Trabecular bone transmits loads to the cortical shell and is therefore most active in bone remodeling. This remodeling alters trabecular material strength thereby changing the bending stiffness. Accounting for trabecular material heterogeneity has been shown to improve empirical-µFEM correlations by allowing for more realistic trabecular bending stiffness. In µFEMs to reduce computation time, region averaging is often used to scale image resolution. However, region averaging not only alters trabecular architecture, but inherently alters the CT-intensity of each trabeculae. The effect of CT-intensity variations on computationally derived apparent modulus (Eapp) in heterogenous µFEMs has not been discussed. The objectives of this study were to compare trabecular Eapp among i) hexahedral and tetrahedral µFEMs, ii) µFEMs generated from 32 µm, 64 µm, and 64 µm down-sampled from 32 µm µ-CT scans, and iii) µFEMs with homogeneous and heterogeneous tissue moduli. Fourteen cadaveric scapulae (7 male; 7 female) were micro-CT scanned at two spatial resolutions (32 µm & 64 µm). Virtual bone cores were extracted from the glenoid vault, maintaining a 2:1 aspect ratio, to create µFEMs from the 32 µm, 64 µm, and down-sampled 64 µm scans. Custom code was used to generate µFEMs with 8-node hexahedral elements (HEX8), while maintaining the bone volume fraction (BV/TV) of each HEX8 32 µm model (BV/TV=0.24±0.10). Each virtual core was also generated as a 10-node tetrahedral (TET10) µFEM. All µFEMs were given either a homogeneous tissue modulus of 20 GPa, or a heterogeneous tissue modulus scaled by CT-intensity. All FEMs were constrained with identical boundary conditions and compressed to 0.5% apparent strain. The apparent modulus of each model was compared.Introduction
Methods
Mechanical property relationships used in the computational modeling of bones are most often derived using mechanical testing of normal cadaveric bone. However, a significant percentage of patients undergoing joint arthroplasties exhibit some form of pathologic bone disease, such as osteoarthritis. As such, the objective of this study was to compare the micro-architecture and apparent modulus (Eapp) of humeral trabecular bone in normal cadaveric specimens and bone extracted from patients undergoing total shoulder arthroplasty. Micro-CT scans were acquired at 20 µm spatial resolution for humeral heads from non-pathologic cadavers (n=12) and patients undergoing total shoulder arthroplasty (n=10). Virtual cylindrical cores were extracted along the medial-lateral direction. Custom-code was used to generate micro finite element models (µFEMs) with hexahedral elements. Each µFEM was assigned either a homogeneous tissue modulus of 20 GPa or a heterogeneous tissue modulus scaled by CT- intensity. Simulated compression to 0.5% apparent strain was performed in the medial-lateral direction. Morphometric parameters and apparent modulus-bone volume fraction relationships were compared between groups.Introduction
Methods
The Walch Type B2 glenoid has the hallmark features of posteroinferior glenoid erosion, retroversion, and posterior humeral head subluxation. Although our understanding of the pathoanatomy of bone loss and its evolution in Type B's has improved, the etiology remains unclear. Furthermore, the morphology of the humerus in Walch B types has not been studied. The purpose of this imaging based anthropometric study was to examine the humeral torsion in Walch Type B2 shoulders. We hypothesized that there would be a compensatory decrease in humeral retroversion in Walch B2 glenoids. Three-dimensional models of the full length humerus were generated from computed tomography data of normal cadaveric (n = 59) and Walch Type B shoulders (n = 59). An anatomical coordinate system referencing the medial and lateral epicondyles was created for each model. A simulated humeral head osteotomy plane was created and used to determine humeral version relative to the epicondylar axis and the head-neck angle. Measurements were repeated by two experienced fellowship-trained shoulder surgeons to determine inter-rater reliability. Glenoid parameters (version, inclination and 2D critical shoulder angle) and posterior humeral head subluxation were calculated in the Type B group to determine the pathologic glenohumeral relationship. Two-way ANOVAs compared group and sex within humeral version and head-neck angle, and intra-class correlation coefficients (ICCs) with a 2-way random effects model and absolute agreement were used for inter-rater reliability.Introduction
Methods
Density-modulus relationships are often used to map the mechanical properties of bone based on CT- intensity in finite element models (FEMs). Although these relationships are thought to be site-specific, relationships developed for alternative anatomic locations are often used regardless of bone being modeled. Six relationships are commonly used in finite element studies of the shoulder; however, the accuracy of these relationships have yet to be compared. This study compares each of these six relationships ability to predict apparent strain energy density (SEDapp) in trabecular bone cores from the glenoid. Quantitative-CT (QCT) (0.625 mm isotropic voxels), and µ-CT scans (0.032 mm isotropic voxels) were obtained for fourteen cadaveric scapulae (7 male, 7 female). Micro finite element models (µ-FEMs) were created from 98 virtual ‘cores’ using direct conversion to hexahedral elements. Two µ-FEM cases were considered: homogeneous tissue modulus of 20 GPa, and heterogeneous tissue modulus scaled by CT intensity of the µ-CT images (196 models). Each µ- FEM model was compressively loaded to 0.5% apparent strain and apparent strain energy density (SEDapp) was calculated. Additionally, each of the six density-modulus relationships were used to map heterogeneous material properties to co- registered QCT-derived models (588 models in total). The loading and boundary conditions were replicated in the QCT-FEMs and the SEDapp was calculated and compared to the µ-FEM SEDapp. To account for more samples than donors, restricted maximum likelihood estimation (REML) linear regression compared µ-FEM SEDapp and QCT-FEM SEDapp for each relationship.Introduction
Methods
