Thermography and asymmetries: normative values of 950 athletes
The metric of thermal asymmetry has always been closely linked to thermographic analysis, due to its usefulness in various applications in sports and health thermography. Today we will present the symmetry results that define the normative values of a total sample of 950 healthy athletes, without pain, injury or influence factors (Escamilla-Galindo et al. 2022).
Importance of mean thermal asymmetry in thermography
The mean thermal asymmetry metric is very often used in scientific studies in both the sports and health fields, with the aim of evaluating imbalances in athletes. If the physiology of an athlete is altered due to an excessive training load, it is probable that several regions of interest have a high asymmetry. There are studies with methodologies that test this effect on other metrics (Formenti et al. 2018). In addition, we have scientific evidence that supports the relationship between thermal asymmetries and injury incidence. The applications of thermography in injury prevention, one of the most explored fields, are based on this metric (Gómez-Carmona et al. 2020).
On the other hand, when there is an injury, the physiology of the tissue is highly compromised, which usually means an increase or decrease in the temperature of that region compared to the healthy contralateral one. Or which is to say that there is a significant thermal asymmetry. Proof of this are the scientific articles on diagnosis support in the clinical world that show that in the presence of a musculoskeletal injury there is an alteration in the thermal asymmetry of the region (Sillero-Quintana et al. 2015).
With the same logic, we also have scientific evidence that supports that in non-athletic subjects, healthy and without injury, there is a tendency towards thermal symmetry (Uematsu et al. 1985; Vardasca et al. 2012). This fact is usually explained by the homeostasis mechanism, which facilitates a balance within all systems, among which we also have the thermoregulatory system.
Normative values of 950 healthy athletes: Objective and methodology
However, the present study goes a step further by demonstrating the normative values of high-performance athletes. In total, there was a sample of 950 healthy athletes from the High Performance Center in Niedersachsen (Germany). Despite the volume of athletes, their characteristics do not have much variability (age: 19.48 ± 3.81 years; height: 1.71 ± 0.07m; weight: 71.12 ± 7.57 kg).
The objective we had, represented in figure 1, was to describe the thermal asymmetries of healthy athletes in the basal state to establish thermal values of normality of the regions of the body through a protocol and a specific segmentation (following the criteria of ThermoHuman) in order to be compared with individual profiles a posteriori.
Regarding its methodology, figure 2 summarizes the details. All the data collections were carried out by the same expert, with the same camera (FLIR T530, 320×240 px resolution), in similar environmental conditions (18-25 ºC) and in a basal state, that is, before training and at least 24 hours after the last training.
The images obtained during the data collection were analyzed using the ThermoHuman software, where the data on pain, injury or influence factors, if any, were added. After processing the images, the values of thermal asymmetry, mean, minimum and maximum temperature of 80 regions of interest for each one of the athletes were automatically calculated through ThermoHuman segmentation.
Main results of the study
As previously seen in scientific evidence, in the absence of injury or influence factors, it is normal to find a balance between the regions on both sides (Uematsu, 1985; Uematsu et al. 1988; Bouzas-Marins et al. 2014). By contrast, in athletes, when there is a sports injury, thermal asymmetry is significant (Fernández-Cuevas et al. 2017). The novelty provided by this study is that a global symmetry is confirmed in athletes without pain, injury or influence factors.
More specifically, the analysis of the data gives us results in which for all the athletes in all the regions there is a global difference, or general thermal asymmetry, of 0.004 ± 0.66 ºC, as can be seen in Figure 3. The most stable regions, that is, those with less asymmetry, are the central regions of the body, such as the chest (0.008 ± 0.24 ºC), the lumbar region (0.007 ± 0.26 ºC) and the vastus medialis (0.003 ± 0.27 ºC). The interesting thing here is that we combine very small asymmetry values and quite small standard deviation values.
Within the regions with the greatest asymmetries, it should be noted that they are small and distal regions, such as the wrist (0.16 ± 0.72 ºC) or the heel (0.37 ± 3.73 ºC), where segmentation problems are more frequent. In addition, some regions had special variability, such as the neck (0.03 ± 2.10 ºC; 0.01 ± 2.04 ºC) or the feet. 0.005 ± 2.26ºC; 0.37 ± 3.73ºC). And this also has more to do with a limitation of the segmentation and the analysis method than of the technology itself.
Still, all regions, excluding the heel, are below what is significant to ThermoHuman analysis, an asymmetry of 0.3°C, as represented by our asymmetry color classification. This is very interesting to monitor the processes that exceed that number, which we consider to be outside the normative values. In this way, we can create individual profiles and compare them with normality.
These data demonstrate that in basal circumstances, without pain, injury or influence factors, the human body tends towards skin temperature symmetry (0.004ºC ± 0.66ºC), reinforcing the theory of thermal homeostasis. Therefore, thermal asymmetries measured with thermography should be considered as a reliable indicator of physiological imbalances.
In turn, these results provide normative values for comparison with the individual thermal profiles of other athletes, which can help the understanding and use of thermography for the prevention and monitoring of injuries.
Below, you have the complete presentation that was shared at the 2022 ECSS in Seville:
Bouzas Marins, J. C., Andrade Fernandes, A., Piñonosa Cano, S., Gomes Moreira, D., Souza da Silva, F., Amaral Costa, C. M., . . . Sillero-Quintana, M. (2014). Thermal body patterns for healthy Brazilian adults (male and female). Journal of Thermal Biology, 42(0), 1-8.
Escamilla-Galindo VL, Del Estal-Martínez A, Fernández-Cuevas I. (2022) Description of the thermal pattern of 950 athletes using thermography to measure skin temperature. 27th Annual Congress of the European College of Sport Sciences ECSS
Fernández-Cuevas, I. et al. Infrared thermography for the detection of injury in sports medicine. Application of infrared thermography in sports science. Springer, Cham, 2017. 81-109.
Formenti, D., Ludwig, N., Rossi, A., Trecroci, A., Alberti, G., Gargano, M., … & Caumo, A. (2018). Is the maximum value in the region of interest a reliable indicator of skin temperature?. Infrared Physics and Technology, 94, 299-304.
Gómez-Carmona, P., Fernández-Cuevas, I., Sillero-Quintana, M., Arnaiz-Lastras, J., & Navandar, A. (2020). Infrared thermography protocol on reducing the incidence of soccer injuries. Journal of sport rehabilitation, 1(aop), 1-6.)
Sillero-Quintana, M., Fernández-Jaén, T., Fernández-Cuevas, I., Gómez-Carmona, P. M., Arnaiz-Lastras, J., Pérez, M. D., & Guillén, P. (2015). Infrared thermography as a support tool for screening and early diagnosis in emergencies. Journal of Medical Imaging and Health Informatics, 5(6), 1223-1228.
Uematsu, S. (1985). Symmetry of skin temperature comparing one side of the body to the other. Thermology, 1, 4-7.
Uematsu, S., Edwin, D. H., Jankel, W. R., Kozikowski, J., & Trattner, M. (1988). Quantification of thermal asymmetry. Part 1: Normal values and reproducibility. J Neurosurg, 69(4), 552-555. doi: 10.3171/jns.1988.69.4.0552
Vardasca, R., Ring, E. F. J., Plassmann, P., & Jones, C. D. (2012). Thermal symmetry of the upper and lower extremities in healthy subjects. Thermology international, 22(2), 53-60.
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