Register now After registration you will be able to apply for this opportunity online.
This opportunity is not published. No applications will be accepted.
Identifying the Nature of Mechanical Signalling in Bone
Although local tissue loading is probably the most important factor triggering bone remodelling, the nature of mechanical signalling is still elusive. The present study will compare different mechanical signals in bone attempting to identify the most realistic candidate.
Keywords: Bone Remodelling, Mechanical Signalling, Micro-FE Analysis, Bone Loading Estimation Algorithm, Micro-CT Imaging
Bone has the remarkable capability of adapting to mechanical forces. It is thought that this is achieved during bone remodelling where bone cells add and remove bone tissue at high and low tissue loading, respectively. We recently found supporting evidence for this hypothesis in mice (Schulte et al., PLoS ONE, 2013) and humans (Christen et al., Nat. Comm., 2014) by testing if local tissue loading and sites of bone resorption and formation correlate with each other as shown in the attached image for the human distal radius. To calculate tissue loading, micro-finite element analysis was used in combination with a bone loading estimation algorithm to define physiological external boundary conditions. Sites of remodelling were determined using a newly developed image processing method based on time-lapse in vivo imaging. However, tissue loading was expressed as strain energy density although other candidates such as strain gradients, compressive strain, or tensile principle strain might lead to an even more realistic result. The purpose of the present study is to compare these mechanical signalling options and identify the most realistic candidate.
The student will first recreate the results of the previous study (Christen et al., Nat. Comm., 2014) and thus setup and run micro-finite element analyses (ParOSol) and determine sites of remodelling using image processing methods (Scanco IPL). Then, the student will choose a set of mechanical signalling candidates and finally test which of them provides the most realistic result.
Task: 60% computational, 40% image processing
Bone has the remarkable capability of adapting to mechanical forces. It is thought that this is achieved during bone remodelling where bone cells add and remove bone tissue at high and low tissue loading, respectively. We recently found supporting evidence for this hypothesis in mice (Schulte et al., PLoS ONE, 2013) and humans (Christen et al., Nat. Comm., 2014) by testing if local tissue loading and sites of bone resorption and formation correlate with each other as shown in the attached image for the human distal radius. To calculate tissue loading, micro-finite element analysis was used in combination with a bone loading estimation algorithm to define physiological external boundary conditions. Sites of remodelling were determined using a newly developed image processing method based on time-lapse in vivo imaging. However, tissue loading was expressed as strain energy density although other candidates such as strain gradients, compressive strain, or tensile principle strain might lead to an even more realistic result. The purpose of the present study is to compare these mechanical signalling options and identify the most realistic candidate.
The student will first recreate the results of the previous study (Christen et al., Nat. Comm., 2014) and thus setup and run micro-finite element analyses (ParOSol) and determine sites of remodelling using image processing methods (Scanco IPL). Then, the student will choose a set of mechanical signalling candidates and finally test which of them provides the most realistic result.
Task: 60% computational, 40% image processing
Comparing different mechanical signalling options in bone and identifying the most realistic candidate.
Comparing different mechanical signalling options in bone and identifying the most realistic candidate.
Patrik Christen (patrik.christen@hest.ethz.ch), Institute for Biomechanics, ETH Zurich, Professorship Ralph Müller
Patrik Christen (patrik.christen@hest.ethz.ch), Institute for Biomechanics, ETH Zurich, Professorship Ralph Müller