Can the body mass index influence the skin temperature of adolescents assessed by infrared thermography?

Exploring the correlation of skin temperature and body composition in athletes undergoing exhaustive physical exercise

During strenuous exercise, skin temperature (Tsk) plays an essential role in thermoregulatory processes. As indicated in the literature, its response might be influenced by body composition, among other factors. Hence, the objectives of this investigation were to determine whether there is a correlation between selected body components, specifically fat tissue and muscle tissue, and Tsk during graded exercise and recovery in athletes, and to identify which body component exhibits the strongest correlation with Tsk. Participants were grouped according to their aerobic capacity (VO2max/kg). A significant main effect was observed for the test stages (p < .001, η2 = 0.71), with Tsk decreasing from the start of the exercise, significantly decreasing at 12 km/h-1 (p < .001), and then increasing after exercise, especially within the first 5 min of recovery. Weak and non-significant effect for group/stage interaction was detected (p = .374, η2 = 0.03). A significant negative correlation was found between Tsk and both total tissue fat [%] (-0.51 < r < -0.63, p < .001) and lower limb tissue fat [%] (-0.50 < r < -0.71, p < .001) across all test stages. The correlation between Tsk and BMI was inconsistent, appearing only during the first stage of exercise and throughout recovery. No correlation was observed between Tsk and skeletal muscle mass, appendicular lean soft tissue, or relative skeletal muscle index. Endurance running to exhaustion leads to a progressive decrease in the Tsk of the lower extremity, followed by rewarming during recovery. The observed inverse correlation between adipose tissue and Tsk, along with the distinct temperature trends in groups with varying levels of fat tissue, could imply that the skin and subcutaneous tissue complex may play a more intricate role in thermal energy exchange beyond its insulating function. This implies a multifaceted involvement of these tissues in thermoregulation.

Thermal threshold for knee osteoarthritis people evaluated with infrared thermography: A scoping review

INTRODUCTION

Knee degenerative processes, such as osteoarthritis, are disabling. An early intervention is generally more effective making important a timely diagnosis. A pre-diagnosis tool could be the thermal camera that allows the detection of joint inflammation. Consequently, the objective of the present study was to evaluate the literature and propose a thermal attention threshold for infrared thermography data in people with knee osteoarthritis.

METHODS

four electronic databases were searched with specific keywords until the 25th of March 2024. Only original articles about joint inflammation due to osteoarthritis evaluated through digital infrared thermal images were included. A quality assessment analysis was performed. The attention threshold was extracted through the median of the extracted data. The findings were narratively discussed.

RESULTS

A total of 9 studies have been included after the eligibility criteria selection. The studies presented some differences in terms of acquisition protocol, thermal imaging camera, data extrapolation, and analysis. Despite these differences, the studies presented similar thermal data.

CONCLUSION

A knee thermography of or above 31.3 °C could indicate osteoarthritis, highlighting the necessity of further, more specific, and accurate analysis.

Response of skin temperature, blood ammonia and lactate during incremental exercise until exhaustion in elite athletes

The study aimed to evaluate the lower limb skin temperature (Tsk) and blood concentrations of lactate (LA) and ammonia (NH3) during exercise and recovery. Eleven elite sprint athletes (25 ± 3.4 yrs) and 11 elite endurance athletes (24.45 ± 5.4 yrs) performed an incremental running test until exhaustion. Body composition was estimated using the DXA method. Thermograms of the anterior and posterior surfaces of the lower limbs were recorded at rest, before each test stage (every 3 min, starting from 10 km h-1 and increasing by 2 km h-1), and in the 5th, 10th, 15th, 20th, and 30th minute of recovery. Endurance athletes had a higher maximum oxygen uptake than sprint athletes (5.0 ± 0.7 vs 4.3 ± 0.4 l·kg-1, p = 0.018), lower percentage of lean content (79 ± 2 vs 83 ± 2%, p < 0.001), and a higher percentage of fat content in the lower limbs (17 ± 2 vs 12 ± 2%, p < 0.001). In both groups, a significant decrease in Tsk was observed compared to resting value (endurance athletes-31.5 ± 0.6 °C; sprint athletes-32.3 ± 0.6 °C), during exercise (p < 0.001) and rewarming during recovery (p < 0.001). However, endurance athletes had a lower Tsk than sprint athletes at the exhaustion point (30.0 ± 1.1 vs 31.6 ± 0.8 °C, p < 0.05) and the pattern of change in Tsk differed between groups (p < 0.001). Tsk in the endurance athletes group decreased throughout the exercise protocol and returned more rapidly to initial values during recovery, while Tsk in the sprint group stabilised between moderate intensity and exhaustion, recovering more slowly after exercise. Both LA (endurance athletes-max 10.2 ± 1.5; sprint athletes-max 10.1 ± 1.4 mmol⋅L-1, p < 0.001) and NH3 (endurance athletes-max 75.6 ± 11.5; sprint athletes-max 76.7 ± 9.0 mmol⋅L-1, p < 0.001) increased during exercise and decreased during recovery (p < 0.001). During exercise, lower levels and slower increases in LA were observed during exercise in the endurance athletes' group (p < 0.05). A negative correlation was revealed between Tsk and fat percentage (r = -0.43 to -0.71, p < 0.05). Tsk was positively correlated with LA during recovery (r = 0.43 to 0.48, p < 0.05), and negatively during recovery (r = -0.45 to -0.54, p < 0.05). Differences between groups in maximum aerobic capacity, the pattern of change in Tsk, and the correlation between Tsk and LA suggest that individuals who decrease less Tsk during exercise and higher Tsk during recovery are those with better aerobic capacity. In addition, athletes with less body fat dissipate heat from their tissues more efficiently.

Best Practices for Body Temperature Measurement with Infrared Thermography: External Factors Affecting Accuracy

Infrared thermographs (IRTs) are commonly used during disease pandemics to screen individuals with elevated body temperature (EBT). To address the limited research on external factors affecting IRT accuracy, we conducted benchtop measurements and computer simulations with two IRTs, with or without an external temperature reference source (ETRS) for temperature compensation. The combination of an IRT and an ETRS forms a screening thermograph (ST). We investigated the effects of viewing angle (θ, 0-75°), ETRS set temperature (TETRS, 30-40 °C), ambient temperature (Tatm, 18-32 °C), relative humidity (RH, 15-80%), and working distance (d, 0.4-2.8 m). We discovered that STs exhibited higher accuracy compared to IRTs alone. Across the tested ranges of Tatm and RH, both IRTs exhibited absolute measurement errors of less than 0.97 °C, while both STs maintained absolute measurement errors of less than 0.12 °C. The optimal TETRS for EBT detection was 36-37 °C. When θ was below 30°, the two STs underestimated calibration source (CS) temperature (TCS) of less than 0.05 °C. The computer simulations showed absolute temperature differences of up to 0.28 °C and 0.04 °C between estimated and theoretical temperatures for IRTs and STs, respectively, considering d of 0.2-3.0 m, Tatm of 15-35 °C, and RH of 5-95%. The results highlight the importance of precise calibration and environmental control for reliable temperature readings and suggest proper ranges for these factors, aiming to enhance current standard documents and best practice guidelines. These insights enhance our understanding of IRT performance and their sensitivity to various factors, thereby facilitating the development of best practices for accurate EBT measurement.

Can Adipose Tissue Influence the Evaluation of Thermographic Images in Adolescents?

Infrared thermography (IRT) is a technology easy to use for clinical purposes as a pre-diagnostic tool for many health conditions. However, the analysis process of a thermographic image needs to be meticulous to make an appropriate decision. The adipose tissue is considered a potential influence factor in the skin temperature (Tsk) values obtained by IRT. This study aimed to verify the influence of body fat percentage (%BF) on Tsk measured by IRT in male adolescents. A total of 100 adolescents (16.79 ± 0.97 years old and body mass index of 18.41 ± 2.32 kg/m²) was divided into two groups through the results of a dual-energy X-ray absorptiometry analysis: obese (n = 50, %BF 30.21 ± 3.79) and non-obese (n = 50, %BF 11.33 ± 3.08). Thermograms were obtained by a FLIR T420 infrared camera and analyzed by ThermoHuman® software version 2.12, subdividing the body into seven regions of interest (ROI). The results showed that obese adolescents presented lower mean Tsk values than the non-obese for all ROIs (p < 0.05), with emphasis on the global Tsk (0.91 °C) and anterior (1.28 °C) and posterior trunk (1.18 °C), with "very large" effect size values. A negative correlation was observed in all the ROI (p < 0.01), mainly in the anterior (r = -0.71, p < 0.001) and posterior trunk (r = -0.65, p < 0.001). Tables of thermal normality were proposed for different ROIs according to the classification of obesity. In conclusion, the %BF affects the registered Tsk values in male Brazilian adolescents assessed by IRT.