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基于多岛遗传算法的生物组织内热源重建研究

Investigation on reconstruction of internal heat source in biological tissue based on multi-island genetic algorithm.

作者信息

Ye Fuli, Shi Diwen, Xu Cheng, Li Kaiyang, Lin Minyue, Shi Guilian

机构信息

School of Biomedical Engineering and Imaging, Xianning Medical College, Hubei University of Science and Technology, Xianning, 437100, China.

School of Physics and Technology, Wuhan University, Wuhan, 430072, China.

出版信息

Heliyon. 2024 Aug 27;10(18):e36983. doi: 10.1016/j.heliyon.2024.e36983. eCollection 2024 Sep 30.

Abstract

With the rapid development of engineering thermophysics, researches on human biological heat transfer phenomena has gradually shifted from qualitative to quantitative. It is a typical inverse problem of heat conduction that deriving the distribution of internal heat sources from the temperature distribution on the body surface. Differing from traditional numerical methods for solving heat conduction, this paper transforms such an inverse problem of bio-heat transfer into a direct one, thereby avoiding complex boundary conditions and regularization processes. To noninvasively reconstruct the internal heat source and its corresponding 3D temperature field in biological tissue, the multi-island genetic algorithm (MIGA) is used in the simulation module, where the position P of point heat source in biological tissue and its corresponding temperature are set as the optimization variables. Under a certain optimized sample, one can obtain the simulated temperature distributing on the surface of the module, then subtract the simulated temperature from the measured temperature of the same surface which was measured using a thermal infrared imager. If the absolute value of the difference is smaller, it indicates that the current sample is closer to the true location and temperature of the heat source. When the values of optimization variables are determined, the corresponding 3D temperature field is also confirmed. The simulation results show the experimental and simulation temperature values of 15.5Ω resistor are 60.75°C and 62.15 °C respectively, with the error of 2.31 %, and those of 30.5Ω resistor are 84.40 °C and 86.33°C respectively, with the error of 2.29 %. The simulated positions are very approximate with those of the real experimental module. The method presented in this paper has enormous potential and promising prospects in clinical research and application, such as tumor hyperthermia, disease thermal diagnosis technology, etc.

摘要

随着工程热物理学的快速发展,对人体生物传热现象的研究已逐渐从定性转向定量。从体表温度分布推导内部热源分布是典型的热传导反问题。与传统的热传导数值解法不同,本文将这种生物传热反问题转化为正问题,从而避免了复杂的边界条件和正则化过程。为了无创地重建生物组织中的内部热源及其相应的三维温度场,在模拟模块中使用了多岛遗传算法(MIGA),将生物组织中点热源的位置P及其相应温度设为优化变量。在某个优化样本下,可以得到模块表面的模拟温度分布,然后用热红外成像仪测量同一表面的实测温度,并减去模拟温度。差值的绝对值越小,表明当前样本越接近热源的真实位置和温度。当确定优化变量的值时,相应的三维温度场也得以确定。模拟结果表明,15.5Ω电阻的实验温度值和模拟温度值分别为60.75°C和62.15°C,误差为2.31%;30.5Ω电阻的实验温度值和模拟温度值分别为84.40°C和86.33°C,误差为2.29%。模拟位置与实际实验模块的位置非常接近。本文提出的方法在肿瘤热疗、疾病热诊断技术等临床研究和应用中具有巨大潜力和广阔前景。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2aeb/11415687/28ee293ebb79/gr1.jpg

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