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OBJECTIVE: This retrospective study aimed to compare the average glandular dose (AGD) per acquisition in breast biopsies guided by contrast-enhanced mammography (CEM), conventional stereotactic breast biopsy (SBB), and digital breast tomosynthesis (DBT). The study also investigated the influence of compressed breast thickness (CBT) and density on AGD. Furthermore, the study aimed to estimate the AGD per procedure for each guidance modality.
METHODS: The study included 163 female patients (mean age 57 ± 10 years) who underwent mammography-guided biopsies using SBB (9%), DBT (65%), or CEM (26%) guidance. AGD and CBT data were extracted from DICOM headers, and breast density was visually assessed. Statistical analyses included two-sample t-tests and descriptive statistics.
RESULTS: Mean AGD per acquisition varied slightly among CEM (1.48 ± 0.22 mGy), SBB (1.49 ± 0.40 mGy), and DBT (1.55 ± 0.47 mGy), with CEM presenting higher AGD at lower CBTs and less dose escalation at higher CBTs. For CBT > 55 mm, CEM showed reduced AGD compared to SBB and DBT (p < 0.001). Breast density had minimal impact on AGD, except for category A. The estimated AGD per procedure was approximately 11.84 mGy for CEM, 11.92 mGy for SBB, and 6.2 mGy for DBT.
CONCLUSIONS: The study found mean AGD per acquisition to be similar for CEM and SBB, with DBT slightly higher. CEM demonstrated higher AGD at lower CBT but lower AGD at higher CBT, indicating reduced dose escalation with increasing thickness. While breast density had minimal overall impact, variations were noted in category A. DBT was more dose-efficient per procedure due to fewer acquisitions required.
CONCLUSIONS: CEM guidance provides effective lesion visualization within safe radiation limits, improving the precision of percutaneous image-guided breast interventions and supporting its potential consideration in a wider range of breast diagnostic procedures.
CONCLUSIONS: Limited data exist on the AGD using CEM guidance for breast biopsies. CEM and SBB exhibit similar AGD per acquisition; DBT demonstrated the lowest AGD per procedure. Radiation from CEM guidance fits within safe limits for percutaneous image-guided breast interventions.

BACKGROUND: Thanks to mammographic screening and the improvement of breast cancer diagnostics, the detection of precancers is also increasing. They are defined as morphological changes of the mammary gland which are more likely to cause cancer. The evaluated precancers are atypical ductal hyperplasia (ADH), lobular carcinoma in situ (LCIS) and radial scar.
METHODS: In the period 1. 1. 2018-31. 12. 2022, we performed 1,302 planned operations for breast disease at the Surgical Clinic of Teaching Hospital Plzeň, of which 30 (2%) were precancer operations. ADH was confirmed 11×, LCIS 8×, and a radical scar 11×. The average age of the patients in all three groups was 56 years (27-85). Precancer was diagnosed 8× only by sonography, 3× by mammography and 19× by a combination of both methods. Subsequently, a puncture biopsy was always completed. We performed 28 tumor excisions with intraoperative biopsy and 2 mastectomies.
RESULTS: In the case of ADH from puncture biopsy, ADH was confirmed intraoperatively 8×, DCIS was diagnosed 2×, and mucinous carcinoma 1×. In LCIS, no tumor was found by intraoperative biopsy 4×, LCIS was confirmed 1×, lobular invasive carcinoma was diagnosed 1×, mastectomy was performed 2× without intraoperative biopsy. In the radial scar, ADH was diagnosed 3×, sclerosing adenosis 6×, DCIS 1×, invasive carcinoma 1×. After the final histological processing of the samples, there was an increase in diagnosed carcinomas. In ADH, DCIS was confirmed 3×, DIC 2×, and mucinous carcinoma 1×. In LCIS, LIC was diagnosed 3×. In the radial scar, DCIS was confirmed 1×, and invasive carcinoma remain 1×. Thus, carcinoma was diagnosed in 11 patients (37%) thanks to the surgical solution. No patient underwent axillary node surgery. All 11 patients subsequently underwent oncological treatment, always a combination of radiotherapy and hormone therapy. All patients are alive, 10 patients are in complete remission of the disease, one with DCIS experienced a local recurrence after 4 years.
CONCLUSIONS: Surgical treatment of precancers of the breast makes sense, DCIS or even invasive cancer is often hidden in addition to precancer. Thanks to the surgical solution, the cancer was detected in time.

BACKGROUND: Although DBT is the standard initial imaging modality for women with focal breast symptoms, the importance of ultrasound has grown rapidly in the past decades. Therefore, the Breast UltraSound Trial (BUST) focused on assessing the diagnostic value of ultrasound and digital breast tomosynthesis (DBT) for the evaluation of breast symptoms by reversing the order of breast imaging; first performing ultrasound followed by DBT. This side-study of the BUST evaluates patients\' perceptions of ultrasound and DBT in a reversed setting.
METHODS: After imaging, 1181/1276 BUST participants completed a survey consisting of open and closed questions regarding both exams (mean age 47.2, ±11.74). Additionally, a different subset of BUST participants (n = 29) participated in six focus group interviews 18-24 months after imaging to analyze their imaging experiences in depth.
RESULTS: A total of 55.3% of women reported reluctance to undergoing DBT, primarily due of pain, while the vast majority also find bilateral DBT reassuring (87.3%). Thematic analysis identified themes related to 1) imaging reluctance (pain/burden, result, and breast harm) and 2) ultrasound and DBT perceptions. Regarding the latter, the theme comfort underscores DBT as burdensome and painful, while ultrasound is largely perceived as non-burdensome. Ultrasound is also particularly valued for its interactive nature, as highlighted in the theme interaction. Perceived effectiveness reflects women\'s interest in bilateral breast evaluation with DBT and the visibility of lesions, while they express more uncertainty about the reliability of ultrasound. Emotional impact portrays DBT as reassuring for many women, whereas opinions on the reassurance provided by ultrasound are more diverse. Additional themes include costs, protocols and privacy.
CONCLUSIONS: Ultrasound is highly tolerated, and particularly valued is the interaction with the radiologist. Nearly half of women express reluctance towards DBT; nevertheless, a large portion report feeling more confident after undergoing bilateral DBT, reassuring them of the absence of abnormalities. Understanding patients\' perceptions of breast imaging examinations is of great value when optimizing diagnostic pathways.

OBJECTIVE: The interpretation of mammograms requires many years of training and experience. Currently, training in mammography, like the rest of diagnostic radiology, is through institutional libraries, books, and experience accumulated over time. We explore whether artificial Intelligence (AI)-generated images can help in simulation education and result in measurable improvement in performance of residents in training.
METHODS: We developed a generative adversarial network (GAN) that was capable of generating mammography images with varying characteristics, such as size and density, and created a tool with which a user could control these characteristics. The tool allowed the user (a radiology resident) to realistically insert cancers within different regions of the mammogram. We then provided this tool to residents in training. Residents were randomized into a practice group and a non-practice group, and the difference in performance before and after practice with such a tool (in comparison to no intervention in the non-practice group) was assessed.
RESULTS: Fifty residents participated in the study, 27 underwent simulation training, and 23 did not. There was a significant improvement in the sensitivity (7.43 percent, significant at p-value = 0.03), negative predictive value (5.05 percent, significant at p-value = 0.008) and accuracy (6.49 percent, significant at p-value = 0.01) among residents in the detection of cancer on mammograms after simulation training.
CONCLUSIONS: Our study shows the value of simulation training in diagnostic radiology and explores the potential of generative AI to enable such simulation training.
CONCLUSIONS: Using generative artificial intelligence, simulation training modules can be developed that can help residents in training by providing them with a visual impression of a variety of different cases.
CONCLUSIONS: Generative networks can produce diagnostic imaging with specific characteristics, potentially useful for training residents. Training with generating images improved residents\' mammographic diagnostic abilities. Development of a game-like interface that exploits these networks can result in improvement in performance over a short training period.

Breast cancer is a global health issue affecting countries worldwide, imposing a significant economic burden due to expensive treatments and medical procedures, given the increasing incidence. In this review, our focus is on exploring the distinct imaging features of known molecular subtypes of breast cancer, underlining correlations observed in clinical practice and reported in recent studies. The imaging investigations used for assessment include screening modalities such as mammography and ultrasonography, as well as more complex investigations like MRI, which offers high sensitivity for loco-regional evaluation, and PET, which determines tumor metabolic activity using radioactive tracers. The purpose of this review is to provide a better understanding as well as a revision of the imaging differences exhibited by the molecular subtypes and histopathological types of breast cancer.

Mammography can reduce breast cancer incidence and mortality. Studies on the utilization of mammography among migrant and non-migrant women are inconsistent. Many of these studies do not take the heterogeneity of migrants in terms of ethnicity and country of origin into account. The aim of the present study was to examine disparities in the use of mammography between non-migrant women and the five largest migrant groups in Austria. The study used data from a nationwide population-based survey of 5118 women aged 45 years and older and analyzed the participation in mammography as a dependent variable. Multivariable logistic regression was used to compare mammography uptake between the aforementioned groups of women, while adjusting for socioeconomic and health variables. The study shows that all migrant groups involved tended to use mammography less frequently than non-migrant women; statistically significant differences, however, were only observed for Hungarian migrant women (adjusted OR = 0.36; 95%-CI: 0.13, 0.95; p = 0.038) and women from a Yugoslavian successor state (adjusted OR = 0.55; 95%-CI: 0.31, 0.99; p = 0.044). These findings are consistent with other studies in Europe and beyond, highlighting the heterogeneity of migrant populations and emphasizing the need for a diversity-sensitive approach to health care.

In order to increase the likelihood of obtaining treatment and achieving a complete recovery, early illness identification and diagnosis are crucial. Artificial intelligence is helpful with this process by allowing us to rapidly start the necessary protocol for treatment in the early stages of disease development. Artificial intelligence is a major contributor to the improvement of medical treatment for patients. In order to prevent and foresee this problem on the individual, family, and generational levels, Monitoring the patient\'s therapy and recovery is crucial. This study\'s objective is to outline a non-invasive method for using mammograms to detect breast abnormalities, classify breast disorders, and identify cancerous or benign tumor tissue in the breast. We used classification models on a dataset that has been pre-processed so that the number of samples is balanced, unlike previous work on the same dataset. Identifying cancerous or benign breast tissue requires the use of supervised learning techniques and algorithms, such as random forest (RF) and decision tree (DT) classifiers, to examine up to thirty features, such as breast size, mass, diameter, circumference, and the nature of the tumor (solid or cystic). To ascertain if the tissue is malignant or benign, the examination\'s findings are employed. These features are mostly what determines how effectively anything may be categorized. The DT classifier was able to get a score of 95.32%, while the RF satisfied a far higher 98.83 percent.

BACKGROUND: Tuberculous mastitis (TBM), is an uncommon form of extra-pulmonary tuberculosis. Clinical and radiological overlap of tuberculous mastitis with malignancy and other granulomatous conditions, along with its paucibacillary nature, make it a diagnostic challenge. In our study, we aim to assess the radiological response of microbiologically negative granulomatous mastitis cases to anti-tuberculous treatment (ATT) in an endemic country.
METHODS: Eighty-seven cases demonstrating granulomatous lesions on breast biopsy were identified. Of these, 49 patients who were treated with ATT and had at least two serial ultrasound follow-ups were included in our study. Mammogram and ultrasound were used for initial imaging. Subsequently, ultrasound was used for serial follow-up. Mantoux skin test, acid fast staining and histological examination of tissue sample were the other investigations used.
RESULTS: Radiologically, on ultrasound, well-circumscribed hypoechoic masses were noted in 18 patients, followed by ill-defined collections with tubular extensions in 15 cases, abscesses in 8, and a focal heterogeneity in 8 patients. Following ATT, 17 patients showed radiological resolution in 4 weeks, 18 of them at 3 months, and nine of them in 6 months.
CONCLUSIONS: Excellent and prompt radiological response to ATT, indicates the need for a high degree of suspicion for tuberculous mastitis (TBM), in endemic countries, even though microbiological tests may turn out negative.