Computed Tomographic Biomarkers in Idiopathic Pulmonary Fibrosis. The Future of Quantitative Analysis

作者：Xiaoping Wu, Grace H. Kim, Margaret L. Salisbury, David Barber, Brian J. Bartholmai, Kevin M. Brown, Craig Conoscenti, Jan De Backer, Kevin R. Flaherty, James F. Gruden, Eric A. Hoffman, Stephen M. Humphries, Joseph Jacob, Toby M. Maher, Ganesh Raghu, Luca Richeldi, Brian D. Ross, Rozsa Schlenker‐Herceg, Nicola Sverzellati, Athol U. Wells, Fernando J. Martínez, David A. Lynch, Jonathan Goldin, Simon Walsh · 发表于：American Journal of Respiratory and Critical Care Medicine · 年份：2018 · DOI：10.1164/rccm.201803-0444pp · 被引用次数：148 · 研究领域：Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis、Medical Imaging and Pathology Studies、Inhalation and Respiratory Drug Delivery

Idiopathic pulmonary fibrosis (IPF) is a chronic lung disease with great variability in disease severity and rate of progression. The need for a reliable, sensitive, and objective biomarker to track disease progression and response to therapy remains a great challenge in IPF clinical trials. Over the past decade, quantitative computed tomography (QCT) has emerged as an area of intensive research to address this need. We have gathered a group of pulmonologists, radiologists and scientists with expertise in this area to define the current status and future promise of this imaging technique in the evaluation and management of IPF. In this Pulmonary Perspective, we review the development and validation of six computer-based QCT methods and offer insight into the optimal use of an imaging-based biomarker as a tool for prognostication, prediction of response to therapy, and potential surrogate endpoint in future therapeutic trials.