Quantitative CT in the real-world evaluation of progressive pulmonary fibrosis; the REVISE PPF multicentre observational study

RATIONALE AND OBJECTIVE: We assessed whether an FDA-cleared quantitative CT (qCT) tool (Brainomix, e-Lung) identifies progressive pulmonary fibrosis (PPF) earlier than routine clinical diagnosis and evaluated the prognostic value of baseline and serial imaging biomarkers. METHODS: Multicentre retrospective study involving University of Alabama (UAB), Weill Cornell Medicine (WCM) and University of Chicago (UChicago); n = 509. HRCTs were analysed with e-Lung to derive Weighted Reticulovascular Score (WRVS, %), Total Disease Extent (TDE, %), and e-Lung Volume (mL). Prespecified progression thresholds were an absolute WRVS increase of ≥ 3 percentage points, an absolute TDE increase of ≥ 1.5 percentage points, and a relative e-Lung Volume decline of ≥ 10%, over less than 2 years. We compared the earliest qCT progression date with recorded clinical PPF diagnoses, assessed clinically stable controls, and modelled associations with future PPF and mortality using adjusted time-varying Cox models. RESULTS: Among 200 patients with PPF and serial HRCTs meeting the prespecified timing criterion, qCT identified progression earlier in 78% (UAB), 83% (WCM), and 47% (UChicago), with mean lead times of 434, 847, and 220 days, respectively. Among 187 clinically stable patients meeting the same serial-imaging criterion, progression thresholds were met in 67%, 56%, and 42%, respectively. High-risk baseline WRVS (≥15%) predicted future PPF (OR 4.09, 2.48, and 2.30) and mortality (HR 2.03 pooled UAB/WCM; 2.75 UChicago). Per 1-percentage-point increase, adjusted mortality HRs were 1.15 and 1.19 for WRVS and 1.05 and 1.04 for TDE in pooled UAB/WCM and UChicago, respectively. Threshold crossings were also associated with mortality (WRVS: HR 6.50 pooled UAB/WCM, 4.05 UChicago; TDE: 7.60 and 3.26; e-Lung Volume: 8.20 and 2.59). CONCLUSION: qCT detects radiological progression months to years before clinical PPF diagnoses. Integrating e-Lung into ILD pathways could accelerate treatment decisions and personalize follow-up.