# Extent of alveolar collapse in expiratory CT as a prognostic marker in idiopathic pulmonary fibrosis

## TL;DR

This study explores whether CT scans during inspiration and expiration can predict outcomes in idiopathic pulmonary fibrosis patients by analyzing alveolar collapse.

## Contribution

The study introduces paired inspiratory/expiratory CT histogram analysis as a novel prognostic marker for idiopathic pulmonary fibrosis.

## Key findings

- CT-derived histogram skewness showed better predictive performance than FVC% for outcome prediction in IPF.
- Histogram measures significantly differed between patients who survived and those who died or were transplanted.
- Paired inspiratory/expiratory CT histogram analysis is a promising method to assess alveolar collapse in IPF.

## Abstract

To evaluate whether distribution measures of CT-based attenuation histograms in inspiration and expiration can indicate alveolar collapse and serve as a predictive marker in patients with idiopathic pulmonary fibrosis (IPF). This single-center retrospective longitudinal study analyzed CT scans of IPF patients in inspiration and expiration. The patient population was divided into two subgroups based on their status 3 years after baseline CT (death or transplantation versus clinical surveillance). Attenuation histograms in inspiration and expiration were created and analyzed. A Mann-Whitney U test was conducted to assess the difference of CT-derived histogram measures (including skewness) between the two subgroups. Logistic regression was applied to model the ability to distinguish between subgroups using baseline forced vital capacity (FVC%) and CT-derived histogram measures. The study included 66 patients (mean age 69.5 ± 10.9 years, 58 males). After the individual three-year observation period, 37 patients were still alive while 29 had either died or received a transplantation. The two patient subgroups were significantly different in terms of all CT-derived histogram measures and the baseline FVC%. A logistic regression model that only included the CT-derived histogram measure skewness had a better predictive performance (AUC = 0.793, 95% CI = 0.685–0.900) compared to the FVC% model alone (0.708, 0.581–0.836). Whereas further evaluation is needed, paired inspiratory/expiratory attenuation histogram analysis offers a promising approach as a prognostic imaging marker to improve outcome prediction and assess alveolar collapse in IPF.