Granulomatous mastitis and pectoralis major muscle defect following polyacrylamide hydrogel injection: a case report and literature review.

Background: Breast augmentation through the injection of polyacrylamide hydrogel (PAAG) was a popular procedure in the past, but it has since been prohibited due to various complications, including masses, migration, infection, inflammation, and even cancer. However, there were rare cases of granulomatous mastitis with pectoralis major muscle defect following PAAG injection for breast augmentation. Case Description: A 40-year-old female patient presented with a swollen and suppurative mass in her left breast and was insensitive to antibiotics. She was admitted to our department for further treatment after 7 months with progressive local and general symptoms. Ultrasound imaging showed ill-defined heterogeneous echoes, and contrast-enhanced magnetic resonance imaging (MRI) revealed non-mass enhancement lesions in the multiregional distribution in Breast Imaging-Reporting and Data System 4A (BI-RADS 4A) with oedema in the retroglandular space and multiple enlarged lymph nodes in the ipsilateral axilla. Intraoperative observations revealed necrotic tissues, multiple abscesses, residual mucoid PAAG prosthesis diffused into the mammary glands and intramuscularly into the pectoralis muscle, and partial loss of pectoralis major muscle. Histopathological results revealed foreign-body granulomas accompanied by gel-like granular PAAG and proliferative inflammatory cells. She recovered after undergoing the characteristic surgical management in our center under general anesthesia and had no recurrence during the 2-year follow-up. Conclusions: This case revealed that PAAG injection for augmentation mammaplasty, even after the removal operation, could result in subsequent complications, including granulomatous mastitis and pectoralis major muscle damage. PAAG filler complications are difficult to treat, therefore, it is essential to establish appropriate and effective therapeutic procedures.

Prediction models for postoperative recurrence of non-lactating mastitis based on machine learning.

OBJECTIVES: This study aims to build a machine learning (ML) model to predict the recurrence probability for postoperative non-lactating mastitis (NLM) by Random Forest (RF) and XGBoost algorithms. It can provide the ability to identify the risk of NLM recurrence and guidance in clinical treatment plan. METHODS: This study was conducted on inpatients who were admitted to the Mammary Department of Shuguang Hospital affiliated to Shanghai University of Traditional Chinese Medicine between July 2019 to December 2021. Inpatient data follow-up has been completed until December 2022. Ten features were selected in this study to build the ML model: age, body mass index (BMI), number of abortions, presence of inverted nipples, extent of breast mass, white blood cell count (WBC), neutrophil to lymphocyte ratio (NLR), albumin-globulin ratio (AGR) and triglyceride (TG) and presence of intraoperative discharge. We used two ML approaches (RF and XGBoost) to build models and predict the NLM recurrence risk of female patients. Totally 258 patients were randomly divided into a training set and a test set according to a 75%-25% proportion. The model performance was evaluated based on Accuracy, Precision, Recall, F1-score and AUC. The Shapley Additive Explanations (SHAP) method was used to interpret the model. RESULTS: There were 48 (18.6%) NLM patients who experienced recurrence during the follow-up period. Ten features were selected in this study to build the ML model. For the RF model, BMI is the most important influence factor and for the XGBoost model is intraoperative discharge. The results of tenfold cross-validation suggest that both the RF model and the XGBoost model have good predictive performance, but the XGBoost model has a better performance than the RF model in our study. The trends of SHAP values of all features in our models are consistent with the trends of these features' clinical presentation. The inclusion of these ten features in the model is necessary to build practical prediction models for recurrence. CONCLUSIONS: The results of tenfold cross-validation and SHAP values suggest that the models have predictive ability. The trend of SHAP value provides auxiliary validation in our models and makes it have more clinical significance.

Staged operation in the surgical treatment of granulomatous lobular mastitis.

Background: Granulomatous lobular mastitis (GLM) is a chronic inflammatory breast condition characterized by an unclear etiology and an undefined therapeutic approach. Surgical intervention is considered an alternative modality for managing GLM. Staged operation is the predominant and characteristic surgical approach in the treatment of GLM in our center; therefore, we evaluated the efficacy of staged operative techniques in this cohort study. Methods: We retrospectively reviewed 212 patients with GLM who underwent staged operation between August 2020 and July 2022 in the inpatient department of our institute. Their clinical history information, clinic complaints, treatment details, surgical outcomes, follow-up results, and scores on the satisfaction questionnaire were analyzed. The patients were called for follow-up and consultation with a deadline of August 2023. Results: The median follow-up time was 27 months (range, 14-37 months). In total, 212 patients were treated with three different staged procedures according to the individual assessment and patient willingness, including 168 patients who underwent one-stage debridement operation and two-stage suture operation (DO + SO), 25 patients who underwent one-stage debridement operation without suture (DO), and 19 patients who underwent one-stage debridement and simultaneous suture operation (DSO). The median recovery time was 29 days (range, 14-60 days). A minority of patients developed postoperative complications, including effusion (1.89%), flap ischemia (0.94%), areola-nipple ischemia (0.94%) and sinus tract formation (2.36%). The scores of the satisfaction questionnaire were 43.10±3.09, and 186 patients (87.74%) gave high scores for postoperative breast appearance. Only 5 of 212 patients (2.36%) developed recurrence. Conclusions: Staged operation performed in our institute is an effective and safe surgical therapy in patients with GLM, yielding a short recovery time, low recurrence and good cosmetic results.

Adolescent Non-Puerperal Mastitis: Risk Factors, Clinical Characteristics, and Prognosis Analysis.

Purpose: To determine the risk factors, clinical characteristics, and prognosis of adolescent non-puerperal mastitis patients. Patients and methods: A retrospective analysis was conducted on 10 cases of NPM in adolescents who underwent surgical treatment at Shuguang Hospital affiliated to Shanghai University of Traditional Chinese Medicine from August 2021 to August 2023. We analyze the patient's general information, clinical characteristics, related medical history, laboratory indicators, breast magnetic resonance imaging examination, postoperative pathology, prognosis, etc. Results: The clinical manifestations of NPM in adolescents mainly included redness, swelling and pain in the breasts, congenital nipple retraction, and extensive lesion range. Inflammatory markers and prolactin were elevated. Magnetic resonance imaging showed circular enhancement with abscess formation as the main type. All patients underwent surgical treatment with a fast recovery time after surgery. No recurrence was observed during follow-up and the postoperative breast appearance was satisfactory. Multivariate Logistic regression analysis indicated that congenital nipple retraction, elevated prolactin levels and trauma were independent risk factors for adolescents non-puerperal mastitis. Conclusion: Adolescent non-puerperal mastitis is a rare and unique type. Summarizing its main risk factors, clinical characteristics, and prognosis provides a basis for further research.

LC/MS-based untargeted lipidomics reveals lipid signatures of nonpuerperal mastitis.

BACKGROUND: Nonpuerperal mastitis (NPM) is a disease that presents with redness, swelling, heat, and pain during nonlactation and can often be confused with breast cancer. The etiology of NPM remains elusive; however, emerging clinical evidence suggests a potential involvement of lipid metabolism. METHOD: Liquid chromatography‒mass spectrometry (LC/MS)-based untargeted lipidomics analysis combined with multivariate statistics was performed to investigate the NPM lipid change in breast tissue. Twenty patients with NPM and 10 controls were enrolled in this study. RESULTS: The results revealed significant differences in lipidomics profiles, and a total of 16 subclasses with 14,012 different lipids were identified in positive and negative ion modes. Among these lipids, triglycerides (TGs), phosphatidylethanolamines (PEs) and cardiolipins (CLs) were the top three lipid components between the NPM and control groups. Subsequently, a total of 35 lipids were subjected to screening as potential biomarkers, and the chosen lipid biomarkers exhibited enhanced discriminatory capability between the two groups. Furthermore, pathway analysis elucidated that the aforementioned alterations in lipids were primarily associated with the arachidonic acid metabolic pathway. The correlation between distinct lipid populations and clinical phenotypes was assessed through weighted gene coexpression network analysis (WGCNA). CONCLUSIONS: This study demonstrates that untargeted lipidomics assays conducted on breast tissue samples from patients with NPM exhibit noteworthy alterations in lipidomes. The findings of this study highlight the substantial involvement of arachidonic acid metabolism in lipid metabolism within the context of NPM. Consequently, this study offers valuable insights that can contribute to a more comprehensive comprehension of NPM in subsequent investigations. TRIAL REGISTRATION: Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine (Number: 2019-702-57; Date: July 2019).