Validation of a computed tomography diagnostic model for differentiating fibrotic hypersensitivity pneumonitis from idiopathic pulmonary fibrosis.

Item request has been placed! ×
Item request cannot be made. ×
loading   Processing Request
Read More Add to Saved list
  • Additional Information
    • Source:
      Publisher: Elsevier Country of Publication: Netherlands NLM ID: 101581124 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2212-5353 (Electronic) Linking ISSN: 22125345 NLM ISO Abbreviation: Respir Investig Subsets: MEDLINE
    • Publication Information:
      Original Publication: Amsterdam : Elsevier
    • Subject Terms:
      Alveolitis, Extrinsic Allergic*/diagnostic imaging ; Alveolitis, Extrinsic Allergic*/diagnosis ; Idiopathic Pulmonary Fibrosis*/diagnostic imaging ; Idiopathic Pulmonary Fibrosis*/pathology ; Tomography, X-Ray Computed*/methods; Humans ; Diagnosis, Differential ; Male ; Female ; Aged ; Middle Aged
    • Abstract:
      Background: The diagnosis of fibrotic hypersensitivity pneumonitis (fHP) from other interstitial lung diseases, particularly idiopathic pulmonary fibrosis (IPF), is often difficult. This study aimed to examine computed tomography (CT) findings that were useful for differentiating between fHP and IPF and to develop and validate a radiological diagnostic model.
      Methods: In this study, 246 patients (fHP, n = 104; IPF, n = 142) from two institutions were included and randomly divided into the test (n = 164) and validation (n = 82) groups (at a 2:1 ratio). Three radiologists evaluated CT findings, such as pulmonary fibrosis, small airway disease, and predominant distribution, and compared them between fHP and IPF using binomial logistic regression and multivariate analysis. A prognostic model was developed from the test group and validated with the validation group.
      Results: Ground-glass opacity (GGO) with traction bronchiectasis (TB), honeycombing, hypoattenuation area, three-density pattern, diffuse craniocaudal distribution, peribronchovascular opacities in the upper lung, and random distribution were more common in fHP than in IPF. In multivariate analysis, GGO with TB, peribronchovascular opacities in the upper lung, and random distribution were significant features. The area under the curve of the fHP diagnostic model with the three aforementioned CT features was 0.733 (95% confidence interval [CI], 0.655-0.811, p < 0.001) in the test group and 0.630 (95% CI, 0.504-0.755, p < 0.047) in the validation group.
      Conclusion: GGO with TB, peribronchovascular opacities in the upper lung, and random distribution were important CT features for differentiating fHP from IPF.
      Competing Interests: Declaration of competing interest KK received lectures fees from Boehringer Ingelheim. YK received lectures fees from Boehringer Ingelheim. YM received grants from Boehringer Ingelheim, and lectures fees from Boehringer Ingelheim and AstraZeneca. TJ received lectures fees from Bohlinger Ingelheim, AstraZeneca, and Kyorin Inc. The other authors have no conflicts of interest.
      (Copyright © 2024 The Japanese Respiratory Society. Published by Elsevier B.V. All rights reserved.)
    • Contributed Indexing:
      Keywords: CT; Diagnostic model; Fibrotic hypersensitivity pneumonitis; Idiopathic pulmonary fibrosis
    • Publication Date:
      Date Created: 20240712 Date Completed: 20240825 Latest Revision: 20240825
    • Publication Date:
      20240826
    • Accession Number:
      10.1016/j.resinv.2024.07.002
    • Accession Number:
      38996781