Virtual knees, with specimen-specific anatomy and mechanics, require heterogeneous data collected on the same knee. Specimen-specific data such as the specimen geometry, physiological joint kinematics-kinetics and contact mechanics are necessary in the development of virtual knee specimens for clinical and scientific simulations. These data are also required to capture or evaluate the predictive capacity of the model to represent joint and tissue mechanical response. This document details the collection of magnetic resonance imaging data and, tibiofemoral joint and patellofemoral joint mechanical testing data . These data were acquired for a cohort of eight knee specimens representing different populations with varying gender, age and perceived health of the joint. These data were collected as part of the Open Knee(s) initiative. Imaging data when combined with joint mechanics data, may enable development and assessment of authentic specimen-specific finite element models of the knee. The data may also guide prospective studies for association of anatomical and biomechanical markers in a specimen-specific manner.

No abstract

The skin, fat, and muscle of the musculoskeletal system provide essential support and protection to the human body. The interaction between individual layers and their composite structure dictate the body’s response during mechanical loading of extremity surfaces. Quantifying such interactions may improve surgical outcomes by enhancing surgical simulations with lifelike tissue characteristics. Recently, a comprehensive tissue thickness and anthropometric database of in vivo extremities was acquired using a load sensing instrumented ultrasound to enhance the fidelity of advancing surgical simulations. However detailed anatomy of tissue layers of musculoskeletal extremities was not captured. This study aims to supplement that database with an enhanced dataset of in vitro specimens that includes ultrasound imaging supported by motion tracking of the ultrasound probe and two additional full field imaging modalities (magnetic resonance and computed tomography). The additional imaging datasets can be used in conjunction with the ultrasound/force data for more comprehensive modeling of soft tissue mechanics. Researchers can also use the image modalities in isolation if anatomy of legs and arms is needed.

Ligament mechanical behavior is primarily regulated by fibrous networks of type I collagen. Although these fibrous networks are typically highly aligned, healthy and injured ligament can also exhibit disorganized collagen architecture. The objective of this study was to determine whether variations in the collagen fibril network between neighboring ligaments can predict observed differences in mechanical behavior. Ligament specimens from two regions of bovine fetlock joints, which either exhibited highly aligned or disorganized collagen fibril networks, were mechanically tested in uniaxial tension. Confocal microscopy and FiberFit software were used to quantify the collagen fibril dispersion and mean fibril orientation in the mechanically tested specimens. These two structural parameters served as inputs into an established hyperelastic constitutive model that accounts for a continuous distribution of planar fibril orientations. The ability of the model to predict differences in the mechanical behavior between neighboring ligaments was tested by (1) curve fitting the model parameters to the stress response of the ligament with highly aligned fibrils and then (2) using this model to predict the stress response of the ligament with disorganized fibrils by only changing the parameter values for fibril dispersion and mean fibril orientation. This study found that when using parameter values for fibril dispersion and mean fibril orientation based on confocal imaging data, the model strongly predicted the average stress response of ligaments with disorganized fibrils ([Formula: see text]); however, the model only successfully predicted the individual stress response of ligaments with disorganized fibrils in half the specimens tested. Model predictions became worse when parameters for fibril dispersion and mean fibril orientation were not based on confocal imaging data. These findings emphasize the importance of collagen fibril alignment in ligament mechanics and help advance a mechanistic understanding of fibrillar networks in healthy and injured ligament.

Musculoskeletal extremities exhibit a multi-layer tissue structure that is composed of skin, fat, and muscle. Body composition and anthropometric measurements have been used to assess health status and build anatomically accurate biomechanical models of the limbs. However, comprehensive datasets inclusive of regional tissue anatomy and response under mechanical manipulation are missing. The goal of this study was to acquire and disseminate anatomical and mechanical data collected on extremities of the general population. An ultrasound system, instrumented with a load transducer, was used for in vivo characterization of skin, fat, and muscle thicknesses in the extremities of 100 subjects at unloaded (minimal force) and loaded (through indentation) states. For each subject, the unloaded and loaded state provided anatomic tissue layer measures and tissue indentation response for 48 and 8 regions, respectively. A publicly available web-based system has been used for data management and dissemination. This comprehensive database will provide the foundation for comparative studies in regional musculoskeletal composition and improve visual and haptic realism for computational models of the limbs.

No abstract

No abstract

Ligament wound healing involves the proliferation of a dense and disorganized fibrous matrix that slowly remodels into scar tissue at the injury site. This remodeling process does not fully restore the highly aligned collagen network that exists in native tissue, and consequently repaired ligament has decreased strength and durability. In order to identify treatments that stimulate collagen alignment and strengthen ligament repair, there is a need to develop in vitro models to study fibroblast activation during ligament wound healing. The objective of this study was to measure gene expression and matrix protein accumulation in fibroblast-collagen gels that were subjected to different static stress conditions (stress-free, biaxial stress, and uniaxial stress) for three time points (1, 2 or 3 weeks). By comparing our in vitro results to prior in vivo studies, we found that stress-free gels had time-dependent changes in gene expression (col3a1, TnC) corresponding to early scar formation, and biaxial stress gels had protein levels (collagen type III, decorin) corresponding to early scar formation. This is the first study to conduct a targeted evaluation of ligament healing biomarkers in fibroblast-collagen gels, and the results suggest that biomimetic in-vitro models of early scar formation should be initially cultured under biaxial stress conditions.