Linlin Qi1, Wenwen Lu2, Lin Yang3, Wei Tang1, Shijun Zhao1, Yao Huang1, Ning Wu1,4, Jianwei Wang1. 1. Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China. 2. Department of Ophthalmology, Beijing Key Laboratory of Restoration of Damaged Ocular Nerve, Peking University Third Hospital, Beijing 100191, China. 3. Department of Diagnostic Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China. 4. PET-CT Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
Abstract
BACKGROUND: To explore the role of qualitative and quantitative imaging features of pulmonary subsolid nodules (SSNs) in differentiating invasive adenocarcinoma (IAC) from minimally invasive adenocarcinoma (MIA) and preinvasive lesions. METHODS: We reviewed the clinical records of our institute from October 2010 to December 2015 and included 316 resected SSNs from 287 patients: 260 pure ground-glass nodules, 47 part-solid nodules with solid components ≤5 mm, and 9 ground-glass nodules (GGNs) with cystic airspaces. According to the pathologic review results, 307 SSNs in addition to nine GGNs with cystic airspaces were divided into two groups: A, including atypical adenomatous hyperplasia (AAH) (n=15), adenocarcinoma in situ (AIS) (n=56), and MIA (n=41); B, including 195 IACs. Univariate and binary logistic regression analyses were conducted to identify independent risk factors for IAC. RESULTS: Univariate analysis showed significant differences between groups regarding patient age, mean diameter, mean and relative computed tomography (CT) values, volume, mass (all P<0.001), and morphological features including lobulated sign (P<0.001), spiculated sign (P=0.028), vacuole sign/air bronchogram (P<0.001), and pleural retraction (P=0.017). Binary logistic regression and receiver operating characteristic analysis indicated the SSN mass as the only independent risk factor of IAC (odds ratio, 1.007; P<0.001), with an optimal cutoff value of 283.2 mg [area under curve (AUC): 0.859; sensitivity: 68.7%; specificity: 92.9%]. Among lepidic, acinar, and papillary adenocarcinomas, we found significant differences for the vacuole sign/air bronchogram (P=0.032) and mean and relative CT values (P<0.001). All nine GGNs with cystic airspaces were IACs. CONCLUSIONS: The SSN mass with an optimal cutoff value of 283.2 mg may be reliable for differentiating IAC from MIA and preinvasive lesions. 2019 Journal of Thoracic Disease. All rights reserved.
BACKGROUND: To explore the role of qualitative and quantitative imaging features of pulmonary subsolid nodules (SSNs) in differentiating invasive adenocarcinoma (IAC) from minimally invasive adenocarcinoma (MIA) and preinvasive lesions. METHODS: We reviewed the clinical records of our institute from October 2010 to December 2015 and included 316 resected SSNs from 287 patients: 260 pure ground-glass nodules, 47 part-solid nodules with solid components ≤5 mm, and 9 ground-glass nodules (GGNs) with cystic airspaces. According to the pathologic review results, 307 SSNs in addition to nine GGNs with cystic airspaces were divided into two groups: A, including atypical adenomatous hyperplasia (AAH) (n=15), adenocarcinoma in situ (AIS) (n=56), and MIA (n=41); B, including 195 IACs. Univariate and binary logistic regression analyses were conducted to identify independent risk factors for IAC. RESULTS: Univariate analysis showed significant differences between groups regarding patient age, mean diameter, mean and relative computed tomography (CT) values, volume, mass (all P<0.001), and morphological features including lobulated sign (P<0.001), spiculated sign (P=0.028), vacuole sign/air bronchogram (P<0.001), and pleural retraction (P=0.017). Binary logistic regression and receiver operating characteristic analysis indicated the SSN mass as the only independent risk factor of IAC (odds ratio, 1.007; P<0.001), with an optimal cutoff value of 283.2 mg [area under curve (AUC): 0.859; sensitivity: 68.7%; specificity: 92.9%]. Among lepidic, acinar, and papillary adenocarcinomas, we found significant differences for the vacuole sign/air bronchogram (P=0.032) and mean and relative CT values (P<0.001). All nine GGNs with cystic airspaces were IACs. CONCLUSIONS: The SSN mass with an optimal cutoff value of 283.2 mg may be reliable for differentiating IAC from MIA and preinvasive lesions. 2019 Journal of Thoracic Disease. All rights reserved.
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