Evidence map›Paper›PMID 40399908›Full record

ArticleRespiratory research2025

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

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 and 2 more

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In one paragraph

Article in Respiratory research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

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5 · Who and what money

Authors and funding

12 authors.

Alexander J BellDepartment of Radiology, University of Michigan, Ann Arbor, MI, USA.
Maria MasottiDepartment of Biostatistics, University of Michigan, Ann Arbor, MI, USA.
Sundaresh RamDepartment of Radiology, University of Michigan, Ann Arbor, MI, USA.
Gregory PappasAirborne Hazards and Burn Pits Center of Excellence, VA New Jersey Health System, East Orange, NJ, USA.
Robert F MillerDivision of Allergy, Pulmonary, and Critical Care Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
Ella A KazerooniDepartment of Radiology, University of Michigan, Ann Arbor, MI, USA.
Charles R HattDepartment of Radiology, University of Michigan, Ann Arbor, MI, USA.
MeiLan K HanDivision of Pulmonary and Critical Care Medicine, University of Michigan, 2215 Fuller Rd (111G), Ann Arbor, MI, 48105, USA.
Bradley W RichmondDivision of Allergy, Pulmonary, and Critical Care Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
Michael J FalvoAirborne Hazards and Burn Pits Center of Excellence, VA New Jersey Health System, East Orange, NJ, USA.
Craig J GalbanDepartment of Radiology, University of Michigan, Ann Arbor, MI, USA.
John J OsterholzerDivision of Pulmonary and Critical Care Medicine, University of Michigan, 2215 Fuller Rd (111G), Ann Arbor, MI, 48105, USA. oster@umich.edu.

Funding

U.S. Department of Defense GW16015U.S. Department of Veterans Affairs Merit Review Award (JJO)
6 · The paper itself

Abstract

backgroundEfforts 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.

methodsQCT 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).

resultsIndividual 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.

conclusionsApplication 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.

Indexed as

Bronchiolitis ObliteransMilitary PersonnelRadiography, ThoracicTomography, X-Ray ComputedVeteransAdultCohort StudiesFemaleHumansMaleMiddle AgedPhenotypeAirway diseaseEnvironmental exposuresLung injuryMilitary deploymentPhenotypes

Identifiers

PMID40399908
PMCPMC12093805

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.