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      Assessing subcutaneous adipose tissue by simple and portable field instruments: Skinfolds versus A-mode ultrasound measurements

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          Abstract

          Purpose

          This study compared subcutaneous adipose tissue (SAT) measurements using a skinfold caliper and Renco Lean-Meater Series 12 A-mode portable ultrasound scanner (A-US). It aimed to assess their inter- and intra-rater reliability and measure the agreement between both methods.

          Methods

          Eighty-four volunteers of different fitness levels were divided into three groups by Ʃ6 skinfolds: G1 ≤ 55 mm (n = 33 males); G2 > 55 mm (n = 32 males); G3 = 98.0 ± 52.3 mm (n = 19 females). Triceps, subscapular, biceps, iliac crest, supraspinal, abdominal, front thigh and medial calf were assessed by ultrasound and skinfolds. Two technicians for both tools performed triplicate measures. Intraclass correlation (ICC), technical error of measurement (TEM) and coefficients of variation (CVs) were applied for test-retest and inter-rater reliability. Non-Parametric statistics were used in order to establish possible statistical differences and correlation between skinfolds thickness and uncompressed subcutaneous adipose tissue thickness from ultrasound. The amount of agreement between both methods was assessed with Lin’s coefficient and a scatterplot of all site locations. A Bland-Altman plot was constructed to establish limits of agreement between groups and regression analysis was employed to assess the ability of skinfolds to explain the variance of ultrasound.

          Results

          Test-retest ICC for skinfolds and ultrasound were higher than 0.989 and 0.793, respectively. Inter-rater ICC for skinfolds was 0.999 with a 95% CI of 0.995 to 0.999 and for ultrasound was 0.755 with a much larger 95% CI of 0.622 to 0.841. TEMs (> 8.50%) and CVs (> 6.72%) compromised ultrasound reliability. Statistical differences were found in most of the analysed anatomical sites (p < 0.001) except in biceps G2 (Z = -1.150, p = 0.25) and G3 (Z = -1.309, p = 0.19). Good correlations (r > 0.7, p ≤ 0.05) were reported at almost all anatomical sites and groups except for biceps (G1: Rho = 0.26, p = 0.140) and abdominal (G2: Rho = -0.16, p = 0.38; G3: Rho = 0.43, p = 0.068). Lin’s concordance correlation coefficient registered low values of agreement between skinfolds and A-mode ultrasound (ranged from—0.009–0.646). The scatterplot and the estimated regression line drawn through the midst of all anatomical sites of the whole sample had a slope of 0.51 and R 2 adjusted = 0.62 was obtained. The combined analysis between the Bland-Altman plot and the linear regression showed that specifically in the G2 and G3 groups, as the SAT increases the differences between skinfolds and ultrasounds measurements also increases.

          Conclusions

          The Renco Lean-Meater ultrasound is not interchangeable with skinfold measures. Its utility is questionable, particularly for assessing SAT in active adult populations. Its poor test-retest and inter-rater reliability as well as the lack of agreement when compared to the skinfolds would exclude the free use of the A-mode ultrasound scanner in its hypothetical replacing of the classical calipers.

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          Most cited references31

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          Current status of body composition assessment in sport: review and position statement on behalf of the ad hoc research working group on body composition health and performance, under the auspices of the I.O.C. Medical Commission.

          Quantifying human body composition has played an important role in monitoring all athlete performance and training regimens, but especially so in gravitational, weight class and aesthetic sports wherein the tissue composition of the body profoundly affects performance or adjudication. Over the past century, a myriad of techniques and equations have been proposed, but all have some inherent problems, whether in measurement methodology or in the assumptions they make. To date, there is no universally applicable criterion or 'gold standard' methodology for body composition assessment. Having considered issues of accuracy, repeatability and utility, the multi-component model might be employed as a performance or selection criterion, provided the selected model accounts for variability in the density of fat-free mass in its computation. However, when profiling change in interventions, single methods whose raw data are surrogates for body composition (with the notable exception of the body mass index) remain useful.
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            Ultrasound as a Tool to Assess Body Fat

            Ultrasound has been used effectively to assess body fat for nearly 5 decades, yet this method is not known as well as many other body composition techniques. The purpose of this review is to explain the technical principles of the ultrasound method, explain the procedures for taking a measurement and interpreting the results, evaluate the reliability and validity of this method for measuring subcutaneous and visceral adipose tissue, highlight the advantages and limitations of ultrasound relative to other body composition methods, consider its utility to clinical populations, and introduce new body composition-specific ultrasound technology. The focus of this review is adipose, although various tissue thicknesses (e.g., muscle and bone) can be measured with ultrasound. Being a portable imaging device that is capable of making fast regional estimates of body composition, ultrasound is an attractive assessment tool in instances when other methods are limited. Furthermore, much of the research suggests that it is reliable, reproducible, and accurate. The biggest limitations appear to be a lack of standardization for the measurement technique and results that are highly dependent on operator proficiency. New ultrasound devices and accompanying software designed specifically for the purpose of body composition assessment might help to minimize these limitations.
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              Quantitative Ultrasound: Measurement Considerations for the Assessment of Muscular Dystrophy and Sarcopenia

              Introduction Diagnostic musculoskeletal ultrasound is a non-invasive, low-cost, imaging modality that may be used to characterize normal and pathological muscle tissue. Sonography has been long proposed as a method of assessing muscle damage due to neuromuscular diseases such as muscular dystrophy (Reimers et al., 1996), and more recently, changes in body and tissue composition associated with muscle wasting disorders such as sarcopenia (Pillen and van Alfen, 2011). The use of quantitative ultrasound as an adjunct diagnostic procedure has different technical challenges than the traditional use of ultrasound in clinical medicine. Examiner-dependent technique and variation are critical considerations when assessing the presence of muscle atrophy via tissue dimension estimates using muscle thickness measures, or when quantifying pathological changes in muscle quality via estimates of echointensity using grayscale analysis. Understanding both the promise of quantitative ultrasound as an assessment tool for muscle disorders and the known threats to measurement validity may foster greater adoption of this imaging modality in the management of muscular dystrophy and sarcopenia. Diagnostic Ultrasound Utilization in the Management of Muscular Dystrophy and Sarcopenia: Similarities and Differences in Approach Common morphological features Muscular dystrophy is a broad term that encompasses a disease group marked by progressive skeletal muscle weakness, atrophy, and myofiber degeneration with heterogeneous genetic etiologies that include epigenetic, monogenic, and repeat expansion abnormalities (Leung and Wagner, 2013). Muscular dystrophy affects both children and adults, which reflects its wide ranging phenotypic expression. In contrast, many investigators regard sarcopenia as an age-related condition denoted by a loss of lean body mass (LBM) with diminished muscle strength or functional performance (Newman et al., 2003; Cruz-Jentoft et al., 2010; Morley et al., 2011). However, it is important to note that a more expansive view of an “all cause” designation for muscle impairment, i.e., myopenia or skeletal muscle function deficit, has been recognized as an approach to nosology that may serve to limit the confounding effect of incongruent definitions, and facilitate the discovery of linkages among apparently disparate forms of muscle dysfunction (Fearon et al., 2011; von Haehling et al., 2012; Correa-de-Araujo and Hadley, 2014). Muscular dystrophy is recognized as a group of diseases, whereas sarcopenia is widely regarded as a geriatric syndrome. Nevertheless, it has been proposed that these two muscle disorders have some common morphological features such as the centralization of sarcolemic nuclei, atrophic groups of muscle fibers, and excessive variation of muscle fiber size (Edström et al., 2007; Malatesta, 2012). Furthermore, individuals with muscular dystrophy or sarcopenia may exhibit excessive intramuscular adipose tissue, intramyocellular triglyceride levels, and non-contractile infiltrates (Pillen et al., 2003; Miljkovic-Gacic et al., 2008; Jansen et al., 2012). Therefore, sonographic measures of echointensity for the purpose of tissue composition estimates, and digital caliper measures of tissue dimensions to assess muscle atrophy are both key elements of the ultrasound assessment of muscular dystrophy and sarcopenia (Pillen and van Alfen, 2011; Tieleman et al., 2012; Janssen et al., 2014). Condition-specific approach to diagnostic ultrasound In muscular dystrophies, quantitative ultrasound has been frequently proposed for Duchenne muscular dystrophy (DMD) (Pillen et al., 2003; Scholten et al., 2003; Jansen et al., 2012). The measurement of echointensity using grayscale histogram analysis has been used as a proxy measure for the increased non-contractile features associated with the pathologic muscle changes that may result in DMD. Jansen et al. (2012) reported that echointensity values were significantly associated with ambulation status, functional performance, and hand-held dynamometry peak force values in children with DMD. The observed standardized response mean (SRM) for their echointensity values over a 1-year period was 0.77 for their summed scores, with the lower extremities (SRM = 0.79–0.89) exhibiting greater responsiveness in comparison with the upper extremities (SRM = 0.35–0.36). Additionally, Pillen et al. (2007) have shown that echointensity and muscle thickness values have diagnostic utility as supported by the demonstrated discriminative validity of quantitative ultrasound among children suspected of having a neuromuscular disorder. Moreover, in some instances, M-mode ultrasound may have advantages over electromyography for the assessment of muscle fasciculations, which is a clinical feature of some forms of muscular dystrophy and myopathy (Walker et al., 1990; Scheel et al., 1997; Pillen and van Alfen, 2011). The use of quantitative ultrasound for the assessment of sarcopenia has been previously proposed (Pillen and van Alfen, 2011), but this approach has not been embraced by the largest international societies that issue position stands and consensus statements regarding the diagnostic criteria for sarcopenia (Cruz-Jentoft et al., 2010; Morley et al., 2011; Studenski et al., 2014). Less developmental work has been completed concerning the use of ultrasound in the assessment of age-related muscle changes in comparison to more well-known approaches involving dual-energy X-ray absorptiometry (DXA), computed tomography (CT), or magnetic resonance imaging (MRI), bioelectrical impedance analysis (BIA), and other anthropometric-based methods. However, important foundational research concerning the use of ultrasound to determine body composition has been completed, which merits the attention of clinicians and investigators interested in the diagnosis and management of sarcopenia. Previous study findings suggest that ultrasound LBM estimates have concurrent validity with MRI (Abe et al., 1994) and hydrodensitometry (Sanada et al., 2006) in Japanese adults. In the study by Abe et al. (1994), a nine-site anatomical model for ultrasound-derived LBM displayed moderate to strong relationships with MRI muscle density values (r = 0.83–0.96 in men, r = 0.53–0.91 in women, n = 72, 18–61 years of age, p  15% decrease in echointensity. While our use of automated image capture and a muscle mimetic phantom are primarily for testing and training purposes, the custom feedback-augmented sound transducer interface is portable and may used to guide free-hand ultrasound imaging. Figure 1 Changes in serial sonographic image characteristics based on examiner force and sound transducer orientation. (A–C) Depict transverse views of a muscle tissue mimetic phantom with a progressive magnitude of stress imposed on the phantom surface by the sound transducer. The material deformation (thickness, centimeter) secondary to the stress progression was as follows: (A) 3.78 cm, (B) 3.45 cm, and (C) 3.21 cm. (D–F) Depict similar sonographic views as the preceding panels. The echointensity observed in the serial images is based on a progressively increasing cranial/caudal tilt angle of the sound transducer applied to the phantom surface. The changes in echointensity (grayscale, unitless, 0–255) secondary to the angle progression were as follows: (D) 56.64, (E) 48.10, and (F) 36.90. (All images were acquired using a 6 MHz linear array sound transducer and a muscle mimetic phantom with anechoic gel via automated image capture by the Kuka LWA robot.) Adoption of Quantitative Ultrasound in the Assessment of Muscular Dystrophy and Sarcopenia Qualitative diagnostic ultrasound is often focused on the identification and subjective description of an anatomical structure or pathological tissue anomaly. Sonographers frequently use variable levels of force and sound transducer angle to obtain images of deep structures with sufficient resolution for clinical use. In contrast, quantitative ultrasound is generally dependent on the examiner exerting minimal stress on the tissue or structure of interest, and using consistent transducer orientation to attain reliable serial or comparative measures. Therefore, the use of calibration phantoms and force-feedback-augmented ultrasound may be viable methods of providing operator training and aiding real-time ultrasound measurement consistency. The constraints associated with quantitative ultrasound tend to limit this form of assessment to superficial tissues (Pillen and van Alfen, 2011), and additional normative datasets are needed to facilitate the interpretation of cross-sectional data – particularly for older adults with sarcopenia. Also, while muscle thickness measures may be fairly uniform across ultrasound platforms, echointensity values require a correction factor for comparisons involving different ultrasound machines (Zaidman et al., 2010). Notably, qualitative ultrasound has an important role in the management of neuromuscular disease as variable examiner-force and transducer orientation is needed to locate focal areas of hyperechoic tissue for potential biopsy sites (Pillen et al., 2007). Despite these limitations and contingencies, quantitative ultrasound remains a useful clinical and research imaging option to characterize skeletal muscle in muscular dystrophy and sarcopenia. This imaging modality provides a non-invasive, inexpensive method to assess muscle morphology and estimate tissue and body composition without the use of ionizing radiation. Attention to factors such as imaging site location, patient positioning, examiner training, the standardization of specific assessment techniques, and the optimal use of imaging feedback may aid the wider adoption of sonography for the management of muscle disorders. Conflict of Interest Statement The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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                Author and article information

                Contributors
                Role: Data curationRole: Formal analysisRole: Writing – original draft
                Role: ConceptualizationRole: Project administrationRole: Visualization
                Role: Data curationRole: MethodologyRole: Project administrationRole: Writing – review & editing
                Role: Formal analysisRole: Methodology
                Role: Formal analysisRole: Investigation
                Role: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: SupervisionRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                29 November 2018
                2018
                : 13
                : 11
                : e0205226
                Affiliations
                [1 ] INEFC-Barcelona Sports Sciences Research Group, Institut Nacional d’Educació Física de Catalunya (INEFC), University of Barcelona, Barcelona, Spain
                [2 ] Department of Experimental Sciences and Technology, University of Vic, Vic, Spain
                [3 ] Universidad Católica San Antonio de Murcia (UCAM), Murcia, Spain
                University of Maiduguri College of Medical Sciences, NIGERIA
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0002-2184-2720
                Article
                PONE-D-17-27673
                10.1371/journal.pone.0205226
                6264474
                30496211
                56410cf4-d239-4988-80c2-e686d28bd5d5
                © 2018 Pérez-Chirinos Buxadé et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 24 July 2017
                : 21 September 2018
                Page count
                Figures: 2, Tables: 3, Pages: 13
                Funding
                The authors received no specific funding for this work.
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