Sefcik, Ryan | Search NASA

NASA NTRS2016

A Flexible Method for Producing F.E.M. Analysis of Bone Using Open-Source Software

Individuals who experience decreases in load-bearing bone densities can be subject to a higher risk of bone fracture during daily activity. Astronauts may lose up to nine percent of their load-bearing bone density for every month they spend in space [1]. Because of this, specialized countermeasures reduce percent loss in bone density and reduce fracture risk upon returning to Earth. Astronauts will typically not be at risk for fracture during spaceflight, because of the lesser loads experienced in microgravity conditions. However, once back on Earth, astronauts have an increased risk for bone fracture as a result of weakened bone and return to 1G conditions [2]. It is therefore important to understand the significance of any bone density loss in addition to developing exercises in an attempt to limit losses in bone strength. NASA seeks to develop a deeper understanding of fracture risk through the development of a computational bone strength model to assess the bone fracture risk of astronauts pre-flight and post-flight. This study addresses the several key processes needed to develop such strength analyses using medical image processing and finite element modeling.

biomechanics↗

NASA NTRS2016

A Flexible Method for Producing F.E.M. Analysis of Bone Using Open-Source Software

This project, performed in support of the NASA GRC Space Academy summer program, sought to develop an open-source workflow methodology that segmented medical image data, created a 3D model from the segmented data, and prepared the model for finite-element analysis. In an initial step, a technological survey evaluated the performance of various existing open-source software that claim to perform these tasks. However, the survey concluded that no single software exhibited the wide array of functionality required for the potential NASA application in the area of bone, muscle and bio fluidic studies. As a result, development of a series of Python scripts provided the bridging mechanism to address the shortcomings of the available open source tools. The implementation of the VTK library provided the most quick and effective means of segmenting regions of interest from the medical images; it allowed for the export of a 3D model by using the marching cubes algorithm to build a surface mesh. To facilitate the development of the model domain from this extracted information required a surface mesh to be processed in the open-source software packages Blender and Gmsh. The Preview program of the FEBio suite proved to be sufficient for volume filling the model with an unstructured mesh and preparing boundaries specifications for finite element analysis. To fully allow FEM modeling, an in house developed Python script allowed assignment of material properties on an element by element basis by performing a weighted interpolation of voxel intensity of the parent medical image correlated to published information of image intensity to material properties, such as ash density. A graphical user interface combined the Python scripts and other software into a user friendly interface. The work using Python scripts provides a potential alternative to expensive commercial software and inadequate, limited open-source freeware programs for the creation of 3D computational models. More work will be needed to validate this approach in creating finite-element models.

gravitational physiology↗