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Numerical prediction of breast skin temperature based on thermographic and ultrasonographic data in healthy and cancerous breasts

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Abstract Breast cancer is one of the most common women’s cancers, so an available diagnostic modality, particularly non-invasive, is important. Infrared thermography (IRT) is a supporting diagnostic modality. Until now,… Click to show full abstract

Abstract Breast cancer is one of the most common women’s cancers, so an available diagnostic modality, particularly non-invasive, is important. Infrared thermography (IRT) is a supporting diagnostic modality. Until now, many finite element methods (FEM) numerical models have been constructed to evaluate IRT’s diagnostic value and to relate breast skin temperature characteristics with breast structural disorder presence, particularly to distinguish between cancerous types and normal structures. However, most of the models were not based on any clinical data, except for several papers based on clinical magnetic resonance imaging (MRI) data, wherein a three-dimensional (3D) breast model was studied. In our paper, we propose a very simplified numerical two-dimensional FEM model constructed based on clinical ultrasound data of breasts, which is much cheaper and available in real-time as opposed to MRI data. We show that our numerical simulations enabled us to distinguish between types of healthy breasts in agreement with the clinical classification and with thermographic results. The numerical breast models predicted the possibility of differentiation of cancerous breasts from healthy breasts by significantly different skin temperature variation ranges. The thermal variations of cancerous breasts were in the range of 0.5 °C–3.0 °C depending on the distance of the tumor from the skin surface, its size, and the cancer type. The proposed model, due to its simplicity and the fact that it was constructed based on clinical ultrasonographic data, can compete with the more sophisticated 3D models based on MRI.

Keywords: skin temperature; breast; breast skin; based clinical; cancerous breasts

Journal Title: Biocybernetics and Biomedical Engineering
Year Published: 2020

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