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CT predictors of outcomes in patients with connective tissue disease and progressive lung fibrosis

  • Arthur Y. Shou
    Correspondence
    Corresponding author at: Department of Radiology, Columbia University Medical Center, 622 West 168th Street, New York, New York 10029, United States of America.
    Affiliations
    Department of Radiology, Columbia University Medical Center, 622 West 168th Street, New York, NY 10032, United States of America
    Search for articles by this author
  • Mary M. Salvatore
    Affiliations
    Department of Radiology, Columbia University Medical Center, 622 West 168th Street, New York, NY 10032, United States of America
    Search for articles by this author
Published:December 02, 2022DOI:https://doi.org/10.1016/j.clinimag.2022.11.022

      Highlights

      • Serial CT variables such as change in extent of fibrosis and pulmonary artery size are predictive of negative outcomes.
      • A novel variable, the right lower lobe anterior bronchial angle, was described. Change predicts negative outcomes.
      • In addition to clinical, pulmonary function test, and single CT variables, serial CT variables predict CTD-ILD progression.

      Abstract

      Purpose

      Progressive fibrosing interstitial lung disease (PF-ILD) is a phenotype defined by rapid clinical progression towards respiratory failure. While idiopathic pulmonary fibrosis is the archetype of PF-ILD, connective tissue disease associated interstitial lung disease (CTD-ILD) can also manifest as PF-ILD. Few studies have described the value of serial computed tomography (CT) in predicting clinical progression of ILD. We explore which single and serial clinical and radiographic variables, in particular serial CT variables and a novel variable, the right lower lobe anterior bronchial angle (RLL-ABA), best predict mortality, oxygen requirement, hospital admissions, and lung transplant in CTD-ILD.

      Methods

      This is a single-center retrospective study of 84 patients with a history of CTD-ILD. Cox survival analysis was used to predict two endpoints, all-cause mortality and composite negative outcomes (CNO): new oxygen requirement, respiratory admission, lung transplant, and death.

      Results

      On serial CT, change in pulmonary artery (PA) size and RLL-ABA were predictive of mortality and CNO, and change in fibrosis was predictive of mortality alone. On single CT, the extent of fibrosis, PA size, and PA to aorta ratio were predictive of mortality and CNO. Among clinical variables, oxygen requirement, forced vital capacity (FVC), change in FVC, and worsening shortness of breath were predictive of mortality and CNO, and diffusing capacity for carbon monoxide was predictive of mortality alone.

      Conclusions

      In addition to clinical and single CT variables, serial CT measurements such as change in extent of fibrosis, PA size, PA to aorta ratio, and RLL-ABA were predictive of mortality and CNO.

      Abbreviations:

      CNO (Composite negative outcomes), CT (computed tomography), CTD (connective tissue disease), CTD-ILD (connective tissue disease-related interstitial lung disease), DLCO (diffusing capacity for carbon monoxide), HRCT (high resolution computed tomography), IPF (idiopathic pulmonary fibrosis), ILD (interstitial lung disease), NSIP (nonspecific interstitial pneumonia), OP (organizing pneumonia), PF-ILD (progressive fibrosing interstitial lung disease), PA (pulmonary artery), PFT (pulmonary function test), RLL ABA (right lower lobe anterior bronchial angle), UIP (usual interstitial pneumonia)

      Keywords

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