Manuel Luna Jose, Romero-Mendez Ricardo, Hernandez-Guerrero Abel, Elizalde-Blancas Francisco
University of Guanajuato, Department of Mechanical Engineering, Salamanca, GTO., Mexico.
J Biomech Eng. 2012 Mar;134(3):031008. doi: 10.1115/1.4006197.
Based on the fact that malignant cancerous lesions (neoplasms) develop high metabolism and use more blood supply than normal tissue, infrared thermography (IR) has become a reliable clinical technique used to indicate noninvasively the presence of cancerous diseases, e.g., skin and breast cancer. However, to diagnose cancerous diseases by IR, the technique requires procedures that explore the relationship between the neoplasm characteristics (size, blood perfusion rate and heat generated) and the resulting temperature distribution on the skin surface. In this research work the dual reciprocity boundary element method (DRBEM) has been coupled with the simulated annealing technique (SA) in a new inverse procedure, which coupled to the IR technique, is capable of estimating simultaneously geometrical and thermophysical parameters of the neoplasm. The method is of an evolutionary type, requiring random initial values for the unknown parameters and no calculations of sensitivities or search directions. In addition, the DRBEM does not require any re-meshing at each proposed solution to solve the bioheat model. The inverse procedure has been tested considering input data for simulated neoplasms of different sizes and positions in relation to the skin surface. The successful estimation of unknown neoplasm parameters validates the idea of using the SA technique and the DRBEM in the estimation of parameters. Other estimation techniques, based on genetic algorithms or sensitivity coefficients, have not been capable of obtaining a solution because the skin surface temperature difference is very small.
基于恶性癌性病变(肿瘤)代谢旺盛且比正常组织需要更多血液供应这一事实,红外热成像(IR)已成为一种可靠的临床技术,用于非侵入性地指示癌症疾病的存在,例如皮肤癌和乳腺癌。然而,要通过红外热成像诊断癌症疾病,该技术需要探索肿瘤特征(大小、血液灌注率和产生的热量)与皮肤表面温度分布之间关系的程序。在这项研究工作中,双互易边界元法(DRBEM)与模拟退火技术(SA)在一种新的反演程序中相结合,该程序与红外热成像技术相结合,能够同时估计肿瘤的几何和热物理参数。该方法属于进化型,需要未知参数的随机初始值,并且不需要计算灵敏度或搜索方向。此外,双互易边界元法在求解生物热模型时,对于每个提出的解不需要任何重新网格化。已经考虑了不同大小和相对于皮肤表面位置的模拟肿瘤的输入数据对反演程序进行了测试。对未知肿瘤参数的成功估计验证了在参数估计中使用模拟退火技术和双互易边界元法的想法。其他基于遗传算法或灵敏度系数的估计技术无法获得解,因为皮肤表面温度差非常小。