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Nonlinear Trimodal Regression Analysis of Radiodensitometric Distributions to Quantify Sarcopenic and Sequelae Muscle Degeneration

Nonlinear Trimodal Regression Analysis of Radiodensitometric Distributions to Quantify Sarcopenic and Sequelae Muscle Degeneration


Titill: Nonlinear Trimodal Regression Analysis of Radiodensitometric Distributions to Quantify Sarcopenic and Sequelae Muscle Degeneration
Höfundur: Edmunds, Kyle   orcid.org/0000-0002-6591-4116
Árnadóttir, Íris Dröfn   orcid.org/0000-0002-6591-4116
Gíslason, Magnús
Carraro, Ugo
Gargiulo, Paolo
Útgáfa: 2016-12
Tungumál: Enska
Umfang: 1-10
Háskóli/Stofnun: Reykjavik University
Háskólinn í Reykjavík
Svið: Tækni- og verkfræðideild (HR)
School of Science and Engineering (RU)
Deild: Institute of Biomedical and Neural Engineering (RU)
Birtist í: Computational and Mathematical Methods in Medicine;2016
ISSN: 1748-670X
1748-6718 (eISSN)
DOI: 10.1155/2016/8932950
Efnisorð: Muscles; Tomography; Eletrical stimulation; Older people; Lipid content; Insulin; Tissues; Vöðvar; Sneiðmyndatökur; Raförvun; Aldraðir; Fituefni; Insúlín
URI: https://hdl.handle.net/20.500.11815/922

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Tilvitnun:

K. J. Edmunds, Í. Árnadóttir, M. K. Gíslason, U. Carraro, and P. Gargiulo, “Nonlinear Trimodal Regression Analysis of Radiodensitometric Distributions to Quantify Sarcopenic and Sequelae Muscle Degeneration,” Computational and Mathematical Methods in Medicine, vol. 2016, Article ID 8932950, 10 pages, 2016. https://doi.org/10.1155/2016/8932950

Útdráttur:

Muscle degeneration has been consistently identified as an independent risk factor for high mortality in both aging populations and individuals suffering from neuromuscular pathology or injury. While there is much extant literature on its quantification and correlation to comorbidities, a quantitative gold standard for analyses in this regard remains undefined. Herein, we hypothesize that rigorously quantifying entire radiodensitometric distributions elicits more muscle quality information than average values reported in extant methods. This study reports the development and utility of a nonlinear trimodal regression analysis method utilized on radiodensitometric distributions of upper leg muscles from CT scans of a healthy young adult, a healthy elderly subject, and a spinal cord injury patient. The method was then employed with a THA cohort to assess pre- and postsurgical differences in their healthy and operative legs. Results from the initial representative models elicited high degrees of correlation to HU distributions, and regression parameters highlighted physiologically evident differences between subjects. Furthermore, results from the THA cohort echoed physiological justification and indicated significant improvements in muscle quality in both legs following surgery. Altogether, these results highlight the utility of novel parameters from entire HU distributions that could provide insight into the optimal quantification of muscle degeneration.

Leyfi:

Copyright © 2016 K. J. Edmunds et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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