Vol. 2, 2017

Original research papers

Medical Imaging


Gordana Laštovička-Medin

Pages: 198-206

DOI: 10.21175/RadProc.2017.41

More than five decades have passed since the hypothesis of thermography in breast imaging was proposed. During this time, thermography has gone from a legitimate, promising technology to one relegated to the shadows outside conventional medicine. Thermal imaging in clinical trials is still controversial issue. However even those who discard the method due to insufficient reliability of data do not validate their arguments by clear understanding of the reasons behind the inaccuracy. While thermography is not well evidenced for use as a screening tool, its use as an adjunctive imaging procedure alongside mammography should be considered, particularly for those with dense breast tissue. It is certain that images captured by digital infrared thermal imaging support the effective recognition of irregular body patterns and that they can be used as indicators of any anomaly over the time period by spotting a trend of changes in the temperature. But data has to be not only interpreted accurately but also taken carefully and the effect of surrounding environment has to be kept minimal. The identified localized patterns have to be accurately assigned to a certain anomaly in order to be treated as diagnostic method, and the evaluation method as well as interpretation have to be standardized, and method replicable. Moreover, validation of protocols, equipment, and analytical techniques is needed to be placed in the context of large, randomized trials before its use can be considered truly evidence-based. Accurate interpretation of thermal data is largely dependent upon an experienced, knowledgeable operator who understands infrared theory and heat transfer concepts, basic anatomy and physiology, and infrared equipment operation and importantly, limitations too. In this paper we integrate theory behind thermal imaging, potential of thermal imaging in clinical research and general uncertainties and misinterpretations that lead to reduced accuracy of data interpretation and feasibility of the method.
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