Pulmonary Surface Irregularity score: A Quantitative CT Biomarker for Idiopathic Pulmonary Fibrosis

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PROJECT SUMMARY: Idiopathic pulmonary fibrosis (IPF) is the most common fibrotic lung disease, with 50,000 new cases per year in the United States. IPF if a rapidly progressive and fatal disease, with half of patients dying within 2 years. The disease is heterogeneous, and there is wide variability in responsiveness to existing antifibrotic therapies. Development of new therapeutic agents for IPF and other forms of pulmonary fibrosis is hindered by a lack of externally validated quantitative biomarkers to stratify patient phenotype, evaluate longitudinal response to therapy, and serve as a surrogate endpoint. Thus, there is an urgent need to develop quantitative biomarkers that accurately predict prognosis and assess disease activity to guide management plans among these patients. Current biomarkers including pulmonary function tests, composite biomarkers, and patient- related outcomes are insufficient for guiding clinical trials and clinical practice. High-resolution computed tomography (CT) is routinely used in all patients with IPF, and a quantitative CT biomarker that can be applied to existing images would avoid additional patient cost and radiation. Current CT biomarkers are based on subjective visual assessment or quantification of lung opacities and have not been successfully used to evaluate longitudinal response to therapy or as a surrogate endpoint for clinical trials. A new quantitative CT biomarker is needed. In patients with IPF and other forms of pulmonary fibrosis, subpleural fibrotic scars result in progressive worsening of pulmonary surface irregularity (PSI). We developed a quantitative CT biomarker to measure PSI on high-resolution CT images to generate a PSI score in tenths of a millimeter. The PSI score is independent of lung opacities and is prognostic of transplant-free survival in pilot single-institution retrospective studies. We propose to externally validate the PSI score using data and high-resolution CTs from the Pulmonary Fibrosis Foundation (PFF) patient registry, a large prospective multicenter database that has collected baseline clinical data, longitudinal patient-related outcomes, and survival data from patients in the United States with IPF (N=1200) and other forms of pulmonary fibrosis (N=603). More specifically, we aim to validate the accuracy of the PSI score on the baseline high-resolution CT images for predicting transplant-free survival and longitudinal changes in pulmonary function test and patient-related outcomes in patients with IPF and other forms of pulmonary fibrosis in the PFF patient registry. We hypothesize that the PSI score will predict transplant-free survival and longitudinal changes in pulmonary functional parameters and patient-related outcomes in patients with IPF and other forms of pulmonary fibrosis. We also aim to develop a fully automated PSI score and validate this against the semi-automated PSI score. We hypothesize that the fully automated PSI score will have high correlation and comparable accuracy to the semi-automated method. This study will move the PSI software towards FDA clearance and full automation for use in clinical trials and clinical practice, thereby speeding up anti-fibrotic drug development for IPF and other forms of pulmonary fibrosis.