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Orthopaedic Proceedings
Vol. 100-B, Issue SUPP_5 | Pages 15 - 15
1 Apr 2018
Walker D Kinney A Banks S Wright T
Full Access

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.


Orthopaedic Proceedings
Vol. 100-B, Issue SUPP_5 | Pages 16 - 16
1 Apr 2018
Walker D Kinney A Banks S Wright T
Full Access

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 in vivo measured surgical placement to determine muscle normalized operating region for the anterior, lateral and posterior aspects of the deltoid muscle. The joint center was varied according to previous published work from the RTSA subject's nominal surgical position ±4 mm in the anterior/posterior direction, ±12mm in the medial/lateral direction, and −10 mm to 14 mm in the superior/inferior direction (Walker 2015 et al. Table 2).

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.


Orthopaedic Proceedings
Vol. 99-B, Issue SUPP_6 | Pages 74 - 74
1 Mar 2017
Walker D Kinney A Wright T Banks S
Full Access

Introduction

Current modeling techniques have been used to model the Reverse Total Shoulder Arthroplasty (RTSA) to account for the geometric changes implemented after RTSA [2,3]. Though these models have provided insight into the effects of geometric changes from RTSA these is still a limitation of understanding muscle function after RTSA on a patient-specific basis. The goal of this study sought to overcome this limitation by developing an approach to calibrate patient-specific muscle strength for an RTSA subject.

Methods

The approach was performed for both isometric 0° abduction and dynamic abduction. A 12 degree of freedom (DOF) model developed in our previous work was used in conjunction with our clinical data to create a set of patient-specific data (3 dimensional kinematics, muscle activations (), muscle moment arms, joint moments, muscle length, muscle velocity, tendon slack length (), optimal fiber length, peak isometric force)) that was used in a novel optimization scheme to estimate muscle parameters that correspond to the patient's muscle strength[4]. The optimization varied to minimize the difference between measured (“in vivo”) and predicted joint moments and measured (“in vivo”) and predicted muscle activations (). The predicted joint moments were constructed as a summation of muscle moments. The nested optimization was implemented within matlab (Mathworks). The optimization yields a set of muscle parameters that correspond to the subject's muscle strength. The abduction activity was optimized [4,5]. To validate the model we predicted dynamic joint moment and activation for the abduction activity (Figure 1).


Orthopaedic Proceedings
Vol. 99-B, Issue SUPP_6 | Pages 73 - 73
1 Mar 2017
Walker D Kinney A Wright T Banks S
Full Access

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 in vivo measured surgical placement to determine muscle activation and normalized operating region for the anterior, lateral and posterior aspects of the deltoid muscle. The joint center was varied from the RTSA subject's nominal surgical position ±4 mm in the anterior/posterior direction, ±12mm in the medial/lateral direction, and −10 mm to 14 mm in the superior/inferior direction.

Overall muscle activity varied over 1521 different implant configurations for the RTSA subject. For initial elevation the RTSA subject showed at least 25% deltoid activation sensitivity in each of the directions of joint configuration change(Figure 1). Posterior deltoid showed a maximal activation variation of 84% in the superior/inferior direction(Figure 1c). Deltoid activation variations lie primarily in the superior/inferior and anterior/posterior directions. An increasing trend was seen for the anterior, lateral and posterior deltoid outside of the discontinuity seen at 28°(Figure 1). Activation variations were compared to subject's experimental data. Reserve actuation for all samples remained below 4Nm(Figure 2). The most optimal deltoid normalized operating length was implemented by changing the joint configuration in the superior/inferior and medial/lateral directions(Figure 3).

Current shoulder models utilize cadaver information in their assessment of generic muscle strength. In adding to this literature we performed a sensitivity study to assess the effects of RTSA joint configurations on deltoid muscle performance in a single patient-specific model. For this patient we were able to assess the best joint configuration to improve the patients muscle function and ideally their clinical outcome. With this information improvements can be made to the surgical placement and design of RTSA on a patient-specific basis to improve functional/clinical outcomes while minimizing complications.

For any figures or tables, please contact authors directly (see Info & Metrics tab above).


Orthopaedic Proceedings
Vol. 98-B, Issue SUPP_10 | Pages 113 - 113
1 May 2016
Walker D Kinney A Wright T Banks S
Full Access

Modern musculoskeletal modeling techniques have been used to simulate shoulders with reverse total shoulder arthroplasty and study how geometric changes resulting from implant placement affect shoulder muscle moment arms. These studies do not, however, take into account how changes in muscle length will affect the force generating capacity of muscles in their post-operative state. The goal of this study was to develop and calibrate a patient-specific shoulder model for subjects with RTSA in order to predict muscle activation during dynamic activities.

Patient-specific muscle parameters were estimated using a nested optimization scheme calibrating the model to isometric arm abduction data at 0°, 45° and 90°. The model was validated by comparing predicted muscle activation for dynamic abduction to experimental electromyography recordings. A twelve-degree of freedom model was used with experimental measurements to create a set of patient-specific data (three-dimensional kinematics, muscle activations, muscle moment arms, joint moments, muscle lengths, muscle velocities, tendon slack lengths, optimal fiber lengths and peak isometric forces) estimating muscle parameters corresponding to each patient's measured strength. The optimization varied muscle parameters to minimize the difference between measured and estimated joint moments and muscle activations for isometric abduction trials. This optimization yields a set of patient-specific muscle parameters corresponding to the subject's own muscle strength that can be used to predict muscle activation and muscle lengths for a range of dynamic activities.

The model calibration/optimization procedure was performed on arm abduction data for a subject with reverse total shoulder arthroplasty. Muscle activation predicted by the model ranged between 3% and 90% of maximum. The maximum joint moment produced was 20 Nm. The model replicated measured joint moments accurately (R2 > 0.99). The optimized muscle parameter set produced feasible muscle moments and muscle activations for dynamic arm abduction, when calibrated using data from isometric force trials.

Current modeling techniques for the upper extremity focus primarily on geometric changes and their effects on shoulder muscle moment arms. In an effort to create patient-specific models, we have developed a framework to predict subject-specific muscle parameters. These estimated muscle parameters, in combination with patient-specific models that incorporate the patient's joint configurations, kinematics and bone anatomy, provide a framework to predict dynamic muscle activation in novel tasks and, for example, predict how joint center changes with reverse total shoulder arthroplasty may affect muscle function.


Orthopaedic Proceedings
Vol. 98-B, Issue SUPP_10 | Pages 115 - 115
1 May 2016
Walker D Kinney A Wright T Banks S
Full Access

Reverse total shoulder arthroplasty (RTSA) is an increasingly common treatment for osteoarthritic shoulders with irreparable rotator cuff tears. Although very successful in alleviating pain and restoring some function, there is little objective information relating geometric changes imposed by the reverse shoulder and arm function, particularly the moment generating capacity of the shoulder muscles. Recent modeling studies of reverse shoulders have shown significant variation in deltoid muscle moment arms over a typical range of humeral offset locations in shoulders with RTSA. The goal of this study was to investigate the sensitivity of muscle moment arms as a function of varying the joint center and humeral offset in three representative RTSA subjects that spanned the anatomical range from our previous study cohort. We hypothesized there may exist a more beneficial joint implant placement, measured by muscle moment arms, compared to the actual surgical implant configuration.

A 12 degree of freedom, subject-specific model was used to represent the shoulders of three patients with RTSA for whom fluoroscopic measurements of scapular and humeral kinematics during abduction had been obtained. The computer model used subject-specific in vivo abduction kinematics and systematically varied humeral offset locations over 1521 different perturbations from the surgical placement to determine moment arms for the anterior, lateral and posterior aspects of the deltoid muscle. The humeral offset was varied from its surgical position ±4 mm in the anterior/posterior direction, ±12mm in the medial/lateral direction, and −10 mm to 14 mm in the superior/inferior direction.

The anterior deltoid moment arm varied up to 20 mm with humeral offset and center of rotation variations, primarily in the medial/lateral and superior/inferior directions. Similarly, the lateral deltoid moment arm demonstrated variations up to 20 mm, primarily with humeral offset changes in the medial/lateral and anterior/posterior directions. The posterior deltoid moment arm varied up to 15mm, primarily in early abduction, and was most sensitive to changes of the humeral offset in the superior/inferior direction.

The goal of this study was to assess the sensitivity of the deltoid muscle moment arms as a function of joint configuration for existing RTSA subjects. High variations were found for all three deltoid components. Variation over the entire abduction arc was greatest in the anterior and lateral deltoid, while the posterior deltoid moment arm was mostly sensitive to humeral offset changes early in the abduction arc. Moment arm changes of 15–20 mm represent a significant amount of the total deltoid moment arm. This means there is an opportunity to dramatically change the deltoid moment arms through surgical placement of the joint center of rotation and humeral stem. Computational models of the shoulder may help surgeons optimize subject-specific placement of RTSA implants to provide the best possible muscle function, and assist implant designers to configure devices for the best overall performance.


Orthopaedic Proceedings
Vol. 98-B, Issue SUPP_10 | Pages 119 - 119
1 May 2016
Walker D Kinney A Wright T Banks S
Full Access

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 in vivo measured surgical placement to determine muscle activation and normalized operating region for the anterior, lateral and posterior aspects of the deltoid muscle. The joint center was varied from the RTSA subject's nominal surgical position ±4 mm in the anterior/posterior direction, ±12mm in the medial/lateral direction, and −10 mm to 14 mm in the superior/inferior direction.

Overall muscle activity varied over 1521 different implant configurations for the RTSA subject. For initial elevation the RTSA subject showed at least 25% deltoid activation sensitivity in each of the directions of joint configuration change(Figure 1A–C). Posterior deltoid showed a maximal activation variation of 84% in the superior/inferior direction(Figure 1C). Deltoid activation variations lie primarily in the superior/inferior and anterior/posterior directions(Figure 1). An increasing trend was seen for the anterior, lateral and posterior deltoid outside of the discontinuity seen at 28°(Figur 1A–C). Activation variations were compared to subject's experimental data (Figure 1). Reserve actuation for all samples remained below 4Nm. 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 utilize cadaver information in their assessment of generic muscle strength. In adding to this literature we performed a sensitivity study to assess the effects of RTSA joint configurations on deltoid muscle performance. With this information improvements can be made to the surgical placement and design of RTSA to improve functional/clinical outcomes while minimizing complications.


Orthopaedic Proceedings
Vol. 98-B, Issue SUPP_4 | Pages 105 - 105
1 Jan 2016
Walker D Kinney A Struk A Fregly B Wright T Banks S
Full Access

Reverse total shoulder arthroplasty (RTSA) is increasingly used in the United States since approval by the FDA in 2003. RTSA relieves pain and restores mobility in arthritic rotator cuff deficient shoulders. Though many advantages of RTSA have been demonstrated, there still are a variety of complications (implant loosening, shoulder impingement, infection, frozen shoulder) making apparent much still is to be learned how RTSA modifies normal shoulder function. The goal of this study was to assess how RTSA affects deltoid muscle moment generating capacity post-surgery using a subject-specific computational model driven by in vivo kinematic data.

A subject-specific 12 degree-of-freedom (DOF) musculoskeletal model was used to analyze the shoulders of 27 subjects (14-RTSA, 12-Normal). The model was modified from the work of Holzbaur et al. to directly input 6 DOF humerus and scapula kinematics obtained using fluoroscopy. Model geometry was scaled according to each subject's skeletal dimensions. In vivo abduction kinematics for each subject were input to their subject-specific model and muscle moment arms for the anterior, lateral and posterior aspects of the deltoid were measured over the arc of motion.

Similar patterns of muscle moment arm changes were observed for normal and RTSA shoulders. The moment arm of the anterior deltoid was positive with the arm at the side and decreased monotonically, crossing zero (the point at which the muscle fibers pass across the joint center) between 50°–60° glenohumeral abduction (Figure 1a). The average moment arm of the lateral deltoid was constant and positive in normal shoulders, but showed a decreasing trend with abduction in RTSA shoulders (Figure 1b). The posterior deltoid moment arm was negative with the arm at the side, and increased monotonically to a positive value with increasing glenohumeral abduction (Figure 1c). Subject-specific moment arm values for RTSA shoulders were highly variable compared to normal shoulders. 2-way repeated measures ANOVA showed significant differences between RTSA and normal shoulders for all three aspects of the deltoid moment arm, where the moment arms in RTSA shoulders were smaller in magnitude.

Shoulder functional capacity is a product of the moment generating ability of the shoulder muscles which, in turn, are a function of the muscle moment arms and muscle forces. Placement of implant components during RTSA can directly affect the geometric relationship between the humerus and scapula and, therefore, the muscle moment arms in the RTSA shoulder. Our results show RTSA shoulders maintain the same muscle moment arm patterns as healthy shoulders, but they show much greater inter-subject variation and smaller moment arm magnitudes. These observations show directly how RTSA configuration and implant placement affect deltoid moment arms, and provide an objective basis for determining optimal implant configuration and surgical placement to maximize RTSA function in a patient-specific manner.


Orthopaedic Proceedings
Vol. 98-B, Issue SUPP_4 | Pages 106 - 106
1 Jan 2016
Walker D Kinney A Struk A Fregly B Wright T Banks S
Full Access

Reverse total shoulder arthroplasty (RTSA) is an increasingly common treatment for osteoarthritic shoulders with irreparable rotator cuff tears. Although very successful in alleviating pain and restoring some function there is little objective information relating geometric changes imposed by the reverse shoulder and the moment generating capacity of the shoulder muscles. Recent modeling studies of reverse shoulders have shown significant variation in deltoid muscle moment arms over varied joint centers for shoulders with RTSA. The goal of this study was to investigate the sensitivity of muscle moment arms as a function of varying the joint center in one representative RTSA subject. We hypothesized there may exist a more beneficial joint implant placement, measured by muscle moment arms, compared to the actual surgical implant placement.

A 12 degree of freedom, subject-specific model was used to represent the shoulder of a patient with RTSA for whom fluoroscopic measurements of scapular and humeral kinematics during abduction had been obtained. The computer model used these abduction kinematics and systematically varied joint center locations over 1521 different perturbations from the surgical placement to determine moment arms for the anterior, lateral and posterior aspects of the deltoid muscle. The joint center was varied from its surgical position ±4 mm in the anterior/posterior direction, 0–24 mm in the medial/lateral direction, and −10 mm to 14 mm in the superior/inferior direction.

The anterior deltoid moment arm varied up to 16mm with center of rotations variations, primarily in the medial/lateral and superior/inferior directions (Figure 2, Table 1(Figure 1)). Similarly, the lateral deltoid moment arm demonstrated variations up to 13 mm, primarily with joint center changes in the anterior/posterior and superior/inferior directions. The posterior deltoid moment arm varied up to 10mm, primarily in early abduction, and was most sensitive to changes of the joint center in demonstrated a sensitivity of 6 mm corresponding to variations in the superior/inferior directions (Figure 2).

The goal of this study was to assess the sensitivity of the deltoid muscle moment arms as a function of joint configuration for an existing RTSA subject. High variations were found for all three deltoid components. Variation over the entire abduction arc was greatest in the anterior and lateral deltoid, while the posterior deltoid moment arm was mostly sensitive to joint center changes early in the abduction arc. Moment arm changes of 10–16mm represent a significant amount of the total deltoid moment arm. This means there is an opportunity to dramatically change the deltoid moments arms through surgical placement of the joint center of rotation. Computational models of the shoulder may help surgeons optimize subject-specific placement of RTSA implants to provide the best possible muscle function, and assist implant designers to configure devices for the best overall performance.


Orthopaedic Proceedings
Vol. 98-B, Issue SUPP_4 | Pages 108 - 108
1 Jan 2016
Walker D Kinney A Fregly B Wright T Banks S
Full Access

Current modeling techniques have been used to model the Reverse Total Shoulder Arthroplasty (RTSA) to account for the geometric changes implemented after RTSA. Though these models have provided insight into the effects of geometric changes from RTSA these is still a limitation of understanding muscle function after RTSA on a patient-specific basis. The goal of this study sought to overcome this limitation by developing an approach to calibrate patient-specific muscle strength for an RTSA subject.

The approach was performed for both isometric 0° abduction and dynamic abduction. A 12 degree of freedom (DOF) model developed in our previous work was used in conjunction with our clinical data to create a set of patient-specific data (3 dimensional kinematics, muscle activations, muscle moment arms, joint moments, muscle length, muscle velocity, tendon slack length, optimal fiber length, peak isometric force)) that was used in a novel optimization scheme to estimate muscle parameters that correspond to the patient's muscle strength[4]. The optimization varied to minimize the difference between measured(“in vivo”) and predicted joint moments and measured (“in vivo”) and predicted muscle activations. The predicted joint moments were constructed as a summation of muscle moments. The nested optimization was implemented within matlab (Mathworks). The optimization yields a set of muscle parameters that correspond to the subject's muscle strength. The abduction activity was optimized.

The maximum activation for the muscles within the model ranged between .03–2.4 (Figure 1). The maximum joint moment produced was 11 newton-meters. The joint moments were reproduced to an value of 1. Muscle parameters were calculated for both isometric and dynamic abduction (Figure 2). The muscle parameters produced provided a feasible solution to reproduce the joint moments seen “in vivo” (Figure 3).

Current modeling techniques of the upper extremity focus primarily on geometry. In efforts to create patient-specific models we have developed a framework to predict subject-specific strength characteristics. In order to fully understand muscle function we need muscle parameters that correspond to the subject's strength. This effort in conjunction with patient-specific models that incorporate the patient's joint configurations, kinematics and bone anatomy hopes to provide a framework to gain insight into muscle tensioning effects after RTSA. With this framework improvements can be made to the surgical implementation and design of RTSA to improve surgical outcomes.