From the Department of Experimental and Clinical Medicine, University of Florence, Largo Brambilla 3, 50134 Florence, Italy.
Radiology. 2015 Aug;276(2):571-8. doi: 10.1148/radiol.2015141769. Epub 2015 Apr 3.
To determine whether the relationship between pulmonary function and computed tomographic (CT) lung attenuation in chronic obstructive pulmonary disease (COPD), which is traditionally described with single univariate and multivariate statistical models, could be more accurately described with a multiple model estimation approach.
The study was approved by the local ethics committee. All participants provided written informed consent. The prediction of the percentage area with CT attenuation values less than -950 HU at inspiration (%LAA-950insp) and less than -910 HU at expiration (%LAA-910exp) obtained with single univariate and multivariate models was compared with that obtained with a multiple model estimation approach in 132 patients with COPD.
At univariate analysis, %LAA-950insp and %LAA-910exp values higher than the mean value of this cohort (19.1% and 22.0%) showed better correlation with percentage of predicted diffusing capacity of lung for carbon monoxide (Dlco%) than with airflow obstruction (forced expiratory volume in 1 second [FEV1]/vital capacity [VC]). Conversely, %LAA-950insp and %LAA-910exp values lower than the mean value were correlated with FEV1/VC but not with Dlco%. Multiple model estimation performed with two multivariate regressions, each selecting the most appropriate functional variables (FEV1/VC for mild parenchymal destruction, Dlco% and functional residual capacity for severe parenchymal destruction), predicted better than single multivariate regression both %LAA-950insp (R(2) = 0.75 vs 0.46) and %LAA-910exp (R(2) = 0.83 vs 0.63).
The relationship between pulmonary function data and CT densitometric changes in COPD varies with the level of lung attenuation impairment. The nonlinear profile of this relationship is accurately predicted with a multiple model estimation approach.
确定慢性阻塞性肺疾病(COPD)患者的肺功能与 CT 肺衰减之间的关系是否可以通过多模型估计方法更准确地描述,因为传统上仅使用单变量和多变量统计模型进行了描述。
本研究经当地伦理委员会批准,所有参与者均提供了书面知情同意书。在 132 例 COPD 患者中,比较了单变量和多变量模型预测的吸气时 CT 衰减值小于-950 HU 的面积百分比(%LAA-950insp)和呼气时 CT 衰减值小于-910 HU 的面积百分比(%LAA-910exp)与多模型估计方法的预测值。
在单变量分析中,高于该队列平均值(19.1%和 22.0%)的 %LAA-950insp 和 %LAA-910exp 值与预测的一氧化碳弥散量(Dlco%)的相关性优于与气流阻塞(1 秒用力呼气量[FEV1]/肺活量[VC])的相关性。相反,低于平均值的 %LAA-950insp 和 %LAA-910exp 值与 FEV1/VC 相关,但与 Dlco% 不相关。使用两个多变量回归进行多模型估计,每个回归选择最合适的功能变量(轻度实质破坏的 FEV1/VC,严重实质破坏的 Dlco%和功能残气量),比单变量回归更好地预测了 %LAA-950insp(R(2)=0.75 比 0.46)和 %LAA-910exp(R(2)=0.83 比 0.63)。
COPD 患者的肺功能数据与 CT 密度变化之间的关系随肺衰减损伤程度的不同而变化。通过多模型估计方法可以准确预测这种关系的非线性特征。