Predicting Postoperative Lung Function in Patients with Lung Cancer Using Imaging Biomarkers

• Published in: Diseases Vol. 12; no. 4; p. 65
• Main Authors: Kwon, Oh-Beom, Lee, Hae-Ung, Park, Ha-Eun, Choi, Joon-Young, Kim, Jin-Woo, Lee, Sang-Haak, Yeo, Chang-Dong
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 01.04.2024
• Subjects: Algorithms; Analysis; Biological markers; Biomarkers; Cancer therapies; Care and treatment; Chemotherapy; Chronic obstructive pulmonary disease; Comorbidity; Computed tomography; CT imaging; Deep learning; Emphysema; Health aspects; imaging biomarkers; Lung cancer; Lung diseases; Lung diseases, Obstructive; Medical imaging; Medical research; Medicine, Experimental; postoperative lung function; Prognosis; Pulmonary arteries; Pulmonary artery; Radiation therapy; Respiratory diseases; Respiratory function; Respiratory tract; Thoracic surgery; Variables; South Korea; lung cancer; imaging biomarkers; deep learning; postoperative lung function
• ISSN: 2079-9721; 2079-9721
• DOI: 10.3390/diseases12040065

There have been previous studies conducted to predict postoperative lung function with pulmonary function tests (PFTs). Computing tomography (CT) can quantitatively measure small airway walls' thickness, lung volume, pulmonary vessel volume, and emphysema area, which reflect the severity of respiratory diseases. These measurements are considered imaging biomarkers. This study aimed to predict postoperative lung function with imaging biomarkers. A retrospective analysis of 79 patients with lung cancer who had undergone lung surgery was completed. Postoperative lung function measured by forced expiratory volume in one second (FEV ) was defined as an outcome. Preoperative clinico-pathological parameters and imaging biomarkers representing airway walls' thickness, severity of emphysema, total lung volume, and pulmonary vessel volume were measured quantitatively in chest CT by an automated segmentation software, AVIEW COPD. Pi1 was defined as the first percentile along the histogram of lung attenuation that represents the degree of emphysema. Wafw was defined as the airway thickness, which was calculated by the full-width at half-maximum method. Logistic and linear regressions were used to assess these variables. If the actual postoperative FEV was higher than the postoperative FEV projected by a formula, the group was considered to be preserved. Among the 79 patients, 16 of the patients were grouped as a non-preserved group, and 63 of them were grouped as a preserved group. The patients in the preserved FEV group had a higher vessel volume than the non-preserved group. Pi1 and Wafw were independent predictors of postoperative lung function. Imaging biomarkers can be considered significant variables in predicting postoperative lung function in patients with lung cancer.