OBJECTIVE: To characterize associations of microcalcifications (calcs) with benign breast disease lesion subtypes and assess whether tissue calcs affect risks of ductal carcinoma in situ (DCIS) and invasive breast cancer (IBC).
METHODS: We analyzed detailed histopathologic data for 4,819 BBD biopsies from a single institution cohort (2002-2013) followed for DCIS or IBC for a median of 7.4 years for cases (N = 338) and 11.2 years for controls. Natural language processing was used to identify biopsies containing calcs based on pathology reports. Univariable and multivariable regression models were applied to assess associations with BBD lesion type and age-adjusted Cox proportional hazard regressions were performed to model risk of IBC or DCIS stratified by the presence or absence of calcs.
RESULTS: Calcs were identified in 2063 (42.8%) biopsies. Calcs were associated with older age at BBD diagnosis (56.2 versus 49.0 years; P < 0.001). Overall, the risk of developing IBC or DCIS did not differ significantly between patients with calcs (HR 1.13, 95% CI 0.90, 1.41) as compared to patients without calcs. Stratification by BBD severity or subtype, age at BBD biopsy, outcomes of IBC versus DCIS, and mammography technique (screen-film versus full-field digital mammography) did not significantly alter association between calcs and risk.
CONCLUSIONS: Our analysis of calcs in BBD biopsies did not find a significant association between calcs and risk of breast cancer.

Dedicated breast CT is an imaging modality that provides true 3D imaging of the breast with many advantages over current conventional breast imaging modalities. The addition of intravascular contrast increases the sensitivity of breast CT substantially. As such, there are immediate potential applications in the clinical workflow. These include using breast CT to replace much of the traditional diagnostic workup when faced with indeterminate breast lesions. Contrast-enhanced breast CT may be appropriate as a supplemental screening tool for women at high risk of breast cancer, similar to breast MRI. In addition, emerging studies are demonstrating the utility of breast CT in neoadjuvant chemotherapy tumor response monitoring as well as planning for surgical treatment options. While short exam times and fully 3D imaging in a noncompressed position are advantages of this modality, limited coverage of chest wall/axilla due to prone positioning and use of ionizing radiation are drawbacks. To date, several studies have reported on the performance characteristics of this promising modality.

UNASSIGNED: We aim to determine the combination of X-ray spectrum and detector scintillator thickness that maximizes the detectability of microcalcification clusters in dedicated cone-beam breast CT.
UNASSIGNED: A cascaded linear system analysis was implemented in the spatial frequency domain and was used to determine the detectability index using numerical observers for the imaging task of detecting a microcalcification cluster with 0.17 mm diameter calcium carbonate spheres. The analysis considered a thallium-doped cesium iodide scintillator coupled to a complementary metal-oxide semiconductor detector and an analytical filtered-back-projection reconstruction algorithm. Independent system parameters considered were the scintillator thickness, applied X-ray tube voltage, and X-ray beam filtration. The combination of these parameters that maximized the detectability index was considered optimal.
UNASSIGNED: Prewhitening, nonprewhitening, and nonprewhitening with eye filter numerical observers indicate that the combination of 0.525 to 0.6 mm thick scintillator, 70 kV, and 0.25 to 0.4 mm added copper filtration maximized the detectability index at a mean glandular dose (MGD) of 4.5 mGy.
UNASSIGNED: Using parallel cascade systems\' analysis, the combination of parameters that could maximize the detection of microcalcifications was identified. The analysis indicates that a harder beam than that used in current practice may be beneficial for the task of detecting microcalcifications at an MGD suitable for breast cancer screening.

OBJECTIVE: To assess the role of contrast-enhanced mammography (CEM) in predicting the malignancy of breast calcifications.
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.

UNASSIGNED: Breast cancer (BC) is the most frequently diagnosed cancer and the leading cause of cancer-related death among women worldwide. For locally advanced diseases and high-risk tumors, neoadjuvant therapy (NAT) is the treatment of choice. Some studies show that mammographic density (MD) tumor margins and the presence of microcalcifications play a prognostic role in BC patients. Hence, the objective of this retrospective study was to assess if MD could predict the response to NAT among different molecular subtypes of BC patients undergoing NAT at The \"Prof. Dr I. Chiricuta\" Oncology Institute of Cluj-Napoca, Romania (IOCN). Furthermore, the association between MD, tumor margins and the presence of microcalcifications with clinico-pathological data was analyzed.
UNASSIGNED: Eighty-four breast cancer patients diagnosed and treated at IOCN were included in this study. The morphological characteristics of the tumors were framed according to the BIRADS lexicon. The presence or absence of microcalcifications was also assessed. First, the significance of associations between breast density, margins and microcalcifications and clinico-pathological parameters of the patients were tested with Fisher or Fisher-Freeman-Halton Exact Test. Next, using multinomial logistic regression, we modelled the associations between the pathological response measured by Miller Payne and Residual cancer burden (RCB) systems and the BI-RADS. Variables having significant univariate tests were selected as candidates for the multivariable analysis (adjusted model).
UNASSIGNED: Breast densities were significantly associated with the age of the patients (p=0.01), number of positive lymph nodes (p=0.037), margins (p=0.002) and combined categories of Miller-Payne (p=0.034) and RCB pathological response (p=0.021). Margins was significantly associated with ki67 proliferation index (p=0.029), estrogen receptor (ER) (p=0.007), progesterone receptor (PR) (p=0.019), molecular subtype (p<0.001) and the number of clinically observed positive lymph nodes at diagnosis (p=0.019).
UNASSIGNED: In our cohort, BC patients with lower MD had higher odds of achieving pCR following NAT, suggesting the role of MD as a clinical prognostic marker. Larger multicenter studies are warranted to validate the prognostic value of MD, which could aid in patients stratification based on their likelihood to respond to NAT.

The rupture of an atherosclerotic plaque cap overlying a lipid pool and/or necrotic core can lead to thrombotic cardiovascular events. In essence, the rupture of the plaque cap is a mechanical event, which occurs when the local stress exceeds the local tissue strength. However, due to inter- and intra-cap heterogeneity, the resulting ultimate cap strength varies, causing proper assessment of the plaque at risk of rupture to be lacking. Important players involved in tissue strength include the load-bearing collagenous matrix, macrophages, as major promoters of extracellular matrix degradation, and microcalcifications, deposits that can exacerbate local stress, increasing tissue propensity for rupture. This review summarizes the role of these components individually in tissue mechanics, along with the interplay between them. We argue that to be able to improve risk assessment, a better understanding of the effect of these individual components, as well as their reciprocal relationships on cap mechanics, is required. Finally, we discuss potential future steps, including a holistic multidisciplinary approach, multifactorial 3D in vitro model systems, and advancements in imaging techniques. The obtained knowledge will ultimately serve as input to help diagnose, prevent, and treat atherosclerotic cap rupture.

OBJECTIVE: We retrospectively investigated clinical, radiological, and pathological features of B3 lesions associated with the risk of subsequent upgrade to malignancy.
METHODS: We included consecutive vacuum-assisted biopsies (VABs) performed during 2011-2020 on suspicious microcalcifications not associated with other radiological signs diagnosed as B3 lesions and followed by surgical excision (SE) with definitive histological examination. Multiple logistic regression models were fitted to identify independent predictors of malignancy.
RESULTS: Out of the 366 B3 lesions included, 56 (15.3 %, 95 % CI 11.8-19.4 %) had upgraded to malignancy at SE: of these, 42/366 (11.5 %, 95 % CI 8.4-15.2 %) and 14/366 (3.8 %, 95 % CI 2.1-6.3 %) were in situ and invasive carcinoma, respectively. At univariate analysis, variables positively associated with upgrade to malignancy were age ≥ 60 years (p = 0.008), mixed morphology (p = 0.018), scattered distribution (p = 0,001), extension of microcalcifications > 10 mm (p = 0.001), and mixed B3 lesion (p = 0.017). Among B3 subtypes, the highest rates of upgrade were observed for AIDEP, LCIS/LIN2, FEA + AIDEP, FEA + LCIS/LIN2, and FEA + AIDEP + LCIS/LIN2 (24.6 %, 21.4 %, 25.3 %, 20.0 % and 40.0 % respectively), while FEA and ALH/LIN1 had a lower rates of upgrade (7.5 % and 3.7 %, respectively). Multiple logistic regression analysis confirmed as risk factors older age (p = 0.029), larger extension (p = 0.001) and mixed morphology (p = 0.007) of microcalcifications, AIDEP (p = 0.011) among pure B3 lesions, and FEA + AIDEP (p = 0.001) and FEA + AIDEP + LCIS/LIN2 (p = 0.037) among mixed B3 lesions.
CONCLUSIONS: Based on our findings, vacuum-assisted excision is reasonable as definitive management for FEA and ALH/LIN1, while SE should remain the mainstay of treatment for AIDEP and LCIS/LIN2, whose upgrade rates are too high to safely recommend VAE.

Breast cancer screening through mammography is crucial for early detection, yet the demand for mammography services surpasses the capacity of radiologists. Artificial intelligence (AI) can assist in evaluating microcalcifications on mammography. We developed and tested an AI model for localizing and characterizing microcalcifications.
Three expert radiologists annotated a dataset of mammograms using histology-based ground truth. The dataset was partitioned for training, validation, and testing. Three neural networks (AlexNet, ResNet18, and ResNet34) were trained and evaluated using specific metrics including receiver operating characteristics area under the curve (AUC), sensitivity, and specificity. The reported metrics were computed on the test set (10% of the whole dataset).
The dataset included 1,000 patients aged 21-73 years and 1,986 mammograms (180 density A, 220 density B, 380 density C, and 220 density D), with 389 malignant and 611 benign groups of microcalcifications. AlexNet achieved the best performance with 0.98 sensitivity, 0.89 specificity of, and 0.98 AUC for microcalcifications detection and 0.85 sensitivity, 0.89 specificity, and 0.94 AUC of for microcalcifications classification. For microcalcifications detection, ResNet18 and ResNet34 achieved 0.96 and 0.97 sensitivity, 0.91 and 0.90 specificity and 0.98 and 0.98 AUC, retrospectively. For microcalcifications classification, ResNet18 and ResNet34 exhibited 0.75 and 0.84 sensitivity, 0.85 and 0.84 specificity, and 0.88 and 0.92 AUC, respectively.
The developed AI models accurately detect and characterize microcalcifications on mammography.
AI-based systems have the potential to assist radiologists in interpreting microcalcifications on mammograms. The study highlights the importance of developing reliable deep learning models possibly applied to breast cancer screening.
• A novel AI tool was developed and tested to aid radiologists in the interpretation of mammography by accurately detecting and characterizing microcalcifications. • Three neural networks (AlexNet, ResNet18, and ResNet34) were trained, validated, and tested using an annotated dataset of 1,000 patients and 1,986 mammograms. • The AI tool demonstrated high accuracy in detecting/localizing and characterizing microcalcifications on mammography, highlighting the potential of AI-based systems to assist radiologists in the interpretation of mammograms.

UNASSIGNED: Microcalcifications persist even if a patient with breast cancer achieves pathologic complete response (pCR) as confirmed by surgery after neoadjuvant treatment (NAT). In practice, surgeons tend to remove all the microcalcifications. This study aimed to explore the correlation between changes in the extent of microcalcification after NAT and pathological tumor response and compare the accuracy of mammography (MG) and magnetic resonance imaging (MRI) in predicting the size of residual tumors.
UNASSIGNED: This was a retrospective study which included a consecutive series of patients in Guangdong Provincial People\'s Hospital. Between January 2010 and January 2020, 127 patients with breast cancer and Breast Imaging Reporting and Data System (BI-RADS) 4-5 microcalcifications were included in this study. The maximum diameter of the microcalcifications on MG and lesion enhancement on MRI pre- and post-NAT were measured. The correlations between the changes in residual microcalcifications on MG and pCR were analyzed. Intraclass correlation coefficients (ICCs) were computed between the extent of the residual microcalcifications, residual enhancement, and residual tumor size.
UNASSIGNED: There were no statistically significant differences in the changes in microcalcifications after NAT according to the RECIST criteria on MRI (P=0.09) and Miller-Payne grade (P=0.14). MRI showed a higher agreement than did residual microcalcifications on MG in predicting residual tumor size (ICC: 0.771 vs. 0.097).
UNASSIGNED: MRI is more accurate for evaluating residual tumor size in breast cancer. In our study, the extent of microcalcifications on MG after NAT had nearly no correlation with the pathological size of the residual tumor. Therefore, residual tumors with microcalcifications may not necessarily be a contraindication to breast-conserving surgery.

OBJECTIVE: Information evaluating the efficacy of 2D synthesized mammography (2Ds) reconstructions in microcalcification detection is limited. This study used stereotactic biopsy data for microcalcifications to evaluate the stepwise implementation of 2Ds in screening mammography. The study aim was to identify whether 2Ds + digital breast tomosynthesis (DBT) is non-inferior to 2D digital mammography (2DM) + 2Ds + DBT, 2DM + DBT, and 2DM in identifying microcalcifications undergoing further diagnostic imaging and stereotactic biopsy.
METHODS: Retrospective stereotactic biopsy data were extracted following 151,736 screening mammograms of healthy women (average age, 56.3 years; range, 30-89 years), performed between 2012 and 2019. The stereotactic biopsy data were separated into 2DM, 2DM + DBT, 2DM + 2Ds + DBT, and 2Ds + DBT arms and examined using Fisher\'s exact test to compare the detection rates of all cancers, invasive cancers, DCIS, and ADH between modalities for patients undergoing stereotactic biopsy of microcalcifications.
RESULTS: No statistical significance in cancer detection was seen for 2Ds + DBT among those calcifications that underwent stereotactic biopsy when comparing the 2Ds + DBT to 2DM, 2DM + DBT, and 2DM + 2Ds + DBT imaging combinations.
CONCLUSIONS: These data suggest that 2Ds + DBT is non-inferior to 2DM + DBT in detecting microcalcifications that will undergo stereotactic biopsy.