Low-dose Computer Tomography Screening For Lung Cancer And Differentiating HRCT Features Of Benign And Malignant Solitary Subsolid Nodules

Part ?Community-based lung cancer screening with Low-dose computed tomographyBackground and objectives: Lung cancer is now the most common cancer and the leading cause of cancer death in China.LDCT has been recently applied as a promising approach for lung cancer screening in Western countries as it showed better performance for the detection of early-stage lung cancer and demonstrated a significant reduction in lung cancer-related mortality mainly.However,no reliable information for selecting the screening population in China is currently available.The objectives of the present study were to investigate the efficiency of LDCT in a China and explore a suitable risk classification criterion for the Chinese population.Methods: From 2013 to 2014,subjects from Xuhui District of Shanghai were invited to fill in a home-based questionnaire.Eligible participants were randomly assigned to a screening group or a control group with questionnaire inquiries.Any non-calcified nodules or masses with longest diameters of ?4 mm identified on LDCT images were considered as positive.Results: A total of 6717 eligible participants were randomly enrolled to a study group(3550 to LDCT screening and 3167 to standard care).Overall 3512 participants underwent LDCT screenings and 3145 participants received questionnaire inquiries.A positive screening result was observed in 804 participants(22.9%).After two-year follow-up,lung cancer was detected in 51 participants(1.5%)in the LDCT group versus 10(0.3%)in the control group.Early-stage lung cancer was found in 94.1% vs 20%,respectively.Two cases of lung cancer-specific deaths occurred in the control group,but no death occurred in the LDCT group.Conclusions: Compared to usual care,LDCT led to a 74.1% increase in detecting early-stage lung cancer.This study provides insights about the non-smoking related risk factors of lung cancer in the Chinese population.Part ? HRCT features distinguishing benign and malignant lesions manifesting as persistent solitary subsolid nodulesObjectives: To retrospectively investigate the high-resolution computed tomographic(HRCT)features that distinguish benign lesions(BL)and malignant lesions(ML)appearing as persistent solitary subsolid nodules of 5 to 30 mm in diameter.Methods: From 2015 to 2016,patients in our department with persistent solitary SSNs of 5 mm to 30 mm in size were analyzed retrospectively.All the nodules were classified into two groups: pure ground-glass nodules(p GGNs)and part-solid nodules(PSNs)according to the presence of a solid component.A total of 2028 nodules were enrolled and 1014(including 94 benign and 920 malignant lesions)were randomly selected to establish a predictive model.Independent factor t test or ? 2 test was used for univariate analysis.Logistic regression was used to screen for independent risk factors and establish prediction models.The validation model was used to verify the discriminative efficacy.We also compared the model with other models including Peking University Model,Brock Model,Mayo Model and VA Model.A statistical difference was set at P < 0.05.Results: In p GGN subgroup,multivariate analysis found that a well-defined border and a higher average CT value favored the diagnosis of malignancy The area under the ROC curve of our model was 0.776(95% CI,0.689-0.862,P < 0.05),which was the highest among all the five models.In PSN subgroup,multivariate analysis revealed that a larger size,a well-defined border and a spiculated margin favored the diagnosis of malignancy.The area under the ROC curve of our model was 0.750(95% CI,0.692-0.807,P < 0.05),which was the highest among all the five models.Conclusions: In p GGNs,a well-defined lesion border and a larger average CT value can be valuable discriminators of malignant lesions from benign lesions.In PSNs,larger size,well-defined border and spiculated margin have greater predictive value for malignancy.