Normalized emphysema scores on low dose CT: Validation as an imaging biomarker for mortality

The purpose of this study is to develop a computed tomography (CT) biomarker of emphysema that is robust across reconstruction settings, and evaluate its ability to predict mortality in patients at high risk for lung cancer. Data included baseline CT scans acquired between August 2002 and April 2004 from 1737 deceased subjects and 5740 surviving controls taken from the National Lung Screening Trial. Emphysema scores were computed in the original scans (origES) and after applying resampling, normalization and bullae analysis (normES). We compared the prognostic value of normES versus origES for lung cancer and all-cause mortality by computing the area under the receiver operator characteristic curve (AUC) and the net reclassification improvement (NRI) for follow-up times of 1–7 years. normES was a better predictor of mortality than origES. The 95% confidence intervals for the differences in AUC values indicated a significant difference for all-cause mortality for 2 through 6 years of follow-up, and for lung cancer mortality for 1 through 7 years of follow-up. 95% confidence intervals in NRI values showed a statistically significant improvement in classification for all-cause mortality for 2 through 7 years of follow-up, and for lung cancer mortality for 3 through 7 years of follow-up. Contrary to conventional emphysema score, our normalized emphysema score is a good predictor of all-cause and lung cancer mortality in settings where multiple CT scanners and protocols are used.本研究旨在开发一种在不同重建设置下均具备稳健性的肺气肿计算机断层扫描（computed tomography, CT）生物标志物，并评估其在肺癌高危患者中预测死亡率的能力。研究数据取自国家肺癌筛查试验（National Lung Screening Trial），纳入2002年8月至2004年4月间获取的1737名已故受试者与5740名存活对照个体的基线CT扫描影像。研究者分别在原始扫描影像中计算肺气肿评分（origES），并在经过重采样、归一化及大疱分析后计算归一化肺气肿评分（normES）。通过计算1至7年随访时长下的受试者工作特征曲线下面积（area under the receiver operator characteristic curve, AUC）与净重新分类改善指数（net reclassification improvement, NRI），对比了normES与origES对肺癌死亡率及全因死亡率的预后价值。研究结果显示，normES的死亡率预测性能优于origES。AUC差值的95%置信区间显示，在2至6年随访期的全因死亡率预测、以及1至7年随访期的肺癌死亡率预测中，二者差异具有统计学意义。NRI值的95%置信区间表明，在2至7年随访期的全因死亡率分类、以及3至7年随访期的肺癌死亡率分类中，normES带来了具有统计学意义的分类性能提升。与传统肺气肿评分不同，本研究提出的归一化肺气肿评分在使用多型号CT扫描仪及多扫描协议的场景下，可有效预测全因死亡率与肺癌死亡率。