Monte Carlo modelling of Raman scattering in heterogeneous breast tissue

在英国，每年有近6万名女性被诊断出患有乳腺癌，其中有1.2万人死亡。早期诊断是关键，90%在早期确诊的女性至少能存活5年，而确诊为晚期的女性只有15%。该研究项目的重点是深度拉曼光谱，为乳腺癌的实时、体内诊断提供了可能性。拉曼光谱是一种光学技术，用于通过振动分子的非弹性散射来识别样品中的化学物质。来自癌变组织和正常组织的拉曼信号的差异已经被用于识别早期上皮性癌症，但直到最近，这项技术还仅限于1毫米深的组织表面。斯通教授的研究小组现在已经证明，通过使用深拉曼光谱技术，可以探测到几厘米深的深度，从而将地下癌症纳入探测范围。我们希望通过最先进的数值模拟来获得拉曼乳腺癌诊断的敏感性和特异性的详细、定量的理解。该项目将使用最初开发的软件来模拟光在太空中通过气体和尘埃的传输，该软件已被用于模拟光如何在组织中传播。该代码使用蒙特卡罗方法，其中照明辐射被模拟为大量光子包，非常适合于高散射介质，如人体组织。可靠的模拟的一个关键要求是对散射介质的光学特性有一个真实的模型。组织的非均质性通常简单地用多个平面平行的均质层来描述。我们的代码结合了三角形网格表面和自适应笛卡尔网格，可以更复杂地实现组织的真正三维结构。该项目的最初目标是将拉曼散射物理实现到代码中，并使用现有的实验数据验证这一点。随后，基于分割的MRI数据构建乳房模型，以识别不同的组织类型。这种异质乳腺组织模型将提供一个环境，在其中可以进行数值实验，以量化拉曼光谱对不同组织特性、癌症分布和探针几何形状的敏感性和特异性。该项目的成果将直接反馈到Stone教授小组的实验工作中，其最终目标是将深度拉曼光谱作为临床环境中的常规诊断方法。

Nearly 60,000 women are diagnosed with breast cancer each year in the UK, and there are 12,000 deaths. Early diagnosis is key, with 90% of women diagnosed at the earliest stage surviving for at least five years, compared to 15% for women diagnosed with the most advanced stage. The focus of this research project, deep Raman spectroscopy, offers the possibility of real-time, in vivo diagnosis of breast cancer.Raman spectroscopy is an optical technique used to identify chemicals in a sample via inelastic scattering from vibrating molecules. Differences in the Raman signal from cancerous and normal tissue has already been used to identify early epithelial cancer, but until recently the technique has been limited to the tissue surface at depths of about 1 mm. Prof Stone's group has now demonstrated that by using deep Raman spectroscopy techniques depths of several centimetres may be probed, bringing subsurface cancers into range.We wish to obtain a detailed, quantitative understanding of the sensitivity and specificity of Raman breast cancer diagnosis via state-of-the-art numerical simulations. The project will use software originally developed to model light transport through gas and dust in space, that has been adapted to model how light propagates through tissue. The code uses the Monte Carlo method, in which the illuminating radiation is modelled as a large number of photon packets, is ideally suited to highly scattering media such as human tissue. A key requirement for a reliable simulation is a realistic model for the optical properties of the scattering medium. The heterogeneous nature of tissue is usually simply described using multiple plane-parallel homogeneous layers. Our code, which combines triangular mesh surfaces with an adaptive Cartesian mesh, enables a much more sophisticated realization of the tissue's true three-dimensional structure.The initial aim of this project is to implement Raman scattering physics into the code and validate this using extant experimental data. Subsequently a breast model will be constructed based on MRI data segmented to identify the different tissue types. This heterogeneous breast tissue model will provide an environment within which numerical experiments may be performed to quantify the sensitivity and specificity of Raman spectroscopy to varying tissue properties, cancer distributions, and probe geometries. The outputs from this project will feed back directly into the experimental work Prof Stone's group, with ultimate aim of establishing deep Raman spectroscopy as a routine diagnostic method in the clinical environment.