ArticleComputational and mathematical methods in medicine2016
Nonlinear Trimodal Regression Analysis of Radiodensitometric Distributions to Quantify Sarcopenic and Sequelae Muscle Degeneration.
Article in Computational and mathematical methods in medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Development of soft tissue asymmetry indicators to characterize aging and functional mobility.Frontiers in bioengineering and biotechnology · 2023Article
- Soft tissue radiodensity parameters mediate the relationship between self-reported physical activity and lower extremity function in AGES-Reykjavík participants.Scientific reports · 2021Article
- Testing soft tissue radiodensity parameters interplay with age and self-reported physical activity.European journal of translational myology · 2021Article
- Psoas Muscle Index Defined by Computer Tomography Predicts the Presence of Postoperative Complications in Colorectal Cancer Surgery.Medicina (Kaunas, Lithuania) · 2021Article
- Translational research on Myology and Mobility Medicine: 2021 semi-virtual PDM3 from Thermae of Euganean Hills, May 26 - 29, 2021.European journal of translational myology · 2021Article
- 30 Years of Translational Mobility Medicine: 2020 Padua Muscle Days go virtual from Euganean Hills, November 19th to 21st.European journal of translational myology · 2020Article
- Machine learning predictive system based upon radiodensitometric distributions from mid-thigh CT images.European journal of translational myology · 2020Article
- Muscle spindles of the rat sternomastoid muscle.European journal of translational myology · 2018Article
- Advanced quantitative methods in correlating sarcopenic muscle degeneration with lower extremity function biometrics and comorbidities.PloS one · 2018Article
- Mobility disorders and pain, interrelations that need new research concepts and advanced clinical commitments.European journal of translational myology · 2017Article
- The Vienna FES Interview Protocol - A mixed-methods protocol to elucidate the opinions of various individuals responsible for the provision of FES exercise.European journal of translational myology · 2017Article
- Effect of electrical stimulation on motor nerve regeneration in sciatic nerve ligated-mice.European journal of translational myology · 2017Article
- 2017Spring PaduaMuscleDays, roots and byproducts.European journal of translational myology · 2017Article
- What Can be Learned from the Time Course of Changes in Low-Frequency Stimulated Muscle?European journal of translational myology · 2017Article
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5 authors.
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Abstract
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.
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