Gland surgery最新文献

{"title":"Intraoperative parathyroid gland recognition prediction model and key feature analysis based on white light images.","authors":"Zufei Li, Xiaoming Cao, Junwei Huang","doi":"10.21037/gs-2024-522","DOIUrl":"https://doi.org/10.21037/gs-2024-522","url":null,"abstract":"<p><strong>Background: </strong>Timely identification and protection of the parathyroid glands during thyroid surgery are important. This study aims to explore a convenient, efficient, and inexpensive method for identifying parathyroid glands during surgery by extracting subtle texture features that cannot be recognized by the naked eye from white light images.</p><p><strong>Methods: </strong>In total, 117 confirmed parathyroid gland photos and 169 oval tissue photos of non-parathyroid glands, such as suspected parathyroid gland fat granules and lymph nodes, were collected. All the photos were subjected to color channel conversion, a region of interest (ROI) was drawn, and seven major types of texture features were extracted for each color channel using the PyRadiomics package. The least absolute shrinkage and selection operator (LASSO) algorithm was used to screen key features, and multiple machine learning algorithms were used to establish a prediction model on the basis of the above texture features. The SHapley Additive exPlanations (SHAP) algorithm was applied for key feature analysis.</p><p><strong>Results: </strong>A parathyroid gland prediction model based on white light texture features was successfully established, with the best performance achieved using the random forest (RF) algorithm. The accuracy, specificity, sensitivity, and area under the receiver operating characteristic (ROC) curve were 89.6%, 85.7%, 91.8%, 88.7%, and 77.5%, respectively. The SHAP algorithm revealed several key texture features of the parathyroid gland.</p><p><strong>Conclusions: </strong>This study is the first to establish and validate a convenient and economical intraoperative parathyroid gland identification model, which has potential clinical application value.</p>","PeriodicalId":12760,"journal":{"name":"Gland surgery","volume":"14 3","pages":"335-343"},"PeriodicalIF":1.5,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12004293/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143987513","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":"Neoadjuvant treatment and premastectomy radiotherapy: oncological and surgical outcomes.","authors":"Marie Bannier, Monique Cohen, Agnès Tallet, Alexandre de Nonneville, Gilles Houvenaeghel","doi":"10.21037/gs-2024-514","DOIUrl":"https://doi.org/10.21037/gs-2024-514","url":null,"abstract":"","PeriodicalId":12760,"journal":{"name":"Gland surgery","volume":"14 3","pages":"276-280"},"PeriodicalIF":1.5,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12004324/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143998377","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":"Clinical characteristics and prognostic factors analysis of patients stricken with double primary breast and ovarian cancer based on the SEER database.","authors":"Lu Wang, Xiaowei Liu, Zijing Lin, Zhesi Xiao, Jia Ming","doi":"10.21037/gs-24-480","DOIUrl":"https://doi.org/10.21037/gs-24-480","url":null,"abstract":"<p><strong>Background: </strong>Dual primary breast cancer (BC) and ovarian cancer (OC) represent a distinct subset of patients with diverse survival situation compared to those with a single primary BC or OC. Nonetheless, comprehensive research on their clinical characteristics and prognosis is lacking. This study conducted a retrospective analysis of clinical characteristics, survival outcomes, and prognostic factors of dual primary BC and OC patients.</p><p><strong>Methods: </strong>We applied the National Cancer Institute Surveillance, Epidemiology, and End Results (SEER) database to identify patients with dual primary BC and primary OC (DPBOC) from 2000 to 2019, and divided patients into two groups: the BC-first group (BO group) and the OC-first group (OB group). Moreover, we employed Kaplan-Meier method to assess overall survival (OS), breast cancer-specific survival (BCSS), and ovarian cancer-specific survival (OCSS), and the Cox proportional hazards model to analyze prognostic factors.</p><p><strong>Results: </strong>There were 1,074 patients enrolled, 665 in the BO group and 409 in the OB group. The median time interval was for 48 (range, 0-228) months. There were significant differences in serous carcinoma and OC tumor stage between the two groups (P<0.001; P<0.001). There was no significant difference in BCSS between the two groups (Log-rank P=0.67), but the BO group had inferior OS and OCSS than the OB group (Log-rank P<0.001). Patients with an interval of ≥48 months had a significantly lower risk of death [hazard ratio (HR) =0.323, 95% confidence interval (CI): 0.264-0.395, P<0.001; HR =0.527, 95% CI: 0.305-0.908, P=0.02; HR =0.709, 95% CI: 0.560-0.897, P=0.004].</p><p><strong>Conclusions: </strong>OC primarily determines the survival outcomes of DPBOC. Patients with BC as the first primary cancer (FPC) have a worse prognosis than patients with OC as FPC. After a diagnosis of BC or OC, we should pay close attention to another site, particularly after BC diagnosis, and monitor screening for ovarian lesions as early as feasible, as well as strengthening the treatment for OC.</p>","PeriodicalId":12760,"journal":{"name":"Gland surgery","volume":"14 3","pages":"405-420"},"PeriodicalIF":1.5,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12004301/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143997835","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":"Striving for higher levels of evidence in sensory restoration in DIEP flap breast reconstruction.","authors":"Anne Huang, Ethan L Mackenzie, Min-Jeong Cho","doi":"10.21037/gs-2024-524","DOIUrl":"https://doi.org/10.21037/gs-2024-524","url":null,"abstract":"","PeriodicalId":12760,"journal":{"name":"Gland surgery","volume":"14 3","pages":"268-271"},"PeriodicalIF":1.5,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12004315/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143998534","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":"Analysis and prediction of contralateral central lymph node metastasis risk in unilateral papillary thyroid carcinoma with ipsilateral lateral cervical lymph node: a retrospective clinical study.","authors":"Linghui Dai, Lulu Zheng, Yixuan Li, Jiabo Qin, Wenxian Guan, Jianfeng Sang","doi":"10.21037/gs-24-473","DOIUrl":"https://doi.org/10.21037/gs-24-473","url":null,"abstract":"<p><strong>Background: </strong>Papillary thyroid carcinoma (PTC) often metastasizes to lymph nodes, increasing recurrence risk and reducing survival. This study identifies predictors for contralateral central lymph node metastasis (Cont-CLNM) in unilateral PTC patients with ipsilateral lateral cervical lymph node metastasis (Ipsi-LLNM).</p><p><strong>Methods: </strong>We retrospectively analyzed data, preoperative ultrasound features, and thyroglobulin (Tg) levels in unilateral PTC patients with Ipsi-LLNM treated at the Thyroid Surgery Department of Nanjing Drum Tower Hospital from August 2017 to August 2024. Least absolute shrinkage and selection operator (LASSO) regression was used for variable selection, with independent <i>t</i>-tests and Chi-squared tests assessing differences. Logistic regression analyses identified risk factors for Cont-CLNM, and a nomogram was validated using 1,000 bootstrap resamples. Decision curve analysis (DCA) evaluated clinical impact.</p><p><strong>Results: </strong>Of 105 PTC patients, 56 (53.3%) had Cont-CLNM. LASSO regression identified three predictors: male sex, lymph node metastasis posterior to the recurrent laryngeal nerve (LN-prRLN), and elevated Tg levels. Multivariate regression confirmed these variables' association with Cont-CLNM. Internal validation yielded an area under the curve of 0.771 [95% confidence interval (CI): 0.684-0.857]. A nomogram was developed and validated through DCA.</p><p><strong>Conclusions: </strong>Our findings indicate that combining male gender, LN-prRLN, and Tg levels effectively predicts Cont-CLNM, providing a basis for risk assessment in unilateral PTC.</p>","PeriodicalId":12760,"journal":{"name":"Gland surgery","volume":"14 3","pages":"380-390"},"PeriodicalIF":1.5,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12004314/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144005923","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":"Breast metastasis from small cell neuroendocrine carcinoma of the cervix: a rare case report.","authors":"Thitiporn Wannasri, Somboon Kittikongwat, Thanaisawan Plookphol, Sarun Lertsatittanakorn","doi":"10.21037/gs-2024-511","DOIUrl":"https://doi.org/10.21037/gs-2024-511","url":null,"abstract":"<p><strong>Background: </strong>Breast metastasis from small cell neuroendocrine carcinoma (SCNEC) of the cervix is an extremely rare condition with a poor prognosis. Metastatic SCNEC to the breast is difficult to differentiate from primary breast carcinoma on the basis of the clinical presentation alone.</p><p><strong>Case description: </strong>We report the case of a 23-year-old woman who was previously diagnosed with cervical cancer. She had undergone definitive concurrent chemoradiation treatment 1 year earlier and presented at this visit with left breast masses. Breast ultrasonography revealed two microlobulated hypoechoic masses with vascularity. Computed tomography revealed enlarged left supraclavicular lymph nodes, and multiple lung, skin, and peritoneal metastases. Core needle biopsies of the left breast masses indicated small cell tumors. Immunohistochemical staining revealed tumor cells diffusely positive for pan-cytokeratin (AE1/AE3), synaptophysin, chromogranin, paired-box gene 8, and p16. These were the same histological results as those for the previous cervical mass. Metastatic SCNEC from the cervix associated with human papillomavirus infection was diagnosed. We planned to initiate systemic chemotherapy; however, the patient's condition worsened rapidly, and chemotherapy was omitted. The patient died 2 months after the initiation of supportive care.</p><p><strong>Conclusions: </strong>This case adds to the knowledge of an extremely rare presentation of breast metastases from an extramammary malignancy, cervical SCNEC. It is important to differentiate between primary breast cancer metastasis and metastasis to the breast from other cancers because of the different therapeutic options.</p>","PeriodicalId":12760,"journal":{"name":"Gland surgery","volume":"14 3","pages":"563-569"},"PeriodicalIF":1.5,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12004317/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143963226","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":"Multifocal cancer is associated with better survival than solitary cancer in non-Hispanic White patients with thyroid carcinoma.","authors":"Yu Li, Da Huang, Jian Ding, Wei Mao, Dan Luo, Yuan Zhou, Baoxin Wang, Haiting Liang, Zhiqiang Wang, Pin Dong","doi":"10.21037/gs-2024-523","DOIUrl":"https://doi.org/10.21037/gs-2024-523","url":null,"abstract":"<p><strong>Background: </strong>Multifocal carcinoma is commonly reported in thyroid cancer. However, its impact on cancer survival is unclear. This study aims to evaluate whether multifocal disease is associated with better thyroid cancer outcomes in different ethnicities.</p><p><strong>Methods: </strong>Cancer registration data in the US from 2000 to 2016 were obtained via the Surveillance, Epidemiology, and End Results (SEER) 18 Registries database. Patients diagnosed with thyroid carcinoma and without other malignancies were enrolled. Univariable and multivariable Cox regressions were applied to evaluate the association of multifocal disease with cancer-specific survival (CSS) and overall survival (OS). Multivariable analyses were performed after adjusting for age, gender, stage, and treatment.</p><p><strong>Results: </strong>A total of 82,217, 8,551, 13,445, and 19,558 non-Hispanic White (NHW), non-Hispanic African American (AA), non-Hispanic Asian or Pacific Islander (AP), and Hispanic White (HW) patients were enrolled in this study, respectively. Univariable analysis suggested that multifocal carcinoma would have significant better CSS [hazard ratio (HR) =0.89, 95% confidence interval (CI): 0.77-1.02, P=0.09; adjusted HR =0.67, 95% CI: 0.53-0.85, P<0.001] and OS (HR =0.83, 95% CI: 0.77-0.90, P<0.001; adjusted HR =0.76, 95% CI: 0.65-0.87, P<0.001) than solitary disease in NHW.</p><p><strong>Conclusions: </strong>Multifocal thyroid carcinoma is associated with better CSS and OS than solitary cancer in NHW patients.</p>","PeriodicalId":12760,"journal":{"name":"Gland surgery","volume":"14 3","pages":"327-334"},"PeriodicalIF":1.5,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12004292/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144014447","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":"Roles of artificial intelligence and high frame-rate contrast-enhanced ultrasound in the differential diagnosis of Breast Imaging Reporting and Data System 4 breast nodules.","authors":"Ping Li, Ming Yin, Susanna Guerrini, Wenxiang Gao","doi":"10.21037/gs-24-187","DOIUrl":"https://doi.org/10.21037/gs-24-187","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Breast cancer prevalence and mortality are rising, emphasizing the need for early, accurate diagnosis. Contrast-enhanced ultrasound (CEUS) and artificial intelligence (AI) show promise in distinguishing benign from malignant breast nodules. We compared the diagnostic values of AI, high frame-rate CEUS (HiFR-CEUS), and their combination in Breast Imaging Reporting and Data System (BI-RADS) 4 nodules, using pathology as the gold standard.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;Patients with BI-RADS 4 breast nodules who were hospitalized at the Department of Thyroid and Breast Surgery, Taizhou People's Hospital from December 2021 to June 2022 were enrolled in the study.80 female patients (80 lesions) underwent preoperative AI and/or HiFR-CEUS. We assessed diagnostic outcomes of AI, HiFR-CEUS, and their combination, calculating sensitivity (SE), specificity (SP), accuracy (ACC), positive/negative predictive values (PPV/NPV). Reliability was compared using Kappa statistics, and AI-HiFR-CEUS correlation was analyzed with Pearson's test. Receiver operating characteristic curves were plotted to compare diagnostic accuracy of AI, HiFR-CEUS, and their combined approach in differentiating BI-RADS 4 lesions.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Of the 80 lesions, 18 were pathologically confirmed to be benign, while the remaining 62 were malignant. The SE, SP, ACC, PPV, and NPV were 75.81%, 94.44%, 80.00%, 97.92%, and 53.13% in the AI group, 74.20%, 94.44%, 78.75%, 97.91%, and 51.51% in the HiFR-CEUS group, and 98.39%, 88.89%, 96.25%, 96.83%, and 94.12% in the combination group, respectively. Thus, the SE, ACC, and NPV of the combination group were significantly higher than those of the AI and HiFR-CEUS groups, and the SP of the combination group was lower (all P&lt;0.05); however, no significant difference was found between the groups in terms of the PPV (P&gt;0.05). No statistically significant difference was observed in the diagnostic performance of the AI and HiFR-CEUS groups (all P&gt;0.05). The AI and HiFR-CEUS groups had moderate agreement with the \"gold standard\" (Kappa =0.551, Kappa =0.530, respectively), while the combination group had high agreement (Kappa =0.890). AI was positively correlated with HiFR-CEUS (r=0.249, P&lt;0.05). The area under the curves (AUCs) of AI, HiFR-CEUS, and both in combination were 0.851±0.039, 0.815±0.047, and 0.936±0.039, respectively. Thus, the AUC of the combination group was significantly higher than those of the AI and HiFR-CEUS groups (&lt;i&gt;Z1&lt;/i&gt;=2.207, &lt;i&gt;Z2&lt;/i&gt;=2.477, respectively, both P&lt;0.05). The AI group had a higher AUC than the HiFR-CEUS group, but the difference was not statistically significant (&lt;i&gt;Z3&lt;/i&gt;=0.554, P&gt;0.05).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Compared with AI alone or HiFR-CEUS alone, the combined use of these two methods had higher diagnostic performance in distinguishing between benign and malignant BI-RADS 4 breast nodules. Thus, our combination method could further improve the dia","PeriodicalId":12760,"journal":{"name":"Gland surgery","volume":"14 3","pages":"462-478"},"PeriodicalIF":1.5,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12004330/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144011379","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":"Development and validation of a semi-automatic radiomics ensemble model for preoperative evaluation of breast masses in mammotome-assisted minimally invasive resection.","authors":"Zhenfeng Huang, Qingqing Zhu, Yijie Li, Kunyi Wang, Yideng Zhang, Qiaowei Zhong, Yi Li, Qingan Zeng, Haihong Zhong","doi":"10.21037/gs-24-440","DOIUrl":"https://doi.org/10.21037/gs-24-440","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Accurate preoperative differentiation of breast masses is critical for guiding individualized treatment strategies in Mammotome-assisted minimally invasive resection. While radiomics shows promise, existing methods rely on manual delineation, which is time-consuming and subjective. This study developed an ultrasound-based semi-automatic segmentation ensemble model to improve preoperative assessment.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;We retrospectively analyzed preoperative ultrasound images from 773 patients (543 tumors, 230 non-tumors). Semi-automatic segmentation was performed using DeepLabv3_ResNet50 and fully convolutional network (FCN)_ResNet50. Radiomic and deep transfer learning (DTL) features were extracted to construct radiomic, deep learning, and combined models. An ensemble strategy integrated these with clinical models. Performance was evaluated via receiver operating characteristic (ROC) curves and decision curve analysis (DCA).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;The cohort included 543 tumor patients and 230 non-tumor patients (95 adenosis, 135 other benign lesions). The semi-automatic segmentation model, DeepLabv3_ResNet50, achieved a peak global accuracy of 99.4% and an average Dice coefficient of 92.0% at its best epoch. On the other hand, the FCN_ResNet50 model exhibited a peak global accuracy of 99.5% and an average Dice coefficient of 93.7% at its best epoch. In the task of predicting tumor and non-tumor patients, age, maximum diameter, and BI-RADS (Breast Imaging Reporting and Data System) classification were ultimately identified as key indicators, and the stacking model ultimately demonstrated an area under the curve (AUC) of 0.890 in the training cohort (with a sensitivity of 0.844 and a specificity of 0.815) and an AUC of 0.780 in the testing cohort (with a sensitivity of 0.713 and a specificity of 0.739). In the task of predicting adenosis and other lesion types, focus emerged as a crucial factor, and the stacking model achieved an AUC of 0.813 in the training cohort (with a sensitivity of 0.613 and a specificity of 0.859) and an AUC of 0.771 in the testing cohort (with a sensitivity of 0.759 and a specificity of 0.765).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Our study has established an ensemble learning model grounded in semi-automatic segmentation techniques. This model accurately distinguishes between tumor and non-tumor patients preoperatively, as well as discriminating adenosis from other lesion types among the non-tumor cohort, thus providing valuable insights for individualized treatment planning. The proposed stacking model demonstrates significant clinical utility by reducing unnecessary biopsies and saving diagnostic time compared to manual review. These improvements directly address the challenges of overtreatment and diagnostic delays in breast lesion management. By enhancing preoperative accuracy, our model supports tailored surgical planning and alleviates patient anxiety associated","PeriodicalId":12760,"journal":{"name":"Gland surgery","volume":"14 3","pages":"391-404"},"PeriodicalIF":1.5,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12004299/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144011071","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":"Risk factor analysis and clinical experience of treating red breast syndrome in acellular dermal matrix and implant-based breast reconstruction.","authors":"Hyung-Chul Lee, Sang-Ho Kwon, Si-Hyun Ahn, Jae-Ho Chung, Seung-Pil Jung, Eul-Sik Yoon","doi":"10.21037/gs-2024-542","DOIUrl":"https://doi.org/10.21037/gs-2024-542","url":null,"abstract":"<p><strong>Background: </strong>Red breast syndrome (RBS) is represented as idiopathic cutaneous erythema overlying the acellular dermal matrix (ADM) after implant-based breast reconstruction without other signs and symptoms of infection. Although a number of etiologies including lymphatic disruption, delayed hypersensitivity reaction to ADM, and residual DNA within ADM have been suggested for RBS, consensus regarding risk factors and treatment for RBS has been reached yet. Thus, the aim of this study was to find risk factors for RBS and introduce our experience of successful treatment of RBS.</p><p><strong>Methods: </strong>A retrospective study was conducted for patients who underwent implant-based breast reconstruction using ADM from October 2018 to February 2021. Demographics, types of ADM used, reconstructive characteristics, and incidence of RBS were analyzed. Risk factors for RBS were investigated using the logistic regression model.</p><p><strong>Results: </strong>A total of 138 implant-based breast reconstructions using ADM were performed. Their average follow-up period was 17.33 months. The incidence of RBS was 5.8% (n=8) with a median onset time of 36 days. Based on the logistic regression analysis, prior history of radiotherapy [odds ratio (OR): 22.703, P=0.001] was the only significant risk factors for RBS. In most cases with RBS suspected (6 of 8), it was resolved with intravenous corticosteroid and 1 week course of oral antibiotics.</p><p><strong>Conclusions: </strong>Prior history of radiotherapy was found to be significant risk factor for RBS. Single dose IV corticosteroid with 1 week course of oral antibiotics might be useful for RBS treatment.</p>","PeriodicalId":12760,"journal":{"name":"Gland surgery","volume":"14 3","pages":"317-326"},"PeriodicalIF":1.5,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12004325/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144007658","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}