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使用自动化计算机断层扫描分析预测特发性肺纤维化的结果。

Predicting Outcomes in Idiopathic Pulmonary Fibrosis Using Automated Computed Tomographic Analysis.

机构信息

1 Department of Respiratory Medicine.

2 Centre for Medical Image Computing, and.

出版信息

Am J Respir Crit Care Med. 2018 Sep 15;198(6):767-776. doi: 10.1164/rccm.201711-2174OC.

Abstract

RATIONALE

Quantitative computed tomographic (CT) measures of baseline disease severity might identify patients with idiopathic pulmonary fibrosis (IPF) with an increased mortality risk. We evaluated whether quantitative CT variables could act as a cohort enrichment tool in future IPF drug trials.

OBJECTIVES

To determine whether computer-derived CT measures, specifically measures of pulmonary vessel-related structures (VRSs), can better predict functional decline and survival in IPF and reduce requisite sample sizes in drug trial populations.

METHODS

Patients with IPF undergoing volumetric noncontrast CT imaging at the Royal Brompton Hospital, London, and St. Antonius Hospital, Utrecht, were examined to identify pulmonary function measures (including FVC) and visual and computer-derived (CALIPER [Computer-Aided Lung Informatics for Pathology Evaluation and Rating] software) CT features predictive of mortality and FVC decline. The discovery cohort comprised 247 consecutive patients, with validation of results conducted in a separate cohort of 284 patients, all fulfilling drug trial entry criteria.

MEASUREMENTS AND MAIN RESULTS

In the discovery and validation cohorts, CALIPER-derived features, particularly VRS scores, were among the strongest predictors of survival and FVC decline. CALIPER results were accentuated in patients with less extensive disease, outperforming pulmonary function measures. When used as a cohort enrichment tool, a CALIPER VRS score greater than 4.4% of the lung was able to reduce the requisite sample size of an IPF drug trial by 26%.

CONCLUSIONS

Our study has validated a new quantitative CT measure in patients with IPF fulfilling drug trial entry criteria-the VRS score-that outperformed current gold standard measures of outcome. When used for cohort enrichment in an IPF drug trial setting, VRS threshold scores can reduce a required IPF drug trial population size by 25%, thereby limiting prohibitive trial costs. Importantly, VRS scores identify patients in whom antifibrotic medication prolongs life and reduces FVC decline.

摘要

背景

定量计算机断层扫描(CT)对疾病基线严重程度的测量可能会识别出特发性肺纤维化(IPF)患者,这些患者具有更高的死亡率风险。我们评估了定量 CT 变量是否可以作为未来 IPF 药物试验的队列富集工具。

目的

确定计算机衍生的 CT 测量值,特别是与肺血管相关结构(VRS)的测量值,是否可以更好地预测 IPF 患者的功能下降和生存情况,并减少药物试验人群的所需样本量。

方法

对在伦敦皇家布朗普顿医院和乌得勒支圣安东尼奥斯医院接受容积非对比 CT 成像的 IPF 患者进行检查,以确定预测死亡率和 FVC 下降的肺功能测量值(包括 FVC)以及视觉和计算机衍生(CALIPER [计算机辅助肺病理评估和评分的信息学] 软件)CT 特征。发现队列包括 247 例连续患者,在另一队列的 284 例符合药物试验入组标准的患者中验证了结果。

测量和主要结果

在发现和验证队列中,CALIPER 衍生的特征,尤其是 VRS 评分,是预测生存和 FVC 下降的最强预测因素之一。在疾病范围较小的患者中,CALIPER 结果更加明显,优于肺功能测量值。当用作队列富集工具时,CALIPER VRS 评分大于肺部的 4.4%,可使 IPF 药物试验所需的样本量减少 26%。

结论

我们的研究在符合药物试验入组标准的 IPF 患者中验证了一种新的定量 CT 测量方法-VRS 评分,该评分优于当前的金标准预后测量方法。当在 IPF 药物试验环境中用于队列富集时,VRS 阈值评分可以将所需的 IPF 药物试验人群减少 25%,从而限制了试验的高成本。重要的是,VRS 评分可识别出接受抗纤维化药物治疗可延长生命并减少 FVC 下降的患者。

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