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      Assessing reliability and validity of different stiffness measurement tools on a multi-layered phantom tissue model

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          Abstract

          Changes in the mechanical properties (i.e., stiffness) of soft tissues have been linked to musculoskeletal disorders, pain conditions, and cancer biology, leading to a rising demand for diagnostic methods. Despite the general availability of different stiffness measurement tools, it is unclear as to which are best suited for different tissue types and the related measurement depths. The study aimed to compare different stiffness measurement tools’ (SMT) reliability on a multi-layered phantom tissue model (MPTM). A polyurethane MPTM simulated the four layers of the thoracolumbar region: cutis (CUT), subcutaneous connective tissue (SCT), fascia profunda (FPR), and erector spinae (ERS), with varying stiffness parameters. Evaluated stiffness measurement tools included Shore Durometer, Semi-Electronic Tissue Compliance Meter (STCM), IndentoPRO, MyotonPRO, and ultrasound imaging. Measurements were made by two independent, blinded examiners. Shore Durometer, STCM, IndentoPRO, and MyotonPRO reliably detected stiffness changes in three of the four MPTM layers, but not in the thin (1 mm thick) layer simulating FPR. With ultrasound imaging, only stiffness changes in layers thicker than 3 mm could be measured reliably. Significant correlations ranging from 0.70 to 0.98 (all p < 0.01) were found. The interrater reliability ranged from good to excellent (ICC(2,2) = 0.75–0.98). The results are encouraging for researchers and clinical practitioners as the investigated stiffness measurement tools are easy-to-use and comparatively affordable.

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          Statistical Power Analysis for the Behavioral Sciences

          Statistical Power Analysis for the Behavioral Sciences, Revised Edition emphasizes the importance of statistical power analysis. This edition discusses the concepts and types of power analysis, t test for means, significance of a product moment rs, and differences between correlation coefficients. The test that a proportion is .50 and sign test, differences between proportions, and chi-square tests for goodness of fit and contingency tables are also elaborated. This text likewise covers the F tests of variance proportions in multiple regression/correlation analysis and computational procedures. This publication is intended for behavioral and biosocial scientists who use statistical inference, but also serves as a supplementary textbook for intermediate level courses in applied statistics in behavioral/biosocial science.
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            Global low back pain prevalence and years lived with disability from 1990 to 2017: estimates from the Global Burden of Disease Study 2017

            Background Low back pain (LBP) is a common musculoskeletal problem globally. Updating the prevalence and burden of LBP is important for researchers and policy makers. This paper presents, compares and contextualizes the global prevalence and years lived with disability (YLDs) of LBP by age, sex and region, from 1990 to 2017. Methods Data were extracted from the GBD (the Global Burden of Disease, Injuries, and Risk Factors Study) 2017 Study. Age, sex and region-specific analyses were conducted to estimate the global prevalence and YLDs of LBP, with the uncertainty intervals (UIs). Results The age-standardized point prevalence of LBP was 8.20% (95% UI: 7.31–9.10%) in 1990 and decreased slightly to 7.50% (95% UI: 6.75–8.27%) in 2017. The prevalent numbers of people with LBP at any one point in time in 1990 was 377.5 million, and this increased to 577.0 million in 2017. Age-standardized prevalence of LBP was higher in females than males. LBP prevalence increased with age, and peaked around the ages of 80 to 89 years, and then decreased slightly. Global YLDs were 42.5 million (95% UI: 30.2 million–57.2 million) in 1990 and increased by 52.7% to 64.9 million (95% UI: 46.5 million–87.4 million) in 2017. YLDs were also higher in females than males and increased initially with age; they peaked at 35–39 years of age in 1990, before decreasing, whereas in 2017, they peaked at 45–49 years of age, before decreasing. Western Europe had the highest number of LBP YLDs. Conclusions Globally, LBP is the leading global cause of YLDs. Greater attention is urgently needed to mitigate this increasing burden and the impact it is having on health and social systems.
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              Ultrasound Elastography: Review of Techniques and Clinical Applications

              Elastography-based imaging techniques have received substantial attention in recent years for non-invasive assessment of tissue mechanical properties. These techniques take advantage of changed soft tissue elasticity in various pathologies to yield qualitative and quantitative information that can be used for diagnostic purposes. Measurements are acquired in specialized imaging modes that can detect tissue stiffness in response to an applied mechanical force (compression or shear wave). Ultrasound-based methods are of particular interest due to its many inherent advantages, such as wide availability including at the bedside and relatively low cost. Several ultrasound elastography techniques using different excitation methods have been developed. In general, these can be classified into strain imaging methods that use internal or external compression stimuli, and shear wave imaging that use ultrasound-generated traveling shear wave stimuli. While ultrasound elastography has shown promising results for non-invasive assessment of liver fibrosis, new applications in breast, thyroid, prostate, kidney and lymph node imaging are emerging. Here, we review the basic principles, foundation physics, and limitations of ultrasound elastography and summarize its current clinical use and ongoing developments in various clinical applications.
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                Author and article information

                Contributors
                Robert.Schleip@tum.de
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                16 January 2023
                16 January 2023
                2023
                : 13
                : 815
                Affiliations
                [1 ]GRID grid.5330.5, ISNI 0000 0001 2107 3311, Department of Sport Science and Sport, , Friedrich-Alexander Universität Erlangen-Nürnberg, ; Erlangen, Germany
                [2 ]GRID grid.6936.a, ISNI 0000000123222966, Conservative and Rehabilitative Orthopedics, Department of Sport and Health Sciences, , Technical University of Munich, ; Munich, Germany
                [3 ]GRID grid.9026.d, ISNI 0000 0001 2287 2617, Department of Sports Medicine, Faculty for Psychology and Human Movement Science, Institute for Human Movement Science, , University of Hamburg, ; Hamburg, Germany
                [4 ]GRID grid.466330.4, ISNI 0000 0005 0484 5964, Department for Medical Professions, , Diploma Hochschule, ; Bad Sooden-Allendorf, Germany
                [5 ]Osteopathic Research Institute, Osteopathie Schule Deutschland, Hamburg, Germany
                [6 ]GRID grid.27593.3a, ISNI 0000 0001 2244 5164, Department for Physical Activity in Public Health, Institute of Movement and Neurosciences, , German Sport University Cologne, ; Cologne, Germany
                [7 ]GRID grid.7520.0, ISNI 0000 0001 2196 3349, Department of Movement Sciences, , University of Klagenfurt, ; Klagenfurt, Austria
                [8 ]GRID grid.7839.5, ISNI 0000 0004 1936 9721, Institute of Occupational, Social and Environmental Medicine, , Goethe University, ; Frankfurt, Frankfurt/Main, Germany
                [9 ]GRID grid.462844.8, ISNI 0000 0001 2308 1657, Université de Technologie de Compiègne, CNRS UMR 7338, Biomechanics and Bioengineering Laboratory, , Sorbonne University, ; Compiègne, France
                [10 ]Charkiv National Medical University, Charkiv, Ukraine
                [11 ]SRH Hospital, Sigmaringen, Germany
                [12 ]GRID grid.6582.9, ISNI 0000 0004 1936 9748, Experimental Anaesthesiology, , Ulm University, ; Ulm, Germany
                Article
                27742
                10.1038/s41598-023-27742-w
                9842673
                36646734
                e77c13f4-fff4-4741-823f-334ff8a2f5e9
                © The Author(s) 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 6 September 2022
                : 6 January 2023
                Funding
                Funded by: Technische Universität München (1025)
                Categories
                Article
                Custom metadata
                © The Author(s) 2023

                Uncategorized
                preclinical research,skeletal muscle
                Uncategorized
                preclinical research, skeletal muscle

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