Surgery has remained the cornerstone of lung cancer therapy. Sleeve lobectomy, which is featured by not only the maximal resection of tumors but also the maximal preservation of functional lung parenchyma, has been proved to be a valid therapeutic option for the treatment of some centrally located lung cancer . Evidence points toward equivalent oncologic outcomes with improved survival and quality of life after sleeve resections compared with pneumonectomy. However, the postoperative morbidities and the long-term results after sleeve lobectomy remain controversial, especially in relation to nodal involvement and after induction therapy. With the development of technology, minimally invasive procedures have been performed more and more widely.
Preoperative mediastinal lymph node staging for non-small cell lung cancer (NSCLC) can be divided into non-invasive imaging techniques staging and invasive surgery techniques staging . Noninvasive imaging techniques are not sufficiently reliable in many situations. Computed tomography (CT) has been used as a routine inspection due to the anatomical images it provides. Magnetic resonance imaging (MRI) and diffusion weighted imaging (DWI) have not been widely applied. As the most accurate technique of noninvasive staging, positron emission tomographycomputed tomography (PET-CT) still has a higher rate of false negative. Invasive staging technique is safe and effective in mediastinal lymph node staging. Mediastinoscopy is the gold standard for invasive mediastinal staging till today. Endoscopic ultrasound-needle aspiration techniques and video-assisted thoracoscopic surgery (VATS) are also safe and effective. Invasive staging technique is the first choice of the re-staging in patients after induction therapy.
Abstract： Air leak is still a common postoperative complication after selective lobectomy. The majority of patients undergoing lobectomy have some risk factors of postoperative air leak or persistent air leak. Nowadays，preventive measures of postoperative air leak mainly include preoperative, intraoperative （surgical technique，reinforcement material，pleural cavity reduction），and postoperative （pleurodesis，chest drainage management） strategies. Many of these new measures have been applied in clinical practice with satisfactory outcomes.
Abstract： Objective To investigate diagnosis and treatment of concealed intrathoracic anastomotic leak of the esophagus. Methods We retrospectively analyzed the clinical data of 32 patients who presented with unexplained sepsis （temperature＞38 ℃ and elevated white blood cell count） after esophagectomy and intrathoracic anastomosis for esophageal carcinoma or gastric cardia carcinoma in Affiliated Hospital, Medical College of Qingdao University from January 2006 to December 2010. All the patients underwent oral water-soluble contrast esophagogram and oral water-soluble contrast computerized tomography of the chest. None of the patients had any sign of contrast leak in these diagnostic examinations, but their chest computerized tomography all showed peri-anastomotic bubble and encapsulated effusion. Fifteen patients were treated as concealed intrathoracic anastomotic leak of the esophagus, including fasting, broad spectrum antibiotic treatment, prolonged gastrointestinal decompression and enteral nutrition via naso-intestinal feeding tube. The other 17 patients were not treated as anastomotic leak of the esophagus and only received broad spectrum antibiotic treatment.?Results?None of the 15 patients who were treated as concealed intrathoracic anastomotic leak finally developed anastomotic leak proved by oral water-soluble contrast esophagogram and computerized tomography of the chest （0%, 0/15）. Among the 17 patients who were not treated as anastomotic leak, fourteen patients developed anastomotic leak later （82.4%, 14/17）, 2 patients died of aorto-esophageal fistula and 3 patients died of multiple organ dysfunction syndrome. Conclusion Peri-anastomotic bubble and irregular encapsulated effusion in oral water-soluble contrast esophagogram and computerized tomography of the chest should be considered as specific signs of concealed intrathoracic anastomotic leak of esophagus after esophagectomy and intrathoracic anastomosis. Patients with such signs should be treated as anastomotic leak.
ObjectiveTo compare and analyze clinical effects of video-assisted thoracoscopic surgery (VATS) lobectomy and systematic lymph node harvests for peripheral non-small cell lung cancer (PNSCLC) patients between single-port (SP) and multi-port (MP) with a propensity-matched analysis.
MethodsWe retrospectively analyzed the clinical data of 324 patients presented with PNSCLC and admitted in the Affiliated Hospital of Qingdao University from January 2013 through December 2015. Six-eight patients underwent single-port thoracoscopic lobectomy were as a SP group and 256 patients with multi-port thoracoscopic lobectomy. Another 68 patients were produced by a propensity-matched analysis in these 256 patients, to match with SP group as a MP group. There were 26 males and 42 females at age of 54-62 (59.3±10.3) years in the SP group. There were 32 males and 36 females at age of 50-66 (61.5±9.4) years in the MP group. Perioperative outcomes were compared between the two groups.
ResultsAll operations were accomplished successfully, without conversion to thoracotomy. Most postoperative outcomes were similar in intraoperative blood loss (136.3±22.7 ml vs. 142.2±20.3 ml), conversion (4.4% vs. 7.4%), lymph node dissection number (19.9±3.5 vs. 20.0±3.0), station (7.9±2.3 vs. 8.3±2.1), postoperative drainage volume (761.4±182.3 ml vs. 736.9±176.4 ml), chest drainage duration (5.2±1.5 d vs. 5.8±1.8 d), length of hospital stay (5.5±2.0 d vs. 5.0±2.5 d), and postoperative complications (2.9% vs. 7.4%) between the two groups (P > 0.05). There were statistical differences in operation time (138.2±20.3 min vs. 126.4±22.4 min), downtrend of pain scores (P=0.03), and patients' satisfaction level (8.8±1.4 vs. 7.3±2.3, P < 0.05). Concision Single-port thoracoscopic lobectomy is not inferior to multi-port and is a safe and feasible surgical procedure for the management of PNSCLC.
ObjectiveTo develop a predictive model for postoperative pulmonary complications (PPC) following video-assisted thoracic surgery (VATS) in lung cancer patients by integrating cardiopulmonary exercise testing (CPET) parameters and machine learning techniques. MethodsA retrospective analysis was conducted on patients with early-stage non-small cell lung cancer who underwent CPET and VATS at Guangdong Provincial People’s Hospital between October 2021 and July 2023. Patients were divided into a PPC group and a non-PPC group. The least absolute shrinkage and selection operator (LASSO) regression was used to select important features associated with PPC. Six machine learning algorithms were utilized to construct prediction models, including logistic regression, support vector machine, k-nearest neighbors, random forest, gradient boosting machine, and extreme gradient boosting. The optimal model was interpreted using SHapley Additive exPlanations (SHAP). ResultsA total of 325 patients were included, with an average age of 60.36 years, and 55.1% were male. Significant differences were observed between the PPC and non-PPC groups in age, diabetes, coronary heart disease, surgical approach, forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), FVC% predicted, peak oxygen uptake (peak VO2), anaerobic threshold (AT), and ventilatory equivalent for carbon dioxide slope (VE/VCO2 slope) (P<0.05). In the predictive model constructed by selecting 7 key features using LASSO regression, the random forest model demonstrated the best overall performance across various metrics, with an area under the receiver operating curve of 0.930, an F1 score of 0.836, and a Brier score of 0.133 in the training set. It also exhibited good predictive ability and calibration in the test set. SHAP analysis ranked feature importance as follows: peak VO2, VE/VCO2 slope, age, FEV1, smoking history, diabetes, and surgical approach. ConclusionIntegrating CPET parameters, the random forest model can effectively identify high-risk patients for PPC and has the potential for clinical application.
