Objective To analyze the imaging features of solitary pulmonary nodules ( SPNs) , and compare the two types of lung cancer prediction models in distinguishing malignancy of SPNs.Methods A retrospective study was performed on the patients admitted to Ruijin Hospital between 2002 and 2009 with newly discovered SPNs. The patients all received pathological diagnosis. The clinical and imaging characteristics were analyzed. Then the diagnostic accuracy of two lung cancer prediction models for distinguishing malignancy of SPNs was evaluated and compared.Results A total of 90 patients were enrolled, of which 32 cases were with benign SPNs, 58 cases were with malignant SPNs. The SPNs could be identified between benign and maligant by the SPN edge features of lobulation ( P lt;0. 05) . The area under ROC curve of VA model was 0. 712 ( 95% CI 0. 606 to 0. 821) . The area under ROC curve of Mayo Clinic model was 0. 753 ( 95% CI 0. 652 to 0. 843) , which was superior to VA model. Conclusions It is meaningful for the identification of benign and maligant SPNs by the obulation sign in CT scan. We can integrate the clinical features and the lung cancer predicting models to guide clinical work.
Objective To evaluate the complication rate of CT-guided percutaneous lung biopsy and determine the risk factors. Methods A retrospective investigation of patients with CT-guided percutaneous lung biopsy in Ruijin Hospital, Shanghai Jiao Tong University School of Medicine between2002 and 2009 was performed. The risk factors for complications were determined by multivariate analysis of variables related to patients’demographics, lung lesions, biopsy procedures, and individual radiological features. Results 281 biopsy procedures were enrolled. The total complication rate was 55. 9% with pneumothorax 32. 4% ( 91/281) , hemoptysis 34. 5% ( 97 /281) , and cutaneous emphysema2. 1% ( 6 /281) , and with no mortality.The pneumothorax rate was correlated with lesion location, lesion depth, and number of pleural passes. The bleeding risk was correlated with lesion size, lesion depth, and age. Prediction models for pneumothorax and bleeding were deduced by logistic regression. The pneumothorax model had a sensitivity of 80. 0% and a specificity of 62. 4% . And the bleeding model had a sensitivity of 67. 4% and a specificity of 88. 8% .Conclusions Lesion location, lesion depth, and number of pleural passes were independent risk factors for pneumothorax. Lesion size, lesion depth, and age were independent risk factors for bleeding. The prediction models for pneumothorax and bleeding will helpfully reduce the complication of CT-guided lung biopsy.
【Abstract】Objective To explore the differential diagnostic value of major fibrinolytic parameters in pleural fluid. Methods Tissue-type plasminogen activator( t-PA) and plasminogen activator inhibitor-1( PAI-1) in pleural fluid at the first thoracentesis were measured with ELISA and D-dimer was measured with immunoturbidimetry. Results Eighty-four patients with pleural effusion were enrolled, among which 40 with malignant effusion, 33 with infectious effusion and 11 with transudative effusion. t-PA level was higher in malignant and transudative pleural fluid than that in infectious pleural fluid[ ( 52. 49 ±31. 46) ng /mL and ( 58. 12 ±23. 14) ng /mL vs ( 37. 39 ±22. 44) ng /mL, P lt; 0. 05] , but was not statistically different between malignant pleural fluid and transudative ( P gt; 0. 05) . PAI-1 level was higher in malignant and infectious pleural fluid than that in transudative [ ( 164. 86 ±150. 22) ng/mL and ( 232. 42 ±175. 77) ng/mL vs ( 46. 38 ±16. 13) ng/mL, P lt; 0. 01] , but was not statistically different between malignant and infectious pleural fluid( P gt;0. 05) . D-dimer levels in the three types of pleural fluid were significantly different, which was ( 23. 66 ±25. 18) mg/L, ( 6. 36 ±10. 87) mg/L and ( 66. 90 ±42. 17) mg/L in malignant, transudative and infectious pleural fluid, respectively. As single-item detection for malignant pleural fluid, the cutoff of t-PA was gt; 38. 7 ng/mL( area under ROC curve was 64. 0 ) , with sensitivity of 60. 0% , specificity of 63. 6%, positive predictive value of 66. 7%, negative predictive value of 56. 8% and accuracy of 61. 6% .The cutoff of D-dimer was lt; 27. 0 mg/L( area under ROC curve was 85. 5) , with sensitivity of 84. 8% ,specificity of 72. 5% , positive predictive value of 85. 3% , negative predictive value of 71. 8% and accuracy of78.1%. The sensitivity, specificity, positive predictive value, negative predictive value and accuracy of combined examination( t-PA + D-dimer) were 92. 5% , 60. 6% , 74. 0% , 87. 0% , 78. 1% , respectively.Conclusions The t-PA, PAI-1 and D-dimer levels are significantly different in the three types of pleural fluid. The detection of fibrinolytic parameters in pleural fluid, especially the value of D-dimer,may be helpful in the differential diagnosis of pleural effusion.
Objective Chronic obstructive pulmonary disease( COPD) is highly heterogeneous. In theory, the patients with same clinical manifestations, treatment response and prognosis can be classified into one phenotype, which may have same biological or physiological mechanisms. In this study the profiles of patients with COPD including body mass index( BMI) , Goddard score, fractional exhaled nitric oxide( FeNO) were analyzed in order to find some special phenotypes.Methods Patients with COPD at stable stage in Ruijin Hospital from May 2011 to February 2012 were evaluated with COPD assessment test ( CAT) in Chinese version, St. George’s Respiratory Questionnaire( SGRQ) , hospital anxiety and depression( HAD) rating scale, pulmonary function test, and 6-minute walking test ( 6MWT) . Baseline data was collected including height, weight, drug use, times of exacerbation, etc. Results A total of 126 patients were recruited. The patients with low BMI had poorer quality of life, lower FEV1 , poorer diffusion function, and higher Goddard score, and was easier to develop anxiety and depression. The patients with high BMI had lower oxygen saturation at rest. We failed to define a certain kind of phenotype according to FeNO. The patients of emphysema phenotype( assessed by Goddard score) had lower BMI, decreased lung diffusion capacity, and poorer quality of life. Conclusion The study can define COPD patients into some special phenotypes( low BMI and emphysema phenotype) , but failed to define a certain kind of phenotype according to FeNO.