Thoracoscopic pulmonary segmentectomy is one of the important treatment methods for early lung cancer. Only the premise of surgical precision can make the radical resection of lesions and maximum reservation of healthy lung tissue be simultaneously guaranteed. As a representative of the precise lung operation, the " cone-shaped lung segmentectomy” focuses on the lesion, and combines the anatomical characteristic of the patient to design individualized operation scheme. The technological core consists of three parts, three dimensional-computed tomography bronchography and angiography (3D-CTBA) surgery path planning, accurate definition of intersegmental demarcation and anatomic dissection of intersegmental borders along the demarcation. This paper aims to explore the technical process and quality control of the key techniques of thoracoscopic precise segmentectomy, so as to standardize the segmentectomy procedure under the principle of radical and minimally invasive therapy.
ObjectiveTo explore the clinical value of three-dimensional computed tomography bronchography and angiography (3D-CTBA) in robotic lung segmentectomy.MethodsA non-randomized control study was performed and continuously enrolled 122 patients who underwent robotic lung segmentectomy in our hospital from January 2019 to January 2020. 3D-CTBA was performed before operations in 53 patients [a 3D-CTBA group, including 18 males, 35 females, with a median age of 52 (26-69) years] and not performed in the other 69 patients [a traditional group, including 23 males, 46 females, with a median age of 48 (30-76) years]. The clinical data of the patients were compared between the two groups.ResultsAll the patients were successfully completed the surgery and recovered from hospital, with no perioperative death. The baseline characteristics of the patients were not significantly different between the two groups (P>0.05). No significant difference was found in the operative time [120 (70-185) min vs. 120 (45-225) min, P=0.801], blood loss [50 (20-300) mL vs. 30 (20-400) mL, P=0.778], complications rate (17.0% vs. 11.6%, P=0.162), postoperative hospital stay [7 (4-19) d vs. 7 (3-20) d, P=0.388] between the two groups. In the 3D-CTBA group, 5 (9.4%) patients did not find nodules after segmentectomy, and only 1 (1.9%) of them needed lobectomy, but in the traditional group, 8 (11.6%) patients did not find nodules and had to carry out lobectomy, the difference was statistically significant (P<0.05). The follow-up time was 10 (1-26) months, and during this period, there was no recurrence, metastasis or death in the two groups.Conclusion3D-CTBA is helpful for accurate localization of nodules and reasonable surgical planning before operations, and reducing wrong resections in segmentectomy, without increasing the operation time, blood loss and complications. It is safe and effective in anatomical lung segmentectomy.
ObjectiveTo explore the value of artificial intelligence (AI) diagnostic imaging system and three dimensional computed tomographic bronchoangiography (3D-CTBA) surgical planning system in the management of multiple primary lung cancer (MPLC).MethodsThe clinical data of 53 patients with MPLC treated surgically in our hospital from January 2018 to August 2020 were retrospectively analyzed, including 16 males and 37 females, with a median age of 60 (39-75) years. The patients' preoperative CT was analyzed by AI and manually, and the data of patients who underwent 3D-CTBA were compiled to evaluate the value of AI and 3D-CTBA in the diagnosis and treatment of MPLC, respectively.Results The sensitivity of AI screening for MPLC was 84.91%. The sensitivity (91.90% vs. 83.78%) and accuracy (85.60% vs. 84.00%) of AI diagnosis of high-risk MPLC infiltrative lesions were better than those of manual diagnosis. 3D-CTBA was used for planning the surgery in 12 patients, and the intraoperative situation was generally consistent with the reconstructed results.ConclusionAI is of high value in identifying infiltrative lesions of MPLC. 3D-CTBA reconstruction of anatomical structures is accurate and can guide preoperative planning.