Infrared Thermography for Measuring Elevated Body Temperature: Clinical Accuracy, Calibration, and Evaluation

Abstract

Infrared thermographs (IRTs) implemented according to standardized best practices have shown strong potential for detecting elevated body temperatures (EBT), which may be useful in clinical settings and during infectious disease epidemics. However, optimal IRT calibration methods have not been established and the clinical performance of these devices relative to the more common non-contact infrared thermometers (NCITs) remains unclear. In addition to confirming the findings of our preliminary analysis of clinical study results, the primary intent of this study was to compare methods for IRT calibration and identify best practices for assessing the performance of IRTs intended to detect EBT. A key secondary aim was to compare IRT clinical accuracy to that of NCITs. We performed a clinical thermographic imaging study of more than 1000 subjects, acquiring temperature data from several facial locations that, along with reference oral temperatures, were used to calibrate two IRT systems based on seven different regression methods. Oral temperatures imputed from facial data were used to evaluate IRT clinical accuracy based on metrics such as clinical bias (Δcb), repeatability, root-mean-square difference, and sensitivity/specificity. We proposed several calibration approaches designed to account for the non-uniform data density across the temperature range and a constant offset approach tended to show better ability to detect EBT. As in our prior study, inner canthi or full-face maximum temperatures provided the highest clinical accuracy. With an optimal calibration approach, these methods achieved a Δcb between ±0.03 °C with standard deviation (σΔcb) less than 0.3 °C, and sensitivity/specificity between 84% and 94%. Results of forehead-center measurements with NCITs or IRTs indicated reduced performance. An analysis of the complete clinical data set confirms the essential findings of our preliminary evaluation, with minor differences. Our findings provide novel insights into methods and metrics for the clinical accuracy assessment of IRTs. Furthermore, our results indicate that calibration approaches providing the highest clinical accuracy in the 37–38.5 °C range may be most effective for measuring EBT. While device performance depends on many factors, IRTs can provide superior performance to NCITs.

The Use of Thermography as an Auxiliary Method for Monitoring Convalescence after Facelift Surgery: A Case Study

“…It has been proved that inner canthi (palpebral commissures) are considered to be optimal locations for non-contact temperature measurement. Perfused by the internal carotid artery, they are typically the warmest regions on the face and have high stability and strong correlation with internal body temperature [ 26 , 27 , 28 , 29 ].…”

Temperature thresholds and screening of febrile people by non-contact measurement of the face using infrared thermography – A methodology proposal

“…Although some authors claim that it is possible and others correlate ROI surface temperatures with core body temperature [ 32 , 39 , 65 ], this research team chose to analyze the temperature of each ROI separately, without correlating them with core body temperature, since the team intends to embed this method to other algorithms developed, as well as further procedures under development in a single device. This proposal eliminates a data processing stage, decreasing the combined uncertainty of the final result, as well as the computational effort.…”

Detecting Essential Landmarks Directly in Thermal Images for Remote Body Temperature and Respiratory Rate Measurement With a Two-Phase System

“…This may have a few potential causes. First, the FLIR Vue Pro camera is designed for drone image retrieval (https://www.flir.com/products/vue-pro/) and may not be a good choice for short-distance medical imaging, whereas two of the three IRTs used in this study have been evaluated for medical use [14], [16], [47]. Also, the thermal images we collected store raw temperature information.…”

“…IRTs detect infrared energy emitted from an object's surface and convert it to a temperature distribution image. Recent studies have demonstrated that IRT can effectively detect subjects with an elevated BT [14], [16]. While remote estimation of RR can be achieved through visible-light videos [17], there have been some efforts in this area using IRTs [10], [15].…”

“…Many studies have also shown that the inner canthus temperature has a good correlation with internal BT. [14], [16], [20], [21] On the other hand, the nostril regions in thermal images are commonly used to calculate RR [10], [15]. However, it is more difficult to accurately identify the inner canthi and nostrils in thermal images, which appear blurred due to the heat flow in objects and relatively low resolution of IRT sensors, than in visible-light images, which are rich with exploitable features like crisp edges and texture [22].…”