Knee joint are the most common region of injuries in athletes, with 130 injuries (out of a total of 1101 injuries) recorded in the Rio 2016 Olympic Games (Soligard T. et al. 2017). These injuries are associated with degenerative changes due to the injury itself or due to sports practice.
One of the most common degenerations is knee osteoarthritis (OA) (Pereira D. et al. 2011). This pathology, which occurs with knee inflammation in its acute phases, may be due to a lack of knee stability, leading to a loss of congruence between joints during sports practice.
In addition, this injury is associated with other injuries such as anterior cruciate ligament (ACL) rupture. There is a higher percentage of athletes with osteoarthritis of the knee (OA) in those who have previously suffered an ACL injury, the data place them at around 52% in a 20-year follow-up after the injury compared to 39% in the population general (Peña Ayala 2007; Cinque 2018)
That is why it is a problem for athletes' health, especially those previously injured. For this reason, the control of the health of the knee through tools that allow us to know the physiological state and inflammation of said joint can help to control the processes of osteoarthritis and its associated comorbidities. This is what the IRCCS “Rizzoli Orthopedic Institute” working group proposed when investigating the control of osteoarthritis through thermography.
The researchers evaluated 40 patients (24 men and 16 women) with a mean age of 61.3 ± 9.3 years and a mean body mass index (BMI) of 25.2 ± 3.0. The evaluation consisted of a thermogram with a FLIR T1020 camera of the symptomatic knee and manual segmentation of the regions (Figure 1).
Figure 1. Image of the study with the segmentation of the knee regions.
Different questionnaires were also recorded, including the International Knee Documentation Committee (IKDC) scale and its objective and subjective scores, the PainDETECT questionnaire for the evaluation of neuropathic pain, and the visual analog pain scale (VAS).
In addition, weight, fat percentage, and demographic data were recorded.
The results show several relationships between knee temperature and the different questionnaires. Furthermore, there is a positive relationship between knee temperature and BMI and a negative relationship between age and knee temperature.
When the IKDC scores were related, it was observed that those who had worse results on the test had a higher knee temperature (Figure 2).
Figure 2. Relationship between knee temperature and IKDC scores. Reminder: (A) means normal and (D) means severely abnormal.
For the PainDETECT questionnaire, it should be noted that their scores are a continuum of the type of pain. This means that low scores are associated with one type of pain while high scores are associated with another (Figure 3).
Figure 3. Types of pain according to the result in the PainDETECT questionnaire. R. Freynhagen, R. Baron, U. Gockel, T.R. Tölle/Curr Med Res Opin, Vol.22, No. 10 (2006)
The results showed a correlation between the temperature data and the results of this questionnaire (rho = −0.319, p = 0.045). (Figure 4).
Figure 4. PainDETECT questionnaire and relationship with knee temperature.
This study demonstrated that the temperature of the region of the knee with osteoarthritis is altered by the demographic and clinical characteristics of the patients: including age, BMI, and knee and pain perception questionnaires.
Men had higher temperatures, especially those younger with a higher BMI. In addition, hyperthermia patterns were related to worse scores on the IKDC objective values. On the other hand, the lowest temperatures in the knee joint were found in the patients affected by neuropathic pain.
This sets a precedent for the study and control of the temperature of the knee region to monitor the problems associated with the degeneration of this joint using thermography.
Soligard T, Steffen K, Palmer D, et alSports injury and illness incidence in the Rio de Janeiro 2016 Olympic Summer Games: A prospective study of 11274 athletes from 207 countriesBritish Journal of Sports Medicine 2017;51:1265-1271.
Pereira, D.; Peleteiro, B.; Araújo, J.; Branco, J.; Santos, R.A.; Ramos, E. The effect of osteoarthritis definition on prevalence and incidence estimates: A systematic review. Osteoarthr. Cartil. 2011, 19, 1270–1285
Peña Ayala AH, Fernández-López JC. Prevalencia y factores de riesgo de la osteoartritis [Prevalence and risk factors in osteoarthritis]. Reumatol Clin. 2007 Oct;3 Suppl 3:S6-S12. Spanish. doi: 10.1016/S1699-258X(07)73648-3. Epub 2008 Nov 13. PMID: 21794484.
Cinque ME, Dornan GJ, Chahla J, et al. High rates of osteoarthritis develop after anterior cruciate ligament surgery: an analysis of 4108 patients. Am J Sports Med 2018;46:2011–9.
De Marziani, L.; Boffa, A.; Angelelli, L.; Andriolo, L.; Di Martino, A.; Zaffagnini, S.; Filardo, G. Infrared Thermography in Symptomatic Knee Osteoarthritis: Joint Temperature Differs Based on Patient and Pain Characteristics. J. Clin. Med. 2023
ThermoHuman has had the support of the Funds of the European Union and the Community of Madrid through the Operational Programme on Youth Employment. Likewise, ThermoHuman within the framework of the Export Initiation Program of ICEX NEXT, had the support of ICEX and the co-financing of the European Regional Development Fund (ERDF).
Thermohuman has received funding from the Centre for the Development of Industrial Technology (CDTI), in participation with the European Regional Development Fund (ERDF), for the R+D activities involved in creating a new tool, based on thermography, for the prediction and prevention of rheumatoid arthritis. See project detail.
