Breast surgery often compromises structures, potentially leading to complications that affect aesthetic outcomes, lactation, breast tissue health, and the patient experience. Tissue-Preserving Breast Augmentation (TPBA) is a novel concept designed to enhance breast and implant stability by preserving the breast's stabilization system, including the circummammary ligament and Cooper's suspensory ligaments. This study presents the TPBA approach, performed in a minimally invasive manner to minimize surgical stimuli and protect the parenchymal breast tissue, along with outcomes observed over a three-year period. This two-center, multi-surgeon retrospective observational study included consecutive female patients undergoing primary breast augmentation or primary augmentation-mastopexy using TPBA between December 2022 and June 2025. All procedures involved an inframammary incision and creation of a pre-pectoral pocket via balloon expansion. Complications were assessed by monitoring cumulative incidence during follow-up visits at 2 weeks, 6-, 12-, and 24-months. A total of 330 procedures were performed. At a mean follow-up of 18 months, the complication rate was 0.9%. No cases of acute complications including seroma, wound breakdown, or infection were observed. Follow-up evaluations revealed no capsular contracture (grade III and IV), implant rupture, lateralization, or inferior malposition. Superior malposition occurred in 2 patients (0.6%), and bleeding was observed in 1 patient (0.3%). Implant rippling was reported by 3 patients (0.9%). TPBA offers a standardized, reproducible approach to breast enhancement via the IMF, performed under general or local anesthesia. It preserves stabilization structures, features a short learning curve, and carries a low risk of complications.

Microwave imaging (MWI) is a non-invasive technique for visualizing the anomalies of biological tissues. The imaging process is accomplished by comparing the electrical parameters of healthy tissues and malignant tissues. This work introduces a microwave imaging system for tumor detection in breast tissue. The experiment is performed in a homogeneous background medium, where a high dielectric contrast material is used to mimic the tumor. The proposed imaging system is experimentally evaluated for multiple tumor locations and sizes using a horn antenna. Reflection coefficients obtained from the monostatic configuration of the horn antenna are used for image reconstruction. The evaluation metrics, such as localization error, absolute area error, DICE score, Intersection over Union (IoU), precision, accuracy, sensitivity and specificity, are computed from the reconstructed image. A modified version of the beamforming algorithm improves the quality of reconstructed images by providing a minimum accuracy of 96% for all test cases, with an evaluation time of less than 48 s. The proposed methodology shows promising results under a controlled environment and can be implemented for clinical applications after adequate biological studies. This methodology can be used to calibrate any antenna system or phantom, as it has high contrast in conductivity, leading to better imaging. The present study contributes to Sustainable Development Goal (SDG) 3 by ensuring healthy lives and promoting wellbeing for all ages.

Plasma anti-DLAT autoantibody as a novel diagnostic biomarker in breast cancer.

Unraveling the microbiome's role in breast cancer progression and treatment response.

Intramammary benign vascular proliferative lesions on MRI during neoadjuvant chemoimmunotherapy with camrelizumab in TNBC patients.

Target-activated genetically programmable light-up fluorescent biosensor for label-free and one-step sensing of glutathione in breast tissues

To investigate the clinicopathological features, immunophenotype, diagnosis, and prognosis of invasive carcinoma originating from microglandular adenosis. Two cases of invasive carcinoma originating from microadenosis were analyzed in the Department of Pathology of the Ruijin Hospital affiliated with the Medical College of Shanghai Jiaotong University. Histopathological morphology, immunohistochemical staining, and prognosis were observed. (1) Histopathological morphology: microscopically, the tumor showed small clusters and nests of infiltrative growth; a few areas showed tubules, and some eosinophilic secretions were observed in the lumen. (2) Immunohistochemistry and molecular genetics: Case 1 was partly positive for S-100, positive for SOX-10, and negative for ER, PR, and HER2 (2+). The result of HER2 gene amplification was negative. Breast and liver tissue lesions in Case 2 were positive for S-100 and SOX-10 but negative for ER and HER2. PR was positive in the liver lesions but showed moderate to strong expression in approximately 80% of the staining. Myoepithelial markers (p63 and calponin) showed loss of myoepithelium around the nests of invasive cancers. TP53 (R213Ter) showed somatic gene variations, and no exon amplification or deletion was detected in BRCA1/2. Invasive carcinoma originating from microadenosis has the same immunophenotype as microadenosis, and its prognosis is difficult to determine.

Fine needle aspiration cytology (FNAC) is widely used to evaluate various lesions. Rapid on-site evaluation (ROSE) can be incorporated into cytology procedures. Our study aims to determine the efficacy of ROSE on the specimen adequacy of FNAC as compared to non-ROSE cases. We conducted a prospective study that included consecutive FNAC cases from various sites between January 10th, 2025, and April 9th, 2025. All cases performed in our laboratory's FNAC clinic had undergone ROSE using a Diff-Quik stain, whereas all FNAC cases in which the glass slides were received from other institutions for cytological evaluation were not subjected to ROSE. The specimen adequacy of ROSE-performed FNAC cases was compared with that of the non-ROSE group. This study included 350 patients. ROSE-performed cases constituted 30.8% (n = 108), while non-ROSE cases accounted for the remaining 69.2% (n = 242). The thyroid was the most frequently sampled site overall (38.86%, n = 136), followed by lymph nodes (31.14%, n = 109), breast (16.58%, n = 58), salivary gland (9.14%, n = 32), and soft tissue (3.14%, n = 11). Cell block preparations were performed in 22.85% (n = 80) of cases, of which 88.75% (n = 71) belonged to the ROSE group. Among the 286 overall adequate cases (81.7%), ROSE was performed in 106 cases (98.14% specimen adequacy, p < 0.001), while 180 out of 242 cases in the non-ROSE group were adequate (74.38% specimen adequacy, p < 0.001). The current study validates ROSE as a relevant and beneficial method that can be used as an adjunct to FNAC to improve the specimen adequacy.

LDH-driven lactic acidosis in hypoxic solid tumors: Mechanisms of metastatic transformation and therapeutic opportunities.

Accurate detection of breast lesion type is crucial for optimizing treatment; however, due to the limited precision of current diagnostic methods, biopsies are often required. To address this limitation, we proposed radio frequency time series dynamic processing (RFTSDP) in 2020, which analyzes the dynamic response of tissue and the impact of scatterer displacement on RF echoes during controlled stimulations to enhance diagnostic information. We developed a vibration-generating device and collected ultrafast ultrasound data from 11 ex vivo breast tissue samples under different stimulations. Deep learning (DL) was used for automated feature extraction and lesion classification into 2, 3, and 5 categories. The performance of the convolutional neural network (CNN)-based RFTSDP method was compared with traditional machine learning techniques, which involved spectral and nonlinear feature extraction from RF time series, followed by a support vector machine (SVM). With 65 Hz vibration, the DL-based RFTSDP method achieved 99.53 ± 0.47% accuracy in classifying and grading breast lesions. CNN consistently outperformed SVM, particularly under vibratory stimulation. In 5-class classification, CNN reached 98.01% versus 95.64% for SVM, with the difference being statistically significant (P < .05). Furthermore, the CNN-based RFTSDP method showed a 28.67% improvement in classification accuracy compared to the non-stimulation condition and the analysis of focused raw data. We developed a DL-based CAD system capable of classifying and grading breast lesions. This study demonstrates that the proposed system not only enhances classification but also ensures increased stability and robustness compared to traditional methods.

Toward accurate breast cancer classification: A review of multi-modal machine learning approaches.

Research on breast ultrasound images lesion localization and diagnosis based on knowledge-driven and data-driven methods.

Supernumerary breasts is a rare disorder that affects 0.4-6% of women . It is frequently misdiagnosed and is primarily found in the axilla. It typically manifests as an asymptomatic tumor during pregnancy or lactation and is bilateral. Since ectopic breast tissue can develop the same pathological alterations as a normal breast, including fibrocystic disease, cancer, and mastitis, diagnosing it is crucial. We describe a 36-year-old woman who has bilateral axillary localization of an accessory breast. Bilateral lipoma was the clinical diagnosis, and discomfort was the main complaint. Later imaging and histological analysis, however, demonstrated that it was an accessory breast tissue.

Over the past 4 years, trichorhinophalangeal syndrome type 1 (TRPS1) has rapidly gained attention among practicing pathologists, with numerous studies emerging that both support and question its diagnostic utility. Initially regarded as a highly specific marker for tumors of mammary origin, TRPS1 is now recognized to have broader expression patterns, including in a variety of cutaneous neoplasms. This is likely due to embryologic parallels between breast tissue and skin adnexal structures, an overlap that was underappreciated in early investigations. Although TRPS1 lacks absolute specificity-even among cutaneous neoplasms-it can still offer meaningful diagnostic value when interpreted alongside conventional immunohistochemical markers and within the appropriate morphologic context. Noteworthy diagnostic applications include mammary Paget disease, primary extramammary Paget disease, rare adnexal neoplasms such as endocrine mucin-producing sweat gland carcinoma and primary cutaneous NUT adnexal carcinoma, and cutaneous metastases from breast carcinoma. In this review, we present the most comprehensive and up-to-date evaluation of the utility and limitations of TRPS1 immunohistochemistry in dermatopathology. Our aim is to deepen understanding of this emerging marker and provide practical guidance on its optimal integration with established immunohistochemical panels to enhance diagnostic accuracy in routine practice.

Effective resource-constrained volumetric ultrasound imaging requires compact, low-power systems capable of wide-angle real-time 3D imaging to accommodate small changes in placement by the operator. However, obtaining such images requires an excessive O(N2) channel count, bulky electronics, and high power consumption. We introduce an end-to-end system architecture to enable high-resolution, real-time 3D ultrasound imaging in a portable form factor. We present: a convolutional optimally distributed array (CODA) geometry that drastically reduces the number of elements (from 1024 to 128), a novel chirped data acquisition (cDAQ) architecture that enhances imaging depth while operating with a 25.3dB lower transmit amplitude than a pulsed system, and an associated new signal processing methodology. We experimentally demonstrate our system's ability to perform deep (> 11cm), high axial resolution (< 600µm), and wide-angle (57°) imaging, while simultaneously reducing power consumption (29.6x reduction) and drive voltage (18V). We validated our system in vitro and further performed in vivo human trials, demonstrating the ability to detect both tumors and cysts in breast tissue. This new architectural approach will unlock a new class of medical devices with enhanced diagnostic and long-term monitoring capabilities and open up future wearable designs of real-time 3D ultrasound systems.

Combined oral contraceptives (COCs) are a widely used method of birth control among women. They have a low Pearl Index, confirming high efficacy. Their mechanism of action relies on suppression of ovulation. This is achieved through the influence of estrogenic and progestogenic components on the release of follicle-stimulating hormone and luteinizing hormone from the pituitary gland. COCs also inhibit fertilization by altering cervical mucus composition and prevent blastocyst implantation. The mechanism of action of COCs allows their use for non-contraceptive purposes. For example, they reduce the risk of ovarian and endometrial cancer. They also limit menstrual bleeding and alleviate acne, migraine headaches, and dysphoric symptoms. Conversely, adverse effects of COCs include an increased risk of cervical cancer. Their impact on breast cancer remains inconclusive. Clinical studies have demonstrated that the overall incidence of breast cancer among women using COCs is comparable to that among women who have never used them. However, during COC use and shortly after discontinuation, the risk of developing breast cancer is elevated, whereas it decreases five years after cessation. Among women with BRCA1 or BRCA2 mutations, the impact of COCs remains uncertain, with some studies reporting increased risk and others suggesting a reduction. Breast cancer is the most frequently diagnosed malignancy among women and the second leading cause of cancer-related death. Prognosis is often dependent on the stage at diagnosis. Mortality risk due to breast cancer is higher among women using COCs, whereas it does not significantly change with the use of progestin-only oral contraceptives. Some patients discontinue oral contraception due to concerns about adverse effects and a potential increase in breast cancer risk. The aim of this study was to present the mechanisms of COC action within breast tissue and their influence on the risk of breast cancer.

ObjectiveTo investigate whether breast tissue composition on preoperative automated breast ultrasound (ABUS) is associated with the accuracy of cancer multiplicity evaluation and postoperative recurrence-free survival (RFS) in patients with early-stage breast cancer.Materials and MethodsThis retrospective analysis included women with early-stage breast cancer (clinical Tis, T1–2/N0) who underwent ABUS and digital mammography (DM) between October 2019 and April 2021. Tissue composition on ABUS was assessed using the Breast Imaging Reporting and Data System background echotexture (BE) (homogeneous-fat, homogeneous-fibroglandular, or heterogeneous). In a subgroup of patients with mammographically dense breasts, the glandular tissue component (GTC) on ABUS were further stratified into high (moderate or marked) or low (minimal or mild). Multivariable logistic and Cox regression analyses were used to identify factors associated with accurate cancer multiplicity categorization (unifocal, multifocal/multicentric, or bilateral) using ABUS + DM, and with RFS, respectively.ResultsAmong 409 women (mean age ± standard deviation, 50.2 ± 8.7 years), ABUS combined with DM yielded accurate cancer multiplicity categorization in 368 patients (90.0%). Neither BE nor GTC on ABUS affected the accuracy of categorization when ABUS was combined with DM. Over a median postoperative follow-up of 3.5 years, 11 recurrences occurred. Heterogeneous BE on ABUS (hazard ratio [HR] 11.24 [95% confidence interval [CI]: 2.82–44.92]; P = 0.001), BRCA mutation (HR 15.94 [2.47–102.97]; P = 0.004), and pathologic index cancer size (HR per 1-cm increase 1.91 [1.13–3.23]; P = 0.02) was independently associated with RFS. In patients with dense breasts, heterogeneous BE (HR 14.17 [95% CI: 2.69–74.60]; P = 0.002) and high GTC (HR 10.32 [2.35–45.28]; P = 0.002) on ABUS, BRCA mutation (HR 24.34 [2.75–215.06]; P = 0.004), and pathologic cancer size (HR per 1-cm increase 2.62 [1.50–4.59]; P = 0.001) was independently associated with RFS.ConclusionIn patients with early-stage breast cancer, heterogeneous BE and high GTC on preoperative ABUS, along with larger cancer size and BRCA mutation, was associated with worse RFS. However, BE and GTC did not affect cancer multiplicity evaluation when ABUS was used in combination with DM.

ABSTRACTSolid papillary carcinoma of the breast is a rare histopathological subtype of papillary neoplasms, and its in situ variant localized to the nipple is particularly uncommon. Current oncology literature provides limited evidence on standardized diagnostic criteria, biological behavior, and optimal treatment strategies for this entity. We describe a 73‐year‐old Chinese woman with a two‐year history of a left nipple mass that developed erythema and ulceration five days prior to presentation. Imaging studies (ultrasonography and MRI) identified an isolated nipple lesion (BI‐RADS 4b) with no other breast tissue involvement. Wide local excision confirmed solid papillary carcinoma in situ (pTisN0M0), with pathological evaluation showing R0 resection margins. The patient received standard adjuvant endocrine therapy (letrozole 2.5 mg/day) and showed no evidence of recurrence at 9 month follow‐up. For patients with nipple‐confined solid papillary carcinoma lacking high‐risk features, complete surgical excision constitutes the mainstay of treatment, complemented by postoperative adjuvant endocrine therapy to mitigate recurrence risk.

BackgroundGiven the highly heterogeneous biology of breast cancer, a more effective noninvasive diagnostic tool that unravels microscopic histopathology patterns is urgently needed.ObjectiveThis study aims to identify cancerous regions in ultrasound images of breast cancer via convolutional neural network based on registered grayscale ultrasound images and readily accessible biopsy whole slide images (WSIs).MethodsThis single-center study prospectively included participants undergoing ultrasound-guided core needle biopsy procedures for Breast Imaging Reporting and Data System category 4 or 5 breast lesions for whom breast cancer was pathologically confirmed from July 2022 to February 2023 consecutively. The basic information, ultrasound image data, biopsy tissue specimens, and corresponding WSIs were collected. After core needle biopsy procedures, the stained breast tissue specimens were sliced and coregistered with an ultrasound image of a needle tract. Convolutional neural network models for identifying breast cancer cells in ultrasound images were developed using FCN-101 and DeepLabV3 networks. The image-level predictive performance was evaluated and compared quantitatively by pixel accuracy, Dice similarity coefficient, and recall. Pixel-level classification was illustrated through confusion matrices. The cancerous region in the testing dataset was further visualized in ultrasound images. Potential clinical applications were qualitatively assessed by comparing the automatic segmentation results and the actual pathological tissue distributions.ResultsA total of 105 participants with 386 ultrasound images of breast cancer were included, with 270 (70%), 78 (20.2%), and 38 (9.8%) images in the training, validation, and test datasets, respectively. Both models performed well in predicting the cancerous regions in the biopsy area, whereas the FCN-101 model was superior to the DeepLabV3 model in terms of pixel accuracy (86.91% vs 69.55%; P=.002) and Dice similarity coefficient (77.47% vs 69.90%; P<.001). The two models yielded recall values of 54.64% and 58.46%, with no significant difference between them (P=.80). Furthermore, the FCN-101 model had an advantage in predicting cancerous regions, while the DeepLabV3 model achieved more accurate predictive pixels in normal tissue (both P<.05). Visualization of cancerous regions on grayscale ultrasound images demonstrated high consistency with those identified on WSIs.ConclusionsThe technique for spatial registration of breast WSIs and ultrasound images of a needle tract was established. Breast cancer regions were accurately identified and localized on a pixel level in high-frequency ultrasound images via an advanced convolutional neural network with histopathologic WSI as the reference standard.

Breast cancer accounts for 31.8% of female cancers in Saudi Arabia, with 56% of cases diagnosed before age 50, 14 years younger than in Western countries. Aggressive subtypes (TNBC: 18-24%; HER2+: 25-28%) are common, and dense breast tissue reduces the effectiveness of mammography. Currently, no age-specific screening protocols exist for this unique epidemiological profile. This study aimed to assess the age-specific diagnostic accuracy of mammography, ultrasound, and magnetic resonance imaging (MRI), and to characterize molecular subtype distribution in Saudi breast cancer patients to guide personalized screening guidelines. A retrospective cohort study was conducted at a tertiary care center in Riyadh, Saudi Arabia (January 2021-December 2023). Medical records of 148 women aged 30-70 with histopathologically confirmed breast cancer (BI-RADS 4/5) were analyzed. The sensitivity and specificity of imaging modalities were assessed across age groups (30-39, 40-49, 50-59, ≥60 years). Subtype distribution and breast density (BI-RADS A-D) were correlated with imaging performance using chi-square tests and logistic regression (SPSS v28, STARD 2015 guidelines). The mean age was 48 years, with 56.4% of cases occurring in women under 50 (peak incidence: 40-49 years, 34.1%). Ultrasound sensitivity exceeded mammography in women under 50 (85.3% vs. 74.5%, p<0.01), while MRI demonstrated the highest overall accuracy (91.7%, 95% confidence interval 89.2-93.5). TNBC prevalence decreased with age (24.7% in 30-39 years to 12.0% in ≥60 years, p<0.01), while invasive lobular carcinoma incidence doubled (8.2% to 18.0%, p<0.001). Delayed diagnosis (>60 days) lowered 2-year survival by 21% (p=0.003). Ultrasound is more effective than mammography for early detection in Saudi women under 50 years old, while MRI remains highly accurate across all age groups. National screening guidelines should adopt biennial ultrasound-first screening starting at age 40, with MRI reserved for high-risk cases and BI-RADS 3-4 lesions.