Titill: | Nonlinear Trimodal Regression Analysis of Radiodensitometric Distributions to Quantify Sarcopenic and Sequelae Muscle Degeneration |
Höfundur: |
|
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 (IBNE) (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 |
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.
|