Gland surgery最新文献

{"title":"SEER-based machine learning prediction of bone metastasis in breast cancer: model development and validation.","authors":"Ying Gao, Lei Liu, Shoujun Wang, Weijie Tao, Jinmiao Wang, Ran Duan, Hai Xie, Hideaki Takahashi, Jie Hao, Ming Gao","doi":"10.21037/gs-2025-168","DOIUrl":"10.21037/gs-2025-168","url":null,"abstract":"<p><strong>Background: </strong>Breast cancer (BC) is the leading cancer in women. It often metastasizes to bone, worsening the prognosis. Diagnostic methods often fail to predict bone metastasis (BM). This study developed a machine learning (ML) model using the Surveillance, Epidemiology, and End Results (SEER) database for BM prediction, to refine treatments and improve outcomes.</p><p><strong>Methods: </strong>Using SEER data, we studied 24,584 BC patients diagnosed 2010-2015 with radiologically confirmed BM. Tumor size, grade, tumor (T)/node (N) stages, and estrogen receptor (ER)/progesterone receptor (PR)/human epidermal growth factor receptor 2 (HER2) status were assessed. Stratified randomization divided the data into 70% training (n=18,438) and 30% validation (n=6,146). Six ML algorithms were developed, emphasizing random forest (RF). Receiver operating characteristic (ROC) curve analysis [area under the curve (AUC), sensitivity, specificity, negative predictive value (NPV)] assessed performance. The SHapley Additive exPlanations (SHAP) framework identified key BM predictors.</p><p><strong>Results: </strong>Our analysis of 24,584 patients identified 1,298 (5.26%) patients with BM. Logistic regression (LR) provided the highest specificity [0.897, 95% confidence interval (CI): 0.889-0.905], contrasting with gradient boosting machine (GBM)'s maximal sensitivity (0.658, 95% CI: 0.609-0.707). With sensitivity at 0.658, better algorithms or multimodal methods are needed for case identification. The multilayer perceptron neural network (MLPNN) model demonstrated superior performance, with the highest AUC of 0.808 (95% CI: 0.798-0.818), surpassing the LR and adaptive boosting (AdaBoost) models, both with AUCs of 0.803 (95% CI: 0.793-0.813). The RF model was particularly adept at ruling out BM, with an NPV above 97%. The SHAP analysis identified tumor size, grade, T/N stages, ER/PR/HER2 status, and brain/liver/lung metastases as key predictors for risk stratification. Decision curve analysis showed RF's superior utility over the American Joint Committee on Cancer (AJCC) Staging System.</p><p><strong>Conclusions: </strong>Our ML model demonstrates potential for predicting BM in patients with BC. It may serve as a clinical aid to identify at-risk individuals early. However, moderate sensitivity requires refinement for better case detection. This study supports integrating ML into clinical practice, advancing personalized oncology medicine.</p>","PeriodicalId":12760,"journal":{"name":"Gland surgery","volume":"14 7","pages":"1366-1378"},"PeriodicalIF":1.6,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12322768/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144794293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The value of multiparametric MRI-based combined intratumoral and peritumoral radiomics in differentiating luminal and non-luminal molecular subtypes of breast cancer: a multicenter study.","authors":"Mingtai Cao, Xinyi Liu, Airu Yang, Yuan Xu, Qian Zhang, Yuntai Cao","doi":"10.21037/gs-2025-83","DOIUrl":"10.21037/gs-2025-83","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Breast cancer remains the predominant contributor to global cancer-related morbidity and mortality in women. Luminal subtypes, accounting for approximately 70% of cases, demonstrate favorable prognoses through endocrine-targeted therapeutic regimens owing to hormone receptor positivity. Conversely, non-luminal breast cancer variants, including human epidermal growth factor receptor 2 (HER2)-enriched and triple-negative subtypes, exhibit aggressive biological characteristics, intrinsic endocrine therapy resistance, and require molecularly guided therapeutic strategies such as HER2-directed biologicals, platinum-based cytotoxic regimens, or radiation therapy. This study aims to evaluate whether preoperative multiparametric magnetic resonance imaging (MRI)-based intratumoral and peritumoral radiomics can effectively discriminate between luminal and non-luminal breast cancer subtypes.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;This retrospective study analyzed 305 female breast cancer patients. Center 1 (Affiliated Hospital of Qinghai University) was randomly split into a training set (n=140) and an internal test set (n=59) in a 7:3 ratio, while Center 2 (Second Hospital of Lanzhou University) (n=67) and Center 3 (The Cancer Imaging Archive I-SPY1 trial) (n=39) served as external test sets 1 and 2, respectively. Tumor subtypes were classified as luminal or non-luminal based on estrogen receptor (ER) and progesterone receptor (PR) status. Two radiologists performed manual tumor segmentation using 3D Slicer on multiparametric MRI sequences: dynamic contrast enhancement (DCE; phases 3 or 4), fat-suppressed T2-weighted imaging (T2WI), and diffusion-weighted imaging (DWI). Peritumoral regions were defined by a 3 mm expansion from the tumor volume of interest (VOI). For each sequence (intratumoral and peritumoral), 2,252 radiomics features were extracted using PyRadiomics. After Z-score normalization, features were selected through univariate analysis, correlation analysis, and simulated annealing. Eight radiomics models were constructed using random forest (RF), including intratumoral-only, combined intratumoral-peritumoral (3 mm), and multisequence fusion models. Performance was assessed using area under the curve (AUC), calibration curves, and decision curve analysis (DCA).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;After feature selection, eight optimal radiomics features were used for model development. The combined DWI_Peri3 + T2WI_Peri3 + DCE_Peri3 RF model demonstrated superior performance, with AUCs of 0.819 [95% confidence interval (CI): 0.748-0.889], 0.795 (95% CI: 0.676-0.915), and 0.771 (95% CI: 0.640-0.902) in training, internal validation, and external validation set 1, respectively. Among single-parameter models, T2WI_Peri3 RF showed the best classification performance (AUC =0.774, 95% CI: 0.698-0.849) for luminal &lt;i&gt;vs.&lt;/i&gt; non-luminal differentiation.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;The model constructed based on multiparame","PeriodicalId":12760,"journal":{"name":"Gland surgery","volume":"14 7","pages":"1195-1212"},"PeriodicalIF":1.6,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12322763/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144794297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Selective elimination of surgery for early invasive breast cancer: promise, challenges, and prospects.","authors":"Janhavi Venkataraman, Kefah Mokbel","doi":"10.21037/gs-2025-191","DOIUrl":"10.21037/gs-2025-191","url":null,"abstract":"","PeriodicalId":12760,"journal":{"name":"Gland surgery","volume":"14 7","pages":"1187-1190"},"PeriodicalIF":1.6,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12322750/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144794294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The application of augmented reality technology in endoscopic pituitary adenoma surgery via nasal approach.","authors":"Jian Zhang, Zhongjie Shi, Yin Kang, Bin Wu, Xiyao Liu, Hongwei Zhu","doi":"10.21037/gs-2025-95","DOIUrl":"10.21037/gs-2025-95","url":null,"abstract":"<p><strong>Background: </strong>In recent years, neuroendoscopy has mostly replaced the microscope for transnasal pituitary adenoma (PA) surgery, where identifying cranial base anatomical landmarks is crucial. Although neuronavigation systems are commonly used in endoscopic procedures to offer locational data, traditional ones are costly, complex to operate, and need surgical pauses for two-dimensional (2D) imaging to verify positions. This makes them hard for resource-limited primary hospitals to use. Augmented reality (AR) technology, integrating three-dimensional (3D) imaging with the intraoperative endoscopic view, overcomes these drawbacks and could be a key advance in next-generation surgical navigation. This study aimed to develop and evaluate an endoscopy-AR system for localizing PAs and adjacent critical structures, assessing its practicality and accuracy in anatomical models and clinical cases to determine its efficacy in transnasal neuroendoscopic PA surgery.</p><p><strong>Methods: </strong>Using 3D-Slicer software, we performed 3D reconstructions of key anatomical structures, including the sphenoid sinus, PA, internal carotid arteries, and optic nerves. The 3D models were integrated into the endoscopic view via a custom-developed personal computer (PC) software module, \"Vrendo\". After verifying registration accuracy using five 3D-printed skull models, the technology was applied in seven clinical surgeries for transnasal PA removal, with postoperative complications and outcomes recorded.</p><p><strong>Results: </strong>The AR system provided precise localization of the optic nerves, bilateral internal carotid arteries, and tumor before opening the sellar floor, significantly improving intraoperative orientation. The average target registration error (TRE) was 2.23±0.57 mm in the 3D-printed models.</p><p><strong>Conclusions: </strong>The integration of AR-based 3D imaging with the endoscopic perspective allows for precise localization of deep-seated anatomical structures. This novel approach to intraoperative navigation reduces the need for visual and cognitive transitions between the navigation and endoscope monitors, potentially enhancing surgical safety and efficiency while improving surgeon comfort.</p>","PeriodicalId":12760,"journal":{"name":"Gland surgery","volume":"14 7","pages":"1318-1335"},"PeriodicalIF":1.6,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12322755/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144794296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A predictive model using platelets and neutrophil-to-lymphocyte ratio for the number of lymph node metastases in papillary thyroid carcinoma: a retrospective analysis.","authors":"Mengqian Ge, Yuying Chen, Fan Wu, Dingcun Luo","doi":"10.21037/gs-2025-119","DOIUrl":"10.21037/gs-2025-119","url":null,"abstract":"<p><strong>Background: </strong>Large number lymph node metastases (LNLNMs) in papillary thyroid carcinoma (PTC) significantly increase recurrence risk, yet preoperative prediction remains challenging. This study aimed to develop a predictive model integrating blood inflammatory markers and clinical features to identify patients with high-risk LNLNM.</p><p><strong>Methods: </strong>A retrospective cohort of 731 patients with PTC who underwent thyroid surgery at Hangzhou First People's Hospital between September 2021 and October 2022 was included. These patients were divided into a model group (n=513) and a validation group (n=218) at a 7:3 ratio. Analyzed variables included age, gender, absolute values of neutrophils (N), monocytes (M), platelets (Plt), and lymphocytes (L), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), systemic immune-inflammatory index (SII), and tumor diameter and multifocality. Independent risk factors for LNLNM were identified through univariate and multivariate logistic regression analyses, and a risk prediction model was subsequently constructed. Model performance was assessed via receiver operating characteristic (ROC) curves, the Hosmer-Lemeshow (HL) test, calibration curves, and decision curve analysis (DCA).</p><p><strong>Results: </strong>Age, tumor diameter, Plt, and NLR were identified as independent risk factors for LNLNM in patients with PTC. A predictive model was developed to evaluate the risk of LNLNM, with an area under the curve (AUC) of 0.827 (95% CI: 0.784-0.870; P<0.001) and the specificity and sensitivity were both 75.8%. The AUC of the validation group was 0.824 (95% CI: 0.757-0.890; P<0.001), with a specificity of 79.5% and a sensitivity of 76.9%. Furthermore, the model demonstrated good calibration in the HL test and favorable diagnostic value in calibration curve analysis and DCA.</p><p><strong>Conclusions: </strong>Age, tumor diameter, Plt count, and NLR count are high-risk factors for LNLNM in patients with PTC, and the predictive model established in combination with the above factors could effectively predict the occurrence of LNLNMs in PTC. This study provides support for surgeons in accurately predicting the possibility of LNLNMs and developing personalized treatment plans before surgery.</p>","PeriodicalId":12760,"journal":{"name":"Gland surgery","volume":"14 7","pages":"1283-1294"},"PeriodicalIF":1.6,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12322758/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144794268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advancing perioperative care: introducing patient-centered comfort management.","authors":"Jun Wang, Zhiwei Xu, Fen Chen, Xiaoyan Wei, Baiyong Shen, Xiaxing Deng","doi":"10.21037/gs-2025-79","DOIUrl":"10.21037/gs-2025-79","url":null,"abstract":"<p><p>The perioperative patient-centered comfort management (2P2CM) model introduces a transformative approach to surgical care, prioritizing patient comfort, psychological well-being, and satisfaction across the perioperative continuum. Unlike traditional models that focus primarily on clinical outcomes, the 2P2CM model emphasizes a holistic framework that integrates preoperative, intraoperative, and postoperative interventions tailored to individual patient needs. This review synthesizes the emerging evidence supporting the 2P2CM model, which aims to alleviate preoperative anxiety, optimize postoperative pain management, and tailor care to individual patient needs. The model integrates contributions from multiple disciplines, leveraging multimodal analgesia, personalized pain management strategies, and nonpharmacological interventions to enhance patient outcomes and reduce reliance on opioids. A key strength of the 2P2CM model lies in its interdisciplinary approach, incorporating insights from anesthesiology, nursing, psychology, and physical therapy to enhance recovery and minimize opioid dependence. By emphasizing shared decision-making and patient-reported outcomes, the 2P2CM model addresses the holistic needs of surgical patients, from preoperative anxiety to postoperative recovery. The review highlights the potential of this model to improve patient satisfaction, reduce postoperative complications, and establish a new standard for patient-centered perioperative care. Future research is necessary to further refine the components of the 2P2CM model and assess its long-term efficacy across a variety of surgical contexts.</p>","PeriodicalId":12760,"journal":{"name":"Gland surgery","volume":"14 7","pages":"1390-1398"},"PeriodicalIF":1.6,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12322764/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144794269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Axillary dissection should not be performed in breast cancer patients with limited nodal disease to determine abemaciclib candidacy.","authors":"Brenton Halsey, Elizabeth McAuley Fish, Walker Lyons, Melissa McShane, Austin D Williams","doi":"10.21037/gs-2025-178","DOIUrl":"10.21037/gs-2025-178","url":null,"abstract":"","PeriodicalId":12760,"journal":{"name":"Gland surgery","volume":"14 7","pages":"1183-1186"},"PeriodicalIF":1.6,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12322772/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144794270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of a new developed robotic system for head and neck surgery: a prospective study.","authors":"Zhongkai Ma, Zhiyong Guo, Chang Cao, Jialu He, Su Chen, Hui Xia, Chunjie Li, Guiquan Zhu","doi":"10.21037/gs-2025-149","DOIUrl":"10.21037/gs-2025-149","url":null,"abstract":"<p><strong>Background: </strong>Robotic surgery has been a revolution for head and neck tumor patients, with the da Vinci system predominating these procedures. This study aims to evaluate the feasibility, safety, and effectiveness of a newly developed robotic system (KangDuo Surgical Robot-1500, KD-SR-1500) for robotic-assisted parotidectomy and submandibular gland (SMG) resection.</p><p><strong>Methods: </strong>This prospective, single-arm clinical study was conducted from November 2023 to January 2024 at the West China Hospital of Stomatology, Sichuan University. All operations were performed using the KD-SR-1500 via a trans-hairline approach by one experienced surgeon. Demographic, perioperative, and follow-up data were prospectively collected. To further assess the safety and feasibility of the KD-SR-1500 for parotidectomy, we included a historical control group of patients who underwent endoscopic parotidectomy (EP) at the same institution between 2021 and 2023.</p><p><strong>Results: </strong>A total of 13 patients underwent parotidectomy and three underwent SMG resection in this prospective study. No cases were converted to endoscopic or open surgery. All robotic procedures were completed successfully, without significant complications observed. None of the 16 patients suffered from facial nerve injury. After propensity score matching, nine patients who underwent robotic parotidectomy (RP) and 28 patients who underwent EP were included. The operation time was not significantly different between the two groups. The RP group demonstrated excellent bleeding control, with an average blood loss of 10.00 mL compared to 47.86 mL in the EP group. Additionally, the robotic group showed superior facial nerve preservation, with no temporary nerve injuries reported, compared to 15 cases in the endoscopic group.</p><p><strong>Conclusions: </strong>The KD-SR-1500 system has been proven to be a feasible, safe, and effective tool for performing parotidectomy and SMG resection, supporting its utility in robotic-assisted head and neck surgery.</p>","PeriodicalId":12760,"journal":{"name":"Gland surgery","volume":"14 7","pages":"1250-1262"},"PeriodicalIF":1.6,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12322771/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144794273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A narrative review on innovations of thyroid nodule ultrasound diagnosis: applications of robot and artificial intelligence technology.","authors":"Yang Li, Jiaojiao Ma, Tongtong Zhou, Zhe Sun, Liangkai Wang, Xuejiao Yu, Zijian Xu, Yong Cheng, Bo Zhang","doi":"10.21037/gs-2025-75","DOIUrl":"10.21037/gs-2025-75","url":null,"abstract":"<p><strong>Background and objective: </strong>As the detection rate of thyroid nodules increases year by year, traditional ultrasonic diagnostic methods face challenges such as inefficiency and high dependence on physician experience. This paper focuses on the research status, advantages and challenges of robot automatic scanning and intelligent diagnosis system.</p><p><strong>Methods: </strong>We systematically retrieved the PubMed and Web of Science databases, screened and integrated relevant articles, and conducted a systematic analysis and summary of the existing research.</p><p><strong>Key content and findings: </strong>The development of robot and artificial intelligence (AI) provides a new method for efficient and accurate ultrasound diagnosis of thyroid nodules. Robot enables automated scanning of thyroid through precise robotic arm control, positioning, and trajectory planning, significantly improving the standardization and repeatability of the diagnostic process. However, its flexibility in clinical application and patient acceptance still needs to be further improved. From the early rule matching research based on manual features to the automatic feature processing of thyroid nodules using deep learning algorithms have made AI outstanding in the ultrasound diagnosis of thyroid nodules. Meanwhile, the innovative research of deep learning in the contrast-enhanced ultrasound (CEUS) video analysis has broadened the application of intelligent diagnosis systems. The interpretability of the deep learning models is solved to some extent by Gradient-weighted Class Activation Mapping (Grad-CAM) and other techniques. However, the interpretability, data dependence, and ability to generalize deep learning models in clinical practice remain key issues to be addressed.</p><p><strong>Conclusions: </strong>Robots and AI have brought revolutionary progress to the diagnosis of thyroid diseases, but their clinical translational application still faces many challenges.</p>","PeriodicalId":12760,"journal":{"name":"Gland surgery","volume":"14 7","pages":"1379-1389"},"PeriodicalIF":1.6,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12322769/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144794267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Minimally invasive pancreatoduodenectomy: caution is warranted.","authors":"Werner Hartwig","doi":"10.21037/gs-2025-150","DOIUrl":"10.21037/gs-2025-150","url":null,"abstract":"","PeriodicalId":12760,"journal":{"name":"Gland surgery","volume":"14 7","pages":"1174-1177"},"PeriodicalIF":1.6,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12322761/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144794279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}