Departments of Radiology.
Epidemiology and Biostatistics.
J Thorac Imaging. 2018 Mar;33(2):112-123. doi: 10.1097/RTI.0000000000000307.
Bronchiolitis obliterans syndrome after lung transplantation (LTx) manifests as a sustained decline in forced expiratory volume in the first second (FEV1). Quantitative computed tomography (QCT) metrics may predict FEV1 better than semiquantitative scores (SQSs), and the transplanted lung may provide better information than the native lung in unilateral LTx.
Paired inspiratory-expiratory CT scans and pulmonary function testing of 178 LTx patients were analyzed retrospectively. SQS were graded (absent, mild, moderate, severe) for features including mosaic attenuation and bronchiectasis. QCT included lung volumes and air-trapping volumes, by lobe. Multivariate Pearson correlation and multivariate linear least squares regression analyses were performed.
Multivariate linear least squares regression models using FEV1 as the outcome variable and SQS or QCT metrics as predictor variables demonstrated SQS to be a weak predictor of FEV1 (adjusted R, 0.114). QCT metrics were much stronger predictors of FEV1 (adjusted R, 0.654). QCT metrics demonstrated stronger correlation (r) with FEV1 than SQS. In bilateral LTx, whole lung volume difference (r=0.69), left lung volume difference (r=0.69), and right lung volume difference (r=0.65) were better than the sum of SQS (r=-0.54). Interestingly, in left LTx we obtained r=0.81, 0.86, 0.25, and -0.39, respectively. In right LTx, we obtained r=0.69, 0.49, 0.68, and -0.31, respectively.
QCT metrics demonstrate stronger correlations with FEV1 and are better predictors of pulmonary function than SQS. SQS performs moderately well in bilateral LTx, but poorly on unilateral LTx. In unilateral LTx, QCT metrics from the transplanted lung are better predictors of FEV1 than QCT metrics from the nontransplanted lung.
肺移植（LTx）后闭塞性细支气管炎综合征表现为第一秒用力呼气量（FEV1）持续下降。定量计算机断层扫描（QCT）指标可能比半定量评分（SQS）更好地预测 FEV1，并且在单侧 LTx 中，移植肺可能比原生肺提供更好的信息。
回顾性分析了 178 例 LTx 患者的吸气-呼气 CT 扫描和肺功能检测的配对数据。对马赛克衰减和支气管扩张等特征进行 SQS 分级（无、轻度、中度、重度）。QCT 包括按叶划分的肺容积和空气潴留容积。进行了多元 Pearson 相关和多元线性最小二乘回归分析。
使用 FEV1 作为因变量，SQS 或 QCT 指标作为预测变量的多元线性最小二乘回归模型表明，SQS 是 FEV1 的弱预测因子（调整后的 R，0.114）。QCT 指标是 FEV1 的更强预测因子（调整后的 R，0.654）。QCT 指标与 FEV1 的相关性（r）强于 SQS。在双侧 LTx 中，全肺容积差（r=0.69）、左肺容积差（r=0.69）和右肺容积差（r=0.65）均优于 SQS 之和（r=-0.54）。有趣的是，在左侧 LTx 中，我们分别获得了 r=0.81、0.86、0.25 和-0.39。在右侧 LTx 中，我们分别获得了 r=0.69、0.49、0.68 和-0.31。
QCT 指标与 FEV1 的相关性更强，是 SQS 更好的肺功能预测因子。SQS 在双侧 LTx 中表现中等，在单侧 LTx 中表现不佳。在单侧 LTx 中，移植肺的 QCT 指标比非移植肺的 QCT 指标更好地预测 FEV1。
