ObjectiveTo explore the clinical application of the comprehensive guidance technologies, such as cone beam computed tomography (CBCT), virtual bronchoscopic navigation (VBN), and superimposed high-frequency jet ventilator for respiratory control in the biopsy of peripheral pulmonary nodules (PPNs). MethodsThe clinical information of 3 patients with PPNs diagnosed by CBCT combined with VBN and superimposed high frequency superposition jet ventilator in Shanghai Changhai Hospital were retrospectively analyzed. Results Clinical data of 3 patients were collected. The average diameter of PPNs was (25.3±0.3) mm with various locations in left and right lung. The first nodule was located in the apex of the left upper lung, and the biopsy was benign without malignant cells. The lesion was not enlarged during the 5-year follow-up. The second one was located in the left lingual lung, and the postoperative pathology was confirmed as mucosa-associated lymphoma. The third one was located in the anterior segment of the right upper lung. After the failure of endobronchial procedure, percutaneous PPNs biopsy under CBCT combined with VBN was performed, and the pathological diagnosis was confirmed as primary lung adenocarcinoma. Postoperative pneumothorax complication occurred in the third patient with right lung compression rate approximately 20%. ConclusionsThe application of CBCT, combined with VBN and the superimposed high frequency jet ventilator for respiratory control can potentially improve the accuracy and safety in the diagnosis of PPNs. Multi-center clinical trials are needed to verify its further clinical application.
ObjectiveTo establish and internally validate a predictive model for poorly differentiated adenocarcinoma based on CT imaging and tumor marker results. MethodsPatients with solid and partially solid lung nodules who underwent lung nodule surgery at the Department of Thoracic Surgery, the Affiliated Brain Hospital of Nanjing Medical University in 2023 were selected and randomly divided into a training set and a validation set at a ratio of 7:3. Patients' CT features, including average density value, maximum diameter, pleural indentation sign, and bronchial inflation sign, as well as patient tumor marker results, were collected. Based on postoperative pathological results, patients were divided into a poorly differentiated adenocarcinoma group and a non-poorly differentiated adenocarcinoma group. Univariate analysis and logistic regression analysis were performed on the training set to establish the predictive model. The receiver operating characteristic (ROC) curve was used to evaluate the model's discriminability, the calibration curve to assess the model's consistency, and the decision curve to evaluate the clinical value of the model, which was then validated in the validation set. ResultsA total of 299 patients were included, with 103 males and 196 females, with a median age of 57.00 (51.00, 67.25) years. There were 211 patients in the training set and 88 patients in the validation set. Multivariate analysis showed that carcinoembryonic antigen (CEA) value [OR=1.476, 95%CI (1.184, 1.983), P=0.002], cytokeratin 19 fragment antigen (CYFRA21-1) value [OR=1.388, 95%CI (1.084, 1.993), P=0.035], maximum tumor diameter [OR=6.233, 95%CI (1.069, 15.415), P=0.017], and average density [OR=1.083, 95%CI (1.020, 1.194), P=0.040] were independent risk factors for solid and partially solid lung nodules as poorly differentiated adenocarcinoma. Based on this, a predictive model was constructed with an area under the ROC curve of 0.896 [95%CI (0.810, 0.982)], a maximum Youden index corresponding cut-off value of 0.103, sensitivity of 0.750, and specificity of 0.936. Using the Bootstrap method for 1000 samplings, the calibration curve predicted probability was consistent with actual risk. Decision curve analysis indicated positive benefits across all prediction probabilities, demonstrating good clinical value. ConclusionFor patients with solid and partially solid lung nodules, preoperative use of CT to measure tumor average density value and maximum diameter, combined with tumor markers CEA and CYFRA21-1 values, can effectively predict whether it is poorly differentiated adenocarcinoma, allowing for early intervention.
The robotic bronchoscopy system is a new technology for lung lesion location, biopsy and interventional therapy. Its safety and effectiveness have been clinically proven. Based on many advanced technologies carried by the robotic bronchoscopy system, it is more intelligent, convenient and stable when clinicians perform bronchoscopy operations. It has higher accuracy and diagnostic rates, and less complications than bronchoscopy with the assistance of magnetic navigation and ordinary bronchoscopy. This article gave a review of the progress of robotic bronchoscopy systems, and a prospect of the combination with artificial intelligence.
Objective To compare the safety and efficacy of thulium laser wedge resection of the lung under uniportal thoracoscopy with the other two traditional surgical methods (mechanical cutting stapler wedge resection and segmentectomy) in the treatment of small pulmonary nodules.MethodsClinical data of 125 patients with small pulmonary nodules receiving uniportal video-assisted thoracoscopic surgery from December 2017 to December 2018 in our hospital were retrospectively analyzed. Among them, 33 patients had thulium laser wedge resection (a thulium laser group), including 10 males and 23 females, with an average age of 59.21±11.31 years; 48 patients had mechanical stapling pulmonary wedge resection (a mechanical stapling pulmonary wedge resection group), including 17 males and 31 females, with an average age of 57.27±11.30 years; and 44 patients had pulmonary segmentectomy (a pulmonary segmentectomy group), including 21 males and 23 females, with an average age of 63.00±9.68 years. The surgical margin air leakage, operation time, intraoperative blood loss, postoperative hospital stay, drainage days, average daily drainage volume, fever, pain and hospitalization expenses were compared among the three groups. ResultsThe body mass index, gender, smoking history, benign and malignant pathological results, average maximum diameter of lesions and lesion location distribution were not statistically different among the three groups (P>0.05). The average age and the proportion of pleural adhesions in the thulium laser group were not statistically different from those of the other two groups (P>0.05). In the distribution of the number of lesions, the proportion of multiple lesions in the mechanical stapling pulmonary wedge resection group was higher than that of the other two groups, and there was no statistical difference between the other two groups. The intraoperative blood loss in the thulium laser group was less than that of the other two groups (P≤0.05). There was no statistical difference in the classification of surgical margin air leakage or the operation time among the three groups (P>0.05). The proportion of postoperative fever and hospitalization expenses in the thulium laser group were lower or less than those of the other two groups (P<0.05). The length of hospitalization stay and postoperative chest tube placement in the thulium laser group was significantly shorter than that of the pulmonary segmentectomy group (P<0.05), which was not statistically different from the mechanical stapling pulmonary wedge resection group (P>0.05). There was no statistical difference in the average daily drainage volume or the proportion of pain among the three groups (P>0.05). Conclusion The thulium laser wedge resection under uniportal thoracoscopy is a safe, effective and economical method for the treatment of small pulmonary nodules.
ObjectiveTo explore the application of artificial intelligence (AI) in the standardized training of thoracic surgery residents, specifically in enhancing clinical skills and anatomical understanding through AI-assisted lung nodule identification and lung segment anatomy teaching. MethodsThoracic surgery residents undergoing standardized training at Peking Union Medical College Hospital from September 2023 to September 2024 were selected. They were randomly assigned to a trial group and a control group using a random number table. The trial group used AI-assisted three-dimensional reconstruction technology for lung nodule identification, while the control group used conventional chest CT images. After basic teaching and self-practice, the ability to identify lung nodules on the same patient CT images was evaluated, and feedback was collected through questionnaires. ResultsA total of 72 residents participated in the study, including 30 (41.7%) males and 42 (58.3%) females, with an average age of (24.0±3.0) years. The trial group showed significantly better overall diagnostic accuracy for lung nodules (91.9% vs. 73.3%) and lung segment identification (100.0% vs. 83.70%) compared to the control group, and the reading time was significantly shorter [ (118.5±10.5) s vs. (332.1±20.2) s, P<0.01]. Questionnaire results indicated that 94.4% of the residents had a positive attitude toward AI technology, and 91.7% believed that it improved diagnostic accuracy. ConclusionAI-assisted teaching significantly improves thoracic surgery residents’ ability to read images and clinical thinking, providing a new direction for the reform of standardized training.
The widespread use of low-dose computed tomography (LDCT) in lung cancer screening has enabled more and more lung nodules to get identified of which more than 20% are multiple pulmonary nodules. At present, there is no guideline or consensus for multiple pulmonary nodules whose management is based primarily on the pulmonary imaging characteristics and associated risk factors. Herein, this review covers the imaging methods, CT appearances and management of multiple pulmonary nodules.
ObjectiveTo compare the imaging characteristics and surgical methods of pulmonary nodules in the external 1/3 group and internal 2/3 group. MethodsA retrospective analysis of clinical data from patients who underwent thoracoscopic preoperative CT-guided lung nodule localization at the Department of Radiology, the First Affiliated Hospital of Xiamen University from September 2020 to April 2022 was conducted. ResultsA total of 215 patients were enrolled (247 pulmonary nodules), including 70 males and 145 females, with a median age of 48 years. Based on the location of the nodules under CT guidance, those located in the external 1/3 area of the lung were classified into an external 1/3 group, while those located in the middle 1/3 and inner 1/3 areas were classified into an internal 2/3 group. There was no statistical difference between the two groups in terms of general clinical data, nature of pulmonary nodules, distribution of pulmonary nodules in lobes, localization time, or localization complications (P>0.05). However, there were statistical differences in the distance of pulmonary nodules from the pleura [0.6 (0.0-1.9) cm vs. 1.8 (0.0-4.5) cm, P<0.001], size of pulmonary nodules [0.7 (0.2-1.8) cm vs. 1.0 (0.2-2.0) cm, P<0.001], and surgical methods (P=0.002). In the external 1/3 group, 92.1% of nodules underwent thoracoscopic wedge resection, while fewer patients underwent other procedures; in the internal 2/3 group, 77.1% of nodules underwent thoracoscopic wedge resection, and 19.3% underwent segmentectomy. ConclusionThe diameter of pulmonary nodules, the distance of pulmonary nodules from the pleura, and surgical methods differ between the external 1/3 group and internal 2/3 group. Thoracic surgeons can develop more precise surgical plans based on the location and size of pulmonary nodules.
ObjectiveTo explore the safety and feasibility of 3D precise localization based on anatomical markers in the treatment of pulmonary nodules during video-assisted thoracoscopic surgery (VATS).MethodsFrom June 2019 to April 2015, 27 patients with pulmonary nodules underwent VATS in our Hospital were collected in the study, including 3 males and 24 females aged 51.8±13.7 years. The surgical data were retrospectively reviewed and analyzed, such as localization time, localization accuracy rate, pathological results, complication rate and postoperative hospital stay.ResultsA total of 28 pulmonary nodules were localized via this method. All patients received surgery successfully. No mortality or major morbidity occurred. The general mean localization time was 17.6±5.8 min, with an accuracy of 96.4%. The mean diameter of pulmonary nodules was 14.0±8.0 mm with a mean distance from visceral pleura of 6.5±5.4 mm. There was no localization related complication. The mean postoperative hospital stay was 6.7±4.3 d. The routine pathological result showed that 78.6% of the pulmonary nodules were adenocarcinoma.Conclusion3D precise localization based on anatomical markers in the treatment of pulmonary nodules during thoracoscopic surgery is accurate, safe, effective, economical and practical, and it is easy to master with a short learning curve.
The possibility of solitary pulmonary nodules tending to lung cancer is very high in the middle and late stage. In order to detect the middle and late solitary pulmonary nodules, we present a new computer-aided diagnosis method based on the geometric features. The new algorithm can overcome the disadvantage of the traditional algorithm which can't eliminate the interference of vascular cross section. The proposed algorithm was implemented by multiple clustering of the extracted geometric features of region of interest (ROI) through K-means algorithm, including degree of slenderness, similar degree of circle, degree of compactness and discrete degree. The 232 lung CT images were selected from Lung Image Database Consortium (LIDC) database to do contrast experiment. Compared with the traditional algorithm, the detection rate of the new algorithm was 92.3%, and the error rate was 14.8%. At the same time, the detection rate of the traditional algorithm was only 83.9%, and the error rate was 78.2%. The results show that the proposed algorithm can mark the solitary pulmonary nodules more accurately and reduce the error rate due to precluding the disturbance of vessel section.
ObjectiveTo compare the effectiveness and safety of electromagnetic navigation-guided localization and CT-guided percutaneous localization for pulmonary nodules.MethodsThe literature published from the inception to January 2021 about the comparison between electromagnetic navigation-guided localization and CT-guided percutaneous localization for pulmonary nodules in the PubMed, The Cochrane Library, Web of Science, EMbase, Chinese Wanfang database and CNKI database was searched. RevMan (version 5.4) software was used for meta-analysis. Nonrandomized controlled trials were evaluated using methodological index for nonrandomized studies (MINORS).ResultsA total of six retrospective studies (567 patients) were included in this meta-analysis. MINORS scores of all studies were all 17 points and above. There were 317 patients in the CT-guided percutaneous localization group and 250 patients in the electromagnetic navigation-guided localization group. The complication rate of the CT-guided percutaneous localization group was significantly higher than that in the electromagnetic navigation-guided localization group (OR=11.08, 95%CI 3.35 to 36.65, P<0.001). There was no significant difference in the success rate of localization (OR=0.48, 95%CI 0.16 to 1.48, P=0.20), localization time (MD=0.30, 95%CI –6.16 to 6.77, P=0.93) or nodule diameter (MD=–0.07, 95%CI –0.19 to 0.06, P=0.29) between the two groups.ConclusionElectromagnetic navigation can be used as an effective preoperative positioning method for pulmonary nodules, which has the advantage of lower complication rate compared with the traditional CT positioning method.
