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Quantification of lacunar morphology in healthy and aging bone using 3D ultra-resolution computed tomography and advanced computing methods
We use state-of-the-art 3D high-resolution imaging to study the properties of nanoscopic structures in bone. This project combines microCT imaging with advanced computational modelling and bone biology to advance our understanding of the mechanisms that lead to bone loss due to aging and disease.
Keywords: Bone, high resolution imaging, computational modelling, image processing, osteocytes
Bone is a complex biological material that continuously remodels itself to maintain structural integrity. This process is guided by the osteocytes, which are cells embedded within the mineralised bone in nanoscopic cavities called lacune. Osteocytes orchestrate bone formation and resorption by responding to mechanical stimuli and communicating to bone cells at the surface through a lacunocanalicular network (LCN). With aging and disease bone remodelling can be impaired, and the causes are yet to be fully understood. It is possible that the osteocytes and the overall “health” of the LCN may be impacted by aging or disease, resulting in impaired communication amongst bone cells.
The Laboratory for Bone Biomechanics uses advanced ultra-resolution computed tomography imaging (~1 μm) to visualise individual lacunae in 3D so that LCN morphology can studied. To date these techniques have been applied to specially cut samples of human iliac crest biopsies from a patient population. We wish to translate the imaging and computational techniques to investigate lacunar analyses across whole mouse vertebrae and femurs to enable in-depth study of lacunar characteristics in preclinical studies that explore the impact of aging and mechanical loading.
However, computational analysis on images of this scale of is challenging and requires efficient image processing techniques to be developed. Further, modifications to the image acquisition, data processing, and morphological analysis are needed to translate the lacunar analysis techniques to vertebral and femur samples.
Bone is a complex biological material that continuously remodels itself to maintain structural integrity. This process is guided by the osteocytes, which are cells embedded within the mineralised bone in nanoscopic cavities called lacune. Osteocytes orchestrate bone formation and resorption by responding to mechanical stimuli and communicating to bone cells at the surface through a lacunocanalicular network (LCN). With aging and disease bone remodelling can be impaired, and the causes are yet to be fully understood. It is possible that the osteocytes and the overall “health” of the LCN may be impacted by aging or disease, resulting in impaired communication amongst bone cells.
The Laboratory for Bone Biomechanics uses advanced ultra-resolution computed tomography imaging (~1 μm) to visualise individual lacunae in 3D so that LCN morphology can studied. To date these techniques have been applied to specially cut samples of human iliac crest biopsies from a patient population. We wish to translate the imaging and computational techniques to investigate lacunar analyses across whole mouse vertebrae and femurs to enable in-depth study of lacunar characteristics in preclinical studies that explore the impact of aging and mechanical loading.
However, computational analysis on images of this scale of is challenging and requires efficient image processing techniques to be developed. Further, modifications to the image acquisition, data processing, and morphological analysis are needed to translate the lacunar analysis techniques to vertebral and femur samples.
This project will focus on developing an end-to-end analysis of lacunar morphology in mouse femur and vertebra samples. The student will have the opportunity to learn how to perform high-resolution scanning using our state-of-the-art microCT system, then be responsible for adapting our computational modelling methods to perform morphological analysis on these images. Following these tasks, the student will have the opportunity to explore differences in lacunar morphology between bones and across samples obtained from mice at different ages.
The project is suited for a Master student with intermediate to expert knowledge in programming with Python, and an interest in learning about advanced medical imaging. The primary focus will be on computational analysis, but you will have the opportunity to gain some crossover experience in a wet lab setting. The student will be given access to many of our pre-developed computational tools, learn how perform microCT scans, and have access to advanced computing resources for computational analysis.
This project will focus on developing an end-to-end analysis of lacunar morphology in mouse femur and vertebra samples. The student will have the opportunity to learn how to perform high-resolution scanning using our state-of-the-art microCT system, then be responsible for adapting our computational modelling methods to perform morphological analysis on these images. Following these tasks, the student will have the opportunity to explore differences in lacunar morphology between bones and across samples obtained from mice at different ages.
The project is suited for a Master student with intermediate to expert knowledge in programming with Python, and an interest in learning about advanced medical imaging. The primary focus will be on computational analysis, but you will have the opportunity to gain some crossover experience in a wet lab setting. The student will be given access to many of our pre-developed computational tools, learn how perform microCT scans, and have access to advanced computing resources for computational analysis.
Please contact Dr. Danielle Whittier (danielle.whittier@hest.ethz.ch) or Dilara Yilmaz (dilara.yilmaz@hest.ethz.ch) if you are interested in learning more.
Please contact Dr. Danielle Whittier (danielle.whittier@hest.ethz.ch) or Dilara Yilmaz (dilara.yilmaz@hest.ethz.ch) if you are interested in learning more.