CT tool may detect pulmonary fibrosis progression more than 2 years sooner
Artificial intelligence-powered quantitative CT analysis is capable of identifying signs of pulmonary fibrosis months before clinical diagnosis, according to a new multicenter study.
Published in the Annals of the American Thoracic Society, the findings suggest the technology could help clinicians recognize disease progression earlier. These results could be clinically relevant because available treatments for progressive pulmonary fibrosis can slow lung function decline but cannot reverse existing damage. Earlier recognition of progression may give clinicians an opportunity to reassess monitoring and treatment before additional lung function is lost.
"Lungs can't wait, especially when a disease is progressive and the loss of lung function is irreversible. Recognizing progression as early as possible is therefore critical for people living with progressive pulmonary fibrosis,” noted Martin Beck, senior VP and head of therapeutic area inflammation at German pharma firm Boehringer Ingelheim, which funded the study. “These findings provide valuable insights into how quantitative CT could complement existing clinical assessments and help identify signs of progression earlier. By supporting research such as this, we aim to deepen understanding of [pulmonary fibrosis] and help advance more informed and timely care decisions for patients."
The retrospective study evaluated 509 patients with fibrotic interstitial lung disease across three U.S. specialist centers: the University of Chicago, Weill Cornell Medicine and the University of Alabama at Birmingham. Researchers used Brainomix’s e-Lung, an FDA-cleared quantitative CT tool, to assess imaging markers of disease burden and progression.
These measures identified radiological progression of disease an average of 16 months before clinical pulmonary fibrosis diagnosis, with the interval reaching up to 28 months at one center. The analysis also detected evidence of disease progression on imaging in a substantial proportion of patients who were considered clinically stable at the time of their exam, indicating that quantitative measurements may reveal changes not recognized through conventional assessments.
The findings also indicated that quantitative CT could provide prognostic information; a higher baseline weighted reticulovascular score was associated with increased risk of future pulmonary fibrosis, while a 1.5% change in total disease extent on serial CT scans was associated with increased mortality.
“Tools such as e-Lung have the potential to complement the information we gain from symptoms, lung function and conventional radiological assessment,” said lead study author Ayodeji Adegunsoye, a professor and pulmonologist at the University of Chicago Medicine.
Brainomix and Boehringer Ingelheim have plans to continue their collaboration through PROGRESS-PPF, a prospective, multicenter U.S. study examining how AI-powered quantitative CT outputs could complement clinical assessments of disease progression. Their research will help determine whether these measurements can be integrated into routine interstitial lung disease care and whether earlier identification of radiological progression leads to meaningful changes in treatment and patient outcomes.
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In addition to her background in journalism, Hannah also has patient-facing experience in clinical settings, having spent more than 12 years working as a registered rad tech. She began covering the medical imaging industry for Innovate Healthcare in 2021.