Quantification of Interstitial Lung Diseases, From the <i>AJR</i> Special Series on Quantitative Imaging.

Abstract

High-resolution CT (HRCT) plays an important role in diagnosing and monitoring interstitial lung diseases (ILDs). Despite advances, predicting disease progression and treatment response remains challenging. HRCT enables noninvasive visualization and classification of patterns of lung injury and assessment of disease extent. Visual estimation of CT extent of fibrotic lung disease is an independent predictor of mortality and progression but is subjective, with only modest interobserver agreement for radiologic interpretation of ILD. Machine learning-based textural analyses of fibrosis extent on baseline and serial HRCT scans show robust correlations with physiologic measures and strong association with risk of disease progression or mortality across various fibrosing ILDs. In idiopathic pulmonary fibrosis, quantitative CT (QCT) assessment is associated with physiologic impairment and risk of progression and death, and increasing severity of fibrosis on longitudinal evaluation is associated with increased risk of progression and death. Similar results have been noted for fibrotic hypersensitivity pneumonitis and connective tissue disease. This review focuses on QCT techniques for ILDs. We describe the clinical need for quantification of lung disease and illustrate the role of conventional visual evaluation and of QCT approaches in defining disease severity, prognosis, and longitudinal progression, both in established disease and in preclinical interstitial abnormalities.