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Diabetic Bone Mechanobiology
We use high-resolution patient imaging to monitor bone’s mechanically driven remodelling process. In FIDELIO, we are now working with clinicians at the University of Sheffield and computer scientists at IBM to improve the care of diabetic patients.
Keywords: Bone Biology, Bone Mechanics, Mechanobiology, Clinical Research, Diabetes, Tomographic Imaging
In a healthy adult, the body’s skeleton fully regenerates — or remodels — itself about every three to five years to maintain its strength. At the microscopic level, this process is orchestrated by cells, called osteocytes, which can sense and respond to local mechanical forces. Osteocytes direct bone-forming cells to regions where mechanical stimulations are high, and bone resorbing cells to areas where the stimulus is low. Through this process, excess bone tissue is removed, and new tissue is added where needed to maintain a metabolic balance.
Scientists have recently observed that diabetes may negatively impact our bone health and reduce bone strength. To unravel the underlying reasons, we have developed novel methods that enable monitoring of local changes in the bone microstructure over time. Utilizing one of the world’s most powerful supercomputers at the Swiss National Supercomputing Centre (CSCS), this was possible at such high spatial resolution that cellular behaviour of the mechanobiological remodelling process could be studied.
There are, however, technological challenges that prevent the use of these techniques in clinical studies. Although these computations are fast on supercomputers, they are still too slow and cumbersome to run on computer systems available within the clinics. In FIDELIO, we work with IBM to push bone imaging and computational methods for bone remodelling studies from bench (supercomputer) to the bedside (clinical computing) in the hospital environment. Ultimately, these precise diagnostic tools may be used to tailor medical treatment of diabetic patients to bone health individually.
A project can be designed for the student’s personal interest. Possible areas are AI Computer Vision & Deep Learning (e.g. Image to Image translation, Classification), Agent-based Multiphysics models, or Finite Element Analysis-based projects. Some projects may require advanced expert or python knowledge; however, students without any prior experience are welcome to apply!
In a healthy adult, the body’s skeleton fully regenerates — or remodels — itself about every three to five years to maintain its strength. At the microscopic level, this process is orchestrated by cells, called osteocytes, which can sense and respond to local mechanical forces. Osteocytes direct bone-forming cells to regions where mechanical stimulations are high, and bone resorbing cells to areas where the stimulus is low. Through this process, excess bone tissue is removed, and new tissue is added where needed to maintain a metabolic balance.
Scientists have recently observed that diabetes may negatively impact our bone health and reduce bone strength. To unravel the underlying reasons, we have developed novel methods that enable monitoring of local changes in the bone microstructure over time. Utilizing one of the world’s most powerful supercomputers at the Swiss National Supercomputing Centre (CSCS), this was possible at such high spatial resolution that cellular behaviour of the mechanobiological remodelling process could be studied.
There are, however, technological challenges that prevent the use of these techniques in clinical studies. Although these computations are fast on supercomputers, they are still too slow and cumbersome to run on computer systems available within the clinics. In FIDELIO, we work with IBM to push bone imaging and computational methods for bone remodelling studies from bench (supercomputer) to the bedside (clinical computing) in the hospital environment. Ultimately, these precise diagnostic tools may be used to tailor medical treatment of diabetic patients to bone health individually.
A project can be designed for the student’s personal interest. Possible areas are AI Computer Vision & Deep Learning (e.g. Image to Image translation, Classification), Agent-based Multiphysics models, or Finite Element Analysis-based projects. Some projects may require advanced expert or python knowledge; however, students without any prior experience are welcome to apply!
Projects will be designed to provide an opportunity to develop more in-depth knowledge and understanding of bone mechano-biology and, as part of your education, have the goal to boost your development and enable you to take ownership of your learning! You will learn how to use state of the art high-resolution bone imaging and apply computational methods to the resulting 3D patient bone geometries. Finally, you will interpret the results in the light of a contemporary mechanobiological understanding.
Projects will be designed to provide an opportunity to develop more in-depth knowledge and understanding of bone mechano-biology and, as part of your education, have the goal to boost your development and enable you to take ownership of your learning! You will learn how to use state of the art high-resolution bone imaging and apply computational methods to the resulting 3D patient bone geometries. Finally, you will interpret the results in the light of a contemporary mechanobiological understanding.
Please contact me via email with your interests and expectations; I am certain we will be able to find a good project for you: matthias.walle@hest.ethz.ch
Projects can be conducted remotely. You will be provided with the necessary resources, tools and support throughout your project.
Please contact me via email with your interests and expectations; I am certain we will be able to find a good project for you: matthias.walle@hest.ethz.ch
Projects can be conducted remotely. You will be provided with the necessary resources, tools and support throughout your project.