Treatments for Periductal Mastitis: Systematic Review and Meta-Analysis

Periductal Mastitis Occurring Among Hubble-Bubble Smokers: A Report of Two Cases and Literature Review

Periductal mastitis (PM) is a form of nonlactational mastitis. The clinical picture varies from mild periareolar inflammation to frank retroareolar abscess formation. A huge amount of literature is incriminating cigarette smoking as a major contributing factor to the etiology of PM, and cessation of smoking is essential for a successful treatment. However, a search in PubMed and Scopus did not reveal any reports regarding the occurrence of PM among hubble-bubble smokers. Herein, we report two cases of PM in relation to hubble-bubble smoking (HBS) and review the related literature. In addition to antibiotic and surgical treatment, cessation of HBS was essential for sustained remission of PM.

Mendelian randomization suggests causal correlations between inflammatory cytokines and immune cells with mastitis

Objectives

Previous studies have reported that immunoinflammatory responses have associations with mastitis. Here, we aimed to further figure out whether circulating inflammatory cytokines and immune cells causally impact mastitis liability.

Methods

The two-sample Mendelian randomization made use of genetic variances of 91 inflammatory cytokines from a large publicly available genome-wide association study (GWAS) containing 14,824 participants, 731 immunophenotypes data from 3,757 individuals as exposures separately, and mastitis from a GWAS summary (1880 cases and 211699 controls of European ancestry) as outcome. The primary analysis applied the inverse-variance weighted (IVW) method to estimate causal influences, with MR-Egger, weighted median, weighted mode and simple mode as supplementary approaches. Heterogeneity and pleiotropy were evaluated by the Cochrane Q test, MR-Egger intercept test, and MR-PRESSO global test.

Results

The results indicated that CX3CL1 may be suggestively relevant to the risk of mastitis (odds ratio, OR = 1.434, 95% CI = 1.142~1.800, p = 0.002). Moreover, three immunophenotypes were identified as having a potential causal link to mastitis (p < 0.05). Significantly, CD28- CD8dim %CD8dim (OR = 1.058, 95% CI = 1.024 ~ 1.093, p = 0.0006) and CD45 on CD33br HLA DR+ (OR = 1.097, 95% CI = 1.039 ~ 1.157, p = 0.0008) were found to induce mastitis possibly. Conversely, CD39+ secreting Treg AC (OR = 0.929, 95% CI = 0.884~ 0.978, p = 0.005) pertained to protective factors of mastitis. Cochran's Q test and MR-Egger intercept test indicated no significant heterogeneity (p > 0.05) or pleiotropy (p > 0.05), supporting the robustness and reliability of our findings.

Conclusion

Our study adds to current knowledge on the causal roles of inflammatory cytokines and immune cells on mastitis by genetic means, thus guiding future clinical research.

High cure rate and satisfaction in patients with periductal mastitis via the latissimus dorsi myocutaneous flap technique: a retrospective study

Background

Periductal mastitis (PDM) is a complex benign breast disease with a prolonged course and a high probability of recurrence after treatment. There is a variety of available treatments for PDM, but none of these options have been widely accepted. A standard strategy has been especially difficult to establish in patients with PDM accompanied by large tumors or large skin ruptures, as these seriously affect the appearance of the breasts after surgeries, which can lead to feelings of lower self-esteem among patients. Therefore, finding a reliable volume replacement has become a focus of our research efforts. With the widespread use of latissimus dorsi in breast reconstruction, we attempted to use the latissimus muscle (skin) flap for stage I repair in patients with large-defect PDM. Our study is the first of its kind to evaluate the clinical effect and patient satisfaction of the latissimus dorsi myocutaneous flap (LDMF) technique in PDM.

Methods

Thirty-two patients with PDM and more than about 20% loss of breast volume admitted to the Department of Breast Surgery of Shanxi Bethune Hospital from March 2017 to July 2021 were enrolled. After lesion removal, the LDMF technique was applied to these patients for immediate completion of breast contour revision. All patients were periodically followed up to assess the efficacy of the procedure and their satisfaction with the breasts' shape.

Results

Three patients (9.4%) developed dorsal effusion after removal of the back drain; six patients (18.8%) developed mild limitation of the activity of the affected upper limb; and three patients (9.4%) experienced local recurrence of inflammation after the operation, all of whom underwent a second operation. The cure rate of the patients treated with LDMF was 90.6%, the overall satisfaction rate of the patients was 96.9%, and doctor's evaluation of satisfaction was 90.6%.

Conclusions

In patients with poor results after anti-infective and local treatment and those with more than 20% defect volume following lesion removal, the LDMF technique yields a high cure rate and good patient satisfaction.

A hematological parameter-based model for distinguishing non-puerperal mastitis from invasive ductal carcinoma

Purpose

Non-puerperal mastitis (NPM) accounts for approximately 4-5% of all benign breast lesions. Ultrasound is the preferred method for screening breast diseases; however, similarities in imaging results can make it challenging to distinguish NPM from invasive ductal carcinoma (IDC). Our objective was to identify convenient and objective hematological markers to distinguish NPM from IDC.

Methods

We recruited 89 patients with NPM, 88 with IDC, and 86 with fibroadenoma (FA), and compared their laboratory data at the time of admission. LASSO regression, univariate logistic regression, and multivariate logistic regression were used to screen the parameters for construction of diagnostic models. Receiver operating characteristic curves, calibration curves, and decision curves were constructed to evaluate the accuracy of this model.

Results

We found significant differences in routine laboratory data between patients with NPM and IDC, and these indicators were candidate biomarkers for distinguishing between the two diseases. Additionally, we evaluated the ability of some classic hematological markers reported in previous studies to differentiate between NPM and IDC, and the results showed that these indicators are not ideal biomarkers. Furthermore, through rigorous LASSO and logistic regression, we selected age, white blood cell count, and thrombin time to construct a differential diagnostic model that exhibited a high level of discrimination, with an area under the curve of 0.912 in the training set and with 0.851 in the validation set. Furthermore, using the same selection method, we constructed a differential diagnostic model for NPM and FA, which also demonstrated good performance with an area under the curve of 0.862 in the training set and with 0.854 in the validation set. Both of these two models achieved AUCs higher than the AUCs of models built using machine learning methods such as random forest, decision tree, and SVM in both the training and validation sets.

Conclusion

Certain laboratory parameters on admission differed significantly between the NPM and IDC groups, and the constructed model was designated as a differential diagnostic marker. Our analysis showed that it has acceptable efficiency in distinguishing NPM from IDC and may be employed as an auxiliary diagnostic tool.

Identification of periductal mastitis and granulomatous lobular mastitis: a literature review

Background and Objective

Non-puerperal mastitis (NPM) is a breast disease with poor clinical manifestations, which seriously affects women's health and quality of life. Due to the low incidence rate of the disease and the paucity of related research, there is much misdiagnosis and mis-management of periductal mastitis (PDM) and granulomatous lobular mastitis (GLM). Therefore, understanding the differences between PDM and GLM, in terms of etiology and clinical manifestations, is crucial for patient treatment and prognosis. At the same time, choosing different treatment methods may not achieve the best treatment effect, so the appropriate treatment method can often reduce the patient's pain and reduce the recurrence of the patient's disease.

Methods

The PubMed database was searched for articles published from 1 January 1990 to 16 June 2022 using the following search terms: "non-puerperal mastitis", "periductal mastitis", "granulomatous lobular mastitis", "mammary duct ectasia", "idiopathic granulomatous mastitis", "plasma cell mastitis", and "identification". The key findings of the related literatures were analyzed and summarized.

Key Content and Findings

We systematically described the key points in the differential diagnosis, treatment, and prognosis of PDM and GLM. The use of different animal models for research and novel drugs to treat the disease were also described in this paper.

Conclusions

The key points in the differentiation of the two diseases are clearly explained, and the respective treatment options and prognosis are summarized.

Diagnostic value of radiomics model based on gray-scale and contrast-enhanced ultrasound for inflammatory mass stage periductal mastitis/duct ectasia

Objective

The present study aimed to investigate the clinical application value of the radiomics model based on gray-scale ultrasound (GSUS) and contrast-enhanced ultrasound (CEUS) images in the differentiation of inflammatory mass stage periductal mastitis/duct ectasia (IMSPDM/DE) and invasive ductal carcinoma (IDC).

Methods

In this retrospective study, 254 patients (IMSPDM/DE: 129; IDC:125) were enrolled between January 2018 and December 2020 as a training cohort to develop the classification models. The radiomics features were extracted from the GSUS and CEUS images. The least absolute shrinkage and selection operator (LASSO) regression model was employed to select the corresponding features. Based on these selected features, logistic regression analysis was used to aid the construction of these three radiomics signatures (GSUS, CEUS and GSCEUS radiomics signature). In addition, 80 patients (IMSPDM/DE:40; IDC:40) were recruited between January 2021 and November 2021 and were used as the validation cohort. The best radiomics signature was selected. Based on the clinical parameters and the radiomics signature, a classification model was built. Finally, the classification model was assessed using nomogram and decision curve analyses.

Results

Three radiomics signatures were able to differentiate IMSPDM/DE from IDC. The GSCEUS radiomics signature outperformed the other two radiomics signatures and the AUC, sensitivity, specificity, and accuracy were estimated to be 0.876, 0.756, 0.804, and 0.798 in the training cohort and 0.796, 0.675, 0.838 and 0.763 in the validation cohort, respectively. The lower patient age (p&lt;0.001), higher neutrophil count (p&lt;0.001), lack of pausimenia (p=0.023) and GSCEUS radiomics features (p&lt;0.001) were independent risk factors of IMSPDM/DE. The classification model that included the clinical factors and the GSCEUS radiomics signature outperformed the GSCEUS radiomics signature alone (the AUC values of the training and validation cohorts were 0.962 and 0.891, respectively). The nomogram was applied to the validation cohort, reaching optimal discrimination, with an AUC value of 0.891, a sensitivity of 0.888, and a specificity of 0.750.

Conclusions

The present study combined the clinical parameters with the GSCEUS radiomics signature and developed a nomogram. This GSCEUS radiomics-based classification model could be used to differentiate IMSPDM/DE from IDC in a non-invasive manner.