Objective To evaluate the clinical effects of harmonic scalpel application in thoracoscopic surgery for lung cancer, which may guide its reasonable application. Methods We retrospectively analyzed the clinical data of 145 lung cancer patients receiving thoracoscopic surgery from January to March 2017 in our hospital. There were 57 patients with thoracoscopic pulmonary wedge resection, and harmonic scalpel was used in 34 patients (8 males, 26 females at age of 59.68±10.91 years), and was not used in 23 patients (13 males and 10 females at age of 59.13±11.21 years). There were 88 patients receiving thoracoscopic pulmonary lobectomy, among whom harmonic scalpel was used in 80 patients (36 males and 44 females at age of 59.68±10.91 years), and was not used in 8 patients (5 males, 3 females at age of 61.63±5.60 years). We recorded the perioperative outcomes of all patients. Results In the 34 patients undergoing thoracoscopic pulmonary wedge resection by harmonic scalpe, the operation time was 90.09±43.52 min, the blood loss was 21.32±12.75 ml, the number of lymph nodes resected was 5.12±4.26, duration of drainage was 3.15±1.16 d, volume of drainage was 535.00±291.69 ml, the length of postoperative hospital stay was 4.56±1.40 d, and no postoperative complication was observed. In the 80 patients receiving thoracoscopic pulmonary lobectomy by harmonic scalpel, operation time was 131.88±41.82 min, blood loss was 42.79±31.62 ml, the number of lymph nodes resected was 13.54±8.75, duration of thoracic drainage was 4.47±2.30 d, drainage volume was 872.09±585.24 ml, the length of postoperative hospital stay was 5.81±2.26 d, and 20 patients had postoperative complications. No complication occurred in the 8 patients without harmonic scalpel. Conclusion Harmonic scalpel showed satisfactory effectiveness and safety in lung cancer thoracoscopic surgery.
The technical combination of artificial intelligence (AI) and thoracic surgery is increasingly close, especially in the field of image recognition and pathology diagnosis. Additionally, robotic surgery, as a representative of high-end technology in minimally invasive surgery is flourishing. What progress has been or will be made in robotic surgery in the era of AI? This article aims to summarize the application status of AI in thoracic surgery and progress in robotic surgery, and looks ahead the future.
ObjectiveTo summarize the experience of minimally invasive anterior mediastinal tumor resection in our center, and compare the Da Vinci robotic and video-assisted thoracoscopic approaches in the treatment of mediastinal tumor.MethodsA retrospective cohort study was conducted to continuously enroll 102 patients who underwent minimally invasive mediastinal tumor resection between September 2014 and November 2019 by the single medical group in our department. They were divided into two groups: a robotic group (n=47, 23 males and 24 females, average age of 52 years) and a thoracoscopic group (n=55, 29 males and 26 females, average age of 53 years). The operation time, intraoperative blood loss, postoperative thoracic drainage volume, postoperative thoracic drainage time, postoperative hospital stay, hospitalization expense and other clinical data of two groups were compared and analyzed.ResultsAll the patients successfully completed the surgery and recovered from hospital, with no perioperative death. Myasthenia gravis occurred in 4 patients of the robotic group and 5 of the thoracoscopic group. The tumor size was 2.5 (0.8-8.7) cm in the robotic group and 3.0 (0.8-7.7) cm in the thoracoscopic group. Operation time was 62 (30-132) min in the robotic group and 60 (29-118) min in the thoracoscopic group. Intraoperative bleeding volume was 20 (2-50) mL in the robotic group and 20 (5-100) mL in the thoracoscopic group. The postoperative drainage volume was 240 (20-14 130) mL in the robotic group and 295 (20-1 070) mL in the thoracoscopic group. The postoperative drainage time was 2 (1-15) days in the robotic group and 2 (1-5) days in the thoracoscopic group. There was no significant difference between the two groups in the above parameters and postoperative complications (P>0.05). The postoperative hospital stay were 3 (2-18) days in the robotic group and 4 (2-14) in the thoracoscopic group (P=0.014). The hospitalization cost was 67 489(26 486-89 570) yuan in the robotic group and 27 917 (16 817-67 603) yuan in the thoracoscopic group (P=0.000).ConclusionCompared with the video-assisted thoracoscopic surgery, Da Vinci robot-assisted surgery owns the same efficacy and safety in the treatment of mediastinal tumor, with shorter postoperative hospital stay, but higher cost.
ObjectiveTo investigate the safety and efficiency of robotic lung segmentectomy.MethodsThe clinical data of 110 patients receiving robotic or thoracoscopic segmentectomy in our hospital between June 2015 and June 2019 were retrospectively analyzed. The patients were divided into a robotic group [n=50, 13 males and 37 females aged 53.0 (46.0, 60.0) years] and a thoracoscopic group [n=60, 21 males and 39 females aged 61.0 (53.0, 67.0) years]. A propensity score-matched analysis was adopted to compare the perioperative data between the two groups.ResultsAfter the propensity score-matched analysis, 34 patients were included in each group. In comparison with the thoracoscopic group, patients in the robotic group had less blood loss [40.0 (20.0, 50.0) mL vs. 60.0 (40.0, 80.0) mL, P<0.001], more stations of lymph node dissection [7.0 (6.0, 8.0) vs. 4.0 (3.0, 6.0), P<0.001], larger number of lymph node dissection [15.0 (11.0, 21.0) vs. 10.0 (6.0, 14.0), P=0.002], and a higher total cost of hospitalization [97.0 (92.0, 103.0) thousand yuan vs. 54.0 (42.0, 59.0) thousand yuan, P<0.001].ConclusionIn contrast with the thoracoscopic segmentectomy, robotic segmentectomy has a similar operative safety, but less blood loss and a thorough lymphadenectomy.
The increasing number of pulmonary nodules being detected by computed tomography scans significantly increase the workload of the radiologists for scan interpretation. Limitations of traditional methods for differential diagnosis of pulmonary nodules have been increasingly prominent. Artificial intelligence (AI) has the potential to increase the efficiency of discrimination and invasiveness classification for pulmonary nodules and lead to effective nodule management. Chinese Experts Consensus on Artificial Intelligence Assisted Management for Pulmonary Nodule (2022 Version) has been officially released recently. This article closely follows the context, significance, core implications, and the impact of future AI-assisted management on the diagnosis and treatment of pulmonary nodules. It is hoped that through our joint efforts, we can promote the standardization of management for pulmonary nodules and strive to improve the long-term survival and postoperative life quality of patients with lung cancer.