Reference data on in vitro anatomy and indentation response of tissue layers of musculoskeletal extremities.

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.

OpenSim: Simulating musculoskeletal dynamics and neuromuscular control to study human and animal movement.

Movement is fundamental to human and animal life, emerging through interaction of complex neural, muscular, and skeletal systems. Study of movement draws from and contributes to diverse fields, including biology, neuroscience, mechanics, and robotics. OpenSim unites methods from these fields to create fast and accurate simulations of movement, enabling two fundamental tasks. First, the software can calculate variables that are difficult to measure experimentally, such as the forces generated by muscles and the stretch and recoil of tendons during movement. Second, OpenSim can predict novel movements from models of motor control, such as kinematic adaptations of human gait during loaded or inclined walking. Changes in musculoskeletal dynamics following surgery or due to human-device interaction can also be simulated; these simulations have played a vital role in several applications, including the design of implantable mechanical devices to improve human grasping in individuals with paralysis. OpenSim is an extensible and user-friendly software package built on decades of knowledge about computational modeling and simulation of biomechanical systems. OpenSim's design enables computational scientists to create new state-of-the-art software tools and empowers others to use these tools in research and clinical applications. OpenSim supports a large and growing community of biomechanics and rehabilitation researchers, facilitating exchange of models and simulations for reproducing and extending discoveries. Examples, tutorials, documentation, and an active user forum support this community. The OpenSim software is covered by the Apache License 2.0, which permits its use for any purpose including both nonprofit and commercial applications. The source code is freely and anonymously accessible on GitHub, where the community is welcomed to make contributions. Platform-specific installers of OpenSim include a GUI and are available on simtk.org.

Comparison of CFD and MRI flow and velocities in an in vitro large artery bypass graft model.

Bypass graft failures have been attributed to various hemodynamic factors, including flow stasis and low shear stress. Ideally, surgeries would minimize the occurrence of these detrimental flow conditions, but surgeons cannot currently assess this. Numerical simulation techniques have been proposed as one method for predicting changes in flow distributions and patterns from surgical bypass procedures, but comparisons against experimental results are needed to assess their usefulness. Previous in vitro studies compared simulated results against experimentally obtained measurements, but they focused on peripheral arteries, which have lower Reynolds numbers than those found in the larger arteries. In this study, we compared simulation results against measurements obtained using magnetic resonance imaging (MRI) techniques for a phantom model of a stenotic vessel with a bypass graft under conditions suitable for surgical planning purposes and with inlet Reynolds numbers closer to those found inthe larger arteries. Comparisons of flow rate and velocity profiles were performed at maximum and minimum flows at four locations and used simulation results that were temporally and spatially averaged, key postprocessing when comparing against phase contrast MRI measurements. The maximum error in the computed volumetric flow rates was 6% of the measured values, and excellent qualitative agreement was obtained for the through-plane velocity profiles in both magnitude and shape. The in-plane velocities also agreed reasonably well at most locations.

Internet-based system for simulation-based medical planning for cardiovascular disease.

Current practice in vascular surgery utilizes only diagnostic and empirical data to plan treatments, which does not enable quantitative a priori prediction of the outcomes of interventions. We have previously described simulation-based medical planning methods to model blood flow in arteries and plan medical treatments based on physiologic models. An important consideration for the design of these patient-specific modeling systems is the accessibility to physicians with modest computational resources. We describe a simulation-based medical planning environment developed for the World Wide Web (WWW) using the Virtual Reality Modeling Language (VRML) and the Java programming language.

In vivo validation of a one-dimensional finite-element method for predicting blood flow in cardiovascular bypass grafts.

Current practice in vascular surgery utilizes only diagnostic and empirical data to plan treatments and does not enable quantitative a priori prediction of the outcomes of interventions. We have previously described a new approach to vascular surgery planning based on solving the governing equations of blood flow in patient-specific models. A one-dimensional finite-element method was used to simulate blood flow in eight porcine thoraco-thoraco aortic bypass models. The predicted flow rate was compared to in vivo data obtained using cine phase-contrast magnet resonance imaging. The mean absolute difference between computed and measured flow distribution in the stenosed aorta was found to be 4.2% with the maximum difference of 10.6% anda minimum difference of 0.4%. Furthermore, the sensitivity of the flow rate and distribution with respect to stenosis and branch losses were quantified.