With the widespread adoption of low-dose CT screening and the extensive application of high-resolution CT, the detection rate of sub-centimeter lung nodules has significantly increased. How to scientifically manage these nodules while avoiding overtreatment and diagnostic delays has become an important clinical issue. Among them, lung nodules with a consolidation tumor ratio less than 0.25, dominated by ground-glass shadows, are particularly worthy of attention. The therapeutic challenge for this group is how to achieve precise and complete resection of nodules during surgery while maximizing the preservation of the patient's lung function. The "watershed topography map" is a new technology based on big data and artificial intelligence algorithms. This method uses Dicom data from conventional dose CT scans, combined with microscopic (22-24 levels) capillary network anatomical watershed features, to generate high-precision simulated natural segmentation planes of lung sub-segments through specific textures and forms. This technology forms fluorescent watershed boundaries on the lung surface, which highly fit the actual lung anatomical structure. By analyzing the adjacent relationship between the nodule and the watershed boundary, real-time, visually accurate positioning of the nodule can be achieved. This innovative technology provides a new solution for the intraoperative positioning and resection of lung nodules. This consensus was led by four major domestic societies, jointly with expert teams in related fields, oriented to clinical practical needs, referring to domestic and foreign guidelines and consensus, and finally formed after multiple rounds of consultation, discussion, and voting. The main content covers the theoretical basis of the "watershed topography map" technology, indications, operation procedures, surgical planning details, and postoperative evaluation standards, aiming to provide scientific guidance and exploration directions for clinical peers who are currently or plan to carry out lung nodule resection using the fluorescent microscope watershed analysis method.

Objective To investigate the significance of spread through air spaces (STAS) in early-stage non-small cell lung cancer (NSCLC) patients undergoing either sublobar resection or lobectomy by pooling evidence available, and to assess the accuracy of frozen sections in determining types of resection among patients with suspected presence of STAS. Methods Studies were identified by searching databases including PubMed, EMbase, Web of Science, and The Cochrane Library from inception to July 2022. Two researchers independently searched, screened, evaluated literature, and extracted data. Statistical analysis was conducted using RevMan 5.4 and STATA 15.0. The Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of the study. Results A total of 26 studies involving 23 surgical related studies (12 266 patients) were included, among which, 11 compared the outcomes of lobectomy with sublobar resection in the STAS-positive patients. NOS score≥6 points. Meta-analysis indicated that presence of STAS shortened patients' survival in both lobectomy group and sublobar resection group (RFS: HR=2.27, 95%CI 1.96-2.63, P＜0.01; OS: HR=2.08, 95%CI 1.74-2.49, P＜0.01). Moreover, lobectomy brought additional survival benefits to STAS-positive patients compared with sublobar resection (RFS: HR=1.97, 95%CI 1.59-2.44, P＜0.01; OS: HR=1.91, 95%CI 1.47-2.48, P＜0.01). Four studies were included to assess the accuracy of identifying presence of STAS on intraoperative frozen sections, of which the pooled sensitivity reached 55% (95%CI 45%-64%), the pooled specificity reached 92% (95%CI 77%-97%), and the pooled area under the curve was 0.68 (95%CI 0.64-0.72) based on the data available. Conclusion This study confirms that presence of STAS is a critical risk factor for patients with early-stage NSCLC. Lobectomy should be recommended as the first choice when presence of STAS is identified on frozen sections, as lobectomy can prolong patients' survival compared with sublobar resection in STAS-positive disease. The specificity of identifying STAS on frozen sections seems to be satisfactory, which may be helpful in determining types of resection. However, more robust methods are urgently in need to make up for the limited sensitivity and accuracy of frozen sections.

Objective To investigate whether adjuvant therapy can bring survival benefits to patients with esophageal squamous cell carcinoma (ESCC) who have received neoadjuvant therapy plus esophagectomy. Methods Studies were identified by searching databases including PubMed, EMbase, Web of Science, The Cochrane Library and CNKI from inception to November 2022 to collect studies which conformed to the objective of this study. Clinical outcomes including overall survival (OS) and recurrence-free survival (RFS) were extracted from eligible studies after screening. RevMan 5.4 and Stata 14.0 were used to perform the meta-analysis. Results A total of 9 studies were selected including 1 340 patients. Compared with the neoadjuvant therapy plus surgery (NS) group, the neoadjuvant therapy plus surgery+adjuvant therapy (NS+A) group had no significant benefit in the OS [HR=0.88, 95%CI (0.75, 1.02), P=0.09], but had remarkable benefit in the RFS [HR=0.75, 95%CI (0.58, 0.97), P=0.03]. Subgroup analysis by nodal status showed that adjuvant therapy could improve the RFS of patients with node-positive disease. Prolonged OS was observed in the patients with both positive and negative nodes but not in the patients with only positive nodes. In terms of the subgroup analysis by prescription, it revealed that triple agents exhibited advantages in improving RFS but not OS. However, dual agents did not bring additional survival benefits to the NS+A group compared with the NS group. Subgroup analysis by adjuvant therapy indicated that neither postoperative chemoradiotherapy nor chemotherapy improved OS, whereas postoperative chemoradiation elongated RFS. Conclusion Adjuvant therapy can improve the prognosis of patients with ESCC after neoadjuvant therapy followed by esophagectomy.

The traditional treatment modalities for esophageal cancer include surgery, chemotherapy, and radiotherapy, each presenting its own limitations. With advancements in endoscopic techniques and the integration of immunotherapy, the feasibility and safety of organ preservation have significantly improved, offering patients improved survival and quality of life. The selection of patients suitable for organ preservation treatment demands ongoing exploration. Those selected for this approach require rigorous monitoring, with surgical intervention as a salvation for tumor progression or metastasis, though the timing of surgery remains a topic of debate. Organ preservation and watch-and-wait strategy may provide a more conservative treatment option, aiming to maximize quality of life.

The traditional treatment modalities for esophageal cancer include surgery, chemotherapy, and radiotherapy, each presenting its own limitations. With advancements in endoscopic techniques and the integration of immunotherapy, the feasibility and safety of organ preservation have significantly improved, offering patients improved survival and quality of life. The selection of patients suitable for organ preservation treatment demands ongoing exploration. Those selected for this approach require rigorous monitoring, with surgical intervention as a salvation for tumor progression or metastasis, though the timing of surgery remains a topic of debate. Organ preservation and watch-and-wait strategy may provide a more conservative treatment option, aiming to maximize quality of life.

【Objective】 To explore the factors influencing the survival and prognosis of patients with bladder urothelial carcinoma (BUC) after surgical treatment, and to establish an artificial intelligence algorithm to predict the effects of different surgical regimens. 【Methods】 BUC patients treated with surgery during Jan.2007 and Jan.2019 in The Second Hospital of Dalian Medical University and Nanfang Hospital of Southern Medical University were enrolled. The complete clinical and follow-up data were collected. Deep neural network (DNN) was used to establish an artificial intelligence algorithm model. A prediction model of survival and prognosis was established, and the influencing factors of survival were explored and ranked by the artificial intelligence algorithm. 【Results】 A total of 832 patients were involved, including 438 (52.64%) treated in The Second Hospital of Dalian Medical University, and 394 (47.36%) treated in Nanfang Hospital of Southern Medical University. Of all cases, 579 (69.6%) were non-muscle invasive bladder cancer, and 253 (30.4%) were muscle invasive bladder cancer. Transurethral resection of bladder tumor was conducted in 539 (64.8%) cases, partial cystectomy in 66 (7.9%) cases, and total cystectomy in 227 (27.3%) cases. The data of patients treated in Second Hospital of Dalian Medical University were used for DNN modeling, and the data of patients treated in Nanfang Hospital of Southern Medical University were used for external verification after modeling. Finally, it was concluded that the factors affecting survival and prognosis were T stage, pathological grade, hypertension or cardiovascular and cerebrovascular disease, hemoglobin, blood calcium, smoking, albumin, lymphocytes, age, ratio of albumin/globulin, operation method, N stage, and creatinine clearance rate in descending order. The model could be used for preoperative prediction. 【Conclusion】 Through DNN modeling and external verification, the influencing factors of postoperative survival can be predicted for patients with bladder cancer, and the surgical effects can also be predicted before operation. The model can provide artificial intelligence algorithm support for the selection of surgical methods and postoperative follow-up plans.

For locally advanced esophageal squamous cell carcinoma (ESCC), neoadjuvant therapy combined with surgery has become the standard treatment schedule. The application of immunotherapy, represented by programmed death-1 and programmed death-ligand 1 inhibitors, has injected new vitality into neoadjuvant therapy for ESCC. At present, a large number of clinical trials are being carried out and explored, which brings new challenges to the diagnosis of clinical pathologists. Combined with the latest researches at home and abroad and clinical diagnosis problems, the authors summarize the relevant problems and progress of pathological evaluation before and after neoadjuvant immunotherapy from the perspective of pathology, in order to improve the level of clinical pathological diagnosis and provide reference for further optimizing the comprehensive treat-ment strategy.

Objective:To investigate the value of immune inflammatory index in predic-ting the therapeutic efficacy of neoadjuvant chemoradiotherapy for esophageal squamous cell carci-noma (ESCC).Methods:The retrospective case-control study was conducted. The clinicopatholo-gical data of 163 patients with ESCC who were admitted to Zhongshan Hospital of Fudan University from December 2015 to December 2020 were collected. There were 135 males and 28 females, aged (62±8)years. All 163 patients underwent neoadjuvant chemoradiotherapy and radical resection for ESCC. Observation indicators: (1) relationship between immune inflammatory index and clinical characteristic in patients; (2) relationship between immune inflammatory index and efficacy of neoadjuvant chemoradiotherapy in patients; (3) influencing factor analysis for pathologic complete response and good response of tumor regression grade after neoadjuvant chemoradiotherapy; (4) efficiency of immune inflammatory index in predicting efficacy of neoadjuvant chemoradiotherapy. Measurement data with normal distribution were represented as Mean± SD. Count data were described as absolute numbers, and comparison between groups was conducted using chi-square test. Comparison of ordinal data was conducted using the rank sum test. The receiver operating characteristic (ROC) curve was used to determine the optimal cut-off value. Univariate and multi-variate analyses were conducted using the Logistic regression model. The area under the curve (AUC) of ROC curve was used to evaluate the efficiency of predictive model. Results:(1) Relationship between immune inflammatory index and clinical characteristic in patients. ① Optimal cut-off value of systemic immune-inflammation index (SII), neutrophil-lymphocyte ratio (NLR), platelet-lympho-cyte ratio (PLR). Results of ROC curve analysis showed that the AUC of SII, NLR, PLR in predicting efficacy of neoadjuvant chemoradiotherapy for patients with ESCC was 0.70(95% confidence interval as 0.61?0.77), 0.78(95% confidence interval as 0.69?0.84), 0.79(95% confidence interval as 0.70?0.85), respectively, with the maximum value of Youden index and the optimal cut-off value as 0.25, 0.32, 0.52 and 446×10 9/L, 2.09, 138. ② Relationship between SII, NLR, PLR and clinical charac-teristic in patients. According to the optimal cut-off value of SII, NLR, PLR, all 163 patients were divided into cases with SII <446×10 9/L as 99, cases with SII ≥446×10 9/L as 64, cases with NLR <2.09 as 107, cases with NLR ≥2.09 as 56, cases with PLR<138 as 88, cases with PLR ≥138 as 75, respectively. There was a significant difference in clinical N staging of tumor in patients with SII <446×10 9/L and SII ≥446×10 9/L ( P<0.05). There were significant differences in clinical N staging and clinical TNM staging of tumor in patients with NLR<2.09 and NLR≥2.09 ( P<0.05). (2) Relationship between immune inflammatory index and efficacy of neoadjuvant chemoradiotherapy in patients. Of 163 patients undergoing neoadjuvant chemoradiotherapy, there were 54 cases with pathologic complete response and 109 cases without pathologic complete response, 94 cases with good response of tumor regression grade and 69 cases with poor response of tumor regression grade. Of the 54 patients with pathologic complete response, cases with SII <446×10 9/L and SII ≥446×10 9/L, cases with NLR <2.09 and NLR ≥2.09, cases with PLR <138 and PLR ≥138 before neoadjuvant chemoradiotherapy were 42 and 12, 47 and 7, 48 and 6, respectively. The above indicators were 57 and 52, 60 and 49, 40 and 69 in the 109 cases without pathologic complete response. There were significant differences in the above indicators between patients with pathologic complete response and without pathologic complete response ( χ2=9.83, 16.39, 39.60, P<0.05). Of the 94 cases with good response of tumor regression grade, cases with SII <446×10 9/L and SII ≥446×10 9/L, cases with NLR <2.09 and NLR ≥2.09, cases with PLR <138 and PLR ≥138 before neoadjuvant chemoradiotherapy were 59 and 35, 78 and 16, 56 and 38, respectively. The above indicators were 40 and 29, 29 and 40, 32 and 37 in the 69 cases with poor response of tumor regression grade. There was no significant difference in the SII and PLR ( χ2=0.38, 2.79, P>0.05) and there was a significant difference in the NLR ( χ2=29.59, P<0.05) between patients with good response of tumor regression grade and poor response of tumor regre-ssion grade. (3) Influencing factor analysis for pathologic complete response and good response of tumor regression grade after neoadjuvant chemoradiotherapy. Results of multivariate analysis showed that PLR <138 before neoadjuvant chemoradiotherapy was an independent protective factor for pathologic complete response in ESCC patients undergoing neoadjuvant chemoradiotherapy ( odds ratio=1.98, 95% confidence interval as 1.56?2.51, P<0.05) and NLR <2.09 before neoadjuvant chemo-radiotherapy was an independent protective factor for good response of tumor regression grade ( odds ratio=2.50, 95% confidence interval as 1.40?4.46, P<0.05). (4) Efficiency of immune inflam-matory index in predicting efficacy of neoadjuvant chemoradio-therapy. The AUC of PLR <138 before neoadjuvant chemoradiotherapy in predicting pathologic complete response of ESCC patients undergoing neoadjuvant chemoradiotherapy was 0.79(95% confidence interval as 0.64?0.87, P<0.05), with the sensitivity, specificity and Youden index as 0.89, 0.63 and 0.52, respectively. The AUC of NLR <2.09 before neoadjuvant chemoradiotherapy in predic-ting good response of tumor regression grade of ESCC patients undergoing neoadjuvant chemoradio-therapy was 0.76 (95% confidence interval as 0.64?0.81, P<0.05), with the sensitivity, specificity and Youden index as 0.83, 0.58 and 0.41, respectively. Conclusion:The PLR<138 and NLR <2.09 before neoadjuvant chemoradiotherapy are independent protective factors for the pathologic complete response and good response of tumor regression grade, respectively, of ESCC patients undergoing neoadjuvant chemoradiotherapy, and both of them can predict the curative effect of neoadjuvant chemoradiotherapy well.

Resection is one of the most important treatments for esophageal squamous cell carcinoma, and routine postoperative follow-up is an effective method for early detection and treatment of recurrent metastases, which can improve patients' quality of life and prognosis. This consensus aims to provide a reference for colleagues responsible for postoperative follow-up of esophageal squamous cell carcinoma patients in China, and further improve the standardization of the diagnosis and treatment of esophageal squamous cell carcinoma.

Blast injury of the chest injury is the most common wound in modern war trauma and terrorist attacks, and is also the most fatal type of whole body explosion injury. Most patients with severe blast injury of the chest die in the early stage before hospitalization or during transportation, so first aid is critically important. At present, there exist widespread problems such as non-standard treatment and large difference in curative effect, while there lacks clinical treatment standards for blast injury of the chest. According to the principles of scientificity, practicality and advancement, the Trauma Society of Chinese Medical Association has formulated the guidance of classification, pre-hospital first aid, in-hospital treatment and major injury management strategies for blast injury of the chest, aiming to provide reference for clinical diagnosis and treatment.