Opt Lett. 2020 Apr 1;45(7):2078-2081. doi: 10.1364/OL.385845.
Cancer progression leads to changing scattering properties of affected tissues. Single fiber reflectance (SFR) spectroscopy detects these changes at small spatial scales, making it a promising tool for early in situ detection. Despite its simplicity and versatility, SFR signal modeling is hugely complicated so that, presently, only approximate models exist. We use a classic approach from geometrical probability to derive accurate analytical expressions for diffuse reflectance in SFR that shows a strong improvement over existing models. We consider the case of limited collection efficiency and the presence of absorption. A Monte Carlo light transport study demonstrates that we adequately describe the contribution of diffuse reflectance to the SFR signal. Additional steps are required to include semi-ballistic, non-diffuse reflectance also present in the SFR measurement.
癌症的发展导致受影响组织的散射特性发生变化。单纤维反射率 (SFR) 光谱检测可以在小的空间尺度上检测到这些变化，因此它是一种很有前途的早期原位检测工具。尽管 SFR 具有简单性和多功能性，但它的信号建模非常复杂，以至于目前仅存在近似模型。我们使用几何概率的经典方法来推导出 SFR 中漫反射的准确解析表达式，该方法与现有模型相比有很大的改进。我们考虑了有限收集效率和吸收的情况。蒙特卡罗光传输研究表明，我们可以很好地描述漫反射对 SFR 信号的贡献。还需要额外的步骤来包括也存在于 SFR 测量中的半弹道、非漫反射。
