Three-dimensional numerical evaluation of skin surface thermal contrast by application of hypothermia at different depths and sizes of the breast tumor.

BACKGROUND AND OBJECTIVE: Thermal procedures can provide improvements in the thermal contrast of thermographic images in an attempt to diagnose early cases of breast cancer. This work aims to analyze the thermal contrast of different stages and depths of breast tumors from hypothermia treatment using an active thermography analysis. The influence of variation in metabolic heat generation and adipose tissue composition on thermal contrasts is also analyzed. METHODS: The proposed methodology was based on the solution of the Pennes equation for a three-dimensional model similar to the real anatomy of the breast by commercial software COMSOL Multiphysics. The thermal procedure consists of three steps: Stationary, hypothermia and thermal recovery. During hypothermia, the boundary condition of the external surface was replaced by a constant temperature of 0, 5, 10, and 15 ∘C, simulating a gel pack, for cooling times of up to 20 min. In the thermal recovery, after the removal of the cooling, the breast was submitted again to the condition of natural convection on the external surface. RESULTS: Thermal contrasts in superficial tumors, for all hypothermia resulted in improvements in thermographs. For smallest tumor, the use of high resolution and sensitive thermal imaging cameras to acquire this thermal change may be necessary. For tumor of diameter of 10 cm, cooling from 0 ∘C can increase the thermal contrast by up to 136% compared to the passive thermography. Analyzes with deeper tumors showed very small temperature variations. Even so, the thermal contrast gain in cooling at 0 ∘C for the tumor with a diameter of 1 cm reached 37% in relation to passive thermography. CONCLUSIONS: Thus, this work contributes as an important tool in the analysis of the appropriate use of hypothermia for different cases in early stages of breast cancer, considering that long times are needed to obtain the best thermal contrast.

First report on quality and purity assessment of sweet almond oil in Brazilian body oils by gas chromatography and mass spectrometry.

Sweet almond oil is a raw material with high-added value used in different products. Then, the aim of this study is to evaluate the quality and purity of 10 body oils based on sweet almond oils currently available in the Brazilian market. Fatty acid composition and triacylglycerol (TAG) profile were determined by gas chromatography with flame ionization detector (GC-FID) and atmospheric solids analysis probe mass spectrometry (ASAP-MS), respectively. The authenticity of samples was assessed using an analytical curve equation. Soybean oil was chosen as the adulterant because it is the cheapest vegetable oil commercialized in Brazil. Hierarchical clustering analysis (HCA) in conjunction with ASAP-MS classified product samples according to the type of vegetable oil (soybean and sweet almond oils). The addition of soybean oil (8.79% to 99.70%) was confirmed in samples. However, only two samples stated in their label the presence of soybean oil as an ingredient. These findings highlight the need for better oversight by regulatory bodies to ensure that consumers acquire high quality and authentic products based on equally high quality and purity of sweet almond oils.

Breast tumor localization using skin surface temperatures from a 2D anatomic model without knowledge of the thermophysical properties.

Breast cancer is the second most common type of cancer among women after nonmelanoma skin cancer. Use of mammography, the main method to diagnose the disease, has several limitations in parts of the population. The primary goal of this work was to detect and localize the geometric centers of mammary tumors using only superficial temperatures of the breast skin. The 2D anatomic geometry of the breast was simulated using the commercial software COMSOL to obtain the distribution of skin temperature in the three main types of breast cancer. Random errors of  ±â€¯2% were added to the simulated temperatures. The temperature variation caused by each type of cancer on the healthy tissue was correlated with auxiliary temperature profiles. These auxiliary temperature profiles were obtained with no prior knowledge of the thermophysical properties of the tumor apart from the mean values for thermal conductivity and blood perfusion of the layers of healthy breast tissue. The results showed that the maximum error for geometric center estimation was 0.32 cm for invasive lobular carcinoma, with a diameter of 1 cm, positioned 5 cm from the skin surface. Thus, this work contributes to studies aiming to improve the use of infrared thermography for early breast cancer diagnosis, as the results showed that localization of tumors using only superficial temperature profiles does not require prior knowledge of the thermophysical properties of the tissues.

Machine Learning and Infrared Thermography for Fiber Orientation Assessment on Randomly-Oriented Strands Parts.

The use of fiber reinforced materials such as randomly-oriented strands has grown in recent years, especially for manufacturing of aerospace composite structures. This growth is mainly due to their advantageous properties: they are lighter and more resistant to corrosion when compared to metals and are more easily shaped than continuous fiber composites. The resistance and stiffness of these materials are directly related to their fiber orientation. Thus, efficient approaches to assess their fiber orientation are in demand. In this paper, a non-destructive evaluation method is applied to assess the fiber orientation on laminates reinforced with randomly-oriented strands. More specifically, a method called pulsed thermal ellipsometry combined with an artificial neural network, a machine learning technique, is used in order to estimate the fiber orientation on the surface of inspected parts. Results showed that the method can be potentially used to inspect large areas with good accuracy and speed.

Carbon fiber composites inspection and defect characterization using active infrared thermography: numerical simulations and experimental results.

Composite materials are widely used in the aeronautic industry. One of the reasons is because they have strength and stiffness comparable to metals, with the added advantage of significant weight reduction. Infrared thermography (IT) is a safe nondestructive testing technique that has a fast inspection rate. In active IT, an external heat source is used to stimulate the material being inspected in order to generate a thermal contrast between the feature of interest and the background. In this paper, carbon-fiber-reinforced polymers are inspected using IT. More specifically, carbon/PEEK (polyether ether ketone) laminates with square Kapton inserts of different sizes and at different depths are tested with three different IT techniques: pulsed thermography, vibrothermography, and line scan thermography. The finite element method is used to simulate the pulsed thermography experiment. Numerical results displayed a very good agreement with experimental results.