Common breast concerns

MS-CFNet: a multi-scale clinical studying-based and feature extraction-guided network for breast fibroadenoma segmentation in ultrasonography

Segmenting breast tumors in ultrasonography is challenging due to the low image quality and presence of artifacts. Radiologists' studying and diagnosis skills are integrated with artificial intelligence to establish a clinical learning-based deep learning network in order to robustly extract and delineate features of breast fibroadenoma. The spatial local feature contrast (SLFC) module captures overall tumor contours, while the channel recursive gated attention (CRGA) module enhances edge perception through high-dimensional information interaction. Additionally, full-scale feature fusion and enhanced deep supervision are applied to improve model stability and performance. To achieve smoother boundaries, we introduce a new loss function (cosh-smooth) that penalizes and finely tunes tumor edges. Our dataset comprises 1016 clinical ultrasound images of breast fibroadenoma with labeled masks, alongside a publicly available dataset of 246 ones. Segmentation performance is evaluated using the Dice similarity coefficient (DSC) and mean intersection over union (MIOU). Extensive experiments demonstrate that our proposed MS-CFNet outperforms state-of-the-art methods. Compared to TransUNet as a baseline model, MS-CFNet improves by 1.47% in DSC and 2.56% in MIOU. The promising result of MS-CFNet is attributed to the integration of radiologists' clinical diagnosis procedure and the bionic mindset, enhancing the network's ability to recognize and segment breast fibroadenomas effectively.

The "Trunk sign": A novel X-ray sign in galactography of patients with nipple discharge suggesting malignancy

The etiology of nipple discharge is often unclear, and there are few studies exploring diagnostic approaches of nipple discharge. Galactography is a common method for clinical diagnosis of patients with nipple discharge. Therefore, this study aimed to evaluate the use of galactography in differentiating between benign and malignant lesions in patients with nipple discharge. A retrospective study of 161 patients with nipple discharges, who were evaluated with galactography and underwent surgery in Qilu Hospital of Shangdong University between January 2018 and December 2019, was conducted. Baseline characteristics were obtained from their electronic records including age, menstruation status, physical examination, galactography, cytology, and pathology. There were 110 cases of benign disease, 12 cases of high-risk disease, and 39 cases of malignant disease. With respect to benign diseases there were 26 (23.6%) patients with hyperplasia and ductal ectasia, and 94 (76.4%) with intraductal papilloma. With respect to high risk diseases, there were 2 (16.7%) patients with atypical intraductal papilloma and 10 (83.4%) with atypical hyperplasia. With respect to malignant lesions, 19 (48.7%) patients had intraductal carcinoma, 4 (10.3%) had solid papillary carcinoma, and 16 (41.0%) had invasive carcinoma. The significant findings of our study are as follows: patients with malignant diseases had a higher proportion of concomitant masses (74.4% vs 41.7% vs 22.7%, P < .001), positive spill cytology (51.3% vs 41.7% vs 2.7%, P < .001), and trunk signs (71.8% vs 33.3% vs 10.9%, P < .001). A forest plot revealed that trunk signs were related to an increased risk of malignant diseases in almost all the subgroups. Galactography is important for the differential diagnosis of benign and malignant lesions in nipple discharge, and the "Trunk sign" is an important radiographic sign of malignant lesions. Combining galactography with other methods is advisable to improve the accuracy of diagnosis in patients with nipple discharge.

Breast fibroadenomas: a review in the light of current literature

&lt;br&gt;&lt;b&gt;Introduction:&lt;/b&gt; Fibroadenomas are one of the most common benign tumors of the breast in the adolescent females accounting for about 2/3&lt;sup&gt;rd&lt;/sup&gt; of all the breast lumps and more than half of all the biopsied breast lesions. They come into being due to overgrowth of glandular tissue under the influence of hormonal changes that the girls undergo at the time of puberty. Due to the wide prevalence of fibroadenomas and the psychosocial morbidity associated with the finding of a breast mass, it is imperative for physicians treating adolescent patients to be thoroughly familiar and updated with this disease. &lt;br&gt;&lt;b&gt;Aim:&lt;/b&gt; The article aims at providing a brief review of the classification, presentation, diagnosis, and update on the management of breast fibroadenomas on the basis of recent literature.

Management of nipple discharge and the associated imaging findings

Nipple discharge is commonly encountered by health care providers, accounting for 2%-5% of medical visits by women. Because nipple discharge is the presenting symptom in 5% to 12% of breast cancers, it causes considerable anxiety for both patient and providers. Furthermore, the work-up and management of nipple discharge can be confusing. Fortunately, the cause of nipple discharge is usually benign, so the primary goal of evaluation and management is separation of patients with pathologic causes of discharge from those with benign or physiologic causes. The evaluation of nipple discharge requires a thorough history, careful physical examination, and an informed approach that selects the most suitable diagnostic modality. Primary care providers, working with their radiologists and surgeons, are well positioned to design appropriate diagnostic and management protocols to assess and treat nipple discharge. A thoughtful and prudent approach to nipple discharge should alleviate patient anxiety by efficiently and effectively defining the underlying etiology.

A nomogram based on mammary ductoscopic indicators for evaluating the risk of breast cancer in intraductal neoplasms with nipple discharge

Mammary ductoscopy (MD) is commonly used to detect intraductal lesions associated with nipple discharge. This study investigated the relationships between ductoscopic image-based indicators and breast cancer risk, and developed a nomogram for evaluating breast cancer risk in intraductal neoplasms with nipple discharge. A total of 879 consecutive inpatients (916 breasts) with nipple discharge who underwent selective duct excision for intraductal neoplasms detected by MD from June 2008 to April 2014 were analyzed retrospectively. A nomogram was developed using a multivariate logistic regression model based on data from a training set (687 cases) and validated in an independent validation set (229 cases). A Youden-derived cut-off value was assigned to the nomogram for the diagnosis of breast cancer. Color of discharge, location, appearance, and surface of neoplasm, and morphology of ductal wall were independent predictors for breast cancer in multivariate logistic regression analysis. A nomogram based on these predictors performed well. The P value of the Hosmer-Lemeshow test for the prediction model was 0.36. Area under the curve values of 0.812 (95 % confidence interval (CI) 0.763-0.860) and 0.738 (95 % CI 0.635-0.841) was obtained in the training and validation sets, respectively. The accuracies of the nomogram for breast cancer diagnosis were 71.2 % in the training set and 75.5 % in the validation set. We developed a nomogram for evaluating breast cancer risk in intraductal neoplasms with nipple discharge based on MD image findings. This model may aid individual risk assessment and guide treatment in clinical practice.