Suppr超能文献

基于多层组织光学模型的人体皮肤体内拉曼光谱测量的蒙特卡罗模拟

Monte Carlo simulation of in vivo Raman spectral measurements of human skin with a multi-layered tissue optical model.

作者信息

Wang Shuang, Zhao Jianhua, Lui Harvey, He Qingli, Bai Jintao, Zeng Haishan

机构信息

Institute of Photonics and Photon-Technology, The cultivation base of the state key laboratory of optoelectronic technology and functional materials co-constructed by Ministry of Education and Shaanxi Province, Northwest University, Xi'an, Shaanxi, China; Imaging Unit - Integrative Oncology Department, British Columbia Cancer Agency Research Centre, Vancouver, BC, Canada.

出版信息

J Biophotonics. 2014 Sep;7(9):703-12. doi: 10.1002/jbio.201300045. Epub 2013 Dec 5.

Abstract

Raman photon generation inside human skin and escaping to skin surface were modeled in an eight-layered skin optical model. Intrinsic Raman spectra of different skin layers were determined by microscopy measurements of excised skin tissue sections. Monte Carlo simulation was used to study the excitation light distribution and intrinsic Raman signal distortion caused by tissue reabsorption and scattering during in vivo measurements. The simulation results demonstrated how different skin layers contributed to the observed in vivo Raman spectrum. Using the strongest Raman peak at 1445 cm(-1) as an example, the simulation suggested that the integrated contributions of the stratum corneum layer is 1.3%, the epidermis layer 28%, the dermis layer 70%, and the subcutaneous fat layer 1.1%. Reasonably good matching between the calculated spectrum and the measured in vivo Raman spectra was achieved, thus demonstrated great utility of our modeling method and approaches for help understanding the clinical measurements.

摘要

在一个八层皮肤光学模型中对人体皮肤内产生并逸出到皮肤表面的拉曼光子进行了建模。通过对切除的皮肤组织切片进行显微镜测量,确定了不同皮肤层的固有拉曼光谱。利用蒙特卡罗模拟研究了体内测量过程中组织重吸收和散射引起的激发光分布和固有拉曼信号失真。模拟结果表明了不同皮肤层对观察到的体内拉曼光谱的贡献。以1445 cm(-1)处最强的拉曼峰为例,模拟表明角质层的综合贡献为1.3%,表皮层为28%,真皮层为70%,皮下脂肪层为1.1%。计算光谱与实测体内拉曼光谱之间实现了合理的良好匹配,从而证明了我们的建模方法和途径对于帮助理解临床测量具有很大的实用性。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验