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Objective: To observe the value of rapid on-site evaluation (ROSE) in CT-guided percutaneous lung biopsy of peripheral pulmonary nodules (≤2 cm). Methods: A total of 108 patients with pulmonary nodules who underwent CT-guided percutaneous lung biopsy were retrospectively analyzed. According to the presence or absence of ROSE, they were divided into ROSE group (n=58) and conventional group (n=50). The adequacy of sampling, diagnostic accuracy, complications, secondary biopsy rate and statistical consistency were compared between ROSE and histopathology. Results: The adequacy and diagnostic accuracy in ROSE group were higher than those in conventional group (93.10% [54/58] vs 78.00% [39/50], 89.66% [52/58] vs 74.00% [37/50], both P0.05). The consistency of ROSE and histopathology for benign and malignant lesions was 91.30% (21/23) and 93.33% (28/30), respectively. Conclusion: ROSE can guide puncture sampling without prolonging operation time and increasing complications, so as to ensure the adequacy of sampling, improve diagnostic accuracy and reduce the rate of secondary puncture during biopsy of pulmonary nodules, which has good consistency with histopathology and can make immediate diagnosis.
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Objective: To compare the qualitative diagnostic value of different Methods: based on PET/CT for solitary pulmonary nodules (SPN). Methods: Data of 161 SPN patients who underwent PET/CT were collected. Clinical information, high resolution CT (HRCT) signs and maximum standard uptake value (SUVmax) were compared between benign and malignant SPN patients. The mathematical diagnostic model of SPN was constructed by using binary Logistic regression, and the diagnostic efficiencies were compared among diagnostic model, PET/CT and HRCT. Results: Among 161 patients, malignant SPN were pathologically diagnosed in 131 cases and benign in 30 cases. The sensitivity, specificity and accuracy of PET/CT in diagnosing malignant SPN was 98.47% (129/131), 76.67% (23/30) and 94.41% (152/161), of HRCT was 59.54% (78/131), 83.33% (25/30) and 63.98%(103/161), respectively. After univariate and multivariate analysis, SUVmax, patient's age, calcification and tracheal vascular bundles were incorporated into the regression equation, and a model was then established. The sensitivity, specificity and accuracy of the model for diagnosing malignant SPN was 82.44% (108/131), 86.67% (26/30) and 83.23% (134/161), respectively. The AUC of the model, PET/CT and HRCT for diagnosis of malignant SPN was 0.909, 0.876 and 0.714, respectively. The AUC of the model and PET/CT were both higher than HRCT (all P<0.001). There was no significant difference between the model and PET/CT (P=0.468). Conclusion: PET/CT-based Logistic regression model and PET/CT are better than HRCT in qualitative diagnosis of SPN, and the specificity of the model is higher than that of PET/CT.
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Objective: To explore the value of 18F-FDG PET/CT combined with three-dimensional reconstruction of thin-slice spiral CT in diagnosis of solitary pulmonary nodules (SPN). Methods: A total of 139 patients with SPN were selected. After routine 18F-FDG PET/CT scanning, thin-slice spiral CT scanning and three-dimensional reconstruction were performed. The accuracy of single 18F-FDG PET/CT and 18F-FDG PET/CT combined with three-dimensional reconstruction of thin-slice spiral CT in diagnosis of SPN were recorded and compared. Results: Totally 139 SPN were pathologically confirmed after operation or puncture, including 83 malignant and 48 benign ones. SPN in 8 patients became small or disappeared after clinical anti-inflammatory treatment, and thus were diagnosed as benign ones. The sensitivity, specificity and coincidence rate of combined diagnosis of SPN nodules was 85.71% (72/84), 78.18% (43/55) and 82.73% (115/139), respectively, all higher than of single 18F-FDG PET/CT (64.29% [54/84], 54.55% [ 30/55] and 60.43% [84/139], respectively). Conclusion: 18F-FDG PET/CT combined with three-dimensional reconstruction of thin-slice spiral CT can significantly improve the accuracy for diagnosing SPN. [Keywords] solitary pulmonary nodules; positron-emission tomography; thin-slice scanning; three-dimensional reconstruction
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Objective To analyze the CT features of solitary pulmonary nodules(SPN) in patients with malignant tumor with the aim of improving its diagnosis and differential diagnosis in this special background .Methods From May 2014 to De-cember 2018, the CT data of 76 pathologically confirmed SPNs in patients with malignant tumor were retrospectively analyzed . The CT features of SPNs, including density, morphology and change of peripheral lung field and adjacent structures, were mainly analyzed.The characteristics of different types of nodules and their differences were summarized .Results Among the 76 SPNs, there were 41(53.9％) primary lung cancers, 14(18.5％) metastatic tumors, and 21(27.6％) benign lesions(in-cluding 12 inflammatory nodules, 7 tuberculous nodules and 2 benign tumors).Of all nodules, there were 57(75％) solid nodules, including 23(40.4％) primary lung cancers which mainly manifested as nodules with rough margin , close to adjacent vessel and bronchus and usually had internal or edge features(19, 82.6％), 14(24.6％) metastatic tumors which mainly showed as round or oval, homogeneous density, smooth margin nodules(12, 85.7％), and 18(31.6％) inflammatory nodules which mainly showed as lesions with rough and blurred margin accompanied by peripheral patch or fibrosis (14, 77.8％). There were 19(25％) sub-solid nodules, including 18(94.7％) primary lung cancers, which mainly manifested as nodules with heterogeneous density and clear border(14, 77.8％).There was only 1(5.3％) sub-solid inflammatory nodule.Conclu-sion The pathological nature of SPNs in patients with malignant tumors is various .Understanding their CT characteristics is helpful for diagnosing and differentiating and providing useful information for further treatment .
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Objective:To evaluate the clinical factors affecting the probability of malignant micro-sized (≤10 mm) solitary pulmonary nodules (≤10 mm, micro-sized SPN), and established a clinical prediction model. Methods:Medical records from 102 patients with a pathological diagnosis of micro-sized SPN (Group A), established between June 2012 and March 2014, were reviewed. Clinical data were collected to evaluate the independent predictors of malignant micro-sized SPN using single factor analysis and Logistic regression analysis. A clinical prediction model was subsequently created. Receiver-operating characteristic (ROC) curves were constructed using the prediction model. Between January 2015 and August 2017, data from an additional 10 patients enrolled from January 2015 to August 2017 from Jinhua Guangfu Hospital (Group B) with a pathological y diagnosed micro-sized SPN were used to validate this clinical prediction model. The model was also compared with the Mayo Clinic Model. Results:Median age of 102 patients (Group A) was 55.31±10.77 years old. There were 75.5％malignant nodules and 24.5％benign ones. Logistic regression analysis identified six clinical characteristics (no symptoms, upper lobe, diameter>5 mm, no clear border, not irregular round, no calcification) as independent predictors of malignancy in patients with micro-sized SPN. The area under the ROC curve for our model was 0.922 (95％CI:0.857-0.986). In our model, the diagnosis sensitivity and specificity were 88.3％and 84.0％, respectively. The test power of the model was better compared with the Mayo Clinic Model. Conclusions:In this study, we had found the independent predictors of malignant micro-sized SPN, and developed a prediction model that could accurately identify malignant micro-sized SPN in patients.
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Objective To analyze the imaging features of solitary pulmonary nodules (SPN).Methods The clinical data and chest imaging features of 55 cases with SPN confirmed by pathology were retrospectively analyzed . Results Of the 55 patients,40 cases (80.00％) were lung cancer and 15 cases (20.00％) were benign lesions . The univariate analysis showed that the age of patients (t=2.972,P=0.004),lobulation sign (χ2 =7.018,P=0.008) and pleural indentation sign (χ2 =4.727,P=0.030) had statistically significant differences in distinguish of the benign and malignant nodules ,but the sex (χ2 =1.760,P=0.185),nodule site (χ2 =0.145,P=0.703),burrs (χ2 =0.555,P=0.456),cavity (χ2 =0.000,P=1.000),nodule size (t=0.608,P=0.546) and other factors had no significant difference.Multivariate Logistic regression analysis showed that age (OR=1.101,P=0.022) and lobulation sign (OR=6.187,P=0.026) were independent influencing factors for judgement of the benign and malig -nant SPN.Conclusion The age of patients,lobulation sign and the pleural indentation sign are related to the benign and malignant SPN .Age and lobulation sign are the independent influencing factors for judgement of the benign and malignant SPN .
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Objective To investigate the diagnostic value of transbronchial lung biopsy (TBLB) under virtual bronchoscopic navigation (direct path), endobronchial ultrasonography with a guide sheath (GS) and rapid on-site evaluation (ROSE) for solitary pulmonary nodules (SPNs). Methods One hundred and seventy-eight patients who were underwent transbronchial lung biopsy in the Tianjin Medical University General Hospital between January 2015 to December 2016 were retrospectively evaluated. CT images of all patients showed solitary pulmonary nodules surrounded by lung tissue, and ROSE was undergone during the procedure. The patients were divided into conventional (C-TBLB) group, virtual bronchoscopic navigation (VBN) group, endobronchial ultrasonography with a guide sheath (GS) group, and virtual bronchoscopic navigation combined with endobronchial ultrasonography with a guide sheath group (combination) depending on the different devices. The diagnostic yield and the location or the effect of lesion on the diagnostic rate were compared between four groups. The coincidence rate of ROSE and the histopathological findings of TBLB were compared. The value of ROSE for the early diagnosis of disease was further evaluated. Results The diagnostic rates were 32.5％(13/40), 66.7％(24/36), 68.2％(30/44) and 75.8％(44/58) for C-TBLB group, VBN group, GS group and combination group, respectively. There were significant differences in diagnostic rates between C-TBLB group and other tree groups (χ2=8.853, 10.677 and 18.293, P0.008). The diagnostic rates for peripheral pulmonary nodules were 12.5％ (2/16), 42.9％ (6/14), 40.0％ (4/10) and 75.9％(22/29) in C-TBLB group, VBN group, GS group and combination group. The diagnostic rate was significantly higher in combination group than that of other three groups (χ2=17.434, P<0.05). The result of ROSE was consistent with result of histopathology (Kappa = 0.775, P<0.001). The sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy of ROSE during transbronchial biopsy for solitary pulmonary nodules were 90.7％, 87.0％, 86.7％, 90.9％ and 88.8％, respectively. No pneumothorax, hemoptysis or other serious complications were found in patients. Conclusion Virtual bronchoscopic navigation, endobronchial ultrasonography with a guide sheath for solitary pulmonary nodules by transbronchial lung biopsy can improve the diagnostic rate of solitary pulmonary nodules.
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Objective To study the relativity between imageology and pathology during lung cancer,and estimate whether the lung cancer is preinvasive lesions,which can support evidences for the operation methods.Methods Clinical data of 624 patients who were diagnosed as lung adenocarcinoma and had solitary pulmonary nodule(diameter≤3 cm) were collected,all of them were scanned by thin layer CT scan(1 mm).The correlation between imageology and pathology data were analyzed.Results In 125 cases of GGO,the ratio of invasive lesions were 0 (0/72),6.1％ (3/49) and 100％ (4/4) in stage T1a,T1b and T1c respectively.In 285 cases of mGGO,if solid component was less than 0.5 cm,the ratio of invasive lesions were 1.7％ (1/58),6.9％ (2/29) and 50.0％ (2/4) in stage T~,T1b and Tic;but the ratio of invasive lesions were 81.3％ (13/16),94.1％ (96/102) and 97.4％ (74/76) respectively when the solid component was more than 0.5 cm.In 214 cases with solid nodules,the ratio of invasive lesions were 87.1％ (27/31),98.8％ (84/85) and 99.0％ (97/98) in stage T1 a,T1b and T1c.Conclusion The ratio of invasive lesions and solid component increased gradually along with the growing of tumor diameter in stage T1 lung cancer.CT imaging was highly correlated with the pathology diagnosis of preinvasive lesions and invasive lesions,which can be used as the guidance for operation methods.
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Objective To study the relativity between imageology and pathology during lung cancer,and estimate whether the lung cancer is preinvasive lesions,which can support evidences for the operation methods.Methods Clinical data of 624 patients who were diagnosed as lung adenocarcinoma and had solitary pulmonary nodule(diameter≤3 cm) were collected,all of them were scanned by thin layer CT scan(1 mm).The correlation between imageology and pathology data were analyzed.Results In 125 cases of GGO,the ratio of invasive lesions were 0 (0/72),6.1％ (3/49) and 100％ (4/4) in stage T1a,T1b and T1c respectively.In 285 cases of mGGO,if solid component was less than 0.5 cm,the ratio of invasive lesions were 1.7％ (1/58),6.9％ (2/29) and 50.0％ (2/4) in stage T~,T1b and Tic;but the ratio of invasive lesions were 81.3％ (13/16),94.1％ (96/102) and 97.4％ (74/76) respectively when the solid component was more than 0.5 cm.In 214 cases with solid nodules,the ratio of invasive lesions were 87.1％ (27/31),98.8％ (84/85) and 99.0％ (97/98) in stage T1 a,T1b and T1c.Conclusion The ratio of invasive lesions and solid component increased gradually along with the growing of tumor diameter in stage T1 lung cancer.CT imaging was highly correlated with the pathology diagnosis of preinvasive lesions and invasive lesions,which can be used as the guidance for operation methods.
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En los últimos años la comunidad científica internacional ha dedicado considerables recursos a la investigación y desarrollo de sistemas de diagnóstico asistidos por ordenador, utilizados por los médicos en el proceso de diagnóstico. Se ha prestado especial atención en algunas áreas médicas, como las especialidades oncológicas, por los altos índices de mortalidad provocados por algunas enfermedades como el cáncer de pulmón. El diagnóstico temprano de este padecimiento puede reducir en gran medida estos indicadores y mejorar la calidad de vida de los pacientes. El objetivo que se pretende con el desarrollo de esta investigación, es la selección adecuada de un algoritmo de clasificación, para ser utilizado en la fase que lleva el mismo nombre como parte de un sistema de diagnóstico asistido por ordenador para la clasificación de nódulos pulmonares solitarios. Para la selección adecuada del algoritmo de clasificación, se realiza un experimento utilizando las herramientas Weka v3.7.10 y Matlab 2013. Para determinar cuál de las técnicas estudiadas arroja mejores resultados de rendimiento, se utilizó el mismo conjunto de datos para las fases de entrenamiento, prueba y validación del clasificador, disponible en la base de datos internacional The Lung Image Database Consortium Image Collection(AU)
In recent years the international scientific community has devoted considerable resources to research and development of systems for computer-aided diagnosis used by physicians in the diagnostic process. Special attention has been provided in some medical areas, such as oncology specialties, by high mortality rates caused by some diseases like lung cancer. Early diagnosis of this condition can greatly reduce these indicators and improve quality of life of patients.The objective pursued with the development of this research is the proper selection of a classification algorithm, to be used in the phase that has the same name, as part of a system of computer-aided diagnosis for classification of solitary pulmonary nodules. For the selection of the appropriate classification algorithm, an experiment was performed using the tools Weka v3.7.10 and Matlab 2013. To determine which of the techniques studied produces better performance results, the same data set was used for the phases of training, testing and validation of the classifier, available in the international database The Lung Image Database Consortium Image Collection(AU)
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Humans , Male , Female , Algorithms , Medical Informatics Applications , Software/standards , Lung Neoplasms/diagnostic imaging , Solitary Fibrous Tumors/diagnostic imagingABSTRACT
La identificación del cáncer de pulmón en fases iniciales ha sido en los últimos años una tarea priorizada de la comunidad científica. Esta enfermedad representa la primera causa de muerte en el varón y la tercera después del cáncer de colon y mama en la mujer. La realización de estudios imagenológicos contribuye a la detección temprana de esta enfermedad. El elevado volumen de imágenes generado por los equipos médicos provoca la revisión de mucha información para emitir un diagnóstico médico. Con frecuencia se requiere la valoración de varios especialistas para llegar a un diagnóstico acertado, retardando el proceso de atención al paciente. En la presente investigación se exponen los resultados obtenidos al desarrollar un algoritmo utilizando métodos de procesamiento de imágenes, para la identificación de nódulos pulmonares solitarios. La utilización de sistemas que dirigen la atención de los especialistas a regiones candidatas en la imagen, proporcionando una segunda opinión en la interpretación de los resultados, pudiera mejorar la consistencia y agilizar el proceso de diagnóstico. Los resultados arrojados por el algoritmo desarrollado fueron contrastados con las anotaciones realizadas en imágenes publicadas en The Lung Image Database Consortium Image Collection (LIDC-IDRI) y se obtuvo un 77.78 por ciento de acierto en la detección de nódulos pulmonares solitarios(AU)
The identification of lung cancer at early stages has been in recent years a prioritized task for the scientific community. This disease is the leading cause of death in men and the third after the colon and breast cancer in women. Performing imaging studies contributes to the early detection of this disease. The high volume of images generated by medical equipment leads to reviewing much information to issue a medical diagnosis. Often are required the assessment of several specialists to reach an accurate diagnosis, slowing the process of patient care. In the present investigation are exposed the results obtained to develop an algorithm using image processing methods for the identification of solitary pulmonary nodules. The use of systems that direct the attention of specialists to candidate regions in the image, providing a second opinion in the interpretation of results could improve consistency and agility in the diagnostic process. The results obtained by the developed algorithm were compared with annotations in images published in The Lung Image Database Consortium Image Collection (LIDC-IDRI) and was obtained 77.78 percent accuracy in the detection of solitary pulmonary nodules(AU)
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Humans , Male , Female , Diagnostic Imaging/methods , Multiple Pulmonary Nodules/diagnosisABSTRACT
Objective To assess the dignosis value of CT three-dimensional reconstruction with Fisher discriminant model in small solitary pulmonary nodules before operation.Methods CT data of 40 cases with SPN were retrospectively analyzed and divided into into malignant pulmonary nodules (25 cases),squamous cell carcinoma (4 cases),adenocarcinoma (13 cases),lung cancer (4 ca-ses),small cell lung cancer (2 cases),large cell carcinoma (1 case),metastases tumor (1 case),benign nodules (1 5 cases,6 cases of tuberculosis,2 cases of hamartoma,and 7 cases of non-specific inflammatory nodules)by pathology and follow-up results.The CT features of pulmonary nodules were evaluated through multi-planar reformation (MPR),curved-planar reformation (CPR),volume rendering (VR),maximum intensity proj ection (MIP)and other three-dimensional reconstruction.The three-dimensional data were divided into benign and malignant groups.In each of the two groups,the significant signs of morphological signs of discrimination indicators were adminstrated Fisher discriminant,and the probalitiy of false positives were estimated using cross-validation method. Results The positive features of pulmonary nodules in there-dismensional images were much more than in two-dimensional images. Fisher discriminant formula of solitary pulmonary nodules in three-dimensional images was Z=1.143X1 + 0.454X2+1.606X3-0.262X4+0.04X5+0.483X6+1.611X7-2.164.Discriminant boundary value Zc was-0.516.When Zcgreater than -0.516,nodules were proneed to considere as malignant nodules.In 25 cases of malignant nodules,4 cases mistook for benign.When Zc less than -0.516,nodules were proneed to considere as benign nod-ules.In 1 5 benign nodules,2 cases mistook for malignant.The total misdiagnosis and accuracy rate were 15 % and 85% respec-tively.Conclusion CT three-dimensional reconstruction combined with Fisher discriminant model have a high clinical value in dif-fereiating diagonsis of pulmonary nodules were proneed to considere as malignant nodules.In 25 cases of malignant nodules,4 cases mistook for benign.When Zc less than -0.516,nodules were proneed to considere as benign nodules. In 15 benign nodules,2 cases mistook for malignant.The total misdiagnosis and accuracy rate were 15 % and 85% respec-tively.Conclusion CT three-dimensional reconstruction combined with Fisher discriminant model have a high clinical value in differeiating diagonsis of pulmonary nodules.
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Objective To explore the value of gemstone spectral imaging (GSI) with single source dual-energy CT in characterizing the benign and malignant solitary pulmonary nodules (SPN).Methods Totally 32 patients with SPN underwent phaseⅢ enhanced CT scan using single source dual-energy CT by GSI mode.Three types of images were reconstructed for analysis:the water concentration (WC),iodine concentration (IC) and normalized iodine concentration (NIC).Results The IC of lung squamous cell carcinoma lung adenocarcinoma,hamartoma,sclerosing hemangioma,inflammatory pseudotumor were (11.66± 2.72) μg/ml,(12.36±2.97) μg/ml,(10.20±3.11) μg/ml,(16.58±3.58) μg/ml,(21.67±3.76) μg/ml,the IC of lung adenocarcinoma and lung squamous cell carcinoma had no difference (P ＞ 0.05),there were significant differences in the value of iodine material between other nodules (all P ＜ 0.05).The WC of lung adenocarcinoma,lung squamous cell carcinoma,hamartoma,sclerosing hemangioma,inflammatory pseudotumor were (1 021.31±13.83) μg/ml,(1 027.98±12.53) μg/ml,(1 003.42±13.67) μg/ml,(1 029.61±12.06) μg/ml,(1 051.61±13.81) μg/ml,there was no significant difference in the value of water material between nodules (all P ＞ 0.05).Conclusion The spectral CT imaging may be helpful for characterizing the pathological type of SPN.
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Objective Based on the mathematical models established in Department of Thoracic Surgery of Peking University People's Hospital for predicting malignant probability for solitary pulmonary nodules ( SPN),another continuous 145 patients with SPN were assessed to verify the accuracy of the model comparing with foreign models (Mayo model and VA model).Methods A retrospective cohort study in our institution included 145 patients with definite pathological diagnosis of SPN from Oct 2009 to Aug 2011,72 males and 73 females,average age (59.4 ± 12.2 ) years old.Clinical data included age,gender,course of disease,symptoms,history and quantity of smoking,time of smoking cessation,history of tumor,family history of tumor,tumor site,diameter,calcification,speculation,border,lobulation,traction of pleural,vascular convergence sign,and cavity.These raw data were incorporated into our model,Mayo model and VA model,the probability of malignant in every patient was calculated separately according to methods described before.The sensitivity and specificity of these 3 models were evaluated then.Afterwards,calibration of the 3 models was assessed by the Hosmer-Lemeshow (H-L) test.Discrimination was tested by calculating the area under curve ( AUC ) after the receiver operating characteristic (ROC) curve was drawn.Results 32.4％ (47 in 145 patients) of the nodules were malignant,and 67.6％ (98 in 145 patients) were benign in this group.Verified the accuracy of our model with sensitivity of 94.9％,specificity of 66.0％,positive predictive value of 85.3％ and negative predictive value of 86.1％.The H-L test showed good fitting in all models ( P ＞0.05 ).The AUC for our model was 0.874 ±0.035,and 0.784 ± 0.041 in Mayo model (P =0.004 compared to our model),0.754 ± 0.041 in VA model (P =0.002 compare to our model).And,there was not significant statistical difference between Mayo model and VA model (P ＞0.05 ).Our model has the best precision indexed by AUC,which were statistically significant differential compared with Mayo model and VA model.Conclusion The model established by our center has superior value than foreign counterparts in predicting the probability of malignant or benign in patients with SPN.
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Objective To explore clinical value of tumor specific growth factors (TSGF) in serum and bronchoalveolar lavage fluid (BALF) on differential diagnosis of benign and malignant periphery solitary pulmonary nodules (PSPN). Methods Serum and BALF from both normal and afflicted side were collected from 211 patients with PSPN(case group) and from 196 patients without any type of tumor (control group). TSGF and carcinoembry-onic antigen (CEA) in serum and BALF were measured in both groups. Results In the malignant PSPN patients, CEA in serum, normal and afflicted side were 28.73 (SD: 15.61) μg/L,63.31 (SD:21.28) μg/L and 85.54(SD: 26.19)μg/L,respectively, which was significantly higher than that of the benign PSPN patients (7.21(SD:2.43) μg/L, 12.36(SD:6.93)μg/L and 14.65 (SD:8.07)μg/L,respectively), as well as that of the control group (4.68 (SD: 1.25) μ/L and 11.06(SD:8.03) μg/L in serum and BALF, respectively (P < 0.05). TSGF in the serum and BALF from the normal and afflicted side of malignant PSPN patients was 88.73 (SD:13.51)μg/L, 110.73 (SD: 18.64) μg/L and 162.80(SD:58.89) μg/L, respectively, which were significantly higher than that of the benign PSPN patients (56.31(SD: 2.43) μg/L, 79.25 [SD: 36.86] and 86.29 (SD: 37.07) μg/L, respectively) (P <0.05). Furthermore, in the malignant PSPN patients, TSGF and CEA in the afflicted side were significantly higher than that of the normal side. Sensitivity, specificity and accuracy of TSGF in BALF from the afflicted side for malig-nant diagnosis were 86.6%,100.0% and 98.6%,respectively,which was higher than that of CEA (70.2% ,78. 9% and 76.5% respectively) and that of serum TSGF (73.1% ,88.9% and 85.7% respectively). Conclusions TSGF in bronchoalveolar lavage fluid and serum has a significant role in differential diagnosis of benign and malig-nant periphery solitary pulmonary nodules. Furthermore, measurement of TSGF in bilateral BALF is helpful in diag-nosis of tumor location.
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Objective To assess the value of contrast-enhanced computed tomography (CT) in the differentiation of benign solitary pulmonary nodules(SPN) from malignant ones.Methods Thirty-seven patients with solitary pulmonary nodules(≤3 cm phi)were examined by contrast-enhanced CT.Qualitative and quantitative characters of benign and malignant lesions were analysed after administration of Ultravist in order to evaluate the attenuation value of contrast-enhanced CT in the differentiation of benign SPN from malignant ones .Results A threshold value of 30 HU was selected on enhanced CT images to distinguish malignant( CT value≥30 HU)from benign( CT value