Recent research from the International Agency for Research on Cancer (IARC) of the World Health Organization (WHO) indicates that breast cancer is the most prevalent malignant tumor among women, posing a significant threat to women's health. Surgery remains the primary therapeutic modality for breast cancer. Recently, endoscopic and robotic breast surgical techniques have gained acceptance among both surgeons and patients. However, considerable variation exists in surgical approaches and outcomes. To standardize these techniques, facilitate their broader clinical adoption, and ultimately improve patient care, the Endoscopic-robotic Breast Surgery Clinical Trials Consortium (ErBSCTC) of China has developed this guideline. This document encompasses the technologies and instrumentation utilized in endoscopic and robotic breast surgery, surgical techniques, perioperative management, complication handling, long-term follow-up, and oncologic outcomes, aiming to provide evidence-based guidance for healthcare professionals involved in the prevention, diagnosis, and treatment of breast diseases.

Breast cancer is the most common malignant tumor among women in China, with surgery being one of the primary treatment modalities. Endoscopic/robotic breast surgery (ErBS) is gaining widespread acceptance among patients and surgeons alike due to its advantages of minimal invasiveness, superior cosmetic outcomes, and accelerated recovery. However, substantial heterogeneity currently exists across China regarding patient selection, standardized operative techniques, perioperative management, and complication handling, underscoring the urgent need for evidence-based consensus guidelines. To promote standardization and ensure consistent quality of ErBS, the Chinese Endoscopic-Robotic Breast Surgery Clinical Trials Consortium (CErBSCTC) has systematically reviewed the latest high-quality evidence and formulated the "Protocol for China Endoscopic and Robotic Breast Surgery Guidelines (2026 edition)", which outlines a comprehensive methodology for guideline development.

This guideline, presented in three parts, details the core aspects of endoscopic/robotic breast surgery, including its techniques, equipment, surgical procedures, perioperative management, complication treatment, long-term follow-up, and outcomes. Part one offered a comprehensive overview of indications for endoscopic and robotic breast surgery, intraoperative techniques, surgical instrument choices, and common endoscopic and robotic breast reconstruction procedures. This part will cover other endoscopic breast procedures beyond immediate breast reconstruction and include perioperative management strategies, to provide healthcare professionals involved in endoscopic and robotic breast surgery with systematic operational guidelines and clinical decision-making references.

With the continuous advancements in immunotherapy and targeted therapy, the treatment management and surgical resection assessment of locally advanced lung cancer have undergone significant changes. In October 2024, the Society of Thoracic Surgeons (STS) released the "STS expert consensus on the multidisciplinary management and resectability of locally advanced non-small cell lung cancer", which provides the latest insights on the evaluation of resectability and multidisciplinary management of locally advanced lung cancer, neoadjuvant (including perioperative) therapy, and adjuvant therapy. This article aims to interpret this consensus, with the goal of introducing the latest perspectives of the STS consensus to thoracic surgeons and providing a reference for the rational implementation of surgical resection, multidisciplinary management, and standardized comprehensive treatment models for non-small cell lung cancer in China.

Objective To explore the clinical and aesthetic results of single axillary approach reverse sequence endoscopic nipple-sparing mastectomy of breast cancer combined with subpectoral implant-based breast reconstruction (IBBR) for breast cancer patients. Methods The clinical data of consecutive female patients who underwent single axillary approach reverse sequence endoscopic nipple-sparing mastectomy of breast cancer combined with subpectoral IBBR from May 2020 to December 2022 were retrospectively analyzed. The patient demographics, perioperative parameters, complications and aesthetic results were collected. Results A total of 62 patients (74 breasts) were included. The mean age of patients was (39.0±7.8) years. The total mean operation time was (185.2±45.5) minutes. Five (8.1%) patients suffered from surgical complications. Two (3.2%) patients experienced major complications, and 3 (4.8%) suffered from minor complications. No patient experienced partial nipple-areola complex necrosis. Seventeen (27.4%) patients experienced implant related complications, of which 11 (17.7%) experienced capsular contracture. During a median follow-up time of 30 months ranging from 11 to 42 months, no patient experienced locoregional recurrence, distant metastasis or death. Thirty-seven (88.1%) patients evaluated their breasts as good or excellent. In the surgeon-reported cosmetic results, 40 (95.2%) patients achieved excellent or good results. Conclusion This surgical technique is characterized by minimal trauma, short operation time, high safety, and excellent cosmetic outcomes for patients with small breasts and mild ptosis, making it worthy of further promotion.

Objective To explore the feasibility and safety of using indocyanine green combined with autologous blood and methylene blue for localization of small lung nodules during thoracoscopic wedge resection. Methods Patients who underwent CT-guided percutaneous lung puncture injection of localization agents to locate lung nodules at the First Affiliated Hospital of Fujian Medical University from November 2023 to January 2024 were selected. Under thoracoscopy, lung nodules were located by white light mode, fluorescence mode, or near-infrared mode and wedge resection was performed. The feasibility of using indocyanine green combined with autologous blood and methylene blue for localization of small lung nodules was preliminarily verified by evaluating whether the localization agent concentrated around the nodules, and the safety of this method was verified by analyzing the incidence of adverse reactions during patient puncture and surgery. Results A total of 30 patients with lung nodules were included, including 10 males and 20 females, with an average age of (55.5±11.2) years. In 26 patients, the amount of localization agent used was moderate, the localization agent concentrated around the nodules, and successful precise localization of small lung nodules was achieved. In 4 patients, due to excessive use of localization agent, the marker was diffuse with pleural staining. The overall localization success rate was 86.7%, and when the injection volume of localization agent was 0.2-0.5 mL, the localization success rate was 100.0%. All patients successfully completed thoracoscopic wedge resection and found nodule lesions, with negative margins and a distance from the margin to the lesion that met the requirements. There were no complications. Conclusion Thoracoscopic surgery using indocyanine green combined with autologous blood and methylene blue for localization of small lung nodules is safe and feasible.

Pathological diagnosis is the gold standard for confirming breast cancer. Traditional manual pathological diagnosis methods for breast cancer are time-consuming, labor-intensive, highly subjective, and exhibit poor diagnostic consistency. In recent years, artificial intelligence (AI) technology has rapidly advanced and is progressively being applied clinically as a promising early diagnostic tool. However, many existing AI models lack interpretability, which limits the trustworthiness of their clinical application. Khater et al, by combining a high-precision machine learning model with an explainable AI model, achieved highly accurate breast tumor diagnosis and provided explanations for key biological and pathological features influencing the diagnostic results. This points the way for the future application and development of AI in medical diagnosis and treatment. The article interprets the main content of that study, and analyzes the advantages and limitations of AI in medical diagnosis and treatment, with the aim of promoting its better application in clinical practice.

Objective To investigate the prognosis and satisfaction of the R2 intervention procedure and develop related predictive models. Methods The clinical data of 64 patients with primary craniofacial hyperhidrosis who underwent R2 intervention surgery at the First Affiliated Hospital of Fujian Medical University from November 2018 to October 2022 were retrospectively analyzed. By statistically analyzing the risk factors for compensatory hyperhidrosis (CH) and satisfaction, and conducting feature screening, a relevant prediction model was established. Results Finally, 51 patients were collected, including 43 (84.3%) males and 8 (15.7%) females, with an average age of (30.27±7.22) years. Overall postoperative satisfaction was high, with only 5.9% of patients expressing regret about the surgery. However, 92.2% of patients experienced CH. The onset of postoperative CH was most prominent within the first 3 months postoperatively, with the incidence rate stabilizing thereafter. Preoperative heart rate and R2 sympathetic nerve clipping were identified as independent risk factors for severe CH. The preoperative body mass index, the degree of sweating in the chest and abdomen, are significantly correlated with postoperative satisfaction. Conclusion The R2 intervention surgery effectively alleviates the symptoms of primary craniofacial hyperhidrosis, and patient satisfaction is high.

Breast cancer is one of the most common malignant tumors in women, and its treatment and management strategies are crucial for improving patients’ prognosis and quality of life. Early breast cancer refers to lesions confined to the breast and regional lymph nodes (N1 stage) without distant metastasis. Thanks to the improvement of screening techniques, the detection rate of early breast cancer has increased. The “early diagnosis and early treatment” model has led to a decrease in breast cancer mortality, especially among young women. The 2024 European Society for Medical Oncology (ESMO) clinical practice guideline for the diagnosis, treatment, and follow-up of early breast cancer aims to provide comprehensive and standardized recommendations for the diagnosis and treatment of early breast cancer, helping clinicians make optimal decisions. This article interprets the main content of the guideline in order to provide references and assistance for the current clinical diagnosis and treatment of early breast cancer in China.

In order to realize the quantitative assessment of muscle strength in hand function rehabilitation and then formulate scientific and effective rehabilitation training strategies, this paper constructs a multi-scale convolutional neural network (MSCNN) - convolutional block attention module (CBAM) - bidirectional long short-term memory network (BiLSTM) muscle strength prediction model to fully explore the spatial and temporal features of the data and simultaneously suppress useless features, and finally achieve the improvement of the accuracy of the muscle strength prediction model. To verify the effectiveness of the model proposed in this paper, the model in this paper is compared with traditional models such as support vector machine (SVM), random forest (RF), convolutional neural network (CNN), CNN - squeeze excitation network (SENet), MSCNN-CBAM and MSCNN-BiLSTM, and the effect of muscle strength prediction by each model is investigated when the hand force application changes from 40% of the maximum voluntary contraction force (MVC) to 60% of the MVC. The research results show that as the hand force application increases, the effect of the muscle strength prediction model becomes worse. Then the ablation experiment is used to analyze the influence degree of each module on the muscle strength prediction result, and it is found that the CBAM module plays a key role in the model. Therefore, by using the model in this article, the accuracy of muscle strength prediction can be effectively improved, and the characteristics and laws of hand muscle activities can be deeply understood, providing assistance for further exploring the mechanism of hand functions .
Neural Networks, Computer ; Humans ; Hand Strength/physiology* ; Support Vector Machine ; Muscle Strength/physiology* ; Hand/physiology* ; Convolutional Neural Networks