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Infrared Thermography for the Detection of Changes in Brown Adipose Tissue Activity
Published on: September 28, 2022
Infrared Thermography in Exercise Physiology: The Dawning of Exercise Radiomics
Barlo Hillen1, Daniel Pfirrmann1, Markus Nägele2
1Department of Sports Medicine, Rehabilitation and Disease Prevention, Faculty of Social Science, Media and Sport, Johannes Gutenberg University Mainz, Albert Schweitzer Straße 22, 55128, Mainz, Germany.
Abstract:
Infrared thermography (IRT) is a non-invasive tool to measure the body surface radiation temperature (Tsr). IRT is an upcoming technology as a result of recent advancements in camera lenses, detector technique and data processing capabilities. The purpose of this review is to determine the potential and applicability of IRT in the context of dynamic measurements in exercise physiology. We searched PubMed and Google Scholar to identify appropriate articles, and conducted six case experiments with a high-resolution IRT camera (640 × 480 pixels) for complementary illustration. Ten articles for endurance exercise, 12 articles for incremental exercise testing and 11 articles for resistance exercise were identified. Specific Tsr changes were detected for different exercise types. Close to physical exertion or during prolonged exercise six recent studies described "tree-shaped" or "hyper-thermal" surface radiation pattern (Psr) without further specification. For the first time, we describe the Tsr and Psr dynamics and how these may relate to physiological adaptations during exercise and illustrate the differential responsiveness of Psr to resistance or endurance exercise. We discuss how bias related to individual factors, such as skin blood flow, or related to environmental factors could be resolved by innovative technological approaches. We specify why IRT seems to be increasingly capable of differentiating physiological traits relevant for exercise physiologists from various forms of environmental, technical and individual bias. For refined analysis, it will be necessary to develop and implement standardized and accurate pattern recognition technology capable of differentiating exercise modalities to support the evaluation of thermographic data by means of radiomics.
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