28 ADIPOSE TISSUE DENSITY, ESTIMATED LIPID FRACTION AND WHOLE-BODY ADIPOSITY IN 6 MALE CADAVERS

High-Frequency Ultrasound Assessment of Skin and Oral Mucosa in Metabolic Syndrome Patients-A Cross-Sectional Study

Background: Exogenous factors (such as sun exposure, smoking habits, and diet) and endogenous (inflammatory status, general diseases) have a direct influence on skin and soft tissue characteristics. The study’s objective was to assess the impact of metabolic syndrome (MS) on characteristics of skin layers in sun-exposed and non-exposed maxillofacial tissues evaluated by high-frequency ultrasound (HFU), as a potential diagnosis and monitoring tool for the aging process. Material and methods: The present study included 102 subjects (24 with MS; 78 without MS). Anthropometric parameters and disease history were recorded, and blood samples were harvested in order to assess biochemical parameters of MS. Sun-exposed skin (zygomatic region) and non-exposed oral mucosa of the lower lip were assessed using HFU (DUB^® cutis, Taberna Pro Medicum) with a 22 MHz probe. Results: Patients with cardiac disease had significantly lower values for epidermis density (p = 0.002). Gender was independently linked to the aged dermis depth (p < 0.001), aged dermis no. of px (pixels) (p < 0.001), dermis depth (p < 0.001), dermis no. of px (p < 0.001), and subcutaneous tissue density (p < 0.001). Patients with MS had thinner epidermis (p = 0.008) and thinner aged dermis (p = 0.037) when compared to non-MS subjects. Conclusion: Patients with MS had thinner epidermis and a lower epidermis number of pixels in sun-exposed skin. Women had lower epidermis density and thicker dermis in sun-exposed skin. Our study showed that HFU, as a non-invasive investigation approach, is useful to diagnose and monitor the aging process in skin and oral mucosa, correlated with skin phenotype pathological conditions.

Race Performance Prediction from the Physiological Profile in National Level Youth Cross-Country Cyclists

Cross-country mountain biking is an Olympic sport discipline with high popularity among elite and amateur cyclists. However, there is a scarcity of data regarding the key determinants of performance, particularly in young cross-country cyclists. The aim of this study was to examine the physiological profile of youth national-level cross-country cyclists and to determine those variables that were able to best predict the performance in an official race. Ten youth cross-country cyclists of a national team underwent a complete evaluation that included anthropometric assessments, laboratory tests to evaluate the wattage at blood lactate thresholds and at maximal oxygen uptake (PO_VO2max), and field tests to make an in-depth power profile of the athletes. The data obtained in the above-mentioned tests was analysed along with total and partial race times during a competition belonging to the Union Cycliste Internationale (UCI) calendar. In the present study, large and statistically significant correlations (r = -0.67 to -0.95, p ≤ 0.05) were found between maximal and submaximal indices of aerobic fitness and cycling performance, especially when they were normalised to body mass. A multiple regression analysis demonstrated that the wattage at 2 mmol/L, 4 mmol/L and PO_VO2max were able to explain 82% of the variance in total race time. In summary, the results of this study support the use of maximal and submaximal indices of aerobic power as predictors of performance in youth cross-country cyclists.

In Vivo Fat Quantification: Monitoring Effects of a 6-Week Non-Energy-Restricted Ketogenic Diet in Healthy Adults Using MRI, ADP and BIA

The ketogenic diet (KD) is a very low-carbohydrate, high-fat, and adequate-protein diet that induces many metabolic adaptations when calorie intake is not limited. Its therapeutic use in a range of diseases including cancer is currently being investigated. Our objective was to firstly assess the impact of a 6-week non-energy-restricted KD on the abdominal fat distribution and the hepatic fat composition in healthy adults. Body fat distribution and composition were measured by comparing magnetic resonance imaging (MRI) and spectroscopy (MRS) results with air displacement plethysmography (ADP) and bioelectrical impedance analysis (BIA) measurements. A total of 12 subjects from the KetoPerformance study were recruited for this ancillary study. Body mass index (BMI), total mass, total fat mass, total subcutaneous mass, and subcutaneous fat mass decreased significantly. None of the MRS parameters showed a significant change during the study. Even though the average change in body weight was >2kg, no significant changes in intrahepatic lipid (IHL) content could be observed. Total fat mass and total fat-free mass derived from MRI has a strong correlation with the corresponding values derived from BIA and ADP data. BMI and the absolute fat parameter of all three modalities decreased, but there were no or only minor changes regarding the fat-free parameter. Magnetic resonance imaging provides body composition information on abdominal fat distribution changes during a ketogenic diet. This information is complementary to anthropomorphic and laboratory measures and is more detailed than the information provided by ADP and BIA measures. It was shown that there was no significant change in internal fat distribution, but there was a decrease in subcutaneous fat.

Numerical characterization of quasi-static ultrasound elastography for the detection of deep tissue injuries

Deep tissue injuries are subcutaneous regions of tissue breakdown associated with excessive mechanical pressure for extended period of time. These wounds are currently clinically undetectable in their early stages and result in severe burdens on not only the patients who suffer from them, but the health care system as well. The goal of this work was to numerically characterize the use of quasi-static ultrasound elastography for detecting formative and progressive deep tissue injuries. In order to numerically characterize the technique, finite-element models of sonographic B-mode imaging and tissue deformation were created. These models were fed into a local strain-estimation algorithm to determine the detection sensitivity of the technique on various parameters. Our work showed that quasi-static ultrasound elastography was able to detect and characterize deep tissue injuries over a range of lesion parameters. Simulations were validated using a physical phantom model. This work represents a step along the path to developing a clinically relevant technique for detecting and diagnosing early deep tissue injuries.