Idiopathic pulmonary fibrosis (IPF) is the most common fibrotic lung disease, with 50,000 new cases peryear in the United States. IPF if a rapidly progressive and fatal disease, with half of patients dying within 2years. The disease is heterogeneous, and there is wide variability in responsiveness to existing antifibrotictherapies. Development of new therapeutic agents for IPF and other forms of pulmonary fibrosis is hindered bya lack of externally validated quantitative biomarkers to stratify patient phenotype, evaluate longitudinalresponse to therapy, and serve as a surrogate endpoint. Thus, there is an urgent need to develop quantitativebiomarkers that accurately predict prognosis and assess disease activity to guide management plans amongthese patients. Current biomarkers including pulmonary function tests, composite biomarkers, and patient-related outcomes are insufficient for guiding clinical trials and clinical practice. High-resolution computedtomography (CT) is routinely used in all patients with IPF, and a quantitative CT biomarker that can be appliedto existing images would avoid additional patient cost and radiation. Current CT biomarkers are based onsubjective visual assessment or quantification of lung opacities and have not been successfully used toevaluate longitudinal response to therapy or as a surrogate endpoint for clinical trials. A new quantitative CTbiomarker is needed. In patients with IPF and other forms of pulmonary fibrosis, subpleural fibrotic scars resultin progressive worsening of pulmonary surface irregularity (PSI). We developed a quantitative CT biomarker tomeasure PSI on high-resolution CT images to generate a PSI score in tenths of a millimeter. The PSI score isindependent of lung opacities and is prognostic of transplant-free survival in pilot single-institution retrospectivestudies. We propose to externally validate the PSI score using data and high-resolution CTs from thePulmonary Fibrosis Foundation (PFF) patient registry, a large prospective multicenter database that hascollected baseline clinical data, longitudinal patient-related outcomes, and survival data from patients in theUnited States with IPF (N=1200) and other forms of pulmonary fibrosis (N=603). More specifically, we aim tovalidate the accuracy of the PSI score on the baseline high-resolution CT images for predicting transplant-freesurvival and longitudinal changes in pulmonary function test and patient-related outcomes in patients with IPFand other forms of pulmonary fibrosis in the PFF patient registry. We hypothesize that the PSI score will predicttransplant-free survival and longitudinal changes in pulmonary functional parameters and patient-relatedoutcomes in patients with IPF and other forms of pulmonary fibrosis. We also aim to develop a fully automatedPSI score and validate this against the semi-automated PSI score. We hypothesize that the fully automatedPSI score will have high correlation and comparable accuracy to the semi-automated method. This study willmove 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.
Project narrative: Idiopathic pulmonary fibrosis (IPF) is the most common fibrotic lung disease and is a rapidly progressive and fatal disease with limited treatment options due to the lack of an externally validated biomarker to stratify patient phenotype, evaluate longitudinal response to therapy, and serve as a surrogate endpoint in clinical trials and clinical practice. High-resolution computed tomography (CT) is routinely acquired for all patients with IPF and other forms of pulmonary fibrosis, and a CT biomarker that can be applied to existing high-resolution CT images would add no additional patient cost or radiation to the standard of care. We developed a quantitative biomarker to measure pulmonary surface irregularity (PSI) on high-resolution CT images to generate a PSI score in tenths of a millimeter, and the purpose of this proposal is to externally validate the PSI score as a quantitative biomarker for IPF and other causes of pulmonary fibrosis using existing high-resolution CT images and data from the Pulmonary Fibrosis Foundation Patient Registry (N=2003). Age ; ages ; Automation ; Carbon Monoxide ; Cicatrix ; Scars ; Clinical Trials ; Diffusion ; Disease ; Disorder ; Foundations ; indexing ; Lung ; Lung Respiratory System ; pulmonary ; Lung diseases ; Pulmonary Diseases ; Pulmonary Disorder ; Respiratory Disease ; Respiratory System Disease ; Respiratory System Disorder ; disease of the lung ; disorder of the lung ; lung disorder ; Pulmonary function tests ; Lung Function Tests ; Respiratory Function Tests ; Methods ; mortality ; Patient Outcomes Assessments ; Patient Reported Measures ; Patient Reported Outcomes ; Patients ; Phenotype ; Physiology ; Pulmonary Fibrosis ; lung fibrosis ; Research ; Retrospective Studies ; Computer software ; Software ; X-Ray Computed Tomography ; CAT scan ; CT X Ray ; CT Xray ; CT imaging ; CT scan ; Computed Tomography ; Tomodensitometry ; X-Ray CAT Scan ; X-Ray Computerized Tomography ; Xray CAT scan ; Xray Computed Tomography ; Xray computerized tomography ; catscan ; computed axial tomography ; computer tomography ; computerized axial tomography ; computerized tomography ; Transplantation ; transplant ; United States ; Vital capacity ; Forced Vital Capacity ; Gender ; Measures ; Surrogate Markers ; surrogate bio-markers ; surrogate biomarkers ; Data Set ; Dataset ; Surrogate Endpoint ; Surrogate End Points ; base ; lung imaging ; Pulmonary imaging ; lung scanning ; Surface ; Clinical ; prognostic ; Training ; Visual ; Databases ; Data Bases ; data base ; Measurement ; Disease Progression ; Patient Selection ; Phase III Clinical Trials ; Phase 3 Clinical Trials ; phase III protocol ; Therapeutic Agents ; millimeter ; Severities ; Protocol ; Protocols documentation ; System ; cohort ; Speed ; advanced illness ; advanced disease ; Agreement ; Radiation ; response ; drug development ; patient registry ; Institution ; Data ; high resolution CT ; High Resolution Computed Tomography ; Molecular Marker of Prognosis ; Prognosis Marker ; prognostic biomarker ; prognostic indicator ; Prognostic Marker ; Clinical Data ; Validation ; Development ; developmental ; Image ; imaging ; cost ; Outcome ; prospective ; novel therapeutics ; new drug treatments ; new drugs ; new therapeutics ; new therapy ; next generation therapeutics ; novel drug treatments ; novel drugs ; novel therapy ; standard of care ; Biological Markers ; bio-markers ; biologic marker ; biomarker ; clinical practice ; patient stratification ; stratified patient ; primary endpoint ; primary end point ; early phase trial ; idiopathic pulmonary fibrosis ; diffuse interstitial pulmonary fibrosis ; antifibrotic treatment ; antifibrotic therapy ; Prognosis ;
