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

TL;DR

This study uses quantitative CT scans to identify a lung condition in veterans linked to military deployment, helping to diagnose those with chronic lung injury non-invasively.

Contribution

The paper introduces a QCT-based radiographic phenotype and probability index to identify deployment-related constrictive bronchiolitis in veterans.

Findings

QCT metrics showed elevated functional small airways disease and high attenuation area in DRCB and FDSV cohorts compared to controls.

Veterans with DRCB-PI > 0.5 had more severe small airways disease and reported worse health effects from deployment exposures.

Principal component analysis distinguished DRCB and FDSV cohorts from controls, suggesting potential for non-invasive DRCB detection.

Abstract

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.

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).

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.

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.

The online version contains supplementary material available at 10.1186/s12931-025-03269-8.

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