Todd L. Bredbenner

Statistical shape modeling describes variation in tibia and femur surface geometry between Control and Incidence groups from the Osteoarthritis Initiative database

We hypothesize that variability in knee subchondral bone surface geometry will differentiate between patients at risk and those not at risk for developing osteoarthritis (OA) and suggest that statistical shape modeling (SSM) methods form the basis for developing a diagnostic tool for predicting the onset of OA. Using a subset of clinical knee MRI data from the osteoarthritis initiative (OAI), the objectives of this study were to (1) utilize SSM to compactly and efficiently describe variability in knee subchondral bone surface geometry and (2) determine the efficacy of SSM and rigid body transformations to distinguish between patients who are not expected to develop osteoarthritis (i.e. Control group) and those with clinical risk factors for OA (i.e. Incidence group). Quantitative differences in femur and tibia surface geometry were demonstrated between groups, although differences in knee joint alignment measures were not statistically significant, suggesting that variability in individual bone geometry may play a greater role in determining joint space geometry and mechanics. SSM provides a means of explicitly describing complete articular surface geometry and allows the complex spatial variation in joint surface geometry and joint congruence between healthy subjects and those with clinical risk of developing or existing signs of OA to be statistically demonstrated.

Fracture risk assessment

Having traditionally relied on measurements of bone mineral density, it is now established that the consideration of other risk variables improves the categorisation of fracture risk. Whereas several models are available, the FRAX models are the most extensively used. The approach uses easily obtained clinical risk factors to estimate 10 year fracture probability, with or without femoral neck bone mineral density (BMD), to enhance fracture risk prediction. It has been constructed and validated using primary data from population based cohorts around the world, including centres from North America, Europe, Asia and Australia. The FRAX® tool should not be considered as a gold standard, but rather as a platform technology on which to build as new validated risk indicators become available. Notwithstanding, the present models provide an aid to enhance patient assessment by the integration of clinical risk factors alone and/or in combination with BMD.

Platelet-derived growth-factor-releasing aligned collagen-nanoparticle fibers promote the proliferation and tenogenic differentiation of adipose-derived stem cells.

In order to enhance the healing potential of an injured tendon, we have prepared a novel biomimetic aligned collagen-nanoparticle (NP) composite fiber using an electrochemical process. The aligned collagen-NP composite fiber is designed to affect the cellular activity of adipose-derived stem cells (ADSCs) through two different ways: (i) topographic cues from the alignment of collagen fibril and (ii) controlled release of platelet-derived growth factors (PDGFs) from the NPs. PDGF released from collagen-NP fibers significantly enhanced the proliferation of ADSCs when tested for up to 7 days. Moreover, compared to random collagen fibers with PDGFs, aligned collagen-NP fibers significantly promoted the desirable tenogenic differentiation of ADSCs, as evidenced by an increased level of tendon markers such as tenomodulin and scleraxis. On the other hand, no undesirable osteogenic differentiation, as measured by the unchanged level of alkaline phosphatase and osteocalcin, was observed. Together, these results indicate that the aligned collagen-NP composite fiber induced the tenogenic differentiation of ADSCs through both a topographic cue (aligned collagen fibril) and a chemical cue (PDGF released from NPs). Thus, our novel aligned collagen-NP composite fiber has a significant potential to be used for tendon tissue engineering and regeneration.

Development of a parametric finite element model of the proximal femur using statistical shape and density modelling

Skeletal fractures associated with bone mass loss are a major clinical problem and economic burden, and lead to significant morbidity and mortality in the ageing population. Clinical image-based measures of bone mass show only moderate correlative strength with bone strength. However, engineering models derived from clinical image data predict bone strength with significantly greater accuracy. Currently, image-based finite element (FE) models are time consuming to construct and are non-parametric. The goal of this study was to develop a parametric proximal femur FE model based on a statistical shape and density model (SSDM) derived from clinical image data. A small number of independent SSDM parameters described the shape and bone density distribution of a set of cadaver femurs and captured the variability affecting proximal femur FE strength predictions. Finally, a three-dimensional FE model of an ‘unknown’ femur was reconstructed from the SSDM with an average spatial error of 0.016 mm and an average bone density error of 0.037 g/cm3.

Fracture Risk Predictions Based on Statistical Shape and Density Modeling of the Proximal Femur

Increased risk of skeletal fractures due to bone mass loss is a major public health problem resulting in significant morbidity and mortality, particularly in the case of hip fractures. Current clinical methods based on two‐dimensional measures of bone mineral density (areal BMD or aBMD) are often unable to identify individuals at risk of fracture. We investigated predictions of fracture risk based on statistical shape and density modeling (SSDM) methods using a case‐cohort sample of individuals from the Osteoporotic Fractures in Men (MrOS) study. Baseline quantitative computed tomography (QCT) data of the right femur were obtained for 513 individuals, including 45 who fractured a hip during follow‐up (mean 6.9 year observation, validated by physician review). QCT data were processed for 450 individuals (including 40 fracture cases) to develop individual models describing three‐dimensional bone geometry and density distribution. Comparison of mean fracture and non‐case models indicated complex structural differences that appear to be responsible for resistance to hip fracture. Logistic regressions were used to model the relation of baseline hip BMD and SSDM weighting factors to the occurrence of hip fracture. Area under the receiver operating characteristic (ROC) curve (AUC) for a prediction model based on weighting factors and adjusted by age was significantly greater than AUC for a prediction model based on aBMD and age (0.94 versus 0.83, respectively). The SSDM‐based prediction model adjusted by age correctly identified 55% of the fracture cases (and 94.7% of the non‐cases), whereas the clinical standard aBMD correctly identified 10% of the fracture cases (and 91.3% of the non‐cases). SSDM identifies subtle changes in combinations of structural bone traits (eg, geometric and BMD distribution traits) that appear to indicate fracture risk. Investigation of important structural differences in the proximal femur between fracture and no‐fracture cases may lead to improved prediction of those at risk for future hip fracture.

Heritability of lumbar trabecular bone mechanical properties in baboons

Genetic effects on mechanical properties have been demonstrated in rodents, but not confirmed in primates. Our aim was to quantify the proportion of variation in vertebral trabecular bone mechanical properties that is due to the effects of genes. L3 vertebrae were collected from 110 females and 46 male baboons (6-32 years old) from a single extended pedigree. Cranio-caudally oriented trabecular bone cores were scanned with microCT then tested in monotonic compression to determine apparent ultimate stress, modulus, and toughness. Age and sex effects and heritability (h(2)) were assessed using maximum likelihood-based variance components methods. Additive effects of genes on residual trait variance were significant for ultimate stress (h(2)=0.58), toughness (h(2)=0.64), and BV/TV (h(2)=0.55). When BV/TV was accounted for, the residual variance in ultimate stress accounted for by the additive effects of genes was no longer significant. Toughness, however, showed evidence of a non-BV/TV-related genetic effect. Overall, maximum stress and modulus show strong genetic effects that are nearly entirely due to bone volume. Toughness shows strong genetic effects related to bone volume and shows additional genetic effects (accounting for 10% of the total trait variance) that are independent of bone volume. These results support continued use of bone volume as a focal trait to identify genes related to skeletal fragility, but also show that other focal traits related to toughness and variation in the organic component of bone matrix will enhance our ability to find additional genes that are particularly relevant to fatigue-related fractures.

Cross-sectional Geometry of the Femoral Midshaft in Baboons is Heritable

A great deal of research into the determinants of bone strength has unequivocally demonstrated that variation in bone strength is highly subject to genetic factors. Increasing attention in skeletal genetic studies is being paid to indicators of bone quality that complement studies of BMD, including studies of the genetic control of bone geometry. The aim of this study is to investigate the degree to which normal population-level variation in femoral midshaft geometry in a population of pedigreed baboons (Papio hamadryas spp.) can be attributed to the additive effect of genes. Using 110 baboons (80 females, 30 males), we 1) characterize normal variation in midshaft geometry of the femur with regard to age and sex, and 2) determine the degree to which the residual variation is attributable to additive genetic effects. Cross-sectional area (CSA), minimum (I(MIN)) and maximum (I(MAX)) principal moments of inertia, and polar moment of inertia (J) were calculated from digitized images of transverse midshaft sections. Maximum likelihood-based variance decomposition methods were used to estimate the mean effects of age, sex, and genes. Together age and sex effects account for approximately 56% of the variance in each property. In each case the effect of female sex is negative and that of age is positive, although of a lower magnitude than the effect of female sex. Increased age is associated with decreased mean cross-sectional geometry measures in the oldest females. Residual h(2) values range from 0.36 to 0.50, reflecting genetic effects accounting for 15% to 23% of the total phenotypic variance in individual properties. This study establishes the potential of the baboon model for the identification of genes that regulate bone geometric properties in primates. This model is particularly valuable because it allows for experimental designs, environmental consistency, availability of tissues, and comprehensive assessments of multiple integrated bone phenotypes that are not possible in human populations. The baboon is of particular importance in genetic studies, because it provides results that are likely highly relevant to the human condition due to the phylogenetic proximity of baboons to humans.

Reproductive status and sex show strong effects on knee OA in a baboon model

OBJECTIVE We aimed to characterize severity and occurrence of knee osteoarthritis (OA), and effects of age, sex, body mass, and reproductive status on population-level normal variation in this condition in the baboon, a natural model of human knee OA. METHODS We visually inspected articular cartilage of distal right femora of 464 baboons (309 females, 155 males) and assigned an OA severity score (comparable to a modified Outerbridge score) from 1 = unaffected to 4 = advanced OA (eburnation). Presence/absence of osteophytes was recorded. We tested for significant effects of age, sex, body mass, and, in females, reproductive status (pre-, peri-, or post-menopausal) on OA. When appropriate, analyses were repeated on an age-matched subset (153 of each sex). RESULTS Knee OA was more frequent and severe in older animals (P < 0.0001), but significant age variation was apparent in each severity grade. Sex differences within the younger and older age groups suggest that males develop knee OA earlier, but females progress more quickly to advanced disease. There is a strong relationship between reproductive status and OA severity grade in females (P = 0.0005) with more severe OA in peri- and post-menopausal female baboons, as in humans. CONCLUSIONS Idiopathic knee OA is common in adult baboons. Occurrence and severity are influenced strongly by reproductive status in females, and by sex with regard to patterns of disease progression - providing an animal model to investigate sex-specific variation in OA susceptibility in which the environmental heterogeneity inherent in human populations is vastly reduced.

Development and validation of a statistical shape modeling-based finite element model of the cervical spine under low-level multiple direction loading conditions

Cervical spinal injuries are a significant concern in all trauma injuries. Recent military conflicts have demonstrated the substantial risk of spinal injury for the modern warfighter. Finite element models used to investigate injury mechanisms often fail to examine the effects of variation in geometry or material properties on mechanical behavior. The goals of this study were to model geometric variation for a set of cervical spines, to extend this model to a parametric finite element model, and, as a first step, to validate the parametric model against experimental data for low-loading conditions. Individual finite element models were created using cervical spine (C3–T1) computed tomography data for five male cadavers. Statistical shape modeling (SSM) was used to generate a parametric finite element model incorporating variability of spine geometry, and soft-tissue material property variation was also included. The probabilistic loading response of the parametric model was determined under flexion-extension, axial rotation, and lateral bending and validated by comparison to experimental data. Based on qualitative and quantitative comparison of the experimental loading response and model simulations, we suggest that the model performs adequately under relatively low-level loading conditions in multiple loading directions. In conclusion, SSM methods coupled with finite element analyses within a probabilistic framework, along with the ability to statistically validate the overall model performance, provide innovative and important steps toward describing the differences in vertebral morphology, spinal curvature, and variation in material properties. We suggest that these methods, with additional investigation and validation under injurious loading conditions, will lead to understanding and mitigating the risks of injury in the spine and other musculoskeletal structures.

Simulation of Fall Loading Using a Probabilistic Shape-Based Finite Element Model of Human Femurs

The efficient construction of finite element models that accurately represent the complex morphology of biological structures is a major challenge. Typically, the model constructed is a representation of a single patient and, in order to investigate a different individual, the majority of the mesh construction process must be repeated.Copyright