## 7 Discussion  
The above findings provide insights into the influence of cooling on breast surface temperature and its potential application in differentiating healthy and tumor regions. This study investigates the impact of cooling on breast surface temperature measurements, focusing on healthy areas and various tumor depths. Understanding the effects of cooling on breast surface temperature could contribute to improved tumor localization and detection accuracy. When benchmarking against the simulation results from COMSOL, several observations stand out. * First, at a large tumor size and a surficial depth of T1, in the case of COMSOL simulation, very small differences are detected. However, temperature differences are well pronounced throughout the experiments without situ-cooling. Increasing the depth to T9 causes the temperature difference to disappear during the COMSOL simulation, whereas it is still well pronounced during the experiments. However, as cooling gel is applied at T9 depth, the temperature difference becomes higher. This is not the case during simulation as temperature difference was not detected at all in many cases as tumor size or breast size are changed. * Second, the observed experimental temperature difference values were maintained throughout the experiments, regardless of the tumor size (e.g., voltage applied). This is true for both cases with and without situ-cooling and for any tumor depth (see Table 1 in the Appendix A). The latter situation can probably be resolved using a higher resolution thermal camera sensor. * Finally, with situ-cooling, the temperature differences were 10.6 \({}^{\circ}\)C at T1 and 4.8 \({}^{\circ}\)C at T9, indicating a sufficient contrast is maintained at any depth between healthy and tumor regions, which can be capitalized on further to detect even smaller tumor sizes in small breasts. The experimental results have demonstrated that, at a fixed tumor size, temperature variations are observed with increasing depth. For example, as the tumor depth increases, the temperature tends to decrease, confirming the same results obtained from the simulation. This can be seen by comparing the temperature measurements at the same tumor size but at different depths. This is true for both cases of with and without situ-cooling. These temperature differences provide valuable information for potential tumor localization and differentiation. In the study reported in [30], the highest variations in skin temperature between healthy and unhealthy breasts can scope from 0.274 \({}^{\circ}\)C to 2.58 \({}^{\circ}\)C for breast sizes of 16.7 cm. With bigger breast sizes, the variations become low, as confirmed by our results. The results in [30] also confirm that the depth of tumor, its size, and its shape do affect the heat transfer across the breast layers, including the skin. Other investigations have confirmed this supposition, and found that the depth of tumor, its size, and the breast size are more significant than any other characteristics. By changing the depth and location of the tumor, (location coordinates of tumor in the breast, see Figure 9) and its size, breast surface temperature changes according to these variables (size location and depth). In addition, the numerical simulation from the COMSOL simulation model and emulation experiment both repeat the same observed results. Table 12 provides a benchmarking comparison of the various methods employed in early breast cancer detection. The methods evaluated include the Pennes bioheat equation, SmartViewTM Desktop Software application, analytical statistics, COMSOL software, FLIR Research IR Max software, and ANSYS Fluent software, among others.