Coulombe Nicolas, Gagnon Hervé, Marquis François, Skrobik Yoanna, Guardo Robert
Institut de génie biomédical, Ecole Polytechnique de Montréal, Montréal, H3T 1J4, Canada.
Physiol Meas. 2005 Aug;26(4):401-11. doi: 10.1088/0967-3334/26/4/006. Epub 2005 Apr 4.
Spirometry and electrical impedance tomography (EIT) data from 26 healthy subjects (14 males, 12 females) were used to develop a model linking contrast variations in EIT difference images to lung volume changes. Eight recordings, each 64 s long, were made for each subject in four postures (standing, sitting, reclining at 45 degrees, supine) and two breathing modes (quiet tidal and deep breathing). Age, gender and five anthropometric variables were recorded. The database was divided into four subsets. The first subset, data from 22 subjects (12 males, 10 females) recorded in deep breathing mode, was used to create the model. Validation was done with the other subsets: data recorded during quiet tidal breathing in the same 22 subjects, and data recorded in both breathing modes for the other four subjects. A quadratic equation in DeltaV(P) (lung volume changes recorded by the spirometer) provided a very good fit to total contrast changes in the EIT images. The model coefficients were found to depend on posture, gender, thoracic circumference and scapular skin fold. To validate the model, the quadratic equation was inverted to estimate lung volume changes from the EIT images. The estimated changes were then compared to the measured volume changes. Validations with each data subset yielded mean standard errors ranging from 9.3% to 12.4%. The proposed model is a first step in enabling inter individual comparisons of EIT images since: (1) it provides a framework for incorporating the effects of anthropometric variables, gender and posture, and (2) it references the images to a physical quantity (volume) verifiable by spirometry.
来自26名健康受试者(14名男性,12名女性)的肺功能测定和电阻抗断层扫描(EIT)数据被用于建立一个模型,该模型将EIT差异图像中的对比度变化与肺容积变化联系起来。为每名受试者在四种姿势(站立、坐着、45度斜躺、仰卧)和两种呼吸模式(平静潮气呼吸和深呼吸)下进行了八次记录,每次记录时长64秒。记录了年龄、性别和五个身体测量变量。数据库被分为四个子集。第一个子集是22名受试者(12名男性,10名女性)在深呼吸模式下记录的数据,用于创建模型。使用其他子集进行验证:同一22名受试者在平静潮气呼吸期间记录的数据,以及其他四名受试者在两种呼吸模式下记录的数据。DeltaV(P)(肺功能仪记录的肺容积变化)的二次方程与EIT图像中的总对比度变化拟合得非常好。发现模型系数取决于姿势、性别、胸围和肩胛皮肤褶。为了验证模型,将二次方程求逆以从EIT图像估计肺容积变化。然后将估计的变化与测量的容积变化进行比较。对每个数据子集的验证产生的平均标准误差范围为9.3%至12.4%。所提出的模型是实现EIT图像个体间比较的第一步,因为:(1)它提供了一个纳入身体测量变量、性别和姿势影响的框架,(2)它将图像参考到一个可通过肺功能测定验证的物理量(容积)。