Journal of the Mechanical Behavior of Biomedical Materials

The treatment of Achilles tendinopathy is challenging, as 40% of patients do not respond to the existing rehabilitation protocols. These rehabilitation protocols do not consider the individual differences in the Achilles tendon (AT) characteristics, which are crucial in creating the optimal strain environment that promotes healing. While previous research suggests an optimal strain for AT regeneration (6% tendon strains), it is still unclear if the current rehabilitation protocols meet this condition. Consequently, this study aimed to investigate the influence of a selection of rehabilitation exercises on strains in patients with Achilles tendinopathy using subject-specific finite element (FE) models of the free AT. Secondly, the study aimed to explain the influence of muscle forces and material properties on the AT strains. The 21 FE models of the AT included the following subject-specific features: geometry estimated from 3D freehand ultrasound images, Elastic modulus estimated from the experimental stress-strain curve, and muscle forces estimated using a combination of 3D motion capture and musculoskeletal modelling. These models were used to determine tendon strain magnitudes and distribution patterns in the mid-portion of the AT. The generalized ranking suggested a progression of exercises to gradually increase the strains in the mid-portion of the AT, starting from the concentric and eccentric exercises and going to more functional exercises, which impose a higher load on the AT: bilateral heel rise (0.031 {+/-} 0.010), bilateral heel drop (0.034 {+/-} 0.009), unilateral heel drop (0.066 {+/-} 0.023), walking (0.069 {+/-} 0.020), unilateral heel drop with flexed knee (0.078 {+/-} 0.023), and bilateral hopping (0.115 {+/-} 0.033). Unilateral heel drop and walking exercises were not significantly different and they both fell within the optimal strain range. However, when examining individual strains, it became evident that there was diversity in exercise rankings among participants, as well as exercises falling within the optimal strain range. Furthermore, the strains were influenced more by the subject-specific muscle forces compared to the material properties. Our study demonstrated the importance of tailored rehabilitation protocols that consider not only individual subject-specific morphological and material characteristics but especially subject-specific muscle forces. These findings make a significant contribution to shape future rehabilitation protocols with a foundation in biomechanics.

The material properties of muscle play a central role in how muscle resists joint motion, transmits forces internally, and repairs itself. While many studies have evaluated muscles tensile material properties, few have investigated muscles shear properties. None of which have taken into account muscles anisotropic structure or investigated how different muscle architecture affect muscles shear properties. The objective of this study was to quantify the shear moduli of skeletal muscle in three orientations relevant to the function of whole muscle. We collected data from the extensor digitorum longus, tibialis anterior, and soleus harvested from both hindlimbs of 12 rats. These muscles were chosen to further evaluate the consistency of shear moduli across muscles with different architectures. We calculated the shear modulus in three orientations: parallel, perpendicular, and across with respect to muscle fiber alignment; while the muscle was subjected to increasing shear strain. For all muscles and orientations, the shear modulus increased with increasing strain. The shear modulus measured perpendicular to fibers was greater than in any other orientation. Despite architectural differences between muscles, we did not find a significant effect of muscle type on shear modulus. Our results show that in rat, muscles shear moduli vary with respect to fiber orientation and are not influenced by architectural differences in muscles.

Osteocytes are capable of resorbing and replacing bone local to the lacunar-canalicular system (LCS remodeling). However, the impacts of these processes on perilacunar bone quality are not understood. It is well established that aging is associated with reduced whole-bone fracture resistance, reduced osteocyte viability, and truncated LCS geometries, but it remains unclear if aging changes perilacunar bone quality. In this study, we employed atomic force microscopy (AFM) to quantify sub-micrometer gradations from 2D maps surrounding osteocyte lacunae in young (5 mo) and aged (22 mo) female mice. AFM-mapped lacunae were also imaged with confocal laser scanning microscopy to determine which osteocytes had recently deposited bone as determined by the presence of fluorochrome labels. These assays allowed us to quantify gradations in nanoscale mechanical properties of bone-forming/non-bone-forming osteocytes in young and aged mice. This study reports for the first time that there are sub-micrometer gradations in modulus surrounding lacunae and that these gradations are dependent upon recent osteocyte bone formation. Perilacunar bone adjacent to bone-forming osteocytes demonstrated lower peak and bulk modulus values when compared to bone near non-bone-forming osteocytes from the same mouse. Bone-forming osteocytes also showed increased perilacunar modulus variability. Age reduced lacunar size but did not significant effect modulus gradation or variability. In general, lacunar morphology was not a strong predictor of modulus gradation patterns. These findings support the idea that lacunar-canalicular remodeling activity changes the material properties of surrounding bone tissue on a sub-micrometer scale. Therefore, conditions that affect osteocyte health have the potential to impact bone quality. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=62 SRC="FIGDIR/small/461298v1_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@1fe5a68org.highwire.dtl.DTLVardef@1e17e90org.highwire.dtl.DTLVardef@13c2e3corg.highwire.dtl.DTLVardef@1ff9f38_HPS_FORMAT_FIGEXP M_FIG C_FIG

The identification of material parameters accurately describing the region-dependent mechanical behavior of human brain tissue is crucial for computational models used to assist, e.g., the development of safety equipment like helmets or the planning and execution of brain surgery. While the division of the human brain into different anatomical regions is well established, knowledge about regions with distinct mechanical properties remains limited. Here, we establish an inverse parameter identification scheme using a hyperelastic Ogden model and experimental data from multi-modal testing of tissue from 19 anatomical human brain regions to identify mechanically distinct regions and provide the corresponding material parameters. We assign the 19 anatomical regions to nine governing regions based on similar parameters and microstructures. Statistical analyses confirm differences between the regions and indicate that at least the corpus callosum and the corona radiata should be assigned different material parameters in computational models of the human brain. We provide a total of four parameter sets based on the two initial Poissons ratios of 0.45 and 0.49 as well as the pre- and unconditioned experimental responses, respectively. Our results highlight the close interrelation between the Poissons ratio and the remaining model parameters. The identified parameters will contribute to more precise computational models enabling spatially resolved predictions of the stress and strain states in human brains under complex mechanical loading conditions.

Single cell mechanical properties represent an increasingly studied descriptor for health and disease. Atomic force microscopy (AFM) has been widely used to measure single cell stiffness, despite its experimental limitations. The development of a computational framework to simulate AFM nanoindentation experiments could be a valuable tool to complement experimental findings. A single cell multi-structural finite element model was designed to this aim by using confocal images of bone cells, comprised of the cell nucleus, cytoplasm and actin cytoskeleton. The computational cell stiffness values were in the range of experimental values acquired on the same cells for nanoindentation of the cell nucleus and periphery, despite showing higher stiffness for the nucleus than for the periphery, oppositely to the average experimental findings. These results suggest it would be of interest to model different single cells with known experimental effective moduli to evaluate the ability of the computational models to replicate experimental results.

Soft hydrated materials, including biological tissues and hydrogels, exhibit complex time-dependent mechanical behaviors due to their poroelastic and viscoelastic properties. These properties often manifest on overlapping time scales, making it challenging to isolate the individual contributions of poroelasticity and viscoelasticity to the overall mechanical response. This study presents a novel semi-analytical model for characterizing these properties through sequential microscale load relaxation indentation testing. By extending existing theories, we developed a poroviscoelastic framework that enables the deconvolution of poroelastic and viscoelastic effects. Using this model to fit sequential microscale indentation data, we characterized porcine heart and liver tissues, as well as collagen and GelMA hydrogels, revealing distinct differences in their poroelastic and viscoelastic parameters. Our findings demonstrate that this approach not only provides rapid and detailed insights into the mechanical properties at the microscale but also offers significant advantages over traditional methods in terms of speed, computational efficiency, and practicality. This methodology has broad implications for advancing the understanding of tissue mechanics and the design of biomimetic materials for tissue engineering applications. Statement of SignificanceThis study introduces a novel approach to understanding the mechanical behavior of soft hydrated materials, like tissues and hydrogels. This study introduces a semi-analytical model to describe the time dependent behavior and a practical approach to distinguish between poroelasticity and viscoelasticity at the microscale. By providing this model along with a rapid and efficient characterization method, our approach enhances understanding of time-dependent mechanical behaviors critical for soft tissue mechanics and biomaterials design.

Mechanical loading is a key factor governing bone adaptation. Both preclinical and clinical studies have demonstrated its effects on bone tissue, which were also notably predicted in the mechanostat theory. Indeed, existing methods to quantify bone mechanoregulation have successfully associated the frequency of (re)modeling events with local mechanical signals, combining time-lapsed in vivo micro-computed tomography (micro-CT) imaging and micro-finite element (micro-FE) analysis. However, a correlation between the local surface velocity of (re)modeling events and mechanical signals has not been shown. As many degenerative bone diseases have also been linked to impaired bone (re)modeling, this relationship could provide an advantage in detecting the effects of such conditions and advance our understanding of the underlying mechanisms. Therefore, in this study, we introduce a novel method to estimate (re)modeling velocity curves from time-lapsed in vivo mouse caudal vertebrae data under static and cyclic mechanical loading. These curves can be fitted with piecewise linear functions as proposed in the mechanostat theory. Accordingly, new (re)modeling parameters can be derived from such data, including formation saturation levels, resorption velocity modulus, and (re)modeling thresholds. Our results revealed that the norm of the gradient of strain energy density yielded the highest accuracy in quantifying mechanoregulation data using micro-FE analysis with homogeneous material properties, while effective strain was the best predictor for micro-FE analysis with heterogeneous material properties. Furthermore, (re)modeling velocity curves could be accurately described with piecewise linear and hyperbola functions (root mean square error below 0.2 {micro}m/day for weekly analysis), and several (re)modeling parameters determined from these curves followed a logarithmic relationship with loading frequency. Crucially, (re)modeling velocity curves and derived parameters could detect differences in mechanically driven bone adaptation, which complemented previous results showing a logarithmic relationship between loading frequency and net change in bone volume fraction over four weeks. Together, we expect this data to support the calibration of in silico models of bone adaptation and the characterization of the effects of mechanical loading and pharmaceutical treatment interventions in vivo.

Methods to repair bone defects arising from trauma, resection, or disease, continue to be sought after. Cyclic mechanical loading is well established to influence bone (re)modelling activity, in which bone formation and resorption are correlated to micro-scale strain. Based on this, the application of mechanical stimulation across a bone defect could improve healing. However, if ignoring the mechanical integrity of defected bone, loading regimes have a high potential to either cause damage or be ineffective. This study explores real-time finite element (rtFE) methods that use three-dimensional structural analyses from micro-computed tomography images to estimate effective peak cyclic loads in a subject-specific and time-dependent manner. It demonstrates the concept in a cyclically loaded mouse caudal vertebral bone defect model. Using rtFE analysis combined with adaptive mechanical loading, mouse bone healing was significantly improved over non-loaded controls, with no incidence of vertebral fractures. Such rtFE-driven adaptive loading regimes demonstrated here could be relevant to clinical bone defect healing scenarios, where mechanical loading can become patient-specific and more efficacious. This is achieved by accounting for initial bone defect conditions and spatio-temporal healing, both being factors that are always unique to the patient.

Technological advancements in the field of robotics have led to endoscopic biopsy devices able to extract diseased tissue from between the layers of the gastrointestinal tract. Despite this, the layer-dependent properties of these tissues have yet to be mechanically characterised using human tissue. In this study, the ex vivo mechanical properties of the passive muscularis propia layer of the human oesophagus were extensively investigated. For this, a series of uniaxial tensile tests were conducted. The results displayed hyperelastic behaviour, while the differences between loading the tissue in both the longitudinal and circumferential directions showcased its anisotropy. The anisotropy of the muscular layer was present at different strain rates, with the longitudinal direction being consistently stiffer than the circumferential one. The circumferential direction was found to have little strain-rate dependency, while the longitudinal direction results suggest pronounced strain-rate-dependent behaviour. The repeated trials showed larger variation in terms of stress for a given strain in the longitudinal direction compared to the circumferential direction. The possible causes of variation between trials are discussed, and the experimental findings are linked to the histological analysis which was carried out via various staining methods. Finally, the direction-dependent experimental data was simulated using an anisotropic, hyperelastic model.

Heart failure remains one of the leading causes of death especially among people over the age of 60 years worldwide. To develop effective therapy and suitable replacement materials for the heart muscle it is necessary to understand its biomechanical behaviour under load. This paper investigates the passive mechanical response of the sheep myocardia excised from three different regions of the heart. Due to the relatively higher cost and huge ethical demands in acquisition and testing of real animal heart models, this paper evaluates the fitting performances of five different constitutive models on the myocardial tissue responses. Ten sheep were sacrificed, and their hearts excised and transported within 3h to the testing biomechanical laboratory. The upper sections of the hearts above the short axes were carefully dissected out. Tissues were dissected from the mid-sections of the left ventricle, mid-wall and right ventricle for each heart. The epicardia and endocardia were then carefully sliced off each tissue to leave the myocardia. Stress-strain curves were calculated, filtered and resampled. The results show that Choi-Vito model was found to provide the best fit to the LV, the polynomial (Anisotropic) model to RV, the Four-Fiber Family model to RV, Holzapfel (2000) to RV, Holzapfel (2005) to RV and the Fung model to LV.

Poor socket fit is the leading cause of prosthetic limb discomfort. However, currently clinicians have limited objective data to support and improve socket design. Prosthesis fit could be predicted by finite element analysis to help improve the fit, but this requires internal and external anatomy models. While external 3D surface scans are often collected in routine clinical computer aided design practice, detailed imaging of internal anatomy (e.g. MRI or CT) is not. This paper presents a prototype Statistical Shape Model (SSM) describing the transtibial amputated residual limb, generated using a sparse dataset of 10 MRI scans. To describe the maximal shape variance, training scans are size-normalised to their estimated intact tibia length. A mean limb is calculated, and Principal Component Analysis used to extract the principal modes of shape variation. In an illustrative use case, the model is interrogated to predict internal bone shapes given a skin surface shape. The model attributes [~]82% of shape variance to amputation height and [~]7.5% to soft tissue profile. Leave-One-Out cross-validation allows mean shape reconstruction with 0.5-3.1mm root-mean-squared-error (RMSE) surface deviation (median 1.0mm), and left-out-shape reconstruction with 4.8-8.9mm RMSE (median 6.1mm). Linear regression between mode scores from skin- only- and full-model SSMs allowed prediction of bone shapes from the skin surface with 4.9-12.6mm RMSE (median 6.5mm). The model showed the feasibility of predicting bone shapes from skin surface scans, which will enable more representative prosthetic biomechanics research, and address a major barrier to implementing simulation within clinical practice. Impact StatementThe presented Statistical Shape Model answers calls from the prosthetics community for residual limb shape descriptions to support prosthesis structural testing that is representative of a broader population. The SSM allows definition of worst-case residual limb sizes and shapes, towards testing standards. Further, the lack of internal anatomic imaging is one of the main barriers to implementing predictive simulations for prosthetic socket interface fitting at the point-of-care. Reinforced with additional data, this model may enable generation of estimated finite element analysis models for predictive prosthesis fitting, using 3D surface scan data already collected in routine clinical care. This would enable prosthetists to assess their design choices and predict a sockets fit before fabrication, important improvements to a time-consuming process which comes at high cost to healthcare providers. Finally, few researchers have access to residual limb anatomy imaging data, and there is a cost, inconvenience, and risk associated with putting the small community of eligible participants through CT or MRI scanning. The presented method allows sharing of representative synthetic residual limb shape data whilst protecting the data contributors privacy, adhering to GDPR. This resource has been made available at https://github.com/abel-research/openlimb, open access, providing researchers with limb shape data for biomechanical analysis.

PurposeThe purpose of this study is to investigate the mechanical behaviour of the tracheal tissue under biaxial tensile loading. Furthermore, the study examines the material properties of the tissue through a study of the model parameters for six constitutive models. Materials and methodsThe fourteen (n = 13) trachea sheep (Vleis Merino) pieces of tissues measured to be ~ 30 x 20 mm where only the effective area subjected to engineering strain was ~ 25 x 16 mm. In this study, we assume that the tracheal tissue is anisotropic and incompressible, therefore we apply and study the material parameters from six models namely the Fung, Choi-Vito, Holzapfel (2000), Holzapfel (2005), Polynomial (Anisotropic) and Four-Fiber Family models. ResultsThe results show that the trachea tissue is twice as stiff along the circumferential direction as it is along the longitudinal direction. It is also observed that the material properties are different (non-homogeneous) along the trachea. ConclusionsThe findings of this study will benefit computational models for the study of tracheal diseases or injuries. Furthermore, these findings will assist in the development of regenerative medicine for different tracheal pathologies and in the bioengineering of replacement tissue in cases of damage.

Human and mouse incisors are both primarily composed of dentin and enamel which meet at an interface called the dentin-enamel junction (DEJ). However, incisors in the two species have very different growth patterns, structures, and loading requirements. Since the DEJ is responsible for minimizing cracking at this at-risk interface between mechanically dissimilar dentin and enamel, its structure is expected to be significantly different between humans and mice. Here, strucutral and compositional gradients across human and murine incisors DEJs were measured via microcomputed tomography and Raman spectroscopy. Density gradients across the DEJ were significantly larger in humans compared to murine teeth likely due to the larger size of the mantle dentin. Multiple gradients in mineral content and crystallinity were found at the murine DEJ while the human DEJ only exhibited gradients in mineral content. Models predicting the modulus across the DEJ according to compositional results show that mineral crystallinity is critical in regulating the mechanical gradient across the murine DEJ. Together these results show the multiple ways in which the DEJ can adapt to variations in loading environment.

Bone is an essential, healing structure in vertebrates that ensures daily function. However, the regenerative capacity of bone declines with age, compromising quality of life in the elderly and increasing cost of care. Here, for the first time, the elasticity of regenerated bone in a mouse digit amputation model is evaluated in order to better investigate biomechanics of skeletal regeneration. Amputation of the distal one third of the digit (third phalangeal element - P3) results in de novo regeneration of the digit, where analyzing the structural quality of this regenerated bone is a challenging task due to its small scale and triangular shape. To date, the evaluation of structural quality of the P3 bone has primarily focused on mineral density and bone architecture. This work describes an image-processing based method for assessment of elasticity in the whole P3 bone by using microcomputed tomography-generated mineral density data to calculate spatially discrete elastic modulus values across the entire P3 bone volume. Further, we validate this method through comparison to nanoindentation-measured values for elastic modulus. Application to a set of regenerated and unamputated digits shows that regenerated bone has a lower elastic modulus compared to the uninjured digit, with a similar trend for experimental hardness values. This method will be impactful in predicting and evaluating the regenerative outcomes of potential treatments and heightens the utility of the P3 regenerative model.

Current models propose that osteogenesis occurs in regions of high mechanical stimuli such as strain, fluid velocity, or pore pressure. However, in vivo experiments on mouse tibiae under cantilever loading revealed new bone formation exclusively on the anterolateral side, despite the opposite posteromedial surface experiencing comparable magnitudes of these stimuli. This indicates that individual stimulus magnitude is insufficient and suggests an interactive mechanism among them. To investigate this, a poroelastic finite element model was developed to quantify the combined effects of load-induced fluid velocity and pore pressure. Tensile loading generated negative pore pressure, stretching osteocyte processes, while compressive loading produced positive pore pressure, compressing them. Since fluid flow exerts drag forces that also stretch osteocytes, the combined effect of flow and negative pressure on the tensile side was hypothesized to enhance mechanotransduction and trigger osteogenesis. Four potential stimuli were evaluated: dissipation energy density arising from (i) pore pressure, (ii) fluid velocity, (iii) their non-interactive sum, and (iv) their interaction. Comparison with in vivo data showed that only the interactive dissipation energy density accurately predicted both the spatial pattern and rate of new bone formation under high, low, and rest-inserted loading regimes. These results establish that the interaction between fluid velocity and pore pressure, rather than their independent contributions, governs load-induced osteogenesis. The proposed framework advances the mechanistic understanding of bone adaptation and offers a predictive basis for optimizing mechanical and clinical interventions to promote bone formation and mitigate bone loss.

End-stage temporomandibular joint (TMJ) disorders often necessitate joint replacement to restore bilateral mastication. Patient-specific TMJ implants typically rely on detailed in silico modelling derived from subject-specific computed tomography (CT) scans of the mandible. However, generating highly detailed finite element (FE) models is computationally expensive. Although structural simplifications of the mandible are known to influence mechanical behaviour, their quantitative impact on TMJ implant evaluation has not been systematically investigated. This study examines the influence of three modelling simplifications on stress-strain predictions in intact and implanted mandibles: (i) a detailed segmented mandible with tissue-specific material properties (Model 1), (ii) a simplified mandible comprising cortical bone only (Model 2), and (iii) a further simplified mandible excluding dental crowns (Model 3). Both narrow and standard TMJ implants were analysed under osseointegrated and non-osseointegrated conditions, resulting in fifteen FE models. Physiological clenching activities were simulated. Compared with the detailed model, simplified models showed reductions of up to 50% in maximum principal strain in bone and up to 44% in von Mises stress in TMJ implants, while preserving spatial stress-strain trends. These findings indicate that simplified models may be suitable for preliminary implant design, whereas detailed FE modelling remains essential for final pre-clinical evaluation.

Digital volume correlation (DVC) has become the benchmark experimental technique for full-field strain measurement in bone mechanics. In our previous work we developed a novel data-driven image mechanics (D2IM) approach that learns from DVC data and predicts displacement fields directly from undeformed X-ray computed tomography (XCT) images, deriving strain fields from such predictions. However, strain fields derived through numerical differentiation of displacement fields amplify high-frequency noise, and regularization techniques compromise spatial resolution while incurring substantial computational costs. Here we propose the upgrade D2IM-Strain to predict strain fields directly from XCT images of bone. Two prediction strategies were compared: displacement-derived strain and direct strain prediction. The direct strain prediction model significantly improved accuracy particularly for strain magnitudes below 10000{micro}{varepsilon}, taken as a representative threshold value for bone tissue yielding in compression. In addition, the direct approach reduced false-positive high-strain classifications by 75%. By eliminating numerical differentiation, the approach reduces noise amplification while maintaining computational efficiency. These findings represent a critical step toward developing robust data-driven volume correlation methods for hierarchical materials.

Curved fibered structures are ubiquitous in nature and this organization is found in the majority of biological tissues. Indeed, the mechanical behavior of these materials is of pivotal importance in biomechanics and mechanobiology fields. In this paper, we develop a multiscale formulation to characterize the macroscopic mechanical nonlinear behavior from the microstructure of fibered matrices. From the analysis of the mechanics of a randomly curved single fiber, a fibered matrix model is built to determine the macroscopic behavior following a homogenization approach. The model is tested for tensile, compression and shear loads in a number of applications reminiscent to collagen extracellular matrices. However, any other fibered microstructures can be studied following the proposed formulation. The presented approach naturally recovers instabilities at compression as well as the strain stiffening regime, which are observed experimentally in the mechanical behavior of collagen matrices. Indeed, it was found that the bending energy associated to fiber unrolling, is the most important source of energy developed by fibers for the analyzed cases in tensile and shear in all deformation regions (except the strain stiffening region), whereas bending energy dominates at compression too during buckling. The proposed computational framework can also be used to perform multiscale simulations in the referred applications. As a result, the developed methodology may be an interesting and complementary tool to characterize the nonlinear behavior and evolution of curved fibered structures present in biology and engineered materials.

The myotendinous junction transfers forces from muscle to tendon. As such, it must hold two tissues of completely different biological and cellular compositions as well as mechanical properties (kPa-MPa to MPa-GPa) and is subject to frequent stresses of high amplitude. This region remains a weak point of the muscle-tendon unit and is involved in frequent injuries. We here produce fibrin (40 mg/mL, E0 =0.10 {+/-} 0.02 MPa) and collagen (60 mg/mL, E0=0.57 {+/-} 0.05 MPa) threads as well as mixed collagen:fibrin threads (3:2 in mass, E0 = 0.33 {+/-} 0.05 MPa) and investigate the difference of affinity between primary murine myoblasts and tenoblasts. We demonstrate a similar behavior of cells on mixed and fibrin threads with high adherence of tenoblasts and myoblasts, in comparison to collagen threads that promote high adherence and proliferation of tenoblasts but not of myoblasts. Besides, we show that myoblasts on threads differentiate but do not fuse, on the contrary to 2D control substrates, raising the question of the effect of substrate curvature on the ability of myoblasts to fuse in vitro.

The structural integrity of cancellous bone, which is essential to its skeletal load-bearing capacity, is governed chiefly by apparent density, trabecular architecture, and tissue material properties. Metabolic bone disorders such as osteoporosis can affect each of these factors, resulting in compromised load-bearing function and fracture. While the impact of apparent density and architecture on bone structural behavior is well-documented, much less is known about the influence of tissue material properties, particularly in osteoporotic bone. In this work, we isolated the influence of tissue modulus on normal and osteoporotic cancellous bone structural integrity, indicated by the apparent elastic modulus under uniaxial compression and patterns of internal tissue strain. Finite element (FE) models derived from 3D micro-computed tomography images were compared to physical testing data of the same samples. Three sets of FE models with increasing material detail were studied: 1) universal tissue elastic modulus (20 GPa), 2) specimen-specific average tissue modulus, and 3) heterogeneous tissue modulus. Applying a universal modulus resulted in overestimation of osteoporotic bone apparent modulus; applying specimen-specific material properties, either as a single average tissue modulus or heterogeneous distribution of tissue moduli, prevented significant apparent modulus overestimation. The greatest improvement in apparent modulus prediction resulted from incorporating a specimen-specific average tissue modulus, though using a specimen-specific heterogeneous tissue modulus provided the most reliable prediction of apparent modulus overall. In addition, median element strain in heterogeneous models also trended lower than in homogeneous models. This finding suggests that heterogeneous material properties may play a role in protective strain-concentrating mechanisms observed in cancellous bone. We conclude that future work exploring trabecular bone mechanics through finite element analysis should incorporate specimen-specific average tissue modulus at a minimum, but heterogeneous tissue modulus is recommended to maximize the functional similarity of bone in silico with bone in vivo.