ABSTRACT
Purpose To explore the independent predictors of malignant solitary pulmonary nodule (SPN) manifesting as ground-glass nodule (GGN),and to establish a prediction model.Materials and Methods The clinical data and CT images of 362 patients (group A) with pathological-confirmed SPN appearing as GGN in Shanghai Chest Hospital Shanghai Jiaotong University from January 2014 to December 2015 were retrospectively analyzed.The independent predictors of malignant SPN were identified,and the clinical prediction model was established.Another 119 SPN patients in Affiliated Zhoushan Hospital of Wenzhou Medical University were selected as group B to verify the diagnostic efficiency of the prediction model.Results Using multivariate Logistic regression analysis,clear border (OR=6.274,P＜0.01),smooth edge (OR=0.391,P＜0.01),lobulation (OR=3.387,P＜0.01),pleural retraction sign (OR=2.430,P＜0.01),and vocule sign (OR=3.076,P＜0.01)were identified as independent predictors of malignant SPN.The area of the model under the ROC curve was 0.859 with 95％ CI (0.804-0.903).The diagnostic accuracy rate,sensitivity,specificity,positive predictive value and negative predictive value were 85.92％,91.03％,81.97％,92.03％ and 73.53％,respectively.Conclusion In this study,the independent predictors of malignant SPN appearing as GGN were identified,and the prediction model was established.The model can accurately identify SPN and provide effective help for early diagnosis of SPN.
ABSTRACT
Purpose To evaluate the CT features and pathological manifestations of the solid components of mixture ground-glass opacity (GGO) in adenocarcinoma in situ (AIS), minimally invasive adenocarcinom (MIA) and invasive adenocarcinoma (IAC), to analyze the qualitative diagnosis value of solid components of mixture GGO in the diagnosis of AIS, MIA and IAC, to provide reference for the selection of clinical treatment.Materials and Methods Eighteen patients with AIS, 53 patients with MIA and 28 patients with IAC (the maximum diameter smaller than 2 cm) proved by surgery and pathology with CT features appearing as mixture GGO were retrospectively analyzed, CT features of the solid components in three groups were analyzed and compared with pathology.Results The solid components in AIS mainly appeared as punctiform or polygon, with extensive distribution, solid nodules were usually single (17 cases, 94.44%), located in the middle of the lesion (14 cases, 77.78%), with clear binderies (16 cases, 88.89%) and the same density with vessels in the same axis (13 cases, 72.22%); the majority of solid components in MIA appeared as circular or elliptical (33 cases, 62.26%), less than or equal to 5 mm (48 cases, 90.57%), with eccentric or multi-point distribution (45 cases, 84.90%), the boundaries were less sharp (40 cases, 75.47%), with slightly lower density than that of the vasculars in the same level (34 cases, 64.15%); the solid components in IAC mainly appeared as irregular lesions (21 cases, 75.00%), lager than 5 mm (24 cases, 85.71%), with eccentric growth (20 cases, 71.43%) and less sharp boundary (15 cases, 53.57%), the integration of multiple nodules could also be observed. There were statistically significant differences in the CT features of solid components within the lesions among the three groups (P<0.01).Conclusion It is possible to predict the pathological typing and the prognosis of pulmonary mixture GGO in a certain extent according to the different CT features of the solid components in it, and to guide clinical treatment principles.