title: Application of Quantitative Autofluorescence Bronchoscopy Image Analysis Method in Identifying Bronchopulmonary Cancer.
abstract: Autofluorescence bronchoscopy shows good sensitivity and poor specificity in detecting dysplasia and cancer of the bronchus. Through quantitative analysis on the target area of autofluorescence bronchoscopy image, determine the optimal identification index and reference value for identifying different types of diseases and explore the value of autofluorescence bronchoscopy in diagnosis of lung cancer. Patients with 1 or more preinvasive bronchial lesions were enrolled and followed up by white-light bronchoscope and autofluorescence bronchoscopy. Color space quantitative image analysis was conducted on the lesion shown in the autofluorescence image using MATLAB image measurement software. A retrospective analysis was conducted on 218 cases with 1208 biopsies. One hundred seventy-three cases were diagnosed as positive, which included 151 true-positive cases and 22 false-positive cases. White-light bronchoscope associated with autofluorescence bronchoscopy was able to differentiate between benign and malignant lesion with a high sensitivity, specificity, positive predictive value, and negative predictive value (92.1%, 59.3%, 87.3%, and 71.1%, respectively). Taking 1.485 as the cutoff value of receiver operating characteristic of red-to-green value to differentiate benign and malignant diseases, the diagnostic sensitivity reached 82.3% and the specificity reached 80.5%. U values could differentiate invasive carcinoma and other groups well. Quantitative image analysis method of autofluorescence bronchoscopy provided effective scientific basis for the diagnosis of lung cancer and precancerous lesions.
authors.affiliation: 1 Department of Endoscopy, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.
authors.forename: Xiaoxuan
authors.initials: X
authors.lastname: Zheng
authors.affiliation: 2 Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai, China.
authors.forename: Hongkai
authors.initials: H
authors.lastname: Xiong
authors.affiliation: 2 Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai, China.
authors.forename: Yong
authors.initials: Y
authors.lastname: Li
authors.affiliation: 3 Department of Pulmonary Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.
authors.forename: Baohui
authors.initials: B
authors.lastname: Han
authors.affiliation: 1 Department of Endoscopy, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.
authors.forename: Jiayuan
authors.initials: J
authors.lastname: Sun
mesh_terms: D001999:Bronchoscopy / Q000379:methods; D002294:Carcinoma, Squamous Cell / Q000000981:diagnostic imaging*; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D061848:Optical Imaging; D012372:ROC Curve; D012189:Retrospective Studies
keywords: autofluorescence bronchoscopy; diagnosis; lung cancer; medical image processing; white-light bronchoscopy