Kayvan Forouhesh Tehrani1, Emily G Pendleton1, W Michael Southern2,3, Jarrod A Call1,2, Luke J Mortensen1,4. 1. Regenerative Bioscience Center, Rhodes Center for ADS, University of Georgia , Athens, GA, USA. 2. Department of Kinesiology, University of Georgia , Athens, GA, USA. 3. Currently with Department of Biochemistry, Molecular Biology, and Biophysics, University of Minnesota , Minneapolis, MN, USA. 4. School of Chemical, Materials and Biomedical Engineering, University of Georgia , Athens, GA, USA.
Abstract
Purpose: Imaging-based metrics for analysis of biological tissues are powerful tools that can extract information such as shape, size, periodicity, and many other features to assess the requested qualities of a tissue. Muscular and osseous tissues consist of periodic structures that are directly related to their function, and so analysis of these patterns likely reflects tissue health and regeneration. Methods: A method for assessment of periodic structures is by analyzing them in the spatial frequency domain using the Fourier transform. In this paper, we present two filters which we developed in the spatial frequency domain for the purpose of analyzing musculoskeletal structures. These filters provide information about 1) the angular orientation of the tissues and 2) their periodicity. We explore periodic structural patterns in the mitochondrial network of skeletal muscles that are reflective of muscle metabolism and myogenesis; and patterns of collagen fibers in the bone that are reflective of the organization and health of bone extracellular matrix. Results: We present an analysis of mouse skeletal muscle in healthy and injured muscles. We used a transgenic mouse that ubiquitously expresses fluorescent protein in their mitochondria and performed 2-photon microscopy to image the structures. To acquire the collagen structure of the bone we used non-linear SHG microscopy of mouse flat bone. We analyze and compare juvenile versus adult mice, which have different structural patterns.Conclusions: Our results indicate that these metrics can quantify musculoskeletal tissues during development and regeneration.
Purpose: Imaging-based metrics for analysis of biological tissues are powerful tools that can extract information such as shape, size, periodicity, and many other features to assess the requested qualities of a tissue. Muscular and osseous tissues consist of periodic structures that are directly related to their function, and so analysis of these patterns likely reflects tissue health and regeneration. Methods: A method for assessment of periodic structures is by analyzing them in the spatial frequency domain using the Fourier transform. In this paper, we present two filters which we developed in the spatial frequency domain for the purpose of analyzing musculoskeletal structures. These filters provide information about 1) the angular orientation of the tissues and 2) their periodicity. We explore periodic structural patterns in the mitochondrial network of skeletal muscles that are reflective of muscle metabolism and myogenesis; and patterns of collagen fibers in the bone that are reflective of the organization and health of bone extracellular matrix. Results: We present an analysis of mouse skeletal muscle in healthy and injured muscles. We used a transgenic mouse that ubiquitously expresses fluorescent protein in their mitochondria and performed 2-photon microscopy to image the structures. To acquire the collagen structure of the bone we used non-linear SHG microscopy of mouse flat bone. We analyze and compare juvenile versus adult mice, which have different structural patterns.Conclusions: Our results indicate that these metrics can quantify musculoskeletal tissues during development and regeneration.
Authors: Jacek K Pijanka; Petar P Markov; Dan Midgett; Neil G Paterson; Nick White; Emma J Blain; Thao D Nguyen; Harry A Quigley; Craig Boote Journal: J Biophotonics Date: 2019-01-10 Impact factor: 3.207
Authors: Karen M Reiser; Clayton Bratton; Diego R Yankelevich; André Knoesen; Israel Rocha-Mendoza; Jeffrey Lotz Journal: J Biomed Opt Date: 2007 Nov-Dec Impact factor: 3.170
Authors: Leila B Mostaço-Guidolin; Alex C-T Ko; Fei Wang; Bo Xiang; Mark Hewko; Ganghong Tian; Arkady Major; Masashi Shiomi; Michael G Sowa Journal: Sci Rep Date: 2013 Impact factor: 4.379
Authors: Cheryl L San Emeterio; Lauren A Hymel; Thomas C Turner; Molly E Ogle; Emily G Pendleton; William Y York; Claire E Olingy; Alan Y Liu; Hong Seo Lim; Todd A Sulchek; Gordon L Warren; Luke J Mortensen; Peng Qiu; Young C Jang; Nick J Willett; Edward A Botchwey Journal: Front Bioeng Biotechnol Date: 2021-03-19