Monte Carlo modeling of light propagation in the human head for applications in sinus imaging.
Monte Carlo modeling of light propagation in the human head for applications in sinus imaging.
复制标题
人体头部光传播的蒙特卡罗建模，用于鼻窦成像。
DOI：
10.1117/1.jbo.20.3.035004
复制
发表时间：
2015
影响因子：
3.5
通讯作者：
Wong,Brian
中科院分区：
文献类型：
--
作者：
Cerussi,AlbertE;Mishra,Nikhil;You,Joon;Bhandarkar,Naveen;Wong,Brian
鼻窦堵塞是医生就诊的常见原因，在美国，每七个人中就有一个受到影响，而且经常需要治疗。初级保健环境中的诊断具有挑战性，因为推荐使用症状标准(通过详细的临床病史)和客观成像[计算机断层扫描(CT)或内窥镜检查]。不幸的是，在初级保健中，这两种选择都不是常规可用的。我们先前证明，低成本的近红外(NIR)透照与CT测量的鼻窦浑浊的大体表现相关。我们已经升级了技术，但源优化、解剖学影响和检测极限的问题仍然存在。为了开始解决这些问题，我们使用基于网格的蒙特卡罗算法(MMCLAB)对通过CT图像构建的三维成人头部内的近红外光传播进行了建模。在这种应用中，窦本身是感兴趣的区域，当健康时，它是一个空区域(例如，非散布的)。我们描述了由于清晰的(即健康的)与阻塞的鼻窦以及照明模式的影响而导致的检测强度的变化。我们对两个临床病例进行了模拟，并将模拟与测量进行了比较。本文给出的模拟结果证明了这种方法可以用于理解近红外鼻窦成像的对比度机制和局限性。
Sinus blockages are a common reason for physician visits, affecting one out of seven people in the United States, and often require medical treatment. Diagnosis in the primary care setting is challenging because symptom criteria (via detailed clinical history) plus objective imaging [computed tomography (CT) or endoscopy] are recommended. Unfortunately, neither option is routinely available in primary care. We previously demonstrated that low-cost near-infrared (NIR) transillumination correlates with the bulk findings of sinus opacity measured by CT. We have upgraded the technology, but questions of source optimization, anatomical influence, and detection limits remain. In order to begin addressing these questions, we have modeled NIR light propagation inside a three-dimensional adult human head constructed via CT images using a mesh-based Monte Carlo algorithm (MMCLAB). In this application, the sinus itself, which when healthy is a void region (e.g., nonscattering), is the region of interest. We characterize the changes in detected intensity due to clear (i.e., healthy) versus blocked sinuses and the effect of illumination patterns. We ran simulations for two clinical cases and compared simulations with 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 sinus imaging.