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Advancing Imaging and Analysis Techn...

Sieverts, Michael John,

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Advancing Imaging and Analysis Techniques to Evaluate Osteocytes' Role in Bone Quality /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Advancing Imaging and Analysis Techniques to Evaluate Osteocytes' Role in Bone Quality // Michael John Sieverts.
Author:	Sieverts, Michael John,
Description:	1 electronic resource (97 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 86-03, Section: B.
Contained By:	Dissertations Abstracts International86-03B.
Subject:	Mechanical engineering. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30990043
ISBN:	9798384437369

Advancing Imaging and Analysis Techniques to Evaluate Osteocytes' Role in Bone Quality /
Sieverts, Michael John,

Advancing Imaging and Analysis Techniques to Evaluate Osteocytes' Role in Bone Quality /Michael John Sieverts. - 1 electronic resource (97 pages)

Source: Dissertations Abstracts International, Volume: 86-03, Section: B.

This dissertation provides four studies on advancing three-dimensional (3D) imaging and analysis techniques to evaluate bone quality. Bone is a fascinating tissue with varied composition, an intricate microstructure, and the ability to remodel dynamically. The term bone quality describes these characteristics of bone. Aspects of bone quality can be evaluated using 3D imaging techniques, such as synchrotron radiation micro-computed tomography (SRµCT) and confocal laser scanning microscopy (CLSM). This research focuses on further developing the reconstruction, processing, and analysis of images acquired through these techniques to evaluate bone quality and the osteocyte's role in maintaining bone quality. In the first study, an in situ SRµCT mechanical testing technique is developed that preserves bone's mechanical properties by combining low-dose imaging with deep learning denoising. Using this technique, digital volume correlation is performed to evaluate the internal strains of the bone and demonstrate that damage to collagen at the nanoscale impacts overall toughness at the macroscale. In the second study, an approach to analyze bone and soft tissue from a single SRµCT scan is developed using phase retrieval during image reconstruction and deep learning segmentation. This analysis indicates a relationship between the osteocyte function and adipose tissue. In the third study, spatial analysis of osteocyte remodeling and local mineral distribution is performed in SRµCT images of lactating bones. This regional analysis was possible by reconstructing the images with phase retrieval. This analysis revealed spatial preferences for osteocyte remodeling. In the fourth study, how the osteocyte communication network is impacted by diabetes is evaluated using CLSM images segmented with deep learning segmentation. Diabetes is found to reduce the density of the communication network significantly and alter its connectivity. All of these studies work together to understand better bone quality and the role of the osteocyte in bone maintenance and remodeling.

English

ISBN: 9798384437369Subjects--Topical Terms:

649730
Mechanical engineering.
Subjects--Index Terms:

3D imaging

Advancing Imaging and Analysis Techniques to Evaluate Osteocytes' Role in Bone Quality /
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245 1 0 $a Advancing Imaging and Analysis Techniques to Evaluate Osteocytes' Role in Bone Quality / $c Michael John Sieverts.
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300 $a 1 electronic resource (97 pages)
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500 $a Advisors: Acevedo, Claire Committee members: Merryweather, Andrew S.; Hochhalter, Jacob Dean; Pascucci, Valerio; Camp, Nicola J.
502 $b Ph.D. $c The University of Utah $d 2024.
520 $a This dissertation provides four studies on advancing three-dimensional (3D) imaging and analysis techniques to evaluate bone quality. Bone is a fascinating tissue with varied composition, an intricate microstructure, and the ability to remodel dynamically. The term bone quality describes these characteristics of bone. Aspects of bone quality can be evaluated using 3D imaging techniques, such as synchrotron radiation micro-computed tomography (SRµCT) and confocal laser scanning microscopy (CLSM). This research focuses on further developing the reconstruction, processing, and analysis of images acquired through these techniques to evaluate bone quality and the osteocyte's role in maintaining bone quality. In the first study, an in situ SRµCT mechanical testing technique is developed that preserves bone's mechanical properties by combining low-dose imaging with deep learning denoising. Using this technique, digital volume correlation is performed to evaluate the internal strains of the bone and demonstrate that damage to collagen at the nanoscale impacts overall toughness at the macroscale. In the second study, an approach to analyze bone and soft tissue from a single SRµCT scan is developed using phase retrieval during image reconstruction and deep learning segmentation. This analysis indicates a relationship between the osteocyte function and adipose tissue. In the third study, spatial analysis of osteocyte remodeling and local mineral distribution is performed in SRµCT images of lactating bones. This regional analysis was possible by reconstructing the images with phase retrieval. This analysis revealed spatial preferences for osteocyte remodeling. In the fourth study, how the osteocyte communication network is impacted by diabetes is evaluated using CLSM images segmented with deep learning segmentation. Diabetes is found to reduce the density of the communication network significantly and alter its connectivity. All of these studies work together to understand better bone quality and the role of the osteocyte in bone maintenance and remodeling.
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650 4 $a Biomedical engineering. $3 535387
650 4 $a Medical imaging. $3 3172799
653 $a 3D imaging
653 $a Bone quality
653 $a Deep learning
653 $a Image processing
653 $a Microstructure
653 $a Osteocyte
690 $a 0548
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710 2 $a The University of Utah. $b Mechanical Engineering. $e degree granting institution. $3 3823790
720 1 $a Acevedo, Claire $e degree supervisor.
773 0 $t Dissertations Abstracts International $g 86-03B.
790 $a 0240
791 $a Ph.D.
792 $a 2024
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