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系统性硬化症(SSc)患者间质性肺疾病(ILD)的计算机断层扫描分析。与肺生理测试以及以患者为中心的呼吸困难感知和功能残疾测量指标的相关性。

Computer-Aided Tomographic Analysis of Interstitial Lung Disease (ILD) in Patients with Systemic Sclerosis (SSc). Correlation with Pulmonary Physiologic Tests and Patient-Centred Measures of Perceived Dyspnea and Functional Disability.

作者信息

Salaffi Fausto, Carotti Marina, Di Donato Eleonora, Di Carlo Marco, Ceccarelli Luca, Giuseppetti Gianmarco

机构信息

Department of Reumatology, Polythecnic University of Marche, Jesi (Ancona), Italy.

Department of Radiology, Polythecnic University of Marche, Ancona, Italy.

出版信息

PLoS One. 2016 Mar 1;11(3):e0149240. doi: 10.1371/journal.pone.0149240. eCollection 2016.

DOI:10.1371/journal.pone.0149240
PMID:26930658
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4773230/
Abstract

OBJECTIVES

This study was designed (a) to evaluate an improved quantitative lung fibrosis score based on a computer-aided diagnosis (CaM) system in patients with systemic sclerosis (SSc),-related interstitial lung disease (SSc-ILD), (b) to investigate the relationship between physiologic parameters (forced vital capacity [FVC] and single-breath diffusing capacity for carbon monoxide [DLCO]), patient-centred measures of dyspnea and functional disability and CaM and visual reader-based (CoVR) methods, and (c) to identify potential surrogate measures from quantitative and visual HRCT measurement.

METHODS

126 patients with SSc underwent chest radiography, HRCT and PFTs. The following patient-centred measures were obtained: modified Borg Dyspnea Index (Borg score), VAS for breathing, and Health Assessment Questionnaire-Disability Index (HAQ-DI). HRCT abnormalities were scored according to the conventional visual reader-based score (CoVR) and by a CaM. The relationships among the HRCT scores, physiologic parameters (FVC and DLCO, % predicted) results and patient-centred measures, were calculated using linear regression analysis and Pearson's correlation. Multivariate regression models were performed to identify the predictor variables on severity of pulmonary fibrosis.

RESULTS

Subjects with limited cutaneous SSc had lower HAQ-DI scores than subjects with diffuse cutaneous SSc (p <0.001). CaM and CoVR scores were similar in the 2 groups. In univariate analysis, a strong correlation between CaM and CoVR was observed (p <0.0001). In multivariate analysis the CaM and CoVR scores were predicted by DLco, FVC, Borg score and HAQ-DI. Age, sex, disease duration, anti-topoisomerase antibodies and mRSS were not significantly associated with severity of pulmonary fibrosis on CaM- and CoVR methods.

CONCLUSIONS

Although a close correlation between CaM score results and CoVR total score was found, CaM analysis showed a more significant correlation with DLco (more so than the FVC), patient-centred measures of perceived dyspnea and functional disability. Computer-aided tomographic analysis is computationally efficient, and in combination with physiologic and patient-centred measures, it could allow a means for accurately assessing and monitoring the disease progression or response to therapy.

摘要

目的

本研究旨在(a)评估基于计算机辅助诊断(CaM)系统的改良定量肺纤维化评分在系统性硬化症(SSc)相关间质性肺病(SSc-ILD)患者中的应用;(b)研究生理参数(用力肺活量[FVC]和单次呼吸一氧化碳弥散量[DLCO])、以患者为中心的呼吸困难和功能残疾测量指标与CaM及基于视觉阅片者(CoVR)方法之间的关系;(c)从定量和视觉HRCT测量中确定潜在的替代指标。

方法

126例SSc患者接受了胸部X线摄影、HRCT和肺功能测试。获取了以下以患者为中心的测量指标:改良Borg呼吸困难指数(Borg评分)、呼吸视觉模拟评分(VAS)和健康评估问卷残疾指数(HAQ-DI)。HRCT异常根据传统的基于视觉阅片者的评分(CoVR)和CaM进行评分。使用线性回归分析和Pearson相关性分析计算HRCT评分、生理参数(FVC和DLCO,预测值百分比)结果与以患者为中心的测量指标之间的关系。进行多变量回归模型以确定肺纤维化严重程度的预测变量。

结果

局限性皮肤型SSc患者的HAQ-DI评分低于弥漫性皮肤型SSc患者(p<0.001)。两组的CaM和CoVR评分相似。在单变量分析中,观察到CaM和CoVR之间存在强相关性(p<0.0001)。在多变量分析中,CaM和CoVR评分由DLco、FVC、Borg评分和HAQ-DI预测。年龄、性别、病程、抗拓扑异构酶抗体和改良Rodnan皮肤评分(mRSS)与CaM和CoVR方法评估的肺纤维化严重程度无显著相关性。

结论

尽管发现CaM评分结果与CoVR总分之间密切相关,但CaM分析显示与DLco的相关性更显著(比FVC更显著),以及与以患者为中心的感知呼吸困难和功能残疾测量指标的相关性更显著。计算机辅助断层分析计算效率高,结合生理和以患者为中心的测量指标,可为准确评估和监测疾病进展或治疗反应提供一种方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/afd8/4773230/538eddfb974a/pone.0149240.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/afd8/4773230/8cda7f1ad7fb/pone.0149240.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/afd8/4773230/538eddfb974a/pone.0149240.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/afd8/4773230/8cda7f1ad7fb/pone.0149240.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/afd8/4773230/538eddfb974a/pone.0149240.g002.jpg

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