Papillary endothelial hyperplasia (Masson's tumor) of the breast: A diagnostic challenge.

Papillary endothelial hyperplasia (PEH) or Masson's tumor is a rare benign vascular tumor that usually appears in the soft tissues of the head and neck, trunk and extremities, being extremely rare in the breast. Its diagnosis can be a challenge, especially in the follow-up of patients with previous disease of breast carcinoma. We present the case of a 65-year-old patient, with a history of bilateral breast cancer and reconstruction with implants, who presented a Masson's tumor during follow-up. An ultrasound scan was performed, showing a well-circumscribed mass in the left breast, located in the posterior contour of the implant. Subsequently, magnetic resonance imaging (MR) depicted an enhancing tumor, without infiltration of adjacent structures. Finally, the definitive anatomopathological diagnosis was obtained after surgical excision.

Deep transfer learning for detection of breast arterial calcifications on mammograms: a comparative study.

INTRODUCTION: Breast arterial calcifications (BAC) are common incidental findings on routine mammograms, which have been suggested as a sex-specific biomarker of cardiovascular disease (CVD) risk. Previous work showed the efficacy of a pretrained convolutional network (CNN), VCG16, for automatic BAC detection. In this study, we further tested the method by a comparative analysis with other ten CNNs. MATERIAL AND METHODS: Four-view standard mammography exams from 1,493 women were included in this retrospective study and labeled as BAC or non-BAC by experts. The comparative study was conducted using eleven pretrained convolutional networks (CNNs) with varying depths from five architectures including Xception, VGG, ResNetV2, MobileNet, and DenseNet, fine-tuned for the binary BAC classification task. Performance evaluation involved area under the receiver operating characteristics curve (AUC-ROC) analysis, F1-score (harmonic mean of precision and recall), and generalized gradient-weighted class activation mapping (Grad-CAM++) for visual explanations. RESULTS: The dataset exhibited a BAC prevalence of 194/1,493 women (13.0%) and 581/5,972 images (9.7%). Among the retrained models, VGG, MobileNet, and DenseNet demonstrated the most promising results, achieving AUC-ROCs > 0.70 in both training and independent testing subsets. In terms of testing F1-score, VGG16 ranked first, higher than MobileNet (0.51) and VGG19 (0.46). Qualitative analysis showed that the Grad-CAM++ heatmaps generated by VGG16 consistently outperformed those produced by others, offering a finer-grained and discriminative localization of calcified regions within images. CONCLUSION: Deep transfer learning showed promise in automated BAC detection on mammograms, where relatively shallow networks demonstrated superior performances requiring shorter training times and reduced resources. RELEVANCE STATEMENT: Deep transfer learning is a promising approach to enhance reporting BAC on mammograms and facilitate developing efficient tools for cardiovascular risk stratification in women, leveraging large-scale mammographic screening programs. KEY POINTS: • We tested different pretrained convolutional networks (CNNs) for BAC detection on mammograms. • VGG and MobileNet demonstrated promising performances, outperforming their deeper, more complex counterparts. • Visual explanations using Grad-CAM++ highlighted VGG16's superior performance in localizing BAC.

Value of sonoelastography for diagnosis of breast non-mass lesions and comparison with BI-RADS: A systematic review and meta-analysis.

BACKGROUND: Not all the breast lesions were mass-like, some were non-mass-like at ultrasonography. In these lesions, conventional ultrasonography had a high sensitivity but a low specificity. Sonoelastography can evaluate tissue stiffness to differentiate malignant masses from benign ones. Then what about the non-mass lesions? The aim of this study was to evaluate the current accuracy of sonoelastography in the breast non-mass lesions and compare the results with those of the American College of Radiology breast Imaging-Reporting and Data System (BI-RADS). METHODS: An independent literature search of English medical databases, including PubMed, Web of Science, Embase & MEDLINE (Embase.com) and Cochrane Library, was performed by 2 researchers. The accuracy of sonoelastography was calculated and compared with those of BI-RADS. RESULTS: Fourteen relevant studies including 1058 breast non-mass lesions were included. Sonoelastography showed a pooled sensitivity of 0.74 (95% CI: 0.70-0.78), specificity of 0.89 (95% CI: 0.85-0.91), diagnostic odds ratio (DOR) of 25.22 (95% CI: 17.71-35.92), and an area under the curve of 0.9042. Eight articles included both sonoelastography and BI-RADS. The pooled sensitivity, specificity, DOR and AUC were 0.69 versus 0.91 (P < .01), 0.90 versus 0.68 (P < .01), 19.65 versus 29.34 (P > .05), and 0.8685 versus 0.9327 (P > .05), respectively. CONCLUSIONS: Sonoelastography has a higher specificity and a lower sensitivity for differential diagnosis between malignant and benign breast non-mass lesions compared with BI-RADS, although there were no differences in AUC between them.

Pseudocalcifications: Radiologic-Pathologic Correlation of Postsurgical Gauze Artifacts.

Artifacts and foreign bodies can mimic microcalcifications. We report a series of 17 postsurgical women in whom mammograms showed fine linear radiodensities at the surgical bed. Vacuum-assisted biopsy histopathology of one of the lesions showed foreign bodies of different sizes with macrophage reaction. After discussion with the surgeons, we ascertained that a particular type of gauze was used that had fragmented, and we reproduced the mammographic appearance in a chicken breast. Furthermore, we showed the same pathology was reproduced in mice implanted with the gauze threads. It is important to be aware of this entity to avoid unnecessary examinations and even biopsy. The presence of foreign body linear gauze fragments at the surgical site can pose challenges in the mammographic follow-up of these patients.

Forget Me Not: Incidental Findings on Breast MRI.

With the growing utilization and expanding role of breast MRI, breast imaging radiologists may encounter an increasing number of incidental findings beyond the breast and axilla. Breast MRI encompasses a large area of anatomic coverage extending from the lower neck to the upper abdomen. While most incidental findings on breast MRI are benign, identifying metastatic disease can have a substantial impact on staging, prognosis, and treatment. Breast imaging radiologists should be familiar with common sites, MRI features, and breast cancer subtypes associated with metastatic disease to assist in differentiating malignant from benign findings. Furthermore, detection of malignancies of nonbreast origin as well as nonmalignant, but clinically relevant, incidental findings can significantly impact clinical management and patient outcomes. Breast imaging radiologists should consistently follow a comprehensive search pattern and employ techniques to improve the detection of these important incidental findings.

The diagnostic value of multimodal imaging based on MR combined with ultrasound in benign and malignant breast diseases.

We aimed to construct and validate a multimodality MRI combined with ultrasound based on radiomics for the evaluation of benign and malignant breast diseases. The preoperative enhanced MRI and ultrasound images of 131 patients with breast diseases confirmed by pathology in Aerospace Center Hospital from January 2021 to August 2023 were retrospectively analyzed, including 73 benign diseases and 58 malignant diseases. Ultrasound and 3.0 T multiparameter MRI scans were performed in all patients. Then, all the data were divided into training set and validation set in a 7:3 ratio. Regions of interest were drawn layer by layer based on ultrasound and MR enhanced sequences to extract radiomics features. The optimal radiomic features were selected by the best feature screening method. Logistic Regression classifier was used to establish models according to the best features, including ultrasound model, MRI model, ultrasound combined with MRI model. The model efficacy was evaluated by the area under the curve (AUC) of the receiver operating characteristic, sensitivity, specificity, and accuracy. The F-test based on ANOVA was used to screen out 20 best ultrasonic features, 11 best MR Features, and 14 best features from the combined model. Among them, texture features accounted for the largest proportion, accounting for 79%.The ultrasound combined with MR Image fusion model based on logistic regression classifier had the best diagnostic performance. The AUC of the training group and the validation group were 0.92 and 091, the sensitivity was 0.80 and 0.67, the specificity was 0.90 and 0.94, and the accuracy was 0.84 and 0.79, respectively. It was better than the simple ultrasound model (AUC of validation set was 0.82) or the simple MR model (AUC of validation set was 0.85). Compared with the traditional ultrasound or magnetic resonance diagnosis of breast diseases, the multimodal model of MRI combined with ultrasound based on radiomics can more accurately predict the benign and malignant breast diseases, thus providing a better basis for clinical diagnosis and treatment.

Sonographic Evaluation of Nigerian Women with Mammographic Focal Asymmetric Density.

BACKGROUND AND OBJECTIVE: Focal asymmetric breast densities (FABD) present a diagnostic challenge concerning the need for a further histologic workup to rule out malignancy. We therefore aim to correlate ultrasonography and mammographic findings in women with FABD and evaluate the use of ultrasonography as a workup tool. METHODOLOGY: This is a retrospective study of women who underwent targeted breast sonography due to FABD with a mammogram in a private diagnostic centre in Abuja over three years (2016-2018). Demographic details, clinical indication, mammographic and ultrasonography features were documented and statistical analysis was done using SAS software version 9.3 with the statistical level of significance set at 0.05. RESULT: The age range of 44 patients was 32-69 years with a majority (79.5%) presenting for screening mammography. The predominant breast density pattern in those <60 years was heterogeneous (ACR C). FABD in mammography was noted mostly in the upper outer quadrant and retro-areolar regions (34.1 and 38.6%). Ultrasonography findings were normal breast tissue (56.8%), 4 simple cysts, 1 abscess, 4 solid masses, 2 focal fibrocystic changes, and 4 cases of duct ectasia. Twenty-nine (65.9%) of the abnormal cases were on the same side as the mammogram, while all the incongruent cases were recorded in heterogeneously dense breasts (ACR C). Final BIRADS Scores on USS showed that 41(93.2%) of mammographic FABD had normal and benign findings while only 2(4.6%) had sonographic features of malignancy. CONCLUSION: Breast ultrasonography allows for optimal lesion characterization and is a veritable tool in the workup of patients with focal asymmetric breast densities with the majority presenting as normal breast tissue and benign pathologies.

CONTEXTE ET OBJECTIF: Les densités asymétriques mammographiques focales mammographiques, FABD présentent un défi diagnostique en ce qui concerne la nécessité d'un examen histologique supplémentaire pour exclure une tumeur maligne. Nous visons donc à corréler les résultats échographiques et mammographiques chez les femmes ayant une densité mammaire focale asymétrique et à établir la nécessité d'un bilan plus approfondi. METHODOLOGIE: Une étude rétrospective de 44 femmes ayant subi une échographie ciblée du sein en raison de FABD à la mammographie dans un centre de diagnostic privé à Abuja sur trois ans (2016-2018) Les détails démographiques, les présentations cliniques, les caractéristiques mammographiques et échographiques ont été documentés et analysés statistiquement fait à l'aide du logiciel SAS version 9.3 avec un niveau de signification statistique fixé à 0,05. RESULTAT: La tranche d'âge des patients était de 32 à 69 ans (SD 1), la majorité (79,5%) se présentant pour une mammographie de dépistage. Le schéma de densité mammaire prédominant chez les moins de 60 ans était hétérogène (ACR C). FABD en mammographie a presque la même distribution dans le quadrant externe supérieur et les régions rétroaréolaires (38,4 vs 36,8%). Les résultats échographiques étaient: tissu mammaire normal (65,9%), 4 kystes simples, 1 kyste complexe, 4 masses solides, 2 fibrokystiques focales et 4 cas d'ectasie canalaire.29 (65,9%) des cas anormaux étaient du même côté que la mammographie, alors que tous les cas incongruents ont été enregistrés dans des seins denses de manière hétérogène (ACR C). Les scores finaux BIRADS sur USS ont montré que 41 (93,2%) des FABD mammographiques avaient des résultats normaux et bénins, tandis que seulement 2 (4,6%) avaient des caractéristiques échographiques de malignité. CONCLUSION: L'échographie mammaire permet une caractérisation optimale des lésions et constitue un véritable outil dans le bilan des patientes présentant des densités mammaires asymétriques focales dont la majorité se présente comme un tissu mammaire normal et des pathologies bénignes. MOTS CLES: Sein, Asymétrie focale, Échographie, Mammographie.

Assessing breast arterial calcification in mammograms and its implications for atherosclerotic cardiovascular disease risk.

PURPOSE: Breast arterial calcifications (BAC) are incidentally observed on mammograms, yet their implications remain unclear. We investigated lifestyle, reproductive, and cardiovascular determinants of BAC in women undergoing mammography screening. Further, we investigated the relationship between BAC, coronary arterial calcifications (CAC) and estimated 10-year atherosclerotic cardiovascular (ASCVD) risk. METHODS: In this cross-sectional study, we obtained reproductive history and CVD risk factors from 215 women aged 18 or older who underwent mammography and cardiac computed tomographic angiography (CCTA) within a 2-year period between 2007 and 2017 at hospital. BAC was categorized as binary (present/absent) and semi-quantitatively (mild, moderate, severe). CAC was determined using the Agatston method and recorded as binary (present/absent). Adjusted odds ratios (ORs) and 95 % confidence intervals (CIs) were calculated, accounting for age as a confounding factor. ASCVD risk over a 10-year period was calculated using the Pooled Cohort Risk Equations. RESULTS: Older age, systolic and diastolic blood pressures, higher parity, and younger age at first birth (≤28 years) were significantly associated with greater odds of BAC. Women with both BAC and CAC had the highest estimated 10-year risk of ASCVD (13.30 %). Those with only BAC (8.80 %), only CAC (5.80 %), and no BAC or CAC (4.40 %) had lower estimated 10-year risks of ASCVD. No association was detected between presence of BAC and CAC. CONCLUSIONS: These findings support the hypothesis that BAC on a screening mammogram may help to identify women at potentially increased risk of future cardiovascular disease without additional cost and radiation exposure.

Assessing the malignancy of suspicious breast microcalcifications: the role of contrast enhanced mammography.

PURPOSE: To assess the role of contrast-enhanced mammography (CEM) in predicting the malignancy of breast calcifications. MATERIAL AND METHODS: We retrospectively evaluated patients with suspicious calcifications (BIRADS 4) who underwent CEM and stereotactic vacuum-assisted biopsy (VAB) at our institution. We assessed the sensitivity (SE), specificity (SP), positive predictive value (PPV) and negative predictive value (NPV) of CEM in predicting malignancy of microcalcifications with a 95% confidence interval; we performed an overall analysis and a subgroup analysis stratified into group A-low risk (BIRADS 4a) and group B-medium/high risk (BIRADS 4b-4c). We then evaluated the correlation between enhancement and tumour proliferation index (Ki-67) for all malignant lesions. RESULTS: Data from 182 patients with 184 lesions were collected. Overall the SE of CEM in predicting the malignancy of microcalcifications was 0.70, SP was 0.85, the PPV was 0.82, the NPV was 0.76 and AUC was 0.78. SE in group A was 0.89, SP was 0.89, PPV was 0.57, NPV was 0.98 and AUC was 0.75. SE in group B was 0.68, SP was 0.80, PPV was 0.87, NPV was 0.57 and AUC was 0.75. Among malignant microcalcifications that showed enhancement (N = 52), 61.5% had Ki-67 ≥ 20% and 38.5% had low Ki-67 values. Among the lesions that did not show enhancement (N = 22), 90.9% had Ki-67 < 20% and 9.1% showed high Ki-67 values 20%. CONCLUSIONS: The absence of enhancement can be used as an indicative parameter for the absence of disease in cases of low-suspicious microcalcifications, but not in intermediate-high suspicious ones for which biopsy remains mandatory and can be used to distinguish indolent lesions from more aggressive neoplasms, with consequent reduction of overdiagnosis and overtreatment.

Multimodality Imaging of Benign and Malignant Diseases of the Nipple-Areolar Complex.

The nipple-areolar complex (NAC), a unique anatomic structure of the breast, encompasses the terminal intramammary ducts and skin appendages. Several benign and malignant diseases can arise within the NAC. As several conditions have overlapping symptoms and imaging findings, understanding the distinctive nipple anatomy, as well as the clinical and imaging features of each NAC disease process, is essential. A multimodality imaging approach is optimal in the presence or absence of clinical symptoms. The authors review the ductal anatomy and anomalies, including congenital abnormalities and nipple retraction. They then discuss the causes of nipple discharge and highlight best practices for the imaging workup of pathologic nipple discharge, a common condition that can pose a diagnostic challenge and may be the presenting symptom of breast cancer. The imaging modalities used to evaluate and differentiate benign conditions (eg, dermatologic conditions, epidermal inclusion cyst, mammary ductal ectasia, periductal mastitis, and nonpuerperal abscess), benign tumors (eg, papilloma, nipple adenoma, and syringomatous tumor of the nipple), and malignant conditions (eg, breast cancer and Paget disease of the breast) are reviewed. Breast MRI is the current preferred imaging modality used to evaluate for NAC involvement by breast cancer and select suitable candidates for nipple-sparing mastectomy. Different biopsy techniques (US -guided biopsy and stereotactic biopsy) for sampling NAC masses and calcifications are described. This multimodality imaging approach ensures an accurate diagnosis, enabling optimal clinical management and patient outcomes. ©RSNA, 2024 Test Your Knowledge questions for this article are available in the supplemental material.

Interpretable Radiomic Signature for Breast Microcalcification Detection and Classification.

Breast microcalcifications are observed in 80% of mammograms, and a notable proportion can lead to invasive tumors. However, diagnosing microcalcifications is a highly complicated and error-prone process due to their diverse sizes, shapes, and subtle variations. In this study, we propose a radiomic signature that effectively differentiates between healthy tissue, benign microcalcifications, and malignant microcalcifications. Radiomic features were extracted from a proprietary dataset, composed of 380 healthy tissue, 136 benign, and 242 malignant microcalcifications ROIs. Subsequently, two distinct signatures were selected to differentiate between healthy tissue and microcalcifications (detection task) and between benign and malignant microcalcifications (classification task). Machine learning models, namely Support Vector Machine, Random Forest, and XGBoost, were employed as classifiers. The shared signature selected for both tasks was then used to train a multi-class model capable of simultaneously classifying healthy, benign, and malignant ROIs. A significant overlap was discovered between the detection and classification signatures. The performance of the models was highly promising, with XGBoost exhibiting an AUC-ROC of 0.830, 0.856, and 0.876 for healthy, benign, and malignant microcalcifications classification, respectively. The intrinsic interpretability of radiomic features, and the use of the Mean Score Decrease method for model introspection, enabled models' clinical validation. In fact, the most important features, namely GLCM Contrast, FO Minimum and FO Entropy, were compared and found important in other studies on breast cancer.

Mammographically detected breast clustered microcalcifications localized by chest thin-section computed tomography.

BACKGROUND: To explore the capability and clinical significance of chest thin-section computed tomography (CT) for localization of mammographically detected clustered microcalcifications. METHODS: A total of 69 patients with 71 mammographically detected clustered microcalcifications received surgical biopsy under the guidance of mammography (MG), CT was used to localize calcifications combined with MG if calcifications can be seen on CT. Intraoperative mammography of the specimens were performed in all cases for identification of the resected microcalcifications. The clinical, imaging and pathological information of these patients were analyzed. RESULTS: A total of 42 (59.15%) cases of calcifications were localized by CT + MG, 29 (40.85%) cases were guided only by the mammography. All suspicious calcifications on the mammography were successfully removed. Pathological results showed 42 cases were cancer, 23 cases were benign, and 6 cases were atypical hyperplasia. The mean age in the CT + MG group was older than that of the MG group (54.12 vs. 49.27 years; P = 0.014). The maximum diameter of clusters of microcalcifications on mammography in the CT + MG group was larger than that of the MG group [(cranio-caudal view, 1.52 vs. 0.61 mm, P = 0.000; mediolateral oblique (MLO) view, 1.53 vs. 0.62 mm, P = 0.000)]. The gray value ratio (calcified area / paraglandular; MLO, P = 0.004) and the gray value difference (calcified area - paraglandular; MLO, P = 0.005) in the CT + MG group was higher than that of the MG group. Multivariate analysis showed that the max diameter of clusters of microcalcifications (MLO view) was a significant predictive factor of localization by CT in total patients (P = 0.001). CONCLUSIONS: About half of the mammographically detected clustered microcalcifications could be localized by thin-section CT. Maximum diameter of clusters of microcalcifications (MLO view) was a predictor of visibility of calcifications by CT. Chest thin-section CT may be useful for localization of calcifications in some patients, especially for calcifications that are only visible in one view on the mammography.

I saw the "breast within a breast" sign.

The "breast within a breast" sign is used to describe the appearance of a breast hamartoma, also known as a fibroadenolipoma. A breast hamartoma is a benign mass made up of the same tissues that are found in a normal breast, giving the appearance of a breast within a breast on mammography. The "breast within a breast" sign is pathognomonic for a breast hamartoma and can help confidently diagnose these masses as benign without the need for further imaging or biopsy.

A single-institution retrospective evaluation of noninvasive localization for non-palpable breast microcalcification.

TECHNIQUE: From January 1, 2018, to December 31, 2021, we localized the breast microcalcification of 40 patients before the surgical excision. We measured the distance between the nipple and the center of the calcification on the CC view and the ML view, respectively. The operation proceeded around the intersection between two lines, slightly larger than the diameter of the microcalcification. We also analyze the pathological findings. RESULTS: All 40 patients successfully detected calcification by mammograms preoperatively using the method mentioned above. 38 patients have the microcalcification removal within the one-time operation, while the other two underwent an extended lumpectomy. 20 of 40 calcifications (50 %) were malignant and 12(30 %) were precancerous lesions. In the group of women older than 45 years old, the percentages of malignant and atypical hyperplasias are 56.25 % (18/32) and 31.25 % (10/32) respectively. CONCLUSION: Our non-invasive method of preoperative localization is safe and cost-effective. Furthermore, initial observations suggest that there may be a link between age and malignant microcalcification.

Underreported and underrecognized: a comprehensive imaging review of breast injury.

Breast injury is commonly encountered yet it remains significantly underreported. Injury to the breast may arise from either primary mechanisms or secondary or iatrogenic mechanisms. Primary mechanisms of breast injury include blunt force, seat-belt, penetrating, and thermal injury. Secondary or iatrogenic mechanisms of breast injury include breast biopsy or intervention as well as operative intervention and cardiopulmonary resuscitation. The severity of breast injury arising from these mechanisms is broad, ranging from breast contusion to avulsion. Sequelae of breast injury include fat necrosis and Mondor's disease. Radiologists play an integral role in the evaluation and management of breast injury both in the acute and non-acute settings. In the acute setting, radiologists must be able to recognize breast injury arising from primary mechanisms or iatrogenic or secondary mechanisms and to identify rare but potentially life-threatening complications promptly to ensure timely, appropriate management. In the non-acute setting, radiologists must be able to discern the sequalae of breast injury from other processes to prevent potentially unnecessary further evaluation and intervention. Nonetheless, though breast injury is commonly encountered there remain few guidelines and a lack of established recommendations for the evaluation and management of breast injury. We provide a comprehensive multi-modality imaging review of breast injury arising in the acute setting as well as the sequela of breast injury arising in the non-acute setting. Moreover, we provide an overview of the management of breast injury.

The "teacup sign": Significance in breast imaging.

Milk of calcium (MOC) is a term used for sedimented calcifications within small cysts (Milk of Calcium - an overview|ScienceDirect Topics, n.d.). MOC in the breast is a benign entity and present in 4-6% of women that undergo diagnostic mammography (Park et al., 2008).2 Calcium particles within cysts produce 'teacup'-shaped calcifications on true lateral views, and smudged calcifications on craniocaudal (CC) views (Veloso Gomes et al., n.d.).3 On the CC projection, the calcifications will have a cloudlike or smudgy appearance like tea leaves in the bottom of a teacup (Milk of Calcium - an overview|ScienceDirect Topics, n.d.). Because this is a characteristic benign finding, there is no need for the patient to undergo a biopsy.

Demystifying Breast Disease Markers.

Breast imaging radiologists regularly perform image-guided biopsies of suspicious breast lesions based on features that are associated with a likelihood of malignancy ranging from 2% to greater than 95% (Breast Imaging Reporting and Data System categories 4 and 5). As diagnostic partners, pathologists perform histopathologic assessment of these tissue samples to confirm a diagnosis. Correlating the imaging findings with the histopathologic results is an integral aspect of multidisciplinary breast care. Assessment of radiologic-pathologic concordance is vital in guiding appropriate management, as it enables identification of discordant results, minimizing the chance of misdiagnosis. Undersampling can lead to false-negative results, with the frequencies of false-negative diagnoses varying on the basis of multiple factors, including biopsy type (eg, core needle, vacuum-assisted needle), needle gauge, and type of lesion sampled at biopsy (ie, mass, calcifications, asymmetry, architectural distortion). Improving a radiologist's knowledge of macroscopic and microscopic breast anatomy and more common breast diseases and their expected imaging findings ensures more accurate radiologic-pathologic correlation and management recommendations. The histopathologic and molecular characteristics of biopsy-sampled breast lesions aid in making an accurate diagnosis. Hematoxylin-eosin staining provides critical morphologic details, whereas immunohistochemical staining enables molecular characterization of many benign and malignant lesions, which is critical for tailored treatment. The authors review commonly encountered benign and malignant breast diseases, their corresponding histopathologic phenotypes, and the histopathologic markers that are essential to clinching the diagnosis of these entities. As part of a multidisciplinary team that provides optimal patient care, radiologists should be knowledgeable of the foundations of histopathologic diagnosis and the implications for patient management to ensure appropriate radiologic-pathologic concordance. ©RSNA, 2023 Quiz questions for this article are available in the supplemental material.

Challenges in Interpretation of US Breast Findings in the Emergency Setting.

Emergencies in breast imaging are infrequent but not rare. Although infectious conditions such as mastitis and breast abscess are the most common breast diseases encountered in acute care settings, other entities that may require additional imaging or different treatment approaches are also seen and include traumatic injury and breast cancer. While mammography is widely available for breast evaluation in outpatient facilities, most emergency departments do not have mammography units. This makes evaluation of patients with breast disease incomplete in the acute care setting and emphasizes the role of appropriate US techniques for interpretation. It also highlights the importance of effective sonographer-to-radiologist communication to ensure patient safety and diagnostic accuracy, especially in an era of increasing adoption of teleradiology. The authors discuss the challenges in image acquisition and remote interpretation that are commonly faced by radiologists when they assess breast anomalies in the emergency setting. They present strategies to overcome these challenges by describing techniques for proper US evaluation, highlighting the importance of sonographer-radiologist communication, defining the goals of the evaluation, reviewing common differential diagnoses, and providing appropriate follow-up recommendations. ©RSNA, 2023 Quiz questions for this article are available in the supplemental material.

Benign and malignant breast diseases during pregnancy and lactation: a diagnostic challenge.

OBJECTIVE: To determine the frequency of breast cancer associated with pregnancy and lactation, and to evaluate the lesions on ultrasound. Methods: The descriptive, observational study was conducted at the Dow Institute of Radiology, DUHS, Karachi from December 2020 to August 2021, and comprised of pregnant and lactating women with clinically palpable breast lumps and/or painful breast. The margins, orientation, echo pattern and associated features of the lesions were studied on ultrasound and were assigned a Breast Imaging Reporting and Data System grade. All the lumps were followed and ultrasound-guided core needle biopsy for histopathology was done of grades IV and V cases. Incidence and Accuracy of ultrasound for diagnosis of pregnancy-associated breast cancer was estimated. Data was analysed using SPSS 26. RESULTS: Of the 237 women, 19(8%) were pregnant and 218(92%) were lactating. The overall mean age was 28.4±5.5 years. Ultrasound findings for lactating and pregnant women were significantly different (p=0.05). Significant association of Breast Imaging Reporting and Data System grades III, IV and V lesions with heterogeneous echo texture of mass was seen (p<0.001). Biopsy was performed in 20(8.4%) cases, and 12(60%) of them had benign results on histopathology. CONCLUSIONS: A variety of benign and malignant breast diseases were found in women during pregnancy and lactation phases.