Lung CT Densitometry in Idiopathic Pulmonary Fibrosis for the Prediction of Natural Course, Severity, and Mortality

Abstract

Background: In this study, we retrospectively assessed the relationships among physiologic measurements, survival, and quantitative high-resolution CT (HRCT) scanning indexes in patients with idiopathic pulmonary fibrosis (IPF).

Methods: Seventy patients (48 male; mean [SD] age, 66.4 [9.0] years) with IPF were enrolled in the study. After segmentation of the lungs in thin-section CT scanning with the patient in the supine position at full inspiration, we assessed following parameters: mean lung attenuation (MLA), skewness, kurtosis, peak attenuation, total lung area, inflexion point with slope, and area right of the inflexion point (AROIP). Additionally, FVC, FEV₁, total lung capacity, diffusing capacity or transfer factor of the lung for carbon monoxide (Dlco), and 6-min walk distance were analyzed. Univariate and multivariate analysis were used for the prediction of physiologic outcomes by HRCT scanning indexes and then were correlated to survival in a proportional hazards analysis.

Results: The strongest correlation was observed between MLA and FEV₁, with an r of -0.63. MLA, peak attenuation, slope, attenuation, and AROIP correlated negatively with all physiologic measurements. AROIP was the best predictor of Dlco. Analysis for prediction of mortality showed that AROIP, kurtosis, and FVC were related significantly to survival. Multivariate regression revealed a significant impact of only AROIP (among age, sex, MLA, skewness, kurtosis, FVC, and Dlco) on survival.

Conclusions: These data indicate that HRCT scanning indexes are correlated to physiologic measurements. The newly defined parameter, AROIP, is of additive value for prediction of outcome.

Trial registry: ClinicalTrials.gov; No.: NCT02951416; URL: www.clinicaltrials.gov.

Keywords: CT densitometry; HRCT index; disease prediction parameters; idiopathic pulmonary fibrosis.