Measurement of subcutaneous fat tissue: reliability and comparison of caliper and ultrasound via systematic body mapping

Whole-Body Human Ultrasound Tomography

Ultrasonography is a vital component of modern clinical care, with handheld probes routinely used for a variety of applications. However, handheld ultrasound imaging is limited by factors such as the partial-body field of view, operator dependency, contact-induced distortion, and lack of transmission contrast. Here, we demonstrate a new system enabling whole-body ultrasound tomography of humans in reflection and transmission modes. To generate 2D isotropically resolved images across the entire cross-section in vivo, we use a custom 512-element circular ultrasound receiver array with a rotating ultrasonic transmitter. We demonstrate this technique in regions such as the abdomen and legs in healthy volunteers. We also showcase two potential clinical extensions. First, we readily observe subcutaneous and preperitoneal abdominal adipose distributions in our images, enabling adipose thickness assessment over the body without ionizing radiation or mechanical deformation. Second, we demonstrate an approach for rapid (seven frame-per-second) biopsy needle localization with respect to internal tissue features. These capabilities make whole-body ultrasound tomography a potential practical tool for clinical needs currently unmet by other modalities.

Practical but Inaccurate? A-Mode Ultrasound and Bioelectrical Impedance Underestimate Body Fat Percentage Compared to Dual-Energy X-ray Absorptiometry in Male College Students

Bioelectrical impedance (BIA) and ultrasound (US) have become popular for estimating body fat percentage (BF%) due to their low cost and clinical convenience. However, the agreement of these devices with the gold-standard method still requires investigation. The aim was to analyze the agreement between a gold-standard %BF assessment method with BIA and US devices. Twenty-three men (aged 30.1 ± 7.7 years, weighing 82.5 ± 14.9 kg, 1.77 ± 0.05 m tall) underwent dual-energy X-ray absorptiometry (DXA), BIA (tetrapolar) and US (three-site method) %BF assessments. Pearson and concordance correlations were analyzed. A T-test was used to compare the means of the methods, and Bland-Altman plots analyzed agreement and proportional bias. Alpha was set at <0.05. The Pearson coefficients of BIA and US with DXA were high (BIA = 0.94; US = 0.89; both p < 0.001). The concordance coefficient was high for BIA (0.80) and moderate for US (0.49). The BF% measured by BIA (24.5 ± 7.5) and US (19.4 ± 7.0) was on average 4.4% and 9.6% lower than DXA (29.0 + 8.5%), respectively (p < 0.001). Lower and upper agreement limits between DXA and BIA were -1.45 and 10.31, while between DXA and US, they were 2.01 and 17.14, respectively. There was a tendency of both BIA (p = 0.09) and US (p = 0.057) to present proportional bias and underestimate BF%. Despite the correlation, the mean differences between the methods were significant, and the agreement limits were very wide. This indicates that BIA and US, as measured in this study, have limited potential to accurately measure %BF compared to DXA, especially in individuals with higher body fat.

Skeletal muscle as a pro- and anti-inflammatory tissue: insights from children to adults and ultrasound findings

Previously regarded as a movement and posture control agent, the skeletal muscle is now recognized as an endocrine organ that may affect systemic inflammation and metabolic health. The discovery of myokines such as IL-6, released from skeletal muscle in response to physical exercise, is now one of the most recent insights. Myokines are the mediators of the balance between the pro-inflammatory and anti-inflammatory responses. This underscores the muscle function as a determinant of good health and prevention of diseases. Advances in ultrasound technology improved evaluation of muscle thickness, composition, and determining fat distribution. Combining imaging with molecular biology, researchers discovered the complicated interplay between muscle function, cytokine production and general health effects.The production of myokines with exercise showcasing the adaptability of muscles to high-stress conditions and contributing to metabolism and inflammation regulation. These findings have significant implications in order to provide improvement in metabolic and inflammatory diseases.

Employing machine learning for enhanced abdominal fat prediction in cavitation post-treatment

This study investigates the application of cavitation in non-invasive abdominal fat reduction and body contouring, a topic of considerable interest in the medical and aesthetic fields. We explore the potential of cavitation to alter abdominal fat composition and delve into the optimization of fat prediction models using advanced hyperparameter optimization techniques, Hyperopt and Optuna. Our objective is to enhance the predictive accuracy of abdominal fat dynamics post-cavitation treatment. Employing a robust dataset with abdominal fat measurements and cavitation treatment parameters, we evaluate the efficacy of our approach through regression analysis. The performance of Hyperopt and Optuna regression models is assessed using metrics such as mean squared error, mean absolute error, and R-squared score. Our results reveal that both models exhibit strong predictive capabilities, with R-squared scores reaching 94.12% and 94.11% for post-treatment visceral fat, and 71.15% and 70.48% for post-treatment subcutaneous fat predictions, respectively. Additionally, we investigate feature selection techniques to pinpoint critical predictors within the fat prediction models. Techniques including F-value selection, mutual information, recursive feature elimination with logistic regression and random forests, variance thresholding, and feature importance evaluation are utilized. The analysis identifies key features such as BMI, waist circumference, and pretreatment fat levels as significant predictors of post-treatment fat outcomes. Our findings underscore the effectiveness of hyperparameter optimization in refining fat prediction models and offer valuable insights for the advancement of non-invasive fat reduction methods. This research holds important implications for both the scientific community and clinical practitioners, paving the way for improved treatment strategies in the realm of body contouring.

A new noninvasive technique for heat-flux-based deep body thermometry together with possible estimation of thermal resistance of the skin tissue

A new noninvasive core-thermometry technique, based on the use of two heat flux sensors with different very low thermal resistances, is proposed. Thermodynamically derived equations, using a pair of skin temperatures and heat fluxes detected from the sensors, can give the estimated deep body temperature (DBT) together with thermal resistance of the skin tissue itself. The validity and accuracy of this method are firstly investigated through in vitro experiments using a tissue phantom model and, secondly, as in vivo comparisons with sublingual (Tsub) or rectal temperature (Trec) measurements in 9 volunteers, attaching the sensors around the upper sternum or the nape. Model experiments showed a good agreement between the measured and estimated temperatures, ranging from approximately 36 to 42 ℃. In vivo experiments demonstrated linear correlations between the estimated DBT and both Tsub and Trec values, though the estimated DBT was 0.13 ℃ higher than Tsub and 0.42 ℃ lower than Trec on average. The results also strongly suggested the possibility to estimate the tissue thermal resistance; this is discussed herein. Although further in vivo experiments under various environmental conditions are necessary, this method appears highly promising as an accurate, useful and convenient core-thermometry system for medical and healthcare settings.

A new approach to quantify visceral fat via bioelectrical impedance analysis and ultrasound compared to MRI

BACKGROUND

Visceral adipose tissue (VAT) has been linked to systemic proinflammatory characteristics, and measuring it accurately usually requires sophisticated instruments. This study aimed to estimate VAT applying a simpler method that uses total subcutaneous fat and total body fat (BF) measurements.

METHOD

As part of our experimental approach, the subcutaneous fat mass (SFT) was measured via US (SFTtotal), and VAT was quantified by assessing MRI data. Both parameters were added to obtain total body fat (BFcalc). Those results were then compared to values obtained from a bioelectrical impedance analysis (BFBIA). Multiple regression analyses were employed to develop a simplified sex-specific equation for SFT, which was subsequently used in conjunction with BFBIA to determine VAT (VATEq).

RESULT

We observed excellent reliability between BFBIA and BFcalc, with no significant difference in body fat values (20.98 ± 8.36 kg vs. 21.08 ± 8.81 kg, p = 0.798, ICC 0.948). VATEq_female/male revealed excellent reliability when compared to VATMRI, and no significant difference appeared (women: 0.03 ± 0.66 kg with a 95% CI ranging from -1.26 kg to 1.32 kg, p = 0.815, ICC: 0.955.; men: -0.01 ± 0.85 kg with a 95% CI ranging from -1.69 kg to 1.66 kg, p = 0.925, ICC: 0.952).

CONCLUSION

Taking an experimental approach, VAT can be determined without MRI.