Idiopathic pulmonary fibrosis disease progression: a dynamic quantitative chest computed tomography follow-up analysis

Haishuang Sun; Min Liu; Han Kang; Xiaoyan Yang; Peiyao Zhang; Rongguo Zhang; Huaping Dai; Chen Wang

doi:10.21037/qims-22-843

Idiopathic pulmonary fibrosis disease progression: a dynamic quantitative chest computed tomography follow-up analysis

Quant Imaging Med Surg. 2023 Mar 1;13(3):1488-1498. doi: 10.21037/qims-22-843. Epub 2023 Jan 9.

Authors

Haishuang Sun^{1

2

3}, Min Liu^{3

4}, Han Kang⁵, Xiaoyan Yang², Peiyao Zhang⁴, Rongguo Zhang⁵, Huaping Dai^{2

3}, Chen Wang^{1

2

3}

Affiliations

¹ Department of Respiratory Medicine, The First Hospital of Jilin University, Changchun, China.
² National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Diseases, Institute of Respiratory Medicine, Chinese Academy of Medical Sciences, Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China.
³ Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
⁴ Department of Radiology, China-Japan Friendship Hospital, Beijing, China.
⁵ Institute of Advanced Research, Infervision Medical Technology Co., Ltd., Beijing, China.

Abstract

Background: To clarify whether dynamic quantification of variables derived from chest high-resolution computed tomography (HRCT) can assess the progression of idiopathic pulmonary fibrosis (IPF).

Methods: Patients with IPF who underwent serial computed tomography (CT) imaging were retrospectively enrolled. Several structural abnormalities seen on HRCT in IPF were segmented and quantified. Patients were divided into 2 groups according to their pulmonary function test (PFT) results: those with disease stabilization and those with disease progression, and differences between the groups were analyzed.

Results: There were no statistically significant differences between the 2 patient groups for the following parameters: baseline PFTs, total lesion extent, lesion extent at different sites in the lungs, and pulmonary vessel-related parameters (with P values ranging from 0.057 to 0.894). Median changes in total lung volume, total lesion volume, and total lesion ratio were significantly higher in patients with worsening disease compared with those with stable disease (P<0.001). There was a significant increase in total lesion volume of 214.73 mL [interquartile range (IQR), 68.26 to 501.46 mL] compared with 3.67 mL (IQR, -71.70 to 85.33 mL) in the disease progression group compared with the disease stability group (P=0.001). The decline in pulmonary vessel volume and number of pulmonary vessel branches was more pronounced in the group with functional worsening compared with the group with functional stability. Moreover, changes in lesion volume ratio were negatively correlated with changes in diffusing capacity of the lungs for carbon monoxide (DLco) during follow-up (R=-0.57, P<0.001), and changes in pulmonary vessel-related parameters demonstrated positive correlation with DLco (with R ranging from 0.27 to 0.53, P<0.001) and forced vital capacity (FVC) (with R ranging from 0.44 to 0.61, P<0.001).

Conclusions: Changes in CT-related parameters during follow-up may have better predictive performance compared with baseline imaging parameters and PFTs for disease progression in IPF.

Keywords: Idiopathic pulmonary fibrosis (IPF); high-resolution computed tomography (HRCT); progression; quantitative computed tomography (CT).