Modification of Humeral Component Results in Increased Impingement Free Range of Motion in a Reverse Shoulder Arthroplasty Model.

Introduction: Shoulder arthroplasties have been demonstrated to provide reliable pain relief as well as functional benefits. The advent of the reverse shoulder arthroplasty allowed for expanded indications for shoulder replacement. Several studies comparing the outcomes of anatomic and reverse total shoulder arthroplasties have demonstrated decreased range of motion in the reverse arthroplasty cohort, especially in internal rotation. The authors hypothesized that slight modifications to the humeral component of a reverse shoulder arthroplasty could result in increased impingement free range of motion without significant sacrifices to stability. Methods: A reverse shoulder arthroplasty model was fashioned to mimic a setting of anterior mechanical impingement after replacement. Sequential resections were taken from the anterior aspect of the polyethylene up to a resection of 10 mm. A solid modeling software was utilized to compare the experimental group to the control group with regard to impingement free motion. Finite element analysis was subsequently utilized to assess stability of the construct in comparison to the nonmodified polyethylene. Results: Impingement free internal rotation increased minimally at 3 mm of resection but considerably at each further increase in resection. A resection of 10 mm resulted roughly 30% improvement in impingement free internal rotation. Instability in this model increased with modifications beyond 7 mm. Conclusion: Slight alterations to the geometry of the humeral tray and polyethene components can result in improvements in impingement-free internal rotation without substantial increased instability in this model. Further work is needed to determine in vivo implications of modifications to the humeral tray and polyethylene.

Pulsatile Pressure Delivery of Continuous-Flow Left Ventricular Assist Devices Is Markedly Reduced Relative to Heart Failure Patients.

Although continuous-flow left ventricular assist devices (CF-LVADs) provide an augmentation in systemic perfusion, there is a scarcity of in vivo data regarding systemic pulsatility on support. Patients supported on CF-LVAD therapy (n = 71) who underwent combined left/right catheterization ramp study were included. Aortic pulsatility was defined by the pulsatile power index (PPI), which was also calculated in a cohort of high-output heart failure (HOHF, n = 66) and standard HF cohort (n = 44). PPI was drastically lower in CF-LVAD-supported patients with median PPI of 0.006 (interquartile range [IQR], 0.002-0.012) compared with PPI in the HF population at 0.09 (IQR, 0.06-0.17) or HOHF population at 0.25 (IQR, 0.13-0.37; p < 0.0001 among groups). With speed augmentation during ramp, PPI values fell quickly in patients with higher PPI at baseline. PPI correlated poorly with left ventricular ejection fraction (LVEF) in all groups. In CF-LVAD patients, there was a stronger correlation with LV dP/dt (r = 0.41; p = 0.001) than LVEF (r = 0.21; p = 0.08; pint < 0.001). CF-LVAD support is associated with a dramatic reduction in arterial pulsatility as measured by PPI relative to HOHF and HF cohorts and decreases with speed. Further work is needed to determine the applicability to the next generation of device therapy.

Evidence-based aerosol clearance times in a healthcare environment.

BACKGROUND: As researchers race to understand the nature of COVID-19 transmission, healthcare institutions must treat COVID-19 patients while also safeguarding the health of staff and other patients. One aspect of this process involves mitigating aerosol transmission of the SARS-CoV2 virus. The U.S. Centers for Disease Control and Prevention (CDC) provides general guidance on airborne contaminant removal, but directly measuring aerosol clearance in clinical rooms provides empirical evidence to guide clinical procedure. AIM: We present a risk-assessment approach to empirically measuring and certifying the aerosol clearance time (ACT) in operating and procedure rooms to improve hospital efficiency while also mitigating the risk of nosocomial infection. METHODS: Rooms were clustered based on physical and procedural parameters. Sample rooms from each cluster were randomly selected and tested by challenging the room with aerosol and monitoring aerosolized particle concentration until 99.9% clearance was achieved. Data quality was analysed and aerosol clearance times for each cluster were determined. FINDINGS: Of the 521 operating and procedure rooms considered, 449 (86%) were issued a decrease in clearance time relative to CDC guidance, 32 (6%) had their clearance times increased, and 40 (8%) remained at guidance. The average clearance time change of all rooms assessed was a net reduction of 27.8%. CONCLUSION: The process described here balances the need for high-quality, repeatable data with the burden of testing in a functioning clinical setting. Implementation of this approach resulted in a reduction in clearance times for most clinical rooms, thereby improving hospital efficiency while also safeguarding patients and staff.

Factors associated with proximal femur fracture determined in a large cadaveric cohort.

Many researchers have used cadaveric fracture tests to determine the relationship between proximal femur (hip) fracture strength and a multitude of possible explanatory variables, typically considered one or two at a time. These variables include subject-specific proximal femur variables such as femoral neck areal bone mineral density (aBMD), sex, age, and geometry, as well as physiological hip fracture event variables such as fall speed and angle of impact. However, to our knowledge, no study has included all of these variables simultaneously in the same experimental dataset. To address this gap, the present study simultaneously included all of these subject-specific and fracture event variables in multivariate models to understand their contributions to femoral strength and fracture type. The primary aim of this study was to determine not only whether each of these variables contributed to the prediction of femoral strength, but also to determine the relative importance of each variable in strength prediction. A secondary aim was to similarly characterize the importance of these variables for the prediction of fracture type. To accomplish these aims, we characterized 197 proximal femurs (covering a wide range of subject-specific variables) with DXA and CT scans, and then tested the femurs to fracture in a sideways fall on the hip configuration. Each femur was tested using one of three fall speed conditions and one of four angles of impact (bone orientations). During each test, we acquired measurements of relevant force and displacement data. We then reduced the test data to determine femoral strength, and we used post-fracture CT scans to classify the fracture type (e.g., trochanteric, cervical). Using these results, the explanatory variables were analyzed with mixed statistical models to explain variations in hip fracture strength and fracture type, respectively. Five explanatory variables were statistically significant in explaining the variability in femoral strength: aBMD, sex, age, fall speed, and neck-shaft angle (P ≤ 0.0135). These five variables, including significant interactions, explained 80% of the variability in hip fracture strength. Additionally, when only aBMD, sex, and age (P < 0.0001) were considered in the model, again including significant interactions, these three variables alone explained 79% of the variability in hip fracture strength. So while fall speed (P = 0.0135) and neck-shaft angle (P = 0.0041) were statistically significant, the inclusion of these variables did not appreciably improve the prediction of hip fracture strength compared to the model that considered only aBMD, sex and age. For the variables we included in this study, in the ranges we considered, our findings indicate that the clinically-available information of patient age, sex and aBMD are sufficient for femoral strength assessment. These findings also suggest that there is little value in the extra effort required to characterize the effect of femoral geometry on strength, or to account for the probabilistic nature of fall-related factors such as fall speed and angle of impact. For fracture type, the only explanatory variable found to be significant was aBMD (P ≤ 0.0099). We found that the odds of having intertrochanteric fractures increased by 47% when aBMD decreased by one standard deviation (0.2 g/cm2).

A Method to Estimate Cadaveric Femur Cortical Strains During Fracture Testing Using Digital Image Correlation.

This protocol describes the method using digital image correlation to estimate cortical strain from high speed video images of the cadaveric femoral surface obtained from mechanical testing. This optical method requires a texture of many contrasting fiduciary marks on a solid white background for accurate tracking of surface deformation as loading is applied to the specimen. Immediately prior to testing, the surface of interest in the camera view is painted with a water-based white primer and allowed to dry for several minutes. Then, a black paint is speckled carefully over the white background with special consideration for the even size and shape of the droplets. Illumination is carefully designed and set such that there is optimal contrast of these marks while minimizing reflections through the use of filters. Images were obtained through high speed video capture at up to 12,000 frames/s. The key images prior to and including the fracture event are extracted and deformations are estimated between successive frames in carefully sized interrogation windows over a specified region of interest. These deformations are then used to compute surface strain temporally during the fracture test. The strain data is very useful for identifying fracture initiation within the femur, and for eventual validation of proximal femur fracture strength models derived from Quantitative Computed Tomography-based Finite Element Analysis (QCT/FEA).

Method and Instrumented Fixture for Femoral Fracture Testing in a Sideways Fall-on-the-Hip Position.

Mechanical testing of femora brings valuable insights into understanding the contribution of clinically-measureable variables such as bone mineral density distribution and geometry on the femoral mechanical properties. Currently, there is no standard protocol for mechanical testing of such geometrically complex bones to measure strength, and stiffness. To address this gap we have developed a protocol to test cadaveric femora to fracture and to measure their biomechanical parameters. This protocol describes a set of adaptable fixtures to accommodate the various load magnitudes and directions accounting for possible bone orientations in a fall on the hip configuration, test speed, bone size, and left leg-right leg variations. The femora were prepared for testing by cleaning, cutting, scanning, and potting the distal end and greater trochanter contact surfaces in poly(methyl methacrylate) (PMMA) as presented in a different protocol. The prepared specimens were placed in the testing fixture in a position mimicking a sideways fall on the hip and loaded to fracture. During testing, two load cells measured vertical forces applied to the femoral head and greater trochanter, a six-axis load cell measured forces and moments at the distal femoral shaft, and a displacement sensor measured differential displacement between the femoral head and trochanter contact supports. High speed video cameras were used to synchronously record the sequence of fracture events during testing. The reduction of this data allowed us to characterize the strength, stiffness, and fracture energy for nearly 200 osteoporotic, osteopenic, and normal cadaveric femora for further development of engineering-based diagnostic tools for osteoporosis research.

Are DXA/aBMD and QCT/FEA Stiffness and Strength Estimates Sensitive to Sex and Age?

Dual X-ray absorptiometry (DXA) measures areal bone mineral density (aBMD) by simplifying a complex 3D bone structure to a 2D projection and is not equally effective for explaining fracture strength in women and men. Unlike DXA, subject-specific quantitative computed tomography-based finite element analysis (QCT/FEA) estimates fracture strength using 3D bone mineral distribution and geometry. By using experimentally-measured femoral stiffness and strength from a one hundred sample cadaveric cohort that included variations in sex and age, we wanted to determine if QCT/FEA estimates were able to better predict the experimental variations than DXA/aBMD. For each femur, DXA/aBMD was assessed and a QCT/FEA model was developed to estimate femoral stiffness and strength. Then, the femur was mechanically tested to fracture in a sideways fall on the hip position to measure stiffness and strength. DXA/aBMD and QCT/FEA estimates were compared for their sensitivity to sex and age with multivariate statistical analyses. When comparing the measured data with DXA/aBMD predictions, both age and sex were significant (p ≤ 0.0398) for both femoral stiffness and strength. However, QCT/FEA predictions of stiffness and strength showed sex was insignificant (p ≥ 0.23). Age was still significant (p ≤ 0.0072). These results indicate that QCT/FEA, unlike DXA/aBMD, accounted for bone differences due to sex.

Proximal Cadaveric Femur Preparation for Fracture Strength Testing and Quantitative CT-based Finite Element Analysis.

Cadaveric fracture testing is routinely used to understand factors that affect proximal femur strength. Because ex vivo biological tissues are prone to lose their mechanical properties over time, specimen preparation for experimental testing must be performed carefully to obtain reliable results that represent in vivo conditions. For that reason, we designed a protocol and a set of fixtures to prepare the femoral specimens such that their mechanical properties experienced minimal changes. The femora were kept in a frozen state except during preparation steps and mechanical testing. The relevant clinical measures of total hip and femoral neck bone mineral density (BMD) were obtained with a clinical dual X-ray absorptiometry (DXA) bone densitometer, and the 3D geometry and distribution of bone mineral were obtained using CT with a calibration phantom for quantitative estimations based on the greyscale values. Any possible bone disease, fracture, or the presence of implants or artifacts affecting the bone structure, was ruled out with X-ray scans. For preparation, all bones were carefully cleaned of excess soft tissue, and were cut and potted at the internal rotation angle of interest. A cutting fixture allowed the distal end of the bone to be cut off leaving the proximal femur at a desired length. To allow positioning of the femoral neck at prescribed angles during later CT scanning and mechanical testing, the proximal femoral shafts were potted in polymethylmethacrylate (PMMA) using a fixture designed specifically for desired orientations. The data collected from our experiments were then used for validation of quantitative computed tomography (QCT)-based finite element analysis (FEA), as described in a different protocol. In this manuscript, we present the protocol for the precise bone preparation for mechanical testing and subsequent QCT/FEA modeling. The current protocol was successfully applied to prepare about 200 cadaveric femora over a 6-year time period.

A method for accounting for test fixture compliance when estimating proximal femur stiffness.

Fracture testing of cadaveric femora to obtain strength and stiffness information is an active area of research in developing tools for diagnostic prediction of bone strength. These measurements are often used in the estimation and validation of companion finite element models constructed from the femora CT scan data, therefore, the accuracy of the data is of paramount importance. However, experimental stiffness calculated from force-displacement data has largely been ignored by most researchers due to inherent error in the differential displacement measurement obtained when not accounting for testing apparatus compliance. However, having such information is necessary for validation of computational models. Even in the few cases when fixture compliance was considered the measurements showed large lab-to-lab variation due to lack of standardization in fixture design. We examined the compliance of our in-house designed cadaveric femur test fixture to determine the errors we could expect when calculating stiffness from the collected experimental force-displacement data and determined the stiffness of the test fixture to be more than 10 times the stiffness of the stiffest femur in a sample of 44 femora. When correcting the apparent femur stiffness derived from the original data, we found that the largest stiffness was underestimated by about 10%. The study confirmed that considering test fixture compliance is a necessary step in improving the accuracy of fracture test data for characterizing femur stiffness, and highlighted the need for test fixture design standardization for proximal femur fracture testing.

QCT/FEA predictions of femoral stiffness are strongly affected by boundary condition modeling.

Quantitative computed tomography-based finite element models of proximal femora must be validated with cadaveric experiments before using them to assess fracture risk in osteoporotic patients. During validation, it is essential to carefully assess whether the boundary condition (BC) modeling matches the experimental conditions. This study evaluated proximal femur stiffness results predicted by six different BC methods on a sample of 30 cadaveric femora and compared the predictions with experimental data. The average stiffness varied by 280% among the six BCs. Compared with experimental data, the predictions ranged from overestimating the average stiffness by 65% to underestimating it by 41%. In addition, we found that the BC that distributed the load to the contact surfaces similar to the expected contact mechanics predictions had the best agreement with experimental stiffness. We concluded that BC modeling introduced large variations in proximal femora stiffness predictions.

Intra-aneurysmal flow rates are reduced by two flow diverters: an experiment using tomographic particle image velocimetry in an aneurysm model.

BACKGROUND: Limitations on treating large, giant, and wide-necked aneurysms with coiling have made flow diverters a promising alternative to current practice by supporting reconstruction of the parent artery. OBJECTIVE: To assess the changes to fluid dynamics within an aneurysm by studying two different endoluminal flow diverters on a simple aneurysm model, using tomographic particle image velocimetry to determine which device would better minimize fluid flow into an aneurysm and observe any significant changes in aneurysm fluid structures. METHODS: Steady velocity fields of the model's aneurysm dome and neck were measured at three inlet velocities (18, 39, and 59 cm/s) for two flow diverter diameters with different porosities and compared against a baseline case with no flow diverter. RESULTS: In the baseline case a large vortex was present inside the dome for all flow rates. However, both devices eliminated this main vortex at all flow rates and reduced the peak aneurysmal velocities by about 90%. A strong correlation between flow diverter porosity and flow reduction was found. In each case the inflow to the aneurysm shifted from the distal neck to the mid- or proximal neck after flow diverter placement. CONCLUSIONS: Even with this relatively simple experimental setup, we were able to observe the major flow field changes, which occurred immediately after the deployment of each flow diverter. Limitations of the study included a simplified geometry and steady-state flow. Constraints included model making and limited availability of flow diverters.

Quantitative computed tomography-based finite element analysis predictions of femoral strength and stiffness depend on computed tomography settings.

The aim of the present study was to compare proximal femur strength and stiffness obtained experimentally with estimations from Finite Element Analysis (FEA) models derived from Quantitative Computed Tomography (QCT) scans acquired at two different scanner settings. QCT/FEA models could potentially aid in diagnosis and treatment of osteoporosis but several drawbacks still limit their predictive ability. One potential reason is that the models are still sensitive to scanner settings which could lead to changes in assigned material properties, thus limiting their results accuracy and clinical effectiveness. To find the mechanical properties we fracture tested 44 proximal femora in a sideways fall-on-the-hip configuration. Before testing, we CT scanned all femora twice, first at high resolution scanner settings, and second at low resolution scanner settings and built 88 QCT/FEA models of femoral strength and stiffness. The femoral set neck bone mineral density, as measured by DXA, uniformly covered the range from osteoporotic to normal. This study showed that the femoral strength and stiffness values predicted from high and low resolution scans were significantly different (p<0.0001). Strength estimated from high resolution QCT scans was larger for osteoporotic, but smaller for normal and osteopenic femora when compared to low resolution scans. In addition, stiffness estimated from high resolution scans was consistently larger than stiffness obtained from low resolution scans over the entire femoral dataset. While QCT/FEA techniques hold promise for use in clinical settings we provided evidence that further improvements are required to increase robustness in their predictive power under different scanner settings and modeling assumptions.