Assessment of survival in patients with idiopathic pulmonary fibrosis using quantitative HRCT indexes

Abstract

Background: The assessment of Idiopathic Pulmonary Fibrosis (IPF) using HRCT requires great experience and is limited by a significant inter-observer variability, even between trained radiologists. The evaluation of HRCT through automated quantitative analysis may hopefully solve this problem. The accuracy of CT-histogram derived indexes in the assessment of survival in IPF patients has been poorly studied. Methods: Forty-two patients with a diagnosis of IPF and a follow up time of 3 years were retrospectively collected; HRCT and Pulmonary Function Tests (PFTs) performed at diagnosis time were analysed; the extent of fibrotic disease was quantified on HRCT using kurtosis, skewness, Mean Lung Density (MLD), High attenuation areas (HAA%) and Fibrotic Areas (FA%). Univariate Cox regression was performed to assess hazard ratios for the explored variables and a multivariate model considering skewness, FVC, DLCO and age was created to test their prognostic value in assessing survival. Through ROC analysis, threshold values demonstrating the best sensitivity and specificity in predicting mortality were identified. They were used as cut-off points to graph Kaplan-Meier curves specific for the CT-indexes. Results: Kurtosis, skewness, MLD, HAA% and FA% were good predictors of mortality (HR 0.44, 0.74, 1.01, 1.12, 1.06; p = 0.03, p = 0.01, p = 0.02, p = 0.02 and p = 0.017 respectively). Skewness demonstrated the lowest Akaike’s information criterion value (55.52), proving to be the best CT variable for prediction of mortality. Significant survival differences considering proposed cut-off points were also demonstrated according to kurtosis (p = 0. 02), skewness (p = 0.005), MLD (p = 0.003), HAA% (p = 0.009) and FA% (p = 0.02) – obtained from quantitative HRCT analysis at diagnosis time. Conclusions: CT-histogram derived indexes may provide an accurate estimation of survival in IPF.