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Anomalous contra-lateral radiometric asymmetry in the diabetic patient
We introduce a methodology for acquisition and analysis of infrared (IR) images, picturing the metabolic heat emission from the human skin. Then we analyze the radiometric asymmetries in the patients with DM2 in comparison to the natural asymmetries, represented by the control group. In this regard,...
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Published in: | Biomedical physics & engineering express 2019-10, Vol.5 (6), p.65015 |
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Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | We introduce a methodology for acquisition and analysis of infrared (IR) images, picturing the metabolic heat emission from the human skin. Then we analyze the radiometric asymmetries in the patients with DM2 in comparison to the natural asymmetries, represented by the control group. In this regard, we introduce three indices (TAI, SAI, TtAI) with conditions for disclosing asymmetries displayed on images acquired in passive mode (the natural thermal emission, NTE). Then, the indices are adapted for analysis of IR-images acquired in what we brand as active mode (the NTE is altered by means of a controlled external stimulus). Out of the passive mode, the TAI and TtAI indices show the best diagnostic performance, with values of sensitivity and specificity of 89% and 72%, and 83% and 78%, respectively. Instead, from the active mode analysis we get 86% of sensitivity and 83% of specificity for the TRI index. We report data obtained form IR-images of 36 patients with Diabetes Mellitus Type II (DM2) and 18 non-diabetic controls. For both groups the image acquisition is made in passive and active mode, picturing the anterior and posterior views of the lower limbs. With this analysis, we manage to unveil the contra-lateral radiometric asymmetries of the legs, along with the differences between patients and controls. Finally, we report the consistency of these indices with glucose and glycated hemoglobin (HbA1c), known to be the golden clinical variables used to diagnose DM2. |
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ISSN: | 2057-1976 2057-1976 |
DOI: | 10.1088/2057-1976/ab49f5 |