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Quantification of Trabecular Bone Morphology using Correspondence-based Shape Modeling Techniques
Existing methods to quantify trabecular bone structure utilize unnecessary classifications and, as a result, ignore the shape-based morphology of the microstructure. In contrast, this project combines 3D morphological quantification with correspondence-based shape analysis to elucidate the trabecul
While many of the millions of distal radius fractures each year heal with minimal to no residual effects, quality of life can be severely diminished in patients with delayed or partial fracture healing (non-union). Clinically, radiographs are often used to assess fracture healing, however these images do not provide the data necessary to investigate the specific cause of non-union. Similarly, other clinical metrics, such as bone mineral density, blood-based biomarkers, and advanced imaging data, have also been investigated to better understand fracture healing, but do not yet provide the information necessary to understand fracture non-union.
Using time-lapsed 3D high-resolution (HR) computed tomography (CT) imaging data, such as HR-pQCT, the specific process of bone resorption and formation can be quantified. Here, the trabecular structure itself may provide significant insight to the remodeling process. However, existing methods to quantify trabecular structure rely on an unnecessary classification of the structure into binary categories that ignore the true shape-based morphology of the structure. Towards this end, this project proposes to quantify and analyze shape-based morphology of trabecular structure using a combination of 3D morphological definition using raybursts and correspondence-based statistical shape modeling. In the future, this technique could be applied to in-vivo time-lapse HR-pQCT images to identify the role of trabecular microstructure in both natural remodeling and fracture healing.
While many of the millions of distal radius fractures each year heal with minimal to no residual effects, quality of life can be severely diminished in patients with delayed or partial fracture healing (non-union). Clinically, radiographs are often used to assess fracture healing, however these images do not provide the data necessary to investigate the specific cause of non-union. Similarly, other clinical metrics, such as bone mineral density, blood-based biomarkers, and advanced imaging data, have also been investigated to better understand fracture healing, but do not yet provide the information necessary to understand fracture non-union. Using time-lapsed 3D high-resolution (HR) computed tomography (CT) imaging data, such as HR-pQCT, the specific process of bone resorption and formation can be quantified. Here, the trabecular structure itself may provide significant insight to the remodeling process. However, existing methods to quantify trabecular structure rely on an unnecessary classification of the structure into binary categories that ignore the true shape-based morphology of the structure. Towards this end, this project proposes to quantify and analyze shape-based morphology of trabecular structure using a combination of 3D morphological definition using raybursts and correspondence-based statistical shape modeling. In the future, this technique could be applied to in-vivo time-lapse HR-pQCT images to identify the role of trabecular microstructure in both natural remodeling and fracture healing.
This project will focus on the development and validation of a framework to objectively analyze shape-based microstructure directly from volumetric high-resolution images using 3D raybursts and correspondence-based shape modeling techniques.
This project will focus on the development and validation of a framework to objectively analyze shape-based microstructure directly from volumetric high-resolution images using 3D raybursts and correspondence-based shape modeling techniques.
Penny Atkins (penny.atkins@hest.ethz.ch), Institute for Biomechanics, ETH Zurich, Professorship Ralph Müller
Penny Atkins (penny.atkins@hest.ethz.ch), Institute for Biomechanics, ETH Zurich, Professorship Ralph Müller