Computer-aided Quantification of Pulmonary Fibrosis in Patients with Lung Cancer: Relationship to Disease-free Survival.

Abstract

Background Interstitial lung abnormalities (ILAs) are present at CT in about 10% of individuals undergoing lung cancer screening. The relationship between histologic findings of ILAs and their influence on patient prognosis remains unknown. Purpose To evaluate the percentage of ILAs at preoperative CT, as measured by radiologists and a computer-aided detection (CAD) software, as a predictor of disease-free survival in patients with lung cancer. Materials and Methods This retrospective study evaluated 217 consecutive patients who underwent complete resection of lung cancer from April 2010 to December 2015. Two radiologists, blinded to the patients' clinical information, scored percentage fibrosis extent and determined whether ILAs and the usual interstitial pneumonia (UIP) pattern were present. They assessed ILA progression at follow-up CT. Two pathologists determined the presence of an UIP pattern. Percentage fibrosis extent was also measured by using CAD. Binary logistic regression analysis was performed to determine whether the CAD percentage fibrosis extent was associated with ILA at CT. Multivariable Cox regression analysis was used to evaluate the significance of CAD percentage fibrosis extent as a predictor of prognosis. Results The radiologists classified 47 patients with ILAs and 24 patients with a UIP pattern at chest CT. The pathologists detected a UIP pattern in 25 patients. CT abnormalities showed progression over a 2-year period in all patients with histologic evidence of UIP. After adjustment for age, sex, and smoking index, the CAD percentage fibrosis extent was independently associated with ILA (odds ratio: 3.1; 95% confidence interval [CI]: 2.1, 4.7; P < .001). After adjustment for age, forced expiratory volume in 1 second (percentage predicted) radiologist-assessed percentage fibrosis extent, and pathologic stage, CAD percentage fibrosis extent was independently associated with worse disease-free survival (hazard ratio: 1.3; 95% CI: 1.1, 1.6; P < .001). Conclusion Greater computer-aided detection percentage fibrosis extent at preoperative CT independently predicted worse disease-free survival in patients with lung cancer. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Goo in this issue.