 1c). During swing phase, the model predicts 1.9mm of separation compared to 1.7mm for fluoroscopy, yielding 11.8% error (Figure 1d). The model was also used to assess component placement, version, and optimal positioning compared to live surgery, producing very promising results. Conclusion. The model has proven accurate in predicting kinematics and forces. Therefore, forward solution mathematical modeling can be used to efficiently evaluate new component designs, positioning and technique differences, patient-specific scenarios, and any specific contribution towards THA outcomes that cannot be controlled in vivo. For any figures or tables, please contact the authors directly

Introduction. While fluoroscopic techniques have been widely utilized to study in vivo kinematic behavior of total knee arthroplasties, determination of the contact forces of large population sizes has proven a challenge to the biomedical engineering community. This investigation utilizes computational modeling to predict these forces and validates these with independent telemetric data for multiple patients, implants, and activities. Methods. Two patients with telemetric implants, the first of which was studied twice with the reexamination occurring 8 years after the first, were studied. Three-dimensional models of the patients' bones were segmented from CT and aligned with the design models of the telemetric implants. Fluoroscopy was collected for gait, deep knee bend, chair rise, and stair activities while being synchronized to the ground reaction force (GRF) plate, telemetric forces, knee flexion angles, electromyography (EMG), and vibration sensors. Registration of the implants and bones to the 2-D fluoroscopy provided the 6 degree of freedom kinematic data for each object. Orientation and position of the components, the GRFs, ligament properties, and muscle attachment locations were the only inputs to the Kane's dynamics inverse solution. Dynamic contact mapping and pseudo-inverse solution method were incorporated to output the predicted muscle forces of the vastus lateralis, rectus femoris, vastus medialis, biceps femoris long head, and gastrocnemius and contact forces at the patellofemoral and medial and lateral tibiofemoral. While every major muscle of the lower limb was incorporated into the model, these five were used in the validation process. EMG signals were processed to determine the neural excitation, muscle activation, and using the dynamic muscle length from the kinematics, the tension generated by these muscles. Results. Comparison of the model predictions for the tibiofemoral contact forces with the telemetric implant data resulted in an error <10% for all patients and activities. Predicted muscle forces were <15% error from the EMG calculated forces. Discussion. An inverse computational model of the knee robust enough to encompass multiple patients and activities was successfully created and validated. The accuracy of the muscle forces demonstrates that the model correctly simulates anatomical motion and not just transferal of GRFs. While this study was conducted on patients with telemetric implants, the required inputs to the model can be obtained from any TKA patient with the mobility to conduct the desired activity. This allows not only kinematic data, but also kinetics, to be provided for the improvement of implant design and surgical techniques accessibly and relatively inexpensively

Introduction:. There is substantial range in kinematics and joint loading in the total knee arthroplasty (TKA) patient population. Prospective TKA designs should be evaluated across the spectrum of loading conditions observed in vivo. Recent research has implanted telemetric tibial trays into TKA patients and measured loads at the tibiofemoral (TF) joint [1]. However, the number of patients for which telemetric data is available is limited and restricts the variability in loading conditions to a small subset of those which may be encountered in vivo. However, there is a substantial amount of fluoroscopic data available from numerous TKA patients and component designs [2]. The purpose of this study was to develop computational simulations which incorporate population-based variability in loading conditions derived from in vivo fluoroscopy, for eventual use in computational as well as experimental activity models. Methods:. Fluoroscopic kinematic data was obtained during squat for several patients with fixed bearing and rotating platform (RP) components. Anterior-posterior (A-P) and internal-external (I-E) motions of the TF joint were extracted from full extension to maximum flexion. Joint compressive loading was estimated using an inverse-dynamics approach. Previously-developed computational models of the knee, lower limb, and Kansas knee simulator were virtually implanted with the same design as the fluoroscopy patients. A control system was integrated with the computational models such that external loading at the hip and ankle were determined in order to reproduce the measured in vivo motions and compressive load (Fig. 1). Accuracy of the model in matching the in vivo motions was assessed, in addition to the resulting joint A-P and I-E loading. The external loading determined for a broader range of patients can subsequently be utilized in a force-controlled simulation to assess the robustness of implant concepts to patient loading variability. The applicability of this work as a comparative tool was illustrated by assessing the kinematics of two PS RP designs under three patient-specific loading conditions. Results:. External hip and ankle loading conditions were determined for each computational model that reproduced in vivo A-P, I-E and flexion-extension joint motions and estimated compressive load. For example, RMS accuracy of 0.4 mm, 0.2° and 0.7° were achieved for A-P, I-E and flexion, respectively (Fig. 1, 2). There was good agreement in both trend and magnitude of joint loads predicted from the externally-loaded models compared to telemetric measurements. Comparative analysis of two designs under multiple loading conditions illustrated variability in joint mechanics as a result of design factors and variation between subjects for the same design (Fig. 3). Discussion:. Pre-clinical evaluation of new devices under physiological joint loading conditions is crucial to robust functionality across the TKA population. The loads applied to a TKA system will affect fixation, wear, and functional performance. Harnessing in vivo kinematic data to develop population-based loading profiles will facilitate development of a platform for comprehensive design-phase evaluation of prospective designs. In addition, loading conditions for experimental simulators can be developed in order to test new devices under the range of variability likely to be encountered in vivo

PROBLEM. Since the COVID-19 pandemic of 2020, there has been a marked rise in the use of telemedicine to evaluate patients following total knee arthroplasty (TKA). Telemedicine is helpful to maintain patient contact, but it cannot provide objective functional TKA data. External monitoring devices can be used, but in the past have had mixed results due to patient compliance and data continuity, particularly for monitoring over numerous years. This novel stem is a translational product with an embedded sensor that can remotely monitor patient activity following TKA. SOLUTION. The Canturio™ TE∗ System (Canary Medical) functions structurally as a tibial extension for the Persona® cemented tibial plate (Zimmer Biomet). The stem is instrumented with internal motion sensors (3-D accelerometer and gyroscope) and telemetry that collects and transmits kinematic data. Raw data is converted by analytics into clinically relevant gait metrics using a proprietary algorithm. The Canturio™ TE∗ will monitor the patient's gait daily for the first year and then with lower frequency thereafter to conserve battery power enabling the potential for 20 years of longitudinal data collection and analysis. A base station in the OR activates the device and links the stem and data to the patient. A base station in the patient's home collects and uploads data to the Cloud Based Canary Data Management Platform (Canary Medical). The Canary Cloud is structured as an FDA regulated and HIPPA-compliant database with cybersecurity protocols integrated into the architecture. A third base station is an accessory used in the health care professional's office to perform an on-demand gait analysis of a patient. A dashboard allows the health care professional and patient to monitor objective data of the patient's activity and progress post treatment. MARKET. The early target market for this device includes total joint surgeons who are early adopters of technology and currently utilize technology in their practice. The kinematic data provided by the Canturio™ TE∗ System will enable clinicians to augment patient care by reviewing their objective gait metrics. In the future, this data has the potential to be integrated with other Zimmer Biomet technologies, such as the Rosa™ Knee robotic platform, mymobility™, and sensored devices like iAssist™, to provide the surgeon with a complete pre-surgical functional assessment, intraoperative data, and post-operative functional data. PRODUCT. Persona IQ will be the combination of the proven Persona personalized total knee system with the Canary Medical Canturio™ TE∗. TIMING AND FUNDING. The Canturio™ TE is currently under De Novo FDA review for market clearance; it is not yet available for commercial distribution. The plan is to launch the product in 2021 pending regulatory De Novo grant. This effort is a partnership between Zimmer Biomet and Canary Medical. ∗ The Canturio™ - TE is currently under De Novo FDA review for market clearance; it is not yet available for commercial distribution

Introduction. Previous research defines the existence of a “safe zone” (SZ) pertaining to acetabular cup implantation during total hip arthroplasty (THA). It is believed that if the cup is implanted at 40°±10° inclination and 15°±10° anteversion, risk of dislocation is reduced. However, recent studies have documented that even when the acetabular cup is placed within the SZ, high incidence dislocation and instability remains due to the combination of patient-specific configuration, cup diameter, head size, and surgical approach. The SZ only investigates the angular orientation of the cup, ignoring translational location. Translational location of the cup can cause a mismatch between anatomical hip center and implanted cup center, which has not been widely explored. Objective. The objective of this study is to define a zone within which the implanted joint center can be altered with respect to the anatomical joint center but will not increase the likelihood of post-operative hip separation or dislocation. Methods. A theoretical forward solution hip model, previously validated by telemetric devices and fluoroscopy data of existing implants, was used for analysis. The model allows for modifications of implant geometries/placement and soft tissue resection to simulate various surgical conditions. For the baseline simulation, the cup center was matched to the anatomical hip joint center, calculated as the center of the best fit sphere mapping the acetabulum, and the orientation of the cup was 40°/15° (inclination/anteversion). Keeping cup orientation the same, the location of the cup was moved in 1 mm increments in all directions to identify the region where a mismatch between the two centers did not lead to separation or instability in the joint. Results. During both swing and stance phase, when the acetabular cup was placed within the optimal conic with a slant height of 5±1 mm, no hip instability or dislocation risk occurred. As the acetabular cup was translated to the boundary of the optimal conic, hip instability increased. When the acetabular cup was placed at the boundary of the optimal conic, up to 2 mm of hip separation in the lateral direction occurred during swing phase, resulting in a decrease in contact area and an increase in contact stress. As the cup was placed outside the optimal conic, severe edge loading and hip separation up to 3.5 mm occurred during swing phase. In general, this resulted in large increases in cup stress, resulting in increased risk of wear leading to early complications. Discussion. This study introduces the concept of an optimal conic in the hip joint space to reduce the incidence of dislocation and hip instability after THA. Placing the cup center within the optimal conic reduces hip instability. Moving the cup further from the anatomical hip center increases the occurrence of hip instability. Cup placement within the optimal conic and angular SZ can lead to better postoperative outcomes. For any figures or tables, please contact authors directly

Introduction. Aseptic loosening is one of the highest causes for revision in total knee arthroplasty (TKA). With growing interest in anatomically aligned (AA) TKA, it is important to understand if this surgical technique affects cemented tibial fixation any differently than mechanical alignment (MA). Previous studies have shown that lipid/marrow infiltration (LMI) during implantation may significantly reduce fixation of tibial implants to bone analogs [1]. This study aims to investigate the effect of surgical alignment on fixation failure load after physiological loading. Methods. Alignment specific physiological loading was determined using telemetric tibial implant data from Orthoload [2] and applying it to a validated finite element lower limb model developed by the University of Denver [3]. Two high demand activities were selected for the loading section of this study: step down (SD) and deep knee bend (DKB). Using the lower limb model, hip and ankle external boundary conditions were applied to the ATTUNE. ®. knee system for both MA and AA techniques. The 6 degree of freedom kinetics and kinematics for each activity were then extracted from the model for each alignment type. Mechanical alignment (MA) was considered to be neutral alignment (0° Hip Knee Ankle Angle (HKA), 0° Joint Line (JL)) and AA was chosen to be 3° varus HKA, 5° JL. It is important not to exceed the limits of safety when using AA as such it is noted that DePuy Synthes recommends staying within 3º varus HKA and 3º JL. The use of 5º JL was used in this study to account for surgical variation [Depuy-Synthes surgical technique DSUS/JRC/0617/2179]. Following a similar method described by Maag et al [1] ATTUNE tibial implants were cemented into a bone analog with 2 mL of bone marrow in the distal cavity and an additional reservoir of lipid adjacent to the posterior edge of the implant. Tibial implant constructs were then subjected to intra-operative ROM/stability evaluation, followed by a hyperextension activity until 15 minutes of cement curing time, and finally 3 additional ROM/stability evaluations were performed using an AMTI VIVO simulator. The alignment specific loading parameters were then applied to the tibial implants using an AMTI VIVO simulator. Each sample was subjected to 50,000 DKB cycles and 120,000 SD cycles at 0.8 Hz in series; approximating 2 years of physiological activity. After physiological loading the samples were tested for fixation failure load by axial pull off. Results. Following alignment specific physiological loading the average fixation pull-off load for MA was 3289 ± 400 N and for AA was 3378 ± 133 N (Figure 1). There was no statistically significant difference fixation failure load by axial pull-off between the two alignment types (p=0.740). Conclusion. This study indicated that anatomic alignment, as defined with the alignment limits of this study, does not adversely affect the fixation failure load of ATTUNE tibial implants. For any figures or tables, please contact the authors directly

Introduction. Infections affect 1–3% of Total Knee Arthroplasty (TKA) patients with severe ramifications to mobility. Unfortunately, reinfection rates are high (∼15%) suggesting improved diagnostics are required. A common strategy to treat TKA infection in North America is the two-stage revision procedure involving the installation of a temporary spacer in the joint while the infection is treated for 6–12 weeks before permanent revision. Subdermal temperature increases during infection by 1–4°C providing a potential indicator for when the infection has been cleared. We propose an implantable temperature sensor integrated into a tibial spacer for telemetric use. We hypothesized that suitable sensing performance for infection monitoring regarding precision and relative accuracy can be attained using a low power, compact, analog sensor with <0.1ºC resolution. Materials & Methods. An experimental sensor was selected for our implanted application due to its extremely low (9 μA) current draw and compact chip package. Based upon dynamic range it was determined that the analog/digital converter must be a minimum of 11 bits to deliver suitable (<0.1ºC) resolution. A 12-bit ADC equipped microcontroller was selected. The MCP9808 (Microchip Technology, Chandler, AZ, USA) delivers manufacturer characterized thermal data in decimal strings through serial communication to the same microcontroller. The rated accuracy of the MCP9808 sensors in the required temperature range is max/typ +/− 0.5/0.25ºC with a precision of +/− 0.05ºC delivered at a resolution of 0.0625ºC. Within a thermally insulated chamber with a resistive heating element, the following experiment was conducted: Using empirical plant modelling tools, simulation and implementation an effective PI control scheme was implemented to create a highly precise temperature chamber. With MCP9808 as reference, the temperature in the thermal chamber was driven to 20 different temperatures between 35 and 40ºC for 10 minutes each and sampled at 5 Hz. This trial was repeated three times over three days. Transient data was discarded so as only to evaluate the steady state characteristics, wavelet denoising was applied, and a regression between the reference MCP9808 temperature response vs the experimental sensor intended for implantation was tabulated in Matlab. Results. Compared to reference values, the experimental temperature sensor displayed relative accuracy of +/− 0.275ºC (with 95% confidence) and precision of +/−0.135ºC over a 35–40ºC range as determined over 190,212 relevant samples. Note that in practice, the precision is independent of reference, but the absolute accuracy is relative to the gold standard's accuracy. Conclusion. Infection frequently results in permanent mobility issues in the context of total knee arthroplasty. This has led to an ongoing call for better treatments. Analysis suggests that the proposed experimental sensor offers high precision and reasonable relative accuracy in temperature sensing, substantially tighter than the expected stimulus from infection, while also offering desirable characteristics for implantation. This sensing platform will be integrated into an instrumented tibial spacer in future work. For any figures or tables, please contact authors directly

Summary. The mathematical model has proven to be highly accurate in measuring leg length before and after surgery to determine how leg length effects hip joint mechanics. Introduction. Leg length discrepancy (LLD) has been proven to be one of the most concerning problems associated with total hip arthroplasty (THA). Long-term follow-up studies have documented the presence of LLD having direct correlation with patient dissatisfaction, dislocation, back pain, and early complications. Several researchers sought to minimize limb length discrepancy based on pre-operative radiological templating or intra-operative measurements. While often being a common occurrence in clinical practice to compensate for LLD intra-operatively, the center of rotation of the hip joint has often changes unintentionally due to excessive reaming. Therefore, the clinical importance of LLD is still difficult to solve and remains a concern for clinicians. Objective. The objective of this study is two-fold: (1) use a validated forward-solution hip model to theoretically analyze the effects of LLD, gaining better understanding of mechanisms leading to early complication of THA and poor patient satisfaction and (2) to investigate the effect of the altered center of rotation of the hip joint regardless LLD compensation. Methods. The theoretical mathematical model used in this study has been previously validated using fluoroscopic results from existing implant designs and telemetric devices. The model can be used to theoretically investigate various surgical alignments, approaches, and procedures. In this study, we analyzed LLD and the effects of the altered center of rotation regardless of LLD compensation surgeons made. The simulations were conducted in both swing and stance phase of gait. Results. During swing phase, leg shortening lead to loosening of the hip capsular ligaments and subsequently, variable kinematic patterns. The momentum of the lower leg increased to levels where the ligaments could not properly constrain the hip leading to the femoral head sliding from within the acetabular cup (Figure 1). This piston motion led to decreased contact area and increased contact stress within the cup. Leg lengthening did not yield femoral head sliding but increased joint tension and contact stress. A tight hip may be an influential factor leading to back pain and poor patient satisfaction. During stance phase, leg shortening caused femoral head sliding leading to decreased contact area and an increase in contact stress. Leg lengthening caused an increase in capsular ligaments tension leading to higher stress in the hip joint (Figure 2). Interestingly, when the acetabular cup was superiorized and the surgeon compensated for LLD, thus matching the pre-operative leg length by increasing the neck length of the femoral implant, the contact forces and stresses were marginally increased at heel strike (Figure 3). Conclusion and Discussion. Altering the leg length during surgery can lead to higher contact forces and contact stresses due to tightening the hip joint or increasing likelihood of hip joint separation. Leg shortening often lead to higher stress within the joint. Further assessment must be conducted to develop tools that surgeons can use to ensure post-operative leg length is similar to the pre-operative condition. For any figures or tables, please contact authors directly

Currently, hip implant designs are evaluated experimentally using mechanical simulators or cadavers, and total hip arthroplasty (THA) postoperative outcomes are evaluated clinically using long-term follow-up. However, these evaluation techniques can be both costly and time-consuming. Neither can provide an assessment of post-operative results at the onset of implant development. More recently, a forward-solution mathematical model was developed that functions as theoretical joint simulator, providing instant feedback to designers and surgeons alike. This model has been validated by comparing the model predictions with kinematic results from fluoroscopy for both implanted and non-implanted hips and kinetics from a telemetric hip. The model allows surgical technique modifications and implant component placement under in vivo conditions. The objective of this study was to further expand the capabilities of the model to function as an intraoperative virtual surgical tool (Figure 1). This new module allows the surgeon to simulate surgery, then predict, compare, and optimize postoperative THA outcomes based on component placement, sizing choices, reaming and cutting locations, and surgical methods. This virtual surgery tool simulates the quadriceps, hamstring, gluteus, iliopsoas, tensor fasciae latae, and an adductor muscle groups, as well as the hip capsular ligament groups. The model can simulate resecting, weakening, loosening, or tightening of soft tissues based on surgical techniques. Additionally, the model can analyze a variety of activities, including gait and deep flexion activities. Initially, the virtual surgery module offers theoretical surgery tools that allow surgeons to alter surgical alignments, component designs, offsets, as well as reaming and cutting simulations. The virtual model incorporates a built-in CT scan bone database which will assist in determining muscle and ligament attachment sites as well as bony landmarks. The virtual model can be used to assist in the placement of both the femoral component and the acetabular cup (Figure 2). Moreover, once the surgeon has decided on the placements of the components, they can use the simulation capabilities to run virtual human body maneuvers based on the chosen parameters. The simulations will reveal force, contact stress, and motion predictions of the hip joint (Figure 3). The surgeon can then choose to modify the positions accordingly or proceed with the surgery. This new virtual surgical tool will allow surgeons to gain a better understanding of possible post-operative outcomes under pre-operative conditions or intra-operatively. Simulations using the virtual surgery model has revealed that improper component placement may lead to non-ideal post-operative function, which has been simulated using the model. Further evaluation is ongoing so that this new module can reveal more information pre-operatively, allowing a surgeon to gain ample information before surgery, especially with difficult and revision cases

During the preoperative examination, surgeons determine whether a patient, with a degenerative hip, is a candidate for total hip arthroplasty (THA). Although research studies have been conducted to investigate in vivo kinematics of degenerative hips using fluoroscopy, surgeons do not have assessment tools they can use in their practice to further understand patient assessment. Ideally, if a surgeon could have a theoretical tool that efficiently allows for predictive post-operative assessment after virtual surgery and implantation, they would have a better understanding of joint conditions before surgery. The objectives of this study were (1) to use a validated forward solution hip model to theoretically predict the in vivo kinematics of degenerative hip joints, gaining a better understanding joint conditions leading to THA and (2) compare the predicted kinematic patterns with those derived using fluoroscopy for each subject. A theoretical model, previously evaluated using THA kinematics and telemetry, was used for this study, incorporating numerous muscles and ligaments, including the quadriceps, hamstring, gluteus, iliopsoas, tensor fasciae latae, an adductor muscle groups, and hip capsular ligaments. Ten subjects having a pre-operative degenerative hip were asked to perform gait while under surveillance using a mobile fluoroscopy unit. The hip joint kinematics for ten subjects were initially assessed using in vivo fluoroscopy, and then compared to the predicted kinematics determined using the model. Further evaluations were then conducted varying implanted component position to assess variability. The fluoroscopic evaluation revealed that 33% of the degenerative hips experienced abnormal hip kinematics known as “hip separation” where the femoral head slides within the acetabulum, resulting in a decrease in contact area. Interestingly, the mathematical model produced similar kinematic profiles, where the femoral head was sliding within the acetabulum (Figure 1). During swing phase, it was determined that this femoral head sliding (FHS) is caused by hip capsular laxity resulting in reducing joint tension. At the point of maximum velocity of the foot, the momentum of the lower leg becomes too great for capsule to properly constrain the hip, leading to the femoral component pistoning outwards. During stance phase, kinematics of degenerative hips were similar to kinematics of a THA subject with mal-positioning of the acetabular cup. Further evaluation revealed that if the cup was placed at a position other than its native, anatomical center, abnormal forces and torques acting within the joint lead to the femoral component sliding within the acetabular cup. It was hypothesized that in degenerative hips, similar to THA, the altered center of rotation is a leading influence of FHS (Figure 2). The theoretical model has now been validated for subjects having a THA and degenerative subjects. The model has successfully derived kinematic patterns similar to subjects evaluated using fluoroscopy. The results in this study revealed that altering the native joint center is the most influential factor leading to FHS, or more commonly known as hip separation. A new module for the mathematical model is being implemented to simulate virtual surgery so that the surgery can pre- operatively plan and then simulate post-operative results

Introduction. Aseptic loosening of total knee replacements is a leading cause for revision. It is known that micromotion has an influence on the loosening of cemented implants though it is not yet well understood what the effect of repeated physiological loading has on the micromotion between implants and cement mantle. This study aims to investigate effect of physiological loading on the stability of tibial implants previously subjected to simulated intra-operative lipid/marrow infiltration. Methods. Three commercially available fixed bearing tibial implant designs were investigated in this study: ATTUNE. ®. , PFC SIGMA. ®. CoCr, ATTUNE. ®. S+. The implant designs were first prepared using a LMI implantation process. Following the method described by Maag et al tibial implants were cemented in a bone analog with 2 mL of bone marrow in the distal cavity and an additional reservoir of lipid adjacent to the posterior edge of the implant. The samples were subjected to intra- operative range of motion (ROM)/stability evaluation using an AMTI VIVO simulator, then a hyperextension activity until 15 minutes of cement cure time, and finally 3 additional ROM/stability evaluations were performed. Implant specific physiological loading was determined using telemetric tibial implant data from Orthoload and applying it to a validated FE lower limb model developed by the University of Denver. Two high demand activities were selected for the loading section of this study: step down (SD) and deep knee bend (DKB). Using the above model, 6 degree of freedom kinetics and kinematics for each activity was determined for each posterior stabilized implant design. Prior to loading, the 3-D motion between tibial implant and bone analog (micromotion) was measured using an ARAMIS Digital Image Correlation (DIC) system. Measurement was taken during the simulated DKB at 0.25Hz using an AMTI VIVO simulator while the DIC system captured images at a frame rate of 10Hz. The GOM software calculated the distance between reference point markers applied to the posterior implant and foam bone. A Matlab program calculated maximum micromotion within each DKB cycle and averaged that value across five cycles. The implant specific loading parameters were then applied to the three tibial implant designs. Using an AMTI VIVO simulator each sample was subjected to 50,000 DKB and 120,000 SD cycles at 0.8Hz in series; equating to approximately 2 years of physiological activity. Following loading, micromotion was measured using the same method as above. Results. Initial micomotion measurements during DKB activity for ATTUNE. ®. , PFC SIGMA. ®. CoCr, ATTUNE. ®. S+ were 155µm, 246µm, and 104µm, respectively, and following physiological loading were 159µm, 264µm, and 112µm, respectively. While there was statistical significance between the micromotion of implant designs (p<0.05), there was no significance between before and after loading. Conclusion. This study shows there is no significant change in micromotion after approximately 2 years of physiological loading. However, there is a significant difference in micromotion between implant designs

Background. In vivo fluoroscopic studies have proven that femoral head sliding and separation from within the acetabular cup during gait frequently occur for subjects implanted with a total hip arthroplasty. It is hypothesized that these atypical kinematic patterns are due to component malalignments that yield uncharacteristically higher forces on the hip joint that are not present in the native hip. This in vivo joint instability can lead to edge loading, increased stresses, and premature wear on the acetabular component. Objective. The objective of this study was to use forward solution mathematical modeling to theoretically analyze the causes and effects of hip joint instability and edge loading during both swing and stance phase of gait. Methods. The model used for this study simulates the quadriceps muscles, hamstring muscles, gluteus muscles, iliopsoas group, tensor fasciae latae, and an adductor muscle group. Other soft tissues include the patellar ligament and the ischiofemoral, iliofemoral, and pubofemoral hip capsular ligaments. The model was previously validated using telemetric implants and fluoroscopic results from existing implant designs. The model was used to simulate theoretical surgeries where various surgical alignments were implemented and to determine the hip joint stability. Parameters of interest in this study are joint instability and femoral head sliding within the acetabular cup, along with contact area, contact forces, contact stresses, and ligament tension. Results. During swing phase, it was determined that femoral head pistoning is caused by hip capsule laxity resulting from improperly positioned components and reduced joint tension. At the point of maximum velocity of the foot (approximately halfway through), the momentum of the lower leg becomes too great for a lax capsule to properly constrain the hip, leading to the femoral component pistoning outwards. This pistoning motion, leading to separation, is coupled with a decrease in contact area and an impulse-like spike in contact stress (Figure 1). During stance phase, it was determined that femoral head sliding within the acetabular cup is caused by the proprioceptive notion that the human hip wants to rotate about its native, anatomical center. Thus, component shifting yields abnormal forces and torques on the joint, leading to the femoral component sliding within the cup. This phenomenon of sliding yields acetabular edge-loading on the supero-lateral aspect of the cup (Figure 2). It is also clear that joint sliding yields a decreased contact area, in this case over half of the stable contact area, corresponding to a predicted increase in contact stress, in this case over double (Figure 2). Discussion. From our current analysis, the causes and effects of hip joint instability are clearly demonstrated. The increased stress that accompanies the pistoning/impulse loading scenarios during swing phase and the supero-lateral edge-loading scenarios during stance phase provide clear explanations for premature component wear on the cup, and thus the importance of proper alignment of the THA components is essential for a maximum THA lifetime. For any figures or tables, please contact authors directly

Background. Extensive research has previously been conducted analyzing the biomechanical effects of rotational changes (i.e. version and inclination) of the acetabular cup. Many sources, citing diverse dislocation statistics, encourage surgeons to strive for various “safe zones” during the THA operation. However, minimal research has been conducted, especially under in vivo conditions, to assess the consequences of cup translational shifting (i.e. offsets, medial and superior reaming, etc.). While it is often the practice to medialize the acetabular cup intraoperatively, there is still a lack of information regarding the biomechanical consequences of such cup medializations and medial/superior malpositionings. Objective. Therefore, the objective of this study is to use a validated forward solution mathematical model to vary cup positioning in both the medial and superior directions to assess simulated in vivo kinematics. Methods. The model used for this study has been validated with telemetric data and incorporates numerous muscles and ligaments. The model is parametrically derived and allows the user to simulate a theoretical THA surgery and to assess the outcomes of proper positioning as well as malpositioning of the cup. Parameters of interest in this study are component positions, joint instability and sliding, and contact area. Results. An intraoperative representation of the pelvis and cup was assessed (Figure 1), with a green star showing the native anatomical center, the red circle showing the acetabular cup center, and the arrow representing the reaming direction. During swing phase, it was determined that unaccounted for acetabular cup shifting of 5–10 mm leads to capsular ligament laxity coupled with an increase in hip joint instability. Two swing phase scenarios were assessed, one simulating adequate capsular tension and therefore a uniform contact patch and the other simulating inadequate capsule tension and therefore femoral component pistoning with a smaller contact patch (Figure 2). During stance phase, it was determined that acetabular cup shifting of 5–10 mm in the medial and/or superior directions yields an increase in hip joint instability. Two stance phase scenarios were simulated, one yielding no hip separation and therefore a uniform, centralized contact patch, and the other yielding ∼1.5 mm of hip separation and therefore a non-uniform, supero-lateral edge loading patch (Figure 3). Cup orientation does not appear to directly cause hip instability, but it will either lessen or exacerbate the instability, depending on the specific scenario. The results in this study did reveal that overly-inclined cups will yield less stability in the lateral direction, and overly-anteverted cups will yield less stability in the anterior direction. Discussion. In general, instability during stance phase comes in the form of femoral head sliding and edge loading, and instability during swing phase comes in the form of femoral head pistoning. This study's analyses did reveal that proper alignment of the acetabular cup is required for ideal clinical results. The results from this study dictate that proper translational alignment of the cup as well as rotational alignment is necessary for patient stability and proper hip mechanics. For any figures or tables, please contact authors directly

Background. Currently, hip implant designs are evaluated experimentally using mechanical simulators or cadavers, and total hip arthroplasty (THA) postoperative outcomes are evaluated clinically using long-term follow-up. However, these evaluation techniques can be both costly and time-consuming. Fortunately, forward solution mathematical models can function as theoretical joint simulators, providing instant feedback to designers and surgeons alike. Recently, a validated forward solution model of the hip has been developed that can theoretically simulate new implant designs and surgical technique modifications under in vivo conditions. Objective. The objective of this study was to expand the use of this hip model to function as an intraoperative virtual implant tool, thereby allowing surgeons to predict, compare, and optimize postoperative THA outcomes based on component placement, sizing choices, reaming and cutting locations, and surgical methods. Methods. The math model simulates the quadriceps muscles, hamstring muscles, gluteus muscles, iliopsoas muscles, tensor fasciae latae, and an adductor muscle group, as well as the ischiofemoral, iliofemoral, and pubofemoral hip capsular ligaments. The model can simulate resecting, weakening, loosening, or tightening of soft tissues based on surgical techniques. Additionally, the model can analyze a variety of activities, both weight-bearing and non-, including swing and stance phase of gait, deep knee bend, and more. The model was previously validated using telemetric implants and fluoroscopic results from existing implant designs. Results. First, the model tool has capabilities that will allow surgeons to pre- or intra-operatively experiment with various surgical alignments, component designs, sizes, and offsets, as well as reaming and cutting locations. The model tool will incorporate a built-in CT scan bone database which will assist in determining muscle and ligament attachment sites as well as bony landmarks. The model tool can be used to assist in the placement of both the femoral component (Figure 1) and the acetabular cup (Figure 2). Moreover, once the surgeon has decided on the placements of the components, he or she can use the modelling capabilities of the tool to run virtual simulations based on the chosen parameters. The simulations will reveal force and motion predictions of the hip joint based on the current component positioning (Figure 3). The surgeon can then choose to modify the positions accordingly or proceed with the surgery. Discussion. Being able to intraoperatively predict postoperative mechanics will improve the functional outcomes of total hip arthroplasty and reduce the frequency of postoperative complications

Background. While not common in the native hip, occurrences of femoral head separation from the acetabular cup during gait are well documented after total hip arthroplasty. Although the effects of this phenomenon are not well understood, we hypothesize that these atypical kinematics are due to component misalignments that yield uncharacteristic forces on the hip joint that are not present in the native hip. Objective. The objective of this study was to theoretically predict the causes of hip separation during stance phase using forward solution mathematical modelling. Methods. The model simulates the quadriceps muscles, hamstring muscles, gluteus muscles, iliopsoas group, tensor fasciae latae, and an adductor muscle group. Other soft tissues include the patellar ligament and the ischiofemoral, iliofemoral, and pubofemoral hip capsular ligaments. The model was previously validated using telemetric implants and fluoroscopic results from existing implant designs. The model is currently being used to analyze the effects that various surgical alignments have on hip separation. Specifically, this study analyzed 4 different hypothetical patients under the same 87 alignment conditions during stance phase. Alignment conditions include anatomical component alignment, intended acetabular cup medial and superior shifts, unintended cup medial and superior reaming errors, variations in cup version angles, leg length discrepancies, and femoral component offset modifications. Results. During stance phase, it was determined that acetabular cup placement had a much more substantial effect on hip separation than femoral component placement. While neither femoral offset nor leg length discrepancy showed a correlation to hip separation, both medial and superior shifting of the acetabular cup showed a positive trend with increased hip separation. Figure 1 shows a comparison of average hip separation with intended shifts in the cup (0mm, 2mm, or 5mm) plus unintended reaming errors (0mm to 10mm extra) Furthermore, larger intended shifts in cup placement yielded smaller margins of error (Figure 2). Observe in Figure 2 how an increase in the size of the blue region (intended shifting region) correlates to a decrease in size of the green region (allowable error region where hip separation will not occur). It was also determined that cup version angles have less of a defined effect on hip separation, as the relationship between angular position and hip separation varied between patients. Discussion. From our current analysis, the importance of proper alignment of the acetabular cup can be clearly seen. Overall, it has been shown that reaming errors of as low as 2 mm can yield separation magnitudes up to 2 mm (and potentially greater)

Introduction. Alignment of the acetabular cup and femoral components directly affects hip joint loading and potential for impingement and dislocation following total hip arthroplasty (THA) [1]. Changes to the lines of action and moment generating capabilities of the muscles as a result of component position may influence overall patient function. The objectives of this study were to assess the effect of component placement on hip joint contact forces (JCFs) and muscle forces during a high demand step down task and to identify important alignment parameters using a probabilistic approach. Methods. Three patients following THA (2 M: 28.3±2.8 BMI; 1 F: 25.7 BMI) performed lower extremity maximum isometric strength tests and a step down task as part of a larger IRB-approved study. Patient-specific musculoskeletal models were created by scaling a model with detailed hip musculature [2] to patient segment dimensions and mass. For each model, muscle maximum isometric strengths were optimized to minimize differences between model-predicted and measured preoperative maximum isometric joint torques at the hip and knee. Baseline simulations used patient-specific models with corresponding measured kinematics and ground reaction forces to predict hip JCFs and muscle forces using static optimization. To assess the combined effects of stem and cup position and orientation, a 1000 trial Monte Carlo simulation was performed with input variability in each degree of freedom based on the ±1 SD range in component placement relative to native geometry reported by Tsai et al. [3] (Figure 1). Maximum confidence bounds (1–99%) were predicted for the hip JCF magnitude and muscle forces for three prime muscles involved in the task (gluteus medius, gluteus minimus and psoas). HJC confidence bounds were compared to Orthoload measurements from telemetric implants from 6 patients performing the step down task. Sensitivity of hip JCF and muscle force outputs was quantified by Pearson Product-Moment correlation between the input parameter and the value of each output averaged across four points in the cycle. Results. Variation in the placement of the stem and cup produced an average maximum confidence bound (1–99%) in hip JCF of 277.7±91.1N and forces of 259.4±58.3N in the gluteus medius for all three patients (Figure 2). Sensitivity to cup and stem placement varied among the three patients; however, in general, hip JCFs were more sensitive to the position of the stem than the cup (Figure 3). Hip JCF was most sensitive to stem anteversion (0.64±0.10) and the superior/inferior stem position (0.42±0.19). Discussion. Variation in stem anteversion and medial/lateral cup position contributed the largest amount of variability in hip JCF and muscle forces during a step down task. The probabilistic analysis characterized bounds for output parameters, considering interactions between alignment parameters. Alignments that avoid increases in JCF and muscle loading during high demand tasks may lead to earlier recovery of function, by reducing muscle fatigue and the need to develop compensatory movement patterns. Acknowledgements. This research was supported in part by DePuy-Synthes

INTRODUCTION. Cementless tibial trays commonly fail through failure of fixation due to excessive interface motion. However, the specific combination of axial and shear forces precipitating implant failure is unknown. This has led to generic loading profiles approximating walking to perform pre-clinical assessment of new designs, even though telemetric data demonstrates that much larger forces and moments are generated during other functional activities. This study was undertaken to test the hypotheses: (i) interface motion of cementless tibial trays varies as a function of specific activities, and (ii) the response of the cementless tibial interface to walking loading is not representative of other functional activities. MATERIALS and METHODS. Six fresh-frozen cadaveric tibias were tested using a custom designed functional activity simulator after implantation of a posterior stabilized total knee replacement (NexGen LPS, Zimmer, Warsaw IN). Activity scenarios were selected using force (Fx, Fy, Fz) and moment (Mx, My, Mz) data from patients with instrumented tibial trays (E-tibia) published by Bergmann et al. A pattern of black and white spray paint was applied to the surface of the specimen including the tibial tray and bone. Each specimen was preconditioned through application of a vertical load of 1050N for 500 cycles of flexion-extension from 5–100°. Following preconditioning, each tibia was loaded using e-tibia values of forces and moments for walking, stair-descent, and sit-to-stand activities. The differential motion of the tibial tray and the adjacent bony surface was monitored using digital image correlation (DIC) (resolution: 1–2 microns in plane; 3–4 microns out-of-plane). Four pairs of stereo-images of the tray and tibial bone were prepared at sites around the circumference of the construct in both the loaded and unloaded conditions: (i) before and after pre-conditioning and (ii) before and after the 6 functional loading profiles. The images were processed to provide circumferential measurements of interface motion during loading. Differences in micromotion and migration were evaluated statistically using step-wise multivariate regression. RESULTS. The average 3D motion of the tibial tray varied extensively with the loading conditions corresponding to the different activities (Figs 1,2). The largest 3D motion was seen during the first peak of stair descent (86.6±8.0µm) and the first peak of walking (83.1±10.2µm; p=0.5516), both of which were characterized by large adduction moments (18.5 and 19.1Nm respectively). The differences between 3D micromotion of all other pairs of activities were statistically significant (p<0.0001 to p=0.0127). Each of the 6 loading scenarios simulated elicited a different combination of components of implant displacement at the cementless interface. The largest differences in interface motion were observed between the first peak of walking and all of the other loading modes with reversal of the direction of the SI (p=0.3828), AP (p<0.0001) and ML (p<0.0001) components of tray displacement (Figs. 2,3). CONCLUSIONS. 1. Magnitude and direction of interface motion between the tibia and a cementless tibial tray vary with specific loading patterns. 2. Interface motion observed during loading conditions representative of walking are not indicative of the stability of cementless implant fixation when exposed to loading conditions generated by other activities. For figures/tables, please contact authors directly.

Introduction. Realistic in-vivo loads on knee implants from telemetric analyses were recently published. Impacting an implant, especially a ceramic one, will produce high peak stresses within the component. Data for loads occurring during implantation of a knee implant are scarce. To ensure a safe impaction of ceramic tibial trays the stresses caused by it need to be known. Materials and Methods. Impaction testing including force measurements (using Kistler piezo load cell 9351B) was performed on a ceramic tibial tray. The same test was simulated by computational analysis using FEM (Finite-Element-Method). Because the forces measured and those calculated by FEM were significantly different, an in vitro impaction study was performed to obtain realistic loads for a ceramic tibial tray. A surgeon was asked to perform heavy hammer blows which may occur during implantation. Using a high speed camera (phantom V7.2) the velocity of the hammer at the time of impaction was determined. Using this parameter instrumented ceramic tibial trays (BPK-S Knee, P. Brehm) were implanted into a biomechanical Sawbones® model. Linear strain gauges were attached to the four fins of the tibial tray as these are the regions of highest stresses. Simulating the surgeon's highest impacts measurements were conducted at a frequency of 1 MHz. The identical hammer was used in this in vitro study and the velocity of the hammer was measured by using the same high speed camera. To investigate the damping effect of bone cement Palacos®R bone cement was used. Only worst-case impacts within the range achieved by the surgeon were applied to evaluate the stress distribution within the ceramic tibial tray. Results. Impaction forces determined from the FEM were significantly higher compared to the force measurements. Therefore the verification by the measured impaction forces failed. Simulating worst-case impacts which may occur during implantation of a tibial tray resulted in hammer velocities within a range of 4.7 m/s to 6.7 m/s. Applying these impacts to instrumented tibial trays high peak stresses similar to those determined by the FEM were observed within the implant. Using bone cement as a realistic approach and damping material stresses decreased significantly but still remained at a high level. Discussion. For extremely high dynamic loads such as the impaction of implants verification of FEM with physical force measurements may not be possible. To achieve reliable values of the stress state within the implant strain gauge measurements are the most appropriate way to evaluate the stress distribution. Although the viscosity of the cement reduces the stress values significantly, the stresses still remained at a considerably high level. Data from more surgeons is needed to improve the quality of the loading estimation (range of hammer velocity) and thus to improve the reliability of the stress evaluation

Introduction. Currently, knee and hip implants are evaluated experimentally using mechanical simulators or clinically using long-term follow-up. Unfortunately, it is not practical to mechanically evaluate all patient and surgical variables and predict the viability of implant success and/or performance. More recently, a validated mathematical model has been developed that can theoretically simulate new implant designs under in vivo conditions to predict joint forces kinematics and performance. Therefore, the objective of this study was to use a validated forward solution model (FSM) to evaluate new and existing implant designs, predicting mechanics of the hip and knee joints. Methods. The model simulates the four quadriceps muscles, the complete hamstring muscle group, all three gluteus muscles, iliopsoas group, tensor fasciae latae, and an adductor muscle group. Other soft tissues include the patellar ligament, MCL, LCL, PCL, ACL, multiple ligaments connecting the patella to the femur, and the primary hip capsular ligaments (ischiofemoral, iliofemoral, and pubofemoral). The model was previously validated using telemetric implants and fluoroscopic results and is now being used to analyze multiple implant geometries. Virtual implantation allows for various surgical alignments to determine the effect of surgical errors. Furthermore, the model can simulate resecting, weakening, or tightening of soft tissues based on surgical errors or technique modifications. Results. The model revealed PCL weakening leads to paradoxical anterior slide of both femoral condyles. This paradoxical slide reduces maximum flexion and increases knee forces as seen in TKA fluoroscopic studies. Cam/post kinematics in posterior-stabilized designs were also analyzed, revealing cam/post forces increasing linearly with flexion. While cam/post engagement should ideally occur superiorly on the post and move inferiorly throughout knee flexion, fluoroscopy documented implants contacting inferiorly and rolling superiorly with flexion. Thus, a theoretical new implant was simulated to overcome this problem such that TKA design would experience the desired motion, yielding inferior contact in later flexion when forces approach 1.0 × BW. At the hip, the model predicts maximum compressive hip forces of 1.5–2.5 xBW throughout stance phase of gait. The model determines how this force is distributed on the femoral head and acetabular cup throughout the entire activity, allowing wear patterns on implant components to be predicted. During stance phase, the model predicts posterior-to-anterior sliding of the femoral head, with larger magnitudes of motion occurring on the supero-lateral aspect of the cup. The model can predict femoral neck impingement on the acetabular cup and shows that excessive anteversion of the cup leads to the femoral component levering away from the acetabular cup, yielding up to 2.0 mm of hip separation. Conclusions. This study demonstrates the ability of an in-vivo data based forward solution model to evaluate the impact of variation upon implant forces, motion and performance. This will improve understanding of observations such as polyethylene wear, pain associated with excessive soft-tissue forces, subluxation and dislocation, among others. Ultimately, the model could become a theoretical simulator that could evaluate implants much quicker for longer time durations, be less costly and provide comparative analyses when compared to present day experimental simulators