ObjectiveTo investigate the CT features and clinicopathological features of thin-walled cystic lung cancer with the largest diameter less than or equal to 3 cm.MethodsThe CT features and clinicopathological data of 26 thin-walled cystic lung cancer patients diagnosed by chest CT and surgical or puncture pathology were retrospectively analyzed. There were 16 males and 10 females, with an average age of 62 years.ResultsThe lesions were distributed in different pulmonary lobes, all of which were peripheral. The maximum diameter of lesion was 21.4 mm on average, and the maximum diameter of cyst was 12.9 mm on average. Among them, there were 19 patients of lobulation sign, 18 patients of spicule sign, 16 patients of pleural indentation, 9 patients of vascular convergence sign, 7 patients of bronchus sign, 21 patients of irregular inner wall, 26 patients of uneven thickening of cystic wall, 18 patients of intra-cystic separation, and 10 patients of vessels through the cystic cavity. The pathological types were all adenocarcinoma and 24 patients were invasive adenocarcinoma.ConclusionAll patients were peripheral adenocarcinoma. CT not only shows the common typical signs of lung cancer, but also has the characteristic fertures of irregular inner wall, intra-cystic separation and vessels through the cystic cavity.
ObjectiveTo investigate the CT signs and clinicopathological features of peripheral cavitary lung adenocarcinoma with the largest diameter less than or equal to 3 cm.Methods From January 2015 to December 2017, the CT signs and clinicopathological fertures of 51 patients with ≤3 cm peripheral cavitary lung adenocarcinoma diagnosed by chest CT and surgical pathology were retrospectively analyzed. Furthermore, CT signs and clinicopathological features of thick-walled cavitary lung adenocarcinoma and thin-walled cavitary lung adenocarcinoma were compared. There were 29 males and 22 females at age of 62 (56, 67) years.ResultsThere were 27 thick-walled cavitary lung adenocarcinoma and 24 thin-walled cavitary lung adenocarcinoma. Thick-walled cavitary adenocarcinoma had greater SUVmax [6.5 (3.7, 9.7) vs. 2.2 (1.4, 3.8), P=0.019], larger cavity wall thickness (11.8±4.6 mm vs. 7.6±3.7 mm, P=0.001), larger tumor tissue size [2.1 (1.7, 2.8) cm vs. 1.6 (1.2, 2.0) cm, P=0.006], and more solid nodules (17 patients vs. 8 patients, P=0.035). Thin-walled cavitary adenocarcinoma had more smoking history (12 patients vs. 6 patients, P=0.038), larger cavity size [12.3 (9.2, 16.6) mm vs. 4.4 (2.8, 7.1) mm, P=0.000], and larger proportion of cavities [0.30 (0.19, 0.37) vs. 0.03 (0.01, 0.09), P=0.000]. On CT signs, there were more features of irregular inner wall (19 patients vs. 6 patients, P=0.000), intra-cystic separation (16 patients vs. 6 patients, P=0.001) and vessels through the cystic cavity (10 patients vs. 1 patient, P=0.001) in thin-walled caviraty lung adenocarcinoma.ConclusionPeripheral cavitary lung adenocarcinoma of ≤3 cm on chest CT has characteristic manifestations in clinical, imaging and pathology, and there is a statistical difference between thick-walled cavitary lung adenocarcinoma and thin-walled cavitary lung adenocarcinoma.
ObjectiveTo investigate the predictive value of preoperative radiological features on spread through air spaces (STAS) in stage cⅠA lung adenocarcinoma with predominant ground-glass opacity, and to provide a basis for the selection of surgical methods for these patients.MethodsThe clinical data of 768 patients with stage cⅠA lung adenocarcinoma undergoing operation in our hospital from 2017 to 2018 were reviewed, and 333 early stage lung adenocarcinoma patients with predominant ground-glass opacity were selected. There were 92 males and 241 females, with an average age of 57.0±10.0 years. Statistical analysis was performed using SPSS 22.0.ResultsSTAS-positive patients were mostly invasive adenocarcinoma (P=0.037), and had more micropapillary component (P<0.001) and more epidermal growth factor receptor (EGFR) gene mutations (P=0.020). There were no statistically significant differences between the STAS-positive and STAS-negative patients in other clinicopathological features. Univariate analysis showed that the maximum diameter of tumor in lung window (P=0.029), roundness (P=0.035), maximum diameter of solid tumor component in lung window (P<0.001), consolidation/tumor ratio (CTR, P<0.001), maximum area of the tumor in mediastinum window (P=0.001), tumor disappearance ratio (TDR, P<0.001), average CT value (P=0.001) and lobulation sign (P=0.038) were risk factors for STAS positive. Multivariate logistic regression analysis showed that the CTR was an independent predictor of STAS (OR=1.05, 95%CI 1.02 to 1.07, P<0.001), and the area under the receiver operating characteristic (ROC) curve was 0.71 (95%CI 0.58 to 0.85, P=0.002). When the cutoff value was 19%, the sensitivity of predicting STAS was 66.7%, and the specificity was 75.2%.ConclusionCTR is a good radiological feature to predict the occurrence of STAS in early lung adenocarcinoma with predominant ground-glass opacity. For the stagecⅠA lung adenocarcinoma with predominant ground-glass opacity and CTR ≥19%, the possibility of STAS positive is greater, and sublobar resection needs to be carefully considered.
ObjectiveTo compare the effectiveness and safety of preoperative lung localization by microcoil and anchor with scaled suture.MethodsA total of 286 patients underwent CT-guided puncture localization consecutively between October 2019 and December 2020 in our hospital. According to the different methods of localization, they were divided into a microcoil group (n=139, including 49 males and 90 females, aged 57.92±10.51 years) and an anchor group (n=147, including 53 males and 94 females, aged 56.68±11.31 years). The clinical data of the patients were compared.ResultsA total of 173 nodules were localized in the microcoil group, and 169 nodules in the anchor group. The localization success rate was similar in the two groups. However, the anchor group was significantly better than the microcoil group in the localization time (8.15±2.55 min vs. 9.53±3.08 min, P=0.001), the pathological receiving time (30.46±14.41 min vs. 34.96±19.75 min, P=0.029), and the hemoptysis rate (10.7% vs. 30.1%, P=0.001), but the pneumothorax rate was higher in the anchor group (21.3% vs. 11.0%, P=0.006).ConclusionPreoperative localization of small pulmonary nodules using anchor with suture is practical and safe. Due to its simplicity and convenience, it is worth of promotion in the clinic.
ObjectiveTo assess the accuracy of CT features of lung nodules (≤3 cm) in predicting the accuracy of the pathological subtype and degree of infiltration of adenocarcinoma. Methods We retrospectively analyzed the clinical data of 333 patients with non-cavitary pulmonary nodules diagnosed as adenocarcinoma by surgery and pathology in the China-Japan Friendship Hospital from 2011 to 2018, including 108 males and 225 females, aged 16-82 (59.57±10.16) years. The basic clinical data and CT characteristics of the patients were recorded. ResultsWhen the average CT value was ≥−507 Hu, the maximum diameter of the lung window was ≥14.5 mm, and the solid component ratio was ≥5.0%, it indicated more likely the invasive adenocarcinoma (IAC). The higher the average CT value of the nodule, the larger the maximum diameter of the lung window, and the more solid components, the higher the degree of infiltration. CT morphological features (including burrs, lobes, vascular signs, bronchial signs, pleural stretch or depression signs) were more common in IAC. Among them, burrs were more common in acinar adenocarcinoma and papillary adenocarcinoma. In invasive adenocarcinoma, the higher the risk of recurrence of the pathological subtype, the greater the average CT value. When the average CT value of IAC was >−106 Hu, and the proportion of solid components was ≥70.5%, the histological subtypes were more inclined to micropapillary/solid predominant adenocarcinoma. Conclusion The evaluation of CT features of lung nodules can improve the predictive value of histopathological types of lung adeno- carcinoma, thereby optimizing clinical treatment decisions and obtaining more ideal therapeutic effects.
Objective To identify risk factors that affect the verification of malignancy in patients with solitary pulmonary nodule (SPN) and verify different prediction models for malignant probability of SPN. Methods We retrospectively analyzed the clinical data of 117 SPN patients with definite postoperative pathological diagnosis who underwent surgical procedure in China-Japan Friendship Hospital from March to September 2017. There were 59 males and 58 females aged 59.10±11.31 years ranging from 24 to 83 years. Imaging features of the nodule including maximum diameter, location, spiculation, lobulation, calcification and serum level of CEA and Cyfra21-1 were assessed as potential risk factors. Univariate analysis was used to establish statistical correlation between risk factors and postoperative pathological diagnosis. Receiver operating characteristic (ROC) curve was drawn by different predictive models for the malignant probability of SPN to get areas under the curves (AUC), sensitivity, specificity, positive predictive values, negative predictive values for each model. The predictive effectiveness of each model was statistically assessed subsequently. Results Among 117 patients, 93 (79.5%) were malignant and 24 (20.5%) were benign. Statistical difference was found between the benign and malignant group in age, maximum diameter, serum level of CEA and Cyfra21-1, spiculation, lobulation and calcification of the nodules. The AUC value was 0.813±0.051 (Mayo model), 0.697±0.066 (VA model) and 0.854±0.045 (Peking University People's Hospital model), respectively. Conclusion Age, maximum diameter of the nodule, serum level of CEA and Cyfra21-1, spiculation, lobulation and calcification are potential independent risk factors associated with the malignant probability of SPN. Peking University People's Hospital model is of high accuracy and clinical value for patients with SPN. Adding serum index into the prediction model as a new risk factor and adjusting the weight of age in the model may improve the accuracy of prediction for SPN.