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Monte Carlo Modeling of Light Propagation in the Human Head for Applications in Sinus Imaging

机译：蒙特卡洛模型在人脑中光传播在窦成像中的应用

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Sinus blockages are a common reason for physician visits, affecting 1 out of 7 in the United States. Over 20 million cases of acute bacterial sinusitis become chronic and require medical treatment. Diagnosis in the primary care setting is challenging because symptom criteria (via detailed clinical history) plus objective imaging (CT or endoscopy) is recommended. Unfortunately, neither option is routinely available in primary care. Our previous work demonstrated that low-cost near infrared (NIR) transillumination instruments produced signals that correlated with the bulk findings of sinus opacity measured by CT. We have upgraded the technology, but questions remain such as finding the optimal arrangement of light sources, measuring the influence of specific anatomical structures, and determining detection limits. In order to begin addressing these questions, we have modeled NIR light propagation inside the adult human head using a mesh-based Monte Carlo algorithm (MMCLab) applied to a detailed anatomical head model constructed from CT images. In this application the sinus itself, which under healthy conditions is a void region (e.g., non-scattering), is the region of interest instead of an obstacle to other contrast mechanisms. We report preliminary simulations that characterize the changes in detected intensity due to clear (i.e., healthy) versus blocked sinuses. We also ran simulations for two of our clinical cases and compared results with the measurements. The simulations presented herein serve as a proof of concept that this approach could be used to understand contrast mechanisms and limitations of NIR imaging of the sinus cavities.
机译：鼻窦阻塞是医师就诊的常见原因，在美国影响了七分之一。超过2000万例急性细菌性鼻窦炎成为慢性病，需要医疗。由于推荐症状标准（通过详细的临床病史）加上客观成像（CT或内窥镜检查），因此在初级保健机构中进行诊断具有挑战性。不幸的是，这两种方法在初级保健中都无法常规使用。我们以前的工作表明，低成本的近红外（NIR）透照仪产生的信号与CT测量的窦性混浊的大量发现相关。我们已经对该技术进行了升级，但是仍然存在诸如寻找光源的最佳布置，测量特定解剖结构的影响以及确定检测限之类的问题。为了开始解决这些问题，我们使用基于网格的蒙特卡洛算法（MMCLab）对成年人头部内部的近红外光传播进行建模，该算法应用于从CT图像构造的详细解剖头模型中。在本申请中，在健康条件下为无效区域（例如，非散射）的窦本身是关注区域，而不是其他对比机制的障碍。我们报告了初步模拟结果，这些特征描述了由于鼻窦清晰（即健康）与阻塞鼻窦而导致的检测强度变化。我们还对两个临床案例进行了模拟，并将结果与​​测量结果进行了比较。本文介绍的模拟可以作为一种概念证明，证明该方法可用于了解对比机制和窦腔NIR成像的局限性。

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