International Mechanical Engineering Congress and Exposition : [proceedings]. International Mechanical Engineering Congress and Exposition最新文献

Deep tissue injuries (DTI) are serious lesions which may develop in deep tissue layers as a result of sustained tissue loading or ischemic injury. These lesions may not become visible on the skin surface until the injury reaches an advanced stage making their early detection a challenging task. Early diagnosis leading to early treatment mitigates the progression of lesion and remains one of the priorities in management. The aim of this study is to examine skin surface temperature distributions of damaged tissue and develop criteria for the detection of incipient DTI. A multilayer quantitative heat transfer model of the skin tissue was developed using finite element based software COMSOL Multiphysics. Thermal response of the skin surface was computed during deep tissue inflammation and deep tissue ischemia and then compared with that of healthy tissue. In the presence of a DTI, an increase of about 0.5°C in skin surface temperatures was noticed during initial phase of deep tissue inflammation, which was followed by a surface temperature decrease of about 0.2°C corresponding to persistent deep tissue ischemia. These temperature differences are large enough to be detected by thermographic imaging. This study, therefore, also enhances the understanding of the previously detected thermographic quantitative changes associated with DTI.

Medical Infrared (IR) Imaging has become an important diagnostic tool over recent years. However, one underlying problem in medical diagnostics is associated with accurate quantification of body surface temperatures. This problem is caused by the artifacts induced by the curvature of objects, which leads to inaccurate temperature mapping and biased diagnostic results. Therefore, in our study, an experiment-based analysis is conducted to address the curvature effects toward the 3D temperature reconstruction of the IR thermography image. For quantification purposes, an isothermal copper plate with flat surface, and a cylindrical metal container filled with water are imaged. For the flat surface, the tilting angle measured from camera axis was varied incrementally from 0° to 60 °, such that the effects of surface viewing angle and travel distance on the measured temperature can be explored. On the cylindrical curved surface, the points viewed from 0° to 90° with respect to the camera axis are simultaneously imaged at different temperature levels. The experimental data obtained for the flat surface indicate that both viewing angle and distance effects become noticeable for angles over 40 °. The travel distance contributes a minor change when compared with viewing angle. The experimental results from the curved surface indicate that the curvature effect becomes pronounced when the viewing angle is larger than 60 °. The measurement error on the curved surface is compared with the simulation using the non-dielectric model, and the normalized temperature difference relative to 0° viewing angle was analyzed at six temperature levels. These results indicate that the linear formula associated with directional emissivity is a reasonable approximation for the measurement error, and the normalized error curves change consistently with viewing angle at various temperatures. Therefore, the analysis in this study implies that the directional emissivity based on the non-dielectric model can be applied for the calibration of measurement error. The normalized error curve serves as a consistent basis to correct the measurement error due to curvature artifacts.

Breast cancer is one of the most common and dangerous cancers. Subsurface breast cancer lesions generate more heat and have increased blood supply when compared to healthy tissue, and this temperature rise is mirrored in the skin surface temperature. The rise in temperature on the skin surface, caused by the cancerous lesion, can be measured noninvasively using infrared thermography, which can be used as a diagnostic tool to detect the presence of a lesion. However, its diagnostic ability is limited when image interpretation relies on qualitative principles. In this study, we present a quantitative thermal analysis of breast cancer using a 3D computational model of the breast. The COMSOL FEM software was used to carry out the analysis. The effect of various parameters (tumor size, location, metabolic heat generation and blood perfusion rate) on the surface temperature distribution (which can be measured with infrared thermography) has been analyzed. Key defining features of the surface temperature profile have been identified, which can be used to estimate the size and location of the tumor based on (measured) surface temperature data. In addition, we employed a dynamic cooling process, to analyze surface temperature distributions during cooling and thermal recovery as a function of time. In this study, the effect of the cooling temperature on the enhancement of the temperature differences between normal tissue and cancerous lesions is evaluated. This study demonstrates that a quantification of temperature distributions by computational modeling, combined with thermographic imaging and dynamic cooling can be an important tool in the early detection of breast cancer.