Is thermal scanner losing its bite in mass screening of fever due to SARS?

• Published in: Medical physics (Lancaster) 2005-01, Vol.32 (1), p.93-97
• Main Author: Ng, Eddie Y.-K.
• Format: Article
• Language: English
• Subjects: avian flu; bio-statistics; biomedical equipment; biomedical optical imaging; biothermics; Biothermics and thermal processes in biology; Body Temperature; Body Temperature Regulation; Cameras; Computer simulation; Data analysis; Disease Outbreaks - prevention & control; Diseases; False Negative Reactions; False Positive Reactions; fever; Fever - diagnosis; General statistical methods; Humans; Image analysis; Image scanners; Inflammation; Infrared and Microwave Imaging; Infrared detectors; infrared imaging; Infrared Rays; IR system; Mass Screening - methods; medical computing; Medical imaging; microorganisms; neural nets; Neural networks and synaptic communication; Neural Networks, Computer; neurophysiology; Non‐ionizing radiation equipment and techniques; Regression Analysis; ROC; ROC Curve; SARS; sensitivity analysis; Sensitivity and Specificity; Severe Acute Respiratory Syndrome - diagnosis; skin; Skin Temperature; Temperature; Thermal analysis; Thermal imaging; Thermography; threshold temperature
• ISSN: 0094-2405; 2473-4209
• DOI: 10.1118/1.1819532

Severe acute respiratory syndrome (SARS) is a highly infectious disease caused by a coronavirus. Screening to detect a potential SARS infected person plays an important role in preventing the spread of SARS. The use of infrared thermal imaging cameras has been proposed as a noninvasive, speedy, cost effective and fairly accurate means for mass blind screening of potential SARS infected persons. Infrared thermography provides a digital image showing temperature patterns. This has been previously utilized in the detection of inflammation and nerve dysfunctions. It is believed that IR cameras can potentially be used to detect subjects with fever, the cardinal symptom of SARS, and avian influenza. The accuracy of the infrared system can, however, be affected by human, environmental, and equipment variables. It is also limited by the fact that the thermal imager measures the skin temperature and not the core body temperature. As known, the body determines a temperature as its so-called “set point” at any one time during the body temperature regulation. Fever happens if the hypothalamus detects pyrogens and then raises the set point. The time course of a typical fever can be divided into three stages. When the fever initiates, the body attempts to raise its temperature but vasoconstriction occurs to prevent heat loss through the skin. With this reason, some individuals at this stage of fever (at the rising slope and immediately after fever begins or falling slope after the fever breaks) will not be detected by the scanner if it is not designed to detect subject at the plateau of the fever (with her/his high core temperature) in particular. This paper aims to study the effectiveness of infrared systems for its application in mass blind screening to detect subjects with elevated body temperature. For this application, it is critical for thermal imagers to be able to identify febrile from normal subjects accurately. Minimizing the number of false positive and false negative cases, improves the efficiency of the screening stations. False negative results should be avoided at all costs, as letting a SARS infected person through the screening process may result in potentially catastrophic results. Various statistical methods such as linear regression, Receiver Operating Characteristics analysis, and neural networks based classification were used to analyze the temperature data collected from various sites on the face on both the frontal and side profiles. Two importan