Colorectal cancer (CRC) is the 3rd most common and the 2nd most deadly type of cancer worldwide. Understanding the biochemical and microstructural aspects of carcinogenesis is a critical step towards developing new technologies for accurate CRC detection. To date, optical detection through analyzing tissue chromophore concentrations and scattering parameters has been mostly limited to chromophores in the visible region and analytical light diffusion models. In this study, tissue parameters were extracted by fitting diffuse reflectance spectra (DRS) within the range 350–1900 nm based on reflectance values from a look-up table built using Monte Carlo simulations of light propagation in tissues. This analysis was combined with machine learning models to estimate parameter thresholds leading to best differentiation between mucosa and tumor tissues based on almost 3000 DRS recorded from fresh ex vivo tissue samples from 47 subjects. DRS spectra were measured with a probe for superficial tissue and another for slightly deeper tissue layers. By using the classification and regression tree algorithm, the most important parameters for CRC detection were the total lipid content (f _lipid), the reduced scattering amplitude (α′), and the Mie scattering power (b _Mie). Successful classification with an area under the receiver operating characteristic curve higher than 90% was achieved. To the best of our knowledge, this is the first study to evaluate the potential tissue biomolecule concentrations and scattering properties in superficial and deeper tissue layers for CRC detection in the luminal wall. This may have important clinical applications for the rapid diagnosis of colorectal neoplasia.

结直肠癌 (CRC) 是全球第三大最常见的癌症，也是第二大最致命的癌症。了解致癌作用的生化和微观结构方面是开发用于准确检测 CRC 的新技术的关键一步。迄今为止，通过分析组织生色团浓度和散射参数进行的光学检测主要限于可见光区域中的生色团和分析光扩散模型。在这项研究中，组织参数是通过拟合 350-1900 nm 范围内的漫反射光谱 (DRS) 提取的，该反射率值来自使用组织中光传播的蒙特卡罗模拟构建的查找表。来自 47 名受试者的离体组织样本。DRS 光谱是用一个探头测量表面组织，另一个探头测量稍深的组织层。通过使用分类和回归树算法，为CRC检测的最重要的参数是总脂质含量（˚F _脂质），减小的散射幅度（α '）和米氏散射功率（b _三重）。达到了受试者操作特征曲线下面积高于 90% 的成功分类。据我们所知，这是第一项评估表层和深层组织层中潜在组织生物分子浓度和散射特性的研究，用于管腔壁中的 CRC 检测。这对于结直肠肿瘤的快速诊断可能具有重要的临床应用。