Monte Carlo modelling of Raman scattering in heterogeneous breast tissue

异质乳腺组织中拉曼散射的蒙特卡罗建模

• 批准号: 1918697
• 金额: --
• 依托单位: UNIVERSITY OF EXETER
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-1918697
• 关键词: Monte; Carlo; modelling; Raman; scattering

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.

在英国，每年有近6万名妇女被诊断出患有乳腺癌，其中1.2万人死亡。早期诊断是关键，在最早期诊断的妇女中有90%存活至少五年，而诊断为最晚期的妇女只有15%。该研究项目的重点是深度拉曼光谱，它提供了实时、体内诊断乳腺癌的可能性。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癌，但直到最近，该技术还仅限于组织表面约1毫米的深度。斯通教授的小组现在已经证明，通过使用深拉曼光谱技术，可以探测几厘米的深度，将表面下的癌症纳入范围。我们希望获得详细的，通过最先进的数值模拟定量了解拉曼乳腺癌诊断的灵敏度和特异性。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，该软件已被改编为模拟光如何通过组织传播。该代码使用蒙特卡罗方法，其中照明辐射被建模为大量的光子包，非常适合于高度散射的介质，如人体组织。一个可靠的模拟的关键要求是一个现实的散射介质的光学特性的模型。组织的异质性通常使用多个平面平行的均匀层来简单地描述。我们的代码，它结合了三角形网格表面的自适应笛卡尔网格，使一个更复杂的实现组织的真实三维结构。该项目的最初目的是实现拉曼散射物理到代码和验证这使用现有的实验数据。随后，将基于分割的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种环境，在该环境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灵敏度和特异性。该项目的输出将直接反馈到Stone教授的实验工作中，最终目标是建立深度拉曼光谱作为临床环境中的常规诊断方法。