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.
ObjectiveTo investigate the feasibility of using magnetic beads to locate small pulmonary nodules.MethodsTwelve rabbits were randomly divided into two groups, 6 in each group. One group underwent thoracotomy after anesthesia and the other group underwent percutaneous puncture under the guidance of X-ray. One and two cylindrical tracer magnets (magnetic beads) with a diameter of 1 mm and a height of 3 mm were injected adjacent to the imaginary pulmonary nodules in left lung in each group. The magnetic beads beside the imaginary nodules were attracted by a pursuit magnet with a diameter of 9 mm and a height of 19 mm. The effectiveness of localization by magnetic beads were determined by attraction between tracer and pursuit magnets.ResultsAll processes were uneven in 12 rabbits. There was micro hemorrhage and no hematoma in the lung tissue at the injection site of the magnetic beads. When tracked with the pursuit magnets, there was one bead divorce in cases that one bead was injected, but no migration or divorce of the magnetic beads in cases that two magnetic beads were simultaneously injected to localize the small pulmonary nodules.ConclusionThe feasibility of using magnetic beads to locate small pulmonary nodules has been preliminarily verified.
Pulmonary adenocarcinoma in situ is reclassified as precursor glandular lesions in the fifth edition of WHO classification of thoracic tumours, causing widespread attention and heated debate among domestic thoracic oncologists, radiologists, pathologists and surgeons. We would like to comment on the topic and make a few suggestions on the management of pulmonary nodule during lung cancer screening. We are open to all suggestion and welcome debates.
ObjectiveTo explore the application value of CT-guided microcoil localization in pulmonary nodule (diameter≤15 mm) surgery.MethodsThe clinical data of 175 patients with pulmonary nodules who underwent single utility port video-assisted thoracoscopic surgery at Nanjing Drum Tower Hospital from August 2018 to December 2019 were retrospectively analyzed. According to whether CT-guided coil localization was performed before operation, they were divided into a locating group and a non-locating group. There were 84 patients (34 males, 50 females, aged 57.8±8.8 years) in the locating group and 91 patients (46 males, 45 females, aged 57.6±10.8 years) in the non-locating group. The localization success rate, localization time, incidence of complications, surgical and postoperative conditions were analyzed between the two groups.ResultsAll 84 patients in the locating group were successfully located, and localization time was 19.0±3.6 minutes. Among them, 19 (22.6%) patients had a small pneumothorax, 4 (4.8%) pulmonary hemorrhage and 2 (2.4%) coil shift; 6 (7.1%) patients had mild pain, 3 (3.6%) moderate pain and 1 (1.2%) severe pain. Sex (P=0.181), age (P=0.673), nodule location (P=0.167), nature of lesion (P=0.244), rate of conversion to thoracotomy (P=0.414), rate of disposable resection of nodules (P=0.251) and postoperative hospital stay (P=0.207) were similar between the two groups. There were significant differences in nodule size (P<0.001), nature of nodule (P<0.001), the shortest distance from nodule to pleura (P<0.001), operation time (P<0.001), lung volume by wedge resection (P=0.031), number of staplers (P<0.001) and total hospitalization costs (P<0.001) between the two groups.ConclusionCT-guided microcoil localization has the characteristics of high success rate, and is simple, practicable, effective, safe and minimally invasive. Preoperative CT-guided microcoil localization has important clinical application value for small pulmonary nodules, especially those with small size, deep location and less solid components. It can effectively shorten the operation time, reduce surgical trauma and lower hospitalization costs, which is a preoperative localization technique worthy of popularization.
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.
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 compare the clinical application of empirical thoracoscopic segmentectomy and precise segmentectomy planned by artificial intelligence software, and to provide some reference for clinical segmentectomy. MethodsA retrospective analysis was performed on the patients who underwent thoracoscopic segmentectomy in our department from 2019 to 2022. The patients receiving empirical thoracoscopic segmentectomy from January 2019 to September 2021 were selected as a group A, and the patients receiving precise segmentectomy from October 2021 to December 2022 were selected as a group B. The number of preoperative Hookwire positioning needle, proportion of patients meeting oncology criteria, surgical time, intraoperative blood loss, postoperative chest drainage time, postoperative hospital stay, and number of patients converted to thoracotomy between the two groups were compared. Results A total of 322 patients were collected. There were 158 patients in the group A, including 56 males and 102 females with a mean age of 56.86±8.82 years, and 164 patients in the group B, including 55 males and 109 females with a mean age of 56.69±9.05 years. All patients successfully underwent thoracoscopic segmentectomy, and patients whose resection margin did not meet the oncology criteria were further treated with extended resection or even lobectomy. There was no perioperative death. The number of positioning needles used for segmentectomy in the group A was more than that in the group B [47 (29.7%) vs. 9 (5.5%), P<0.001]. There was no statistical difference in the number of positioning needles used for wedge resection between the two groups during the same period (P=0.572). In the group A, the nodule could not be found in the resection target segment in 3 patients, and the resection margin was insufficient in 10 patients. While in the group B, the nodule could not be found in 1 patient, and the resection margin was insufficient in 3 patients. There was a statistical difference between the two groups [13 (8.2%) vs. 4 (2.4%), P=0.020]. There was no statistical difference between the two groups in terms of surgical time, intraoperative blood loss, duration of postoperative thoracic drainage, postoperative hospital stay, or conversion to open chest surgery (P＞0.05). Conclusion Preoperative surgical planning performed with the help of artificial intelligence software can effectively guide the completion of thoracoscopic anatomical segmentectomy. It can effectively ensure the resection margin of pulmonary nodules meeting the oncological requirements and significantly reduce the number of positioning needles of pulmonary nodules.
Computer-aided diagnosis based on computed tomography (CT) image can realize the detection and classification of pulmonary nodules, and improve the survival rate of early lung cancer, which has important clinical significance. In recent years, with the rapid development of medical big data and artificial intelligence technology, the auxiliary diagnosis of lung cancer based on deep learning has gradually become one of the most active research directions in this field. In order to promote the deep learning in the detection and classification of pulmonary nodules, we reviewed the research progress in this field based on the relevant literatures published at domestic and overseas in recent years. This paper begins with a brief introduction of two widely used lung CT image databases: lung image database consortium and image database resource initiative (LIDC-IDRI) and Data Science Bowl 2017. Then, the detection and classification of pulmonary nodules based on different network structures are introduced in detail. Finally, some problems of deep learning in lung CT image nodule detection and classification are discussed and conclusions are given. The development prospect is also forecasted, which provides reference for future application research in this field.
Objective To explore the correlation between the imaging features of peripheral ground-glass pulmonary nodules and the invasion degree of lung adenocarcinoma, and the high risk factors for infiltrating lung adenocarcinoma under thin-slice CT, which provides some reference for clinicians to plan the surgical methods of pulmonary nodules before operation and to better communicate with patients, and assists in building a clinical predictive model for invasive adenocarcinoma. MethodsClinical data of the patients with peripheral ground-glass pulmonary nodules (diameter≤3 cm) in thin-slice chest CT in the First Affiliated Hospital of Soochow University from January 2019 to January 2020 were continuously collected. All patients underwent thin-slice CT scan and thoracoscopic surgery in our center. According to the pathological examination results, they were divided into two groups: an adenocarcinoma lesions before infiltration group, and an invasive lung adenocarcinoma group. The thin-slice CT imaging parameters of pulmonary nodules were collected. The nodular diameter, mean CT value, consolidation tumor ratio (CTR), nodular shape, vacuolar sign, bronchial air sign, lobulation sign, burr sign, lesion boundary, pleural depression sign, vascular cluster sign and other clinical data were collected. Univariate and multivariate analyses were conducted to analyze the independent risk factors for the infiltrating lung adenocarcinoma, and to analyze the threshold value and efficacy of each factor for the identification of infiltrating lung adenocarcinoma. Results Finally 190 patients were enrolled. There were 110 patients in the adenocarcinoma lesions before infiltration group, including 21 males and 89 females with a mean age of 53.57±10.90 years, and 80 patients in the invasive lung adenocarcinoma group, including 31 males and 49 females with a mean age of 56.45±11.30 years. There was a statistical difference in the mean CT value, nodular diameter, CTR, gender, smoking, nodular type, nodular shape, vacuolar sign, lobulation sign, burr sign, lesion boundary, pleural depression sign, vascular cluster sign between the two groups (P＜0.05). However, there was no statistical difference between the two groups in age (P=0.081), lesion site (P=0.675), and bronchial air sign (P=0.051). Multiple logistic regression analysis showed that nodular diameter, mean CT value, CTR and lobulation sign were independent risk factors for differentiating preinvasive adenocarcinoma from invasive adenocarcinoma. At the same time, the threshold value was calculated by Youden index, indicating that the CTR was 0.45, the nodal diameter was 10.5 mm and the mean CT value was –452 Hu. Conclusion In the peripheral ground-glass pulmonary nodules, according to the patient's CT imaging features, such as mixed ground-glass nodules, irregular shapes, vacuoles, short burrs, clear boundaries, pleural indentations, and vascular clusters, have a certain reference value in the discrimination of the invasion degree of ground-glass pulmonary nodules. At the same time, it is found in this research that peripheral ground-glass pulmonary nodules with diameter greater than 10.5 mm, CT value greater than –452 Hu, CTR greater than 0.45 and lobulation sign are more likely to be infiltrating lung adenocarcinoma.
Objective To evaluate the safety and efficacy of basic anesthesia combined with local anesthesia in the preoperative localization of multiple pulmonary nodules. Methods The clinical data of patients who underwent preoperative localization for multiple pulmonary nodules resection under single-port thoracoscopy in Nanjing Brain Hospital from July 2023 to September 2023 were extracted. They were divided into a group A and a group B according to the localization method. The patients in the group A were localized under local anesthesia, and the patients in the group B were localized with basic anesthesia combined with local anesthesia. The basic clinical characteristics, localization success rate, incidence of localization complications, localization time, and pain score of the two groups were compared and analyzed. Results Finally, we included 200 patients with 100 patients in each group. There were 49 males and 51 females at age of 25-77 (50.94±14.29) years in the group A. There are 45 males and 55 females at age of 24-78 (48.25±14.04) years in the group B. The incidence of localization complications (4% vs. 13%, P=0.04), localization time [(19.90±8.66) min vs. (15.23±5.98) min, P<0.01], and pain score[ (2.01±2.09) vs. (3.29±2.54), P<0.01] in the group B were significantly lower than those in the group A, and the differences were statistically significant. The localization success rate of the group B was significantly higher than that of the group A (98% vs. 92%, P=0.04), and the difference was statistically significant.Conclusion Mobile CT combined with basic anesthesia for preoperative localization of multiple pulmonary nodules is highly safe, has a high success rate, and provides high patient comfort, making it a valuable approach for clinical promotion.