In recent years, the computer science represented by artificial intelligence and high-throughput sequencing technology represented by omics play a significant role in the medical field. This paper reviews the research progress of the application of artificial intelligence combined with omics data analysis in the diagnosis and treatment of non-small cell lung cancer (NSCLC), aiming to provide ideas for the development of a more effective artificial intelligence algorithm, and improve the diagnosis rate and prognosis of patients with early NSCLC through a non-invasive way.
Surgery is the preferred treatment for early esophageal cancer. Minimally invasive esophagectomy (MIE) can significantly reduce the incidence of postoperative complications and mortality, but due to the complex esophageal anatomy, intraoperative esophageal exposure, separation, anastomosis and lymph node dissection are difficult. The da Vinci surgical system provides a 3D vision and a more flexible as well as stable robotic arm, which is very helpful in completing fine surgical procedures. Robot-assisted minimally invasive esophagectomy(RAMIE) has been carried out in a number of countries, including China. Robot-assisted Ivor-Lewis esophagectomy (RAILE) is a transthoracic approach of robots developed in recent years. This paper summarizes the current researches on RAILE.
Objective To evaluate the effects of robot-assisted Ivor Lewis esophagectomy (RAILE) in surgical treatment of esophageal cancer. Methods We retrospectively analyzed the clinical data of 70 patients diagnosed with mid-lower esophageal cancer undergoing RAILE in the Department of Thoracic Surgery in Ruijin Hospital Affiliated to Shanghai Jiaotong University between May 2015 and April 2018. There were 54 males and 16 females at average age of 62.0±7.6 years. Forty patients underwent circular end-to-end stapled intrathoracic anastomosis and 30 had a double-layered, completely hand-sewn intrathoracic anastomosis. Results The mean operating time was 308.7±60.6 minutes. And blood loss was 190.0±95.1 ml. There were 2 patients who underwent conversion to thoracotomy. There was no in-hospital and 30-day mortality. Overall complications were observed in 24 patients (34.3%), of whom 6 patients (8.6%) had anastomotic leakage. The median length of hospitalization was 9.0 (interquartile range, IQR, 5.0) days. The mean tumor size was 3.2±1.5 cm, and R0 resection was achieved in all patients. The mean number of totally dissected lymph nodes was 19.3±8.7. Conclusion RAILE is safe and technically feasible with satisfactory perioperative outcomes.
Recently, anatomical segmentectomy emerges as a hot spot in clinical research for surgical treatment of early-stage lung cancer. The techniques of segmentectomy are more elaborate and complicated than lobectomy, because of the considerable anatomic variations of segment blood vessels and bronchus. In a long term, video-assisted thoracic surgery is the mainly minimally invasive approach. As a new approach of minimally invasive surgery, da Vinci robot system possesses three-dimensional and high definition view, better dexterity mechanical wrist and tremor filtering system, which are the main advantages over video-assisted thoracic surgery. All the superiorities of robot system provide good supports for performing segmentectomy. Robot-assisted segmentectomy has been carried out in many medical centers in China and abroad until now. However, most surgery cases often lack adequate controls on quality.
ObjectiveTo explore the training mode for improving the innovative scientific research ability of postgraduates of thoracic surgery.MethodsTwenty-two postgraduate students enrolled in the Department of Thoracic Surgery, Ruijin Hospital from September 2016 to June 2019 were targeted for training, and the teachers were 13 doctors in our department. Training methods included grant-based learning, formative learning and translational medical learning. In addition to the postgraduate education provided by the medical school, the training content also included more than 50 lectures about thoracic surgery, including surgical video explanation, perioperative management of thoracic surgery, interpretation of clinical guidelines, and intensive reading of the literature; it also included half-year clinical internship, 100 surgical operations and management of 5 medical beds in ward.ResultsClinical ability of the postgraduates were improved. Six postgraduate students enrolled in 2016 graduated successfully. They published 15 SCI papers and won more than 20 awards.ConclusionCultivating postgraduates of thoracic surgery oriented by innovative scientific research ability is conducive to the comprehensive understanding of thoracic diseases and the ability of innovative translation research.
Segmentectomy is the removal of certain segments of the lung with lesions and retaining the normal lung tissue of the lobe. Lung segmentectomy is considered difficult due to the lack of clear anatomical boundaries between lung segments. Segmentectomy has a variety of indications, such as lung cancer, metastatic lung tumors, and many non-malignant diseases. In the treatment of early stage lung cancer, segmentectomy was initially considered only as a treatment option for patients not suitable for conventional lobectomy. As more evidence emerged, the indications for segmentectomy have continued to change over time, and segmentectomy has been widely performed in patients with early stage lung cancer. Theoretically, segmentectomy leads to better preservation of lung function than lobectomy, but the risk of incomplete tumor resection is higher, so the indication of segmentectomy has become a focus of debate. This article will introduce the surgical techniques of segmentectomy and summarize the published and unpublished clinical studies on segmentectomy for the treatment of early stage lung cancer.
ObjectiveTo analyze the risk factors for complications after robotic segmentectomy.MethodsClinical data of 207 patients undergoing robot-assisted anatomical segmentectomy in our hospital from June 2015 to July 2019 were retrospectively analyzed, including 69 males and 138 females with a median age of 54.0 years. The relationship between clinicopathological factors and prolonged air leakage, pleural effusion, and pulmonary infection after surgery was analyzed.ResultsAfter robot-assisted segmentectomy, 20 (9.7%) patients developed prolonged air leakage (>5 d), 17 (8.2%) patients developed pleural effusion, and 4 (1.9%) patients developed pulmonary infection. Univariate logistic regression showed that body mass index (BMI, P=0.018), FEV1% (P=0.024), number of N1 lymph nodes resection (P=0.008) were related to prolonged air leakage after robot-assisted segmentectomy. Benign lesion was a risk factor for pleural effusion (P=0.013). The number of lymph node sampling stations was significantly related to the incidence of pulmonary infection (P=0.035). Multivariate logistic analysis showed that the BMI (OR=0.73, P=0.012) and N1 lymph node sampling (OR=1.38, P=0.001) had a negative and positive relationship with prolonged air leakage after robot-assisted segmentectomy, respectively.ConclusionThe incidence of pulmonary complications after robot-assisted segmentectomy is low. The lower BMI and more N1 lymph node sampling is, the greater probability of prolonged air leakage is. Benign lesions and more lymph node sampling stations are risk factors for pleural effusion and lung infection, respectively. Attention should be paid to the prevention and treatment of perioperative complications for patients with such risk factors.
Based on new clinical evidence, the National Comprehensive Cancer Network (NCCN) annually updates and releases the "NCCN Guidelines for the Clinical Diagnosis and Treatment of Non-Small Cell Lung Cancer" which has become the reference for clinical diagnosis and treatment approved and complied by clinicians worldwide. On November 25, 2020, the latest 2021 V1 version of "NCCN Clinical Diagnosis and Treatment Guidelines for Non-Small Cell Lung Cancer" (hereinafter referred to as "Guidelines") was released. Compared with the 8th edition of the "Guidelines" in 2020, many updates focused on the progress of targeted and immunotherapy. This article will provide the interpretations of the updated therapy content of this edition of the guidelines.
The National Comprehensive Cancer Network (NCCN) released the latest version 1, 2022 of "NCCN guidelines for the clinical diagnosis and treatment of small cell lung cancer" (hereinafter referred to as "guideline"). Based on high-quality evidence-based medicine, this guideline provides references of clinical diagnosis and treatment for clinicians around the world. Compared with the version 3, 2021 of the "guideline", updates and revisions mainly focused on the progress of radiotherapy and systemic treatment. This article will interpret the updated therapy content in this new version of the "guideline".
The National Comprehensive Cancer Network (NCCN) has updated and released the latest content of the NCCN guidelines for the clinical diagnosis and treatment of non-small cell lung cancer (NSCLC) in the version 1, 2022. Based on high-quality clinical evidence and the latest research progress of the diagnosis and treatment of NSCLC, the guidelines have been widely recognized and welcomed by clinicians around the world. Compared with the version 7, 2021, the new version has been updated and revised in some parts of chapters and sections, mainly focusing on targeted therapies and molecular testing. This article will interpret the updated therapy content of the new version.