Department of Ophtalmology and Otorhinolaryngology, Universidade de São Paulo, São Paulo, Brazil.
Department of Radiology, Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil.
PLoS One. 2018 Nov 16;13(11):e0207178. doi: 10.1371/journal.pone.0207178. eCollection 2018.
Computational fluid dynamics (CFD) allows quantitative assessment of transport phenomena in the human nasal cavity, including heat exchange, moisture transport, odorant uptake in the olfactory cleft, and regional delivery of pharmaceutical aerosols. The first step when applying CFD to investigate nasal airflow is to create a 3-dimensional reconstruction of the nasal anatomy from computed tomography (CT) scans or magnetic resonance images (MRI). However, a method to identify the exact location of the air-tissue boundary from CT scans or MRI is currently lacking. This introduces some uncertainty in the nasal cavity geometry. The radiodensity threshold for segmentation of the nasal airways has received little attention in the CFD literature. The goal of this study is to quantify how uncertainty in the segmentation threshold impacts CFD simulations of transport phenomena in the human nasal cavity. Three patients with nasal airway obstruction were included in the analysis. Pre-surgery CT scans were obtained after mucosal decongestion with oxymetazoline. For each patient, the nasal anatomy was reconstructed using three different thresholds in Hounsfield units (-800HU, -550HU, and -300HU). Our results demonstrate that some CFD variables (pressure drop, flowrate, airflow resistance) and anatomic variables (airspace cross-sectional area and volume) are strongly dependent on the segmentation threshold, while other CFD variables (intranasal flow distribution, surface area) are less sensitive to the segmentation threshold. These findings suggest that identification of an optimal threshold for segmentation of the nasal airway from CT scans will be important for good agreement between in vivo measurements and patient-specific CFD simulations of transport phenomena in the nasal cavity, particularly for processes sensitive to the transnasal pressure drop. We recommend that future CFD studies should always report the segmentation threshold used to reconstruct the nasal anatomy.
计算流体动力学（CFD）允许对人体鼻腔中的传输现象进行定量评估，包括热交换、水分传输、嗅裂中的气味吸收以及药物气溶胶的局部输送。将 CFD 应用于研究鼻腔气流的第一步是根据计算机断层扫描（CT）扫描或磁共振成像（MRI）创建鼻腔解剖结构的 3 维重建。然而，目前缺乏从 CT 扫描或 MRI 中识别空气 - 组织边界的确切位置的方法。这给鼻腔几何形状带来了一些不确定性。在 CFD 文献中，气道分割的放射密度阈值很少受到关注。本研究的目的是量化分割阈值的不确定性如何影响人体鼻腔中传输现象的 CFD 模拟。分析中包括 3 例鼻腔气道阻塞的患者。在使用羟甲唑啉进行粘膜充血后获得术前 CT 扫描。对于每个患者，使用 Hounsfield 单位的三个不同阈值（-800HU、-550HU 和-300HU）重建鼻腔解剖结构。我们的结果表明，一些 CFD 变量（压降、流量、气流阻力）和解剖学变量（空气空间横截面积和体积）强烈依赖于分割阈值，而其他 CFD 变量（鼻腔内气流分布、表面积）对分割阈值的敏感性较低。这些发现表明，从 CT 扫描中识别鼻腔气道的最佳分割阈值对于在体内测量和鼻腔内传输现象的患者特异性 CFD 模拟之间的良好一致性非常重要，特别是对于对跨鼻压降敏感的过程。我们建议未来的 CFD 研究应始终报告用于重建鼻腔解剖结构的分割阈值。
