e-Lung computed tomography biomarkers are associated with outcomes in fibrotic interstitial lung diseases.

Katharina Abbasi Dezfouli^1,2, Anand Devaraj^3,4,5, Finja A Ottink⁵, Christian Rennison-Jones⁵, Aliki Sifostratoudaki⁵, Claire Fernandez⁵, Oyunbileg von Stackelberg^1,2, Hans-Ulrich Kauczor^1,2, Manuel Debic¹, Kai Schlamp⁶, Katharina Buschulte^2,7, Claus Peter Heussel^2,6, James H Briggs⁵, Stephen Gerry⁸, George W J Harston^5,9, Wassim Bou-Zeid⁵, Olivier Joly⁵, Peter M George^3,4,5, Michael Kreuter¹⁰

¹Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Heidelberg, Germany.

²Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Heidelberg, Germany.

³Interstitial Lung Disease Unit, Royal Brompton Hospital, London, UK.

⁴National Heart and Lung Institute, Imperial College London, London, UK.

⁵Brainomix, Oxford, UK.

⁶Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University Hospital Heidelberg, Heidelberg, Germany.

⁷Center for Interstitial and Rare Lung Diseases, Pneumology and Respiratory Critical Care Medicine, Thoraxklinik, Heidelberg, Germany.

⁸Centre for Statistics in Medicine, University of Oxford, Oxford, UK.

⁹Acute General Medicine, Oxford University Hospitals NHSFT, Oxford, UK.

¹⁰Mainz Center for Pulmonary Medicine, Department of Pneumology, Mainz University Medical Center and Department of Pulmonary, Critical Care and Sleep Medicine, Marienhaus Clinic Mainz, Mainz, Germany.

PubMed PMC DOI PDF

Abstract

BACKGROUND: The e-Lung weighted reticulovascular score (WRVS) is an automated computed tomography biomarker that quantifies interstitial lung disease (ILD) severity and is associated with prognosis in patients with idiopathic pulmonary fibrosis (IPF). The aims of the present study were to evaluate WRVS as a prognostic factor in patients with non-IPF ILD. METHODS: The test cohort comprised patient…

Create a free account to keep reading

Free members get 10 full research views every month across publications, clinical trials, FDA clearances, adverse events, and NIH grants. No credit card required.

Create Free Account Sign In

Want unlimited research access? See Pro plans

Data Accuracy Notice: Research intelligence on Health AI Central is aggregated from public sources (PubMed, ClinicalTrials.gov, FDA, NIH, CMS, and others) and refreshed nightly. Classifications and derived metrics are produced by automated methods described in our Methodology. We recommend verifying critical data points against the primary sources before making decisions.