使用計算流體力學模擬氣管模型之肺功能分析

Abstract

肺計量測定在慢性阻塞性肺病的診斷上扮演相當重要的角色。在臨床上，肺功能量計記錄了病人吸滿氣時用力吐出的吐氣量。但事實上對於慢性阻塞性肺病或是呼吸困難的病患來說，用力的吐氣是相當困難的，故時常肺功能量計的數據會與真實數值有所誤差，並有可能會造成診斷上的誤判。因此，對於肺功能量計數值的準確預估對於診斷慢性阻塞性肺病會有相當大的幫助。傳統上對於肺功能量計數值的預測是使用病人的健康資訊，包括年齡、身高與體重等。在本篇研究中，利用計算流體力學在人體氣管模型中模擬出的氣體入口到出口的壓力差也將被用於肺功能量計的預測。首先，先利用區域生長將氣管的區域從胸腔電腦斷層攝影影像中切割出來。但由於切割出來的氣管是由許多平面的切片所組成的，所以第二步是將切割出的氣管區域建立出立體的氣管模型。第三，標示出氣管模型的入口及出口以供計算流體力學模擬使用。最後，在邊界標設作業完成的氣管模型上使用計算流體力學模擬出氣管從入口到出口的氣體壓力差。在本篇研究中提出了一個新的肺計量的預測模型，其方法為結合氣管的資訊以及病人的健康資訊以達到更高的準確度。

Spirometry plays an important role in the diagnosis of chronic obstructive pulmonary disease (COPD). In the present clinical workflow, spirometry records the volume of air exhausted from the fully aerated lungs of every patients. However, it was difficult to forcibly exhale for the patients that suffer with the difficulties in breathing. Therefore, the prediction model for spirometry could powerfully support the diagnosis of COPD. In the traditional prediction, the health information such as age and height of patients was used for predicting the values of spirometry. In this study, the pressure drop generated from computational fluid dynamics (CFD) simulation in the airway was considered. First, the airway was segmented from CT slices based on a 3-D region growing method. However, the segmented airway was composed by 2-D slices. Therefore, second, the 3-D airway model was constructed based on the segmented airway from region growing. Third, in order to run the CFD simulation, the inlet and the outlets had to be set correctly. Finally, the CFD simulation ran on the well-prepared airway model to generate the pressure drop from the inlet to the outlets of the airway model. In this study, a new prediction model, which used the combination of the airway information which was the pressure drop in the airway model and the health information, was proposed.