Use of quantitative CT chest imaging to derive and assess a radiographic phenotype of deployment-related constrictive bronchiolitis.

IF 5.8 2区 医学 Q1 Medicine
Alexander J Bell, Maria Masotti, Sundaresh Ram, Gregory Pappas, Robert F Miller, Ella A Kazerooni, Charles R Hatt, MeiLan K Han, Bradley W Richmond, Michael J Falvo, Craig J Galban, John J Osterholzer
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引用次数: 0

Abstract

Background: Efforts to phenotype veterans that developed respiratory symptoms following deployments to the Southwest Asia Theater of Military Operation have been limited by the insensitivity of current non-invasive testing to objectively identify deployment-related constrictive bronchiolitis and other features of chronic lung injury. In this study, we derived a quantitative CT (QCT)-based radiographic phenotype of biopsy-proven deployment-related constrictive bronchiolitis (DRCB) and assessed its ability to assist in the phenotyping of non-biopsied formerly deployed symptomatic veterans.

Methods: QCT analysis combined with demographic, physiologic, symptom, and exposure data was obtained from three cohorts: military personnel with biopsy-proven deployment-related constrictive bronchiolitis (DRCB, n = 37), formerly deployed symptomatic veterans (FDSV, n = 71), and asymptomatic civilians (Control, n = 98). Differences in unadjusted QCT metrics and demographic variables between cohorts were identified and further assessed by principal component analysis. Thereafter, adjusted data from the DRCB cohort was used to derive a QCT-based radiographic phenotype of DRCB expressed as a DRCB-Probability Index (DRCB-PI). Application of the DRCB-PI to the FDSV cohort was used to assess additional phenotypic metrics associated with the DRCB phenotype (DRCB-PI > 0.5).

Results: Individual unadjusted QCT metrics for functional small airways disease and high attenuation area were elevated in DRCB and FDSV cohorts (relative to Control). Primary component analysis revealed that DRCB and FDSV cohorts overlapped and were distinguished from the Control cohort. The FDSV subjects whose DRCB-PI was > 0.5 had greater evidence of small airways disease (assessed by oscillometry and QCT) and self-reported more intense immediate health effects to their exposures to military burn pit smoke, and sand and dust.

Conclusions: Application of a QCT-derived radiographic phenotype of DRCB identified a subset of veterans with evidence of abnormal small airways and more severe self-reported health effects following inhalational exposures during military deployment. Future studies incorporating QCT may help establish non-invasive strategies to detect DRCB and other forms of chronic lung injury.

使用定量CT胸部成像来推导和评估与部署相关的缩窄性细支气管炎的影像学表型。
背景:对部署到西南亚军事行动战区后出现呼吸道症状的退伍军人进行表型分析的努力受到限制,因为目前的非侵入性检测对客观识别部署相关的缩窄性细支气管炎和其他慢性肺损伤特征不敏感。在这项研究中,我们得出了一种基于定量CT (QCT)的放射学表型,该表型是由活检证实的部署相关的缩窄性细支气管炎(DRCB),并评估了其帮助未活检的前有症状的部署退伍军人进行表型分析的能力。方法:结合人口统计学、生理学、症状和暴露数据,从三个队列中获得QCT分析:活检证实与部署相关的缩窄性细支气管炎的军人(DRCB, n = 37),以前有症状的部署退伍军人(FDSV, n = 71)和无症状的平民(对照组,n = 98)。未调整的QCT指标和人口学变量在队列之间的差异被确定并通过主成分分析进一步评估。此后,利用来自DRCB队列的调整数据,得出基于qct的DRCB放射学表型,表示为DRCB-概率指数(DRCB- pi)。将DRCB- pi应用于FDSV队列,用于评估与DRCB表型相关的其他表型指标(DRCB- pi > 0.5)。结果:在DRCB和FDSV队列中,功能性小气道疾病和高衰减区域的个体未经调整的QCT指标(相对于对照组)升高。主成分分析显示,DRCB和FDSV队列重叠,与对照队列不同。DRCB-PI为>.5的FDSV受试者有更大的小气道疾病证据(通过振荡测量法和QCT评估),并且自我报告暴露于军事烧伤坑烟雾和沙尘对他们的直接健康影响更强烈。结论:应用qct衍生的DRCB放射学表型确定了一组退伍军人,他们有证据表明在军事部署期间吸入性暴露后存在异常的小气道和更严重的自我报告健康影响。未来结合QCT的研究可能有助于建立非侵入性策略来检测DRCB和其他形式的慢性肺损伤。
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来源期刊
Respiratory Research
Respiratory Research RESPIRATORY SYSTEM-
CiteScore
9.70
自引率
1.70%
发文量
314
审稿时长
4-8 weeks
期刊介绍: Respiratory Research publishes high-quality clinical and basic research, review and commentary articles on all aspects of respiratory medicine and related diseases. As the leading fully open access journal in the field, Respiratory Research provides an essential resource for pulmonologists, allergists, immunologists and other physicians, researchers, healthcare workers and medical students with worldwide dissemination of articles resulting in high visibility and generating international discussion. Topics of specific interest include asthma, chronic obstructive pulmonary disease, cystic fibrosis, genetics, infectious diseases, interstitial lung diseases, lung development, lung tumors, occupational and environmental factors, pulmonary circulation, pulmonary pharmacology and therapeutics, respiratory immunology, respiratory physiology, and sleep-related respiratory problems.
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