BI-RADS Research Articles

Diagnostic value of strain elastography and shear wave elastography in differentiating benign and malignant breast lesions.

Conventional B-mode breast ultrasonography, though the primary modality to determine benign or malignant nature of a solid breast lesion, sometimes encounters overlapping sonographic morphological features in a single lesion. Elastography leads to improvement by evaluating the structural aspects and characterization of the lesion as benign or malignant on the basis of multi-parametric assessment. Determine the role of strain elastography (SE) and shear wave elastography (SWE) in differentiating benign and malignant breast lesions. Cross sectional SETTING: Radiology department of hospital PATIENTS AND METHODS: Patients meeting inclusion criteria referred to our hospital for ultrasonography followed by biopsy or surgical excisions were examined with B-mode ultrasonography and by both strain and shear wave elastography. Mean values of SE and SWE in benign and malignant breast lesions, determination of cutoff using AUC curves and sensitivity and specificity of both techniques. One hundred breast lesions from 95 consecutive patients. The mean (SD) strain elastography ratio in the overall patient population was 4.1 (2.0). Cutoff for benign vs. malignant lesions was 2.86 on the ROC curve. The AUC was 0.911 (95%CI; 0.835-0.988: SE, 0.039) with a sensitivity of 95.8% and a specificity of 89.3%. For the SWE kPa values, the ROC curve showed the AUC was 0.929 (95% CI, 0.870-0.988; SE: 0.030, P<.001). Assigning 45.3 as a cut off value provided a sensitivity of 95.8% with a specificity of 85.7%; the positive predictive value was 94.5% and the negative predictive value was 89.6%. The Breast Imaging Reporting and Data System (BI-RADS) category alone was able to differentiate between benign and malignant lesions with a sensitivity of 91.7% and a specificity 100% keeping the cut off value between 4a and 4b. The area under the ROC curve was 0.979. Combining the three (BI-RADS + SE + SWE) distinguished benign vs. malignant lesions with a sensitivity up to 100% and specificity up to 96.3%. Combining SE and SWE as a complementary tool with conventional B-mode ultrasonography has a significant potential for better characterization of solid breast lesions and decreasing unnecessary biopsies of BI-RADS IVa lesions. Single institution study. None.

Assessment Challenges of Echogenic Breast Lesions

An echogenic breast mass is defined as a hyperechoic lesion compared with subcutaneous adipose tissue at ultrasonography (US). This is in accordance with the US lexicon of the Breast Imaging Reporting and Data System (BI-RADS) of the American College of Radiology. Although most echogenic solid breast masses identified on ultrasound imaging are benign, hyper-echogenicity alone does not exclude malignancy. Approximately 0.5% of malignant breast lesions appear echogenic. Therefore, upon finding a solid, echogenic mass on ultrasound, it is important to correlate with the mammographic findings to decide on the necessity of a biopsy. The case reports in this paper confirm that similar-looking masses on ultrasound imaging can have a different diagnosis.

Breast ultrasound in Chinese hospitals: A cross-sectional study of the current status and influencing factors of BI-RADS utilization and diagnostic accuracy

SummaryBackgroundWith the growing demand for breast screening in public health services and clinical care, ultrasound departments in China are facing tremendous challenges.MethodsA cross-sectional nationwide survey was conducted in 5,460 departments providing ultrasound diagnoses in mainland China from 2020 to 2021. The survey included general information about the ultrasound department, the characteristics of sonologists, the use of Breast Imaging Reporting and Data System (BI-RADS) templates, and the diagnostic accuracy rate of breast cancer ultrasound.FindingsThere were on average 2.25 sonologists per 10,000 patients in mainland China per year. The average utilization rate of BI-RADS in Chinese hospitals was 87.02%. The GDP per capita of the province (P = 0.008), whether the hospital was specialized (P = 0.002) or a Tier 3 facility (P < 0.001), the percentage of doctors with master's and doctoral degrees (P < 0.001) and doctors ≤35 years (P = 0.005) were significantly and independently associated with the utilization rate of BI-RADS. The average diagnostic accuracy rate of breast cancer ultrasound in Chinese hospitals was 73.64%, and we observed significant positive associations between GDP per capita (P = 0.02), BI-RADS utilization rate (P = 0.019), and breast cancer ultrasound diagnostic accuracy.InterpretationThe utilization of BI-RADS templates effectively improved the diagnostic accuracy of ultrasound. Moreover, the survey summarized the current situation of departments and sonologists providing breast ultrasound diagnosis in mainland China, which helped monitor the development of the discipline and provide information for administrators to meet the growing demand.FundingThis work was supported by Natural Science Foundation of Beijing (7202156) and Foundation of ihecc (2019-C-0646-2).

Stereotactic breast biopsies: Radiological-pathological concordance in a South African referral unit.

BackgroundStereotactic breast biopsies have become the gold standard for tissue diagnosis in non-palpable, sonographically occult breast abnormalities seen on mammogram. Only limited data exist in South Africa on the correlation between imaging findings and stereotactic biopsy histology.ObjectivesTo describe the mammographic findings and histological diagnosis in patients who underwent stereotactic breast biopsy at a referral hospital. In addition, to evaluate the proportion of malignancy in each Breast Imaging Reporting and Data System (BI-RADS) category.MethodA retrospective review of stereotactic breast biopsies was performed. Imaging characteristics (including BI-RADS category) and histological diagnosis were recorded. Using histopathology, cases were classified as benign, high-risk or malignant.ResultsA total of 131 biopsies, from 123 patients, were included in the study. Most biopsies were performed on asymptomatic patients (79.3%, 104/131). The majority were categorised as BI-RADS 4 and demonstrated calcifications. Histology revealed a malignant diagnosis in 40 (30.5%) patients, a high-risk lesion in 8 (6.1%) patients and a benign diagnosis in 83 (63.4%) patients. There was a stepwise increase in the proportion of malignancy from BI-RADS category 3 to 5. When compared with surgical histology, the stereotactic biopsies demonstrated an overall ductal carcinoma in situ (DCIS) underestimation rate of 10.3%.ConclusionDespite resource restrictions, stereotactic breast biopsies performed in a South African context produce radiological-pathological concordance in keeping with BI-RADS guidelines, as well as with local and international studies.

Invited Commentary: Evolving Management of COVID-19 Vaccine-related Axillary Adenopathy.

Invited Commentary: Evolving Management of COVID-19 Vaccine-related Axillary Adenopathy.

Family history of breast cancer, mammographic breast density and breast cancer risk: Findings from a cohort study of Korean women

BackgroundThis study investigated whether the association between family history of breast cancer in first-degree relatives and breast cancer risk varies by breast density. MethodsWomen aged 40 years and older who underwent screening between 2009 and 2010 were followed up until 2020. Family history was assessed using a self-reported questionnaire. Using Breast Imaging Reporting and Data System (BI-RADS), breast density was categorized into dense breast (heterogeneously or extremely dense) and non-dense breast (almost entirely fatty or scattered areas of fibro-glandular). Cox regression model was used to assess the association between family history and breast cancer risk. ResultsOf the 4,835,507 women, 79,153 (1.6%) reported having a family history of breast cancer and 77,238 women developed breast cancer. Family history led to an increase in the 5-year cumulative incidence in women with dense- and non-dense breasts. Results from the regression model with and without adjustment for breast density yielded similar HRs in all age groups, suggesting that breast density did not modify the association between family history and breast cancer. After adjusting for breast density and other factors, family history of breast cancer was associated with an increased risk of breast cancer in all three age groups (age 40–49 years: aHR 1.96, 95% confidence interval [CI] 1.85–2.08; age 50–64 years: aHR 1.70, 95% CI 1.58–1.82, and age ≥65 years: aHR 1.95, 95% CI 1.78–2.14). ConclusionFamily history of breast cancer and breast density are independently associated with breast cancer. Both factors should be carefully considered in future risk prediction models of breast cancer.

Which combination of different ultrasonography modalities is more appropriate to diagnose breast cancer?: A network meta-analysis (a PRISMA-compliant article).

Background:Abundant amount of literature that analyze the various detection of different ultrasound methods, no comprehensive literature that investigates the diagnostic values of breast cancer (BC) by different ultrasonography modalities through a network meta-analysis (NMA) has been made available. Each imaging diagnostic examination has its own advantages and disadvantages, and any imaging examination is not enough to make an accurate diagnosis of the disease. Thus, this study aimed to compare diagnostic values among different ultrasonography modalities, including the information of 2-dimension, stiffness and blood flow, by a network meta-analysis in the hopes of understanding which imaging methods are better and which combination of different ultrasonography modalities is more appropriate to diagnose BC.Methods:We made use of Cochrane Library, PubMed, and Embase in order to obtain literature and papers. The combination analysis of both direct and indirect evidence in terms of sensitivity, specificity, positive predictive value (PPV), negative predictive value(NPV) and accuracy was conducted so as to assess the odds ratios (ORs) and surface under the cumulative ranking curve (SUCRA) values of the 8 different ultrasound methods.Results:A total of 36 eligible diagnostic tests regarding 8 ultrasound methods were included in the study. According to this network meta-analysis, Breast Imaging Reporting and Data System (BI-RADS) 4b exhibited higher specificity, PPV, and accuracy and lower sensitivity and NPV than BI-RADS 4a. Contrast-enhanced ultrasound (CEUS) had the highest sensitivity, PPV, NPV and accuracy and superb microvascular imaging (SMI) had the highest specificity among color Doppler flow imaging (CDFI), power Doppler imaging(PDI), SMI and CEUS. There was no significant difference in diagnostic indexes between SMI and CEUS. Shear wave elastrography (SWE) had higher PPV and accuracy and lower sensitivity, specificity NPV than strain elastography (SE).Conclusion:The results of this network meta-analysis suggested more appropriate combination of different ultrasound modalities is BI-RADS 4b, SMI, and SWE for the diagnosis of breast cancer.

Features of breast cancer initially assessed as probably benign on ultrasound: A retrospective study.

We evaluated the features of breast cancers initially assessed as probably benign at ultrasound (US).Of the 7098 patients who underwent breast cancer surgery at our institution between 2014 and 2016, 179 lesions in 178 patients who had both a prior US with Breast Imaging Reporting and Data System (BI-RADS) category 3 assessment and a recent US with a diagnosis of breast cancer were enrolled. Prior and recent US findings and category were retrospectively reassessed in line with the BI-RADS Atlas and analyzed.Of the 179 BI-RADS 3 lesions, 105 (59%) were retrospectively reassessed to category 4 and 74 (41%) retained category 3. Noncircumscribed margin, irregular shape, posterior enhancement, and nonparallel orientation were more frequently observed in the reassessment category 4 group than in the reassessment category 3 group (94% vs 43%, 81% vs 19%, 16% vs 4%, 14% vs 0%, respectively). The recent US revealed that 150 of the 179 lesions (84%) had > 20% size increase, and 121 (68%) showed morphologic changes. Margin was the most frequently observed morphologic feature to change (41%, 73/179).Care should be taken to look for subtle but suspicious US features and changes in mass, especially of margin, for early diagnosis of breast cancer.

Establishment of a deep-learning system to diagnose BI-RADS4a or higher using breast ultrasound for clinical application.

Although the categorization of ultrasound using the Breast Imaging Reporting and Data System (BI‐RADS) has become widespread worldwide, the problem of inter‐observer variability remains. To maintain uniformity in diagnostic accuracy, we have developed a system in which artificial intelligence (AI) can distinguish whether a static image obtained using a breast ultrasound represents BI‐RADS3 or lower or BI‐RADS4a or higher to determine the medical management that should be performed on a patient whose breast ultrasound shows abnormalities. To establish and validate the AI system, a training dataset consisting of 4028 images containing 5014 lesions and a test dataset consisting of 3166 images containing 3656 lesions were collected and annotated. We selected a setting that maximized the area under the curve (AUC) and minimized the difference in sensitivity and specificity by adjusting the internal parameters of the AI system, achieving an AUC, sensitivity, and specificity of 0.95, 91.2%, and 90.7%, respectively. Furthermore, based on 30 images extracted from the test data, the diagnostic accuracy of 20 clinicians and the AI system was compared, and the AI system was found to be significantly superior to the clinicians (McNemar test, p < 0.001). Although deep‐learning methods to categorize benign and malignant tumors using breast ultrasound have been extensively reported, our work represents the first attempt to establish an AI system to classify BI‐RADS3 or lower and BI‐RADS4a or higher successfully, providing important implications for clinical actions. These results suggest that the AI diagnostic system is sufficient to proceed to the next stage of clinical application.

Histopathological Correlation of Breast Carcinoma with Breast Imaging-Reporting and Data System.

BackgroundBreast cancer is one of the commonest malignancy cancer worldwide and the Breast Imaging-Reporting and Data System (BI-RADS) classification has been extensively utilised as an adjunct to histopathological examination for malignant breast diseases. This study aims to analyse the concordance between radiological and histopathological findings, demonstrate the high predictive value in the BI-RADS category and evaluate the impact of these findings on surgical intervention and treatment outcome.MethodsThis is a single-centre retrospective study, analysing patients who underwent radiological examination with BI-RADS categories 3, 4 and 5 followed by histopathological examination confirming the diagnosis based on breast core biopsy or excision specimen over 3 years.ResultsA total of 316 specimens from 310 patients were included in this study; 75 cases were categorised BI-RADS 3, 166 as BI-RADS 4 and 75 as BI-RADS 5. Of these, 66 (20.8%) patients in BI-RADS category 3, 82 (25.9%) in BI-RADS category 4 and 5 (1.6%) in BI-RADS category 5 were reported as benign on histopathological examination. Malignant cases were reported in nine (2.8%) cases in BI-RADS category 3, 84 (26.6%) in BI-RADS category 4 and 70 (22.2%) in BI-RADS category 5. The positive predictive value (PPV), negative predictive value (NPV), sensitivity and specificity were 63.9%, 88%, 94.48%, and 43.14%, respectively.ConclusionThere is a significant correlation between BI-RADS score and histopathological results of breast cancer. A higher BI-RADS score is associated with a higher possibility of malignancy (P < 0.001). Our institution’s performance is comparable to other previously published data.

A comprehensive comparison of circulating tumor cells and breast imaging modalities as screening tools for breast cancer in Chinese women.

BackgroundCirculating tumor cells (CTCs) have been recognized as a sensitive biomarker for breast cancer (BC). This study aimed to comprehensively compare CTC with imaging modalities, including ultrasonography, mammography, and contrast-enhanced magnetic resonance imaging (MRI) in screening for BC in Chinese women.MethodsThree hundred forty-three participants were enrolled in this study, including 102 treatment-naive BC patients, 177 with breast benign diseases (BBD) and 64 healthy female patients. All participants underwent CTC testing and at least one of the following examinations, ultrasonography, mammography, and MRI at the Second Affiliated Hospital of Zhejiang University between December 2017 and November 2020. CTCs were quantitatively assessed using cell counting (CTC detection rate/counts) and categorically examined using a cutoff value (CTC classification). The diagnostic power of CTC tests and imaging modalities, including accuracy and capability to predict clinicopathological characteristics of BC, were evaluated and compared.ResultsCTC classification with a cutoff value of 2 showed a “good” diagnostic accuracy of 0.889 for early- to mid-stage BC comparable to breast imaging modalities using Breast Imaging-Reporting and Data System (BI-RADS). MRI demonstrated the highest sensitivity of 0.872 for BC, and CTC classification had the highest specificity of 0.938. A relatively low sensitivity was found for mammography in this cohort of patients. Successful detection of BC by CTC detection rate/counts, but not CTC classification, correlated with two important clinicopathological features, American Joint Committee on Cancer (AJCC) stage and tumor-node-metastasis (TNM) stage. The detection power of certain imaging modalities was also associated with AJCC stage (ultrasonography, p = 0.0438 and MRI, p = 0.0422) and lymph node metastasis (ultrasonography, 0.0157). There were clear correlations between CTC tests (counts or classification) and imaging BI-RADS scoring system in detecting positive BC cases (p < 0.05). Further correlation analysis suggested that CTC quantity, but not CTC classification, had the capability to predict clinicopathological traits of BC that were identified by ultrasonography.ConclusionsCTC tests have a diagnostic potency comparable to breast imaging modalities, and may be used as an alternative screening tool for BC.

The value of noncontrast MRI in evaluating breast imaging reporting and data system category 0 lesions on digital mammograms.

BackgroundBenign and malignant diagnosis of nonpalpable breast imaging reporting and data system (BI-RADS) category 0 lesions on digital mammograms (DMs) is very important. We compared the diagnostic performance of non-contrast-enhanced magnetic resonance imaging (MRI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for them. We sought to evaluate BI-RADS category 0 lesions using 3 MRI sequences: short tau inversion recovery (STIR), STIR combined with high b value diffusion-weighted imaging (STIR-DWI), and DCE-MRI.MethodsWe retrospectively reviewed 114 breast DMs rated as nonpalpable BI-RADS category 0 lesions in 112 patients from January 2014 to June 2019. STIR, high b value DWI, and DCE-MRI were performed for all patients. Two breast radiologists read individual sequences (STIR, DWI, DCE-MRI) and pairs of sequences (STIR-DWI) to detect BI-RADS category 0 lesions in DMs. Receiver operating characteristic (ROC) curve analysis was used to assess diagnostic performance according to a best valuable comparator that combined MRI imaging, clinical, and pathological data.ResultsAmong of 114 lesions (the median age of patients was 47 years; the median size of the lesion was 19 mm), 32 (48.5%) malignant lesions were missed by STIR, 9 (13.6%) malignant lesions were missed by STIR-DWI, and 3 (4.5%) malignant lesions were missed by DCE-MRI. The principal finding of our study was that STIR-DWI and DCE-MRI showed higher diagnostic accuracy than did STIR (P<0.01). STIR-DWI showed higher accuracy [area under the curve (AUC) =0.858; sensitivity =87.8%] for BI-RADS category 0 lesions in DMs than did STIR (AUC =0.754; sensitivity =51.5%), while the performance was comparable to that of DCE-MRI (AUC =0.884; sensitivity =95.5%).ConclusionsUsing pairs of sequences (STIR-DWI) is a non-contrast-enhanced MRI technique and had an equal diagnostic performance in distinguishing benign from malignant lesions among nonpalpable BI-RADS category 0 lesions to that of DCE-MRI. As a result, STIR-DWI as having the potential to improve the safety and efficacy in of breast cancer screening, especially in nonpalpable BI-RADS category 0 lesions at in DMs.

The value of imaging combined with clinicopathological features in the diagnosis of high-risk breast lesions.

BackgroundThe upgrade of high-risk breast lesions (HRLs) is closely related to subsequent treatment, but the current predictors for upgrade are limited to intratumoral features of single imaging mode.MethodsWe retrospectively reviewed 230 HRLs detected by mammography, ultrasound, and magnetic resonance imaging (MRI) before biopsy at the Fudan University Cancer Hospital from January 2017 to March 2018. The clinical features, imaging data according to the Breast Imaging Reporting and Data System (BI-RADS) lexicon, and tumor upgrade situation were received. Based on the different risks of upgrade reported, the lesions were classified into high-risk I [HR-I, with atypical hyperplasia (AH)] and high-risk II (HR-II, without AH). We analyzed the association between clinicopathological and imaging factors and upgrade. We used the receiver operating characteristic (ROC) curve to compare the efficacy of three imaging modes for predicting upgrade.ResultsWe included 230 HRLs in 230 women in the study, and the overall upgrade rate was 20.4% (47/230). The upgrade rate was higher in HR-I compared to HR-II (38.5% vs. 4.1%, P<0.01). In patients with AH, estrogen receptor-positive (ER+) patients accounted for 81.0% (64/79). For all HRLs and HR-I, in clinical characteristics, age, maximum size of lesion, and menopausal status were significantly associated with upgrade (P<0.05). In imaging factors, MRI background parenchymal enhancement (BPE), signs of MRI and ultrasound were significantly correlated with upgrade (P<0.05). Patients with negative MRI or ultrasound manifestations had lower upgrade rates (P<0.01). For HR-II, only BPE showed a significant difference between groups (P=0.001). Multifactorial analysis of all HRLs showed that age and BPE were independent predictors of upgrade (P<0.01). The areas under the ROC cure (AUCs) for predicting upgrade in mammography, ultrasound, and MRI were 0.606, 0.590, and 0.913, respectively, indicating that MRI diagnosis was significantly better than mammography and ultrasound (P<0.001).ConclusionsHRLs with AH had a higher rate of upgrade and increased ER expression. Among three imaging modes, MRI was more effective than ultrasound and mammography in diagnosing the upgrade of HRLs. Older age and moderate to marked BPE can indicate malignant upgrade. MRI can provide a certain value for the diagnosis and follow-up of HRLs.

Computer aided diagnosis system for breast density classification in mammograms

Breast cancer is a deadly disease affecting women around the globe. Mass detection in the breast tissue at an early stage can lessen the mortality rate occurring due to breast cancer. Through mammograms, the presence of masses can be detected at an early stage, however, it’s sensitivity and specificity are limited in the case of dense tissues. Identification of the breast density type prior to the detection of mass can lessen the chance of misclassifying a breast tissue as normal or abnormal, which eventually decreases the false negative and false positive rate. The proposed system classifies breast density on the basis of Breast Imaging Reporting and Data System (BI-RADS). The proposed method has explored the effect of local descriptors on breast density classification and various feature-classifier combinations have also been explored for the classification. The proposed method validated on 624 mammograms from the Image Retrieval in Medical Applications (IRMA) version of the Digital Database for Screening Mammography (DDSM) database has produced an accuracy of 73% for multi-class breast density classification using the speeded-up robust features (SURF) and support vector machine (SVM) classifier.

Sociodemographic Determinants in Breast Cancer Screening among Uninsured Women of West Texas.

Background and Objectives: Early detection through appropriate screening is key to curing breast cancer. The Access to Breast Care for West Texas (ABC4WT) program offers no-cost mammography to underserved women in West Texas. The U.S. Preventative Task Force (USPSTF) guidelines are breast cancer screening guidelines which suggest screening for all women at the age of 50 years. The focus of this study was to identify sociodemographic barriers and determinants for breast cancer screenings, as well as screening outcomes, in low income, uninsured, or under-insured communities in West Texas. Materials and Methods: The ABC4WT program’s patient database was queried from 1 November, 2018, to 1 June, 2021, for sociodemographic variables, screening history, and results to identify high-risk groups for outreach. The American College of Radiology’s risk assessment and quality assurance tool, BI-RADS (Breast Imaging-Reporting and Data System), a widely accepted lexicon and reporting schema for breast imaging, was used for risk differentiation. Results: The cancer rate for ABC4WT’s program was significantly higher than the national mean (5.1), at 23.04 per 1000 mammograms. Of the 1519 mammograms performed, women between 40 and 49 years old represented the highest percentages of BI-RADS 4 and 5 (42.0% and 28.0%, respectively; p = 0.049). This age group also received 43.7% of biopsies performed and comprised 28.6% (n = 10) of cancers diagnosed (n = 35) (p = 0.031). Additionally, participants with a monthly household income of less than USD 800/month/person were more likely to result in a cancer diagnosis (70.6%) than higher incomes (29.4%) (p = 0.021). Conclusions: These determinants most starkly impacted women 40–49 years old who would not have been screened by U.S. Preventative Services Task Force (USPSTF) guidelines. This population with increased cancer risk should be encouraged to undergo screening for breast cancer via mammography.

Digital breast tomosynthesis-guided vacuum-assisted biopsy of suspicious calcifications at different sites within one breast: Is biopsy of more than one location needed?

ObjectiveTo investigate how often biopsy of two sites of morphologically similar or equally suspicious calcifications within the same breast yield differing histopathologic results, and how this may affect clinical management. Materials and methodsWe identified patients with two or more sites of calcifications categorized as Breast Imaging Reporting and Data System (BI-RADS) ≥ 4b within the same breast who underwent digital breast tomosynthesis-guided vacuum-assisted biopsy (DBT-guided VAB). We analyzed how often biopsy of two distinct sites yielded the same or differing histopathologic findings. The histopathologic findings were dichotomized into “actionable” and “non-actionable”, depending on the respective further management. We then analyzed how often the consecutive management would have been the same or different. ResultsOf 206 women undergoing DBT-guided VAB at our institution within 24 months, 21 consecutive patients (54 ± 10.2 years; range: 35–71) underwent DBT-guided VAB of two distinct sites of calcifications. Management of histologic findings was the same (both sites actionable or both sites non-actionable) in 12/21 (57 %), different in the remaining 9/21 patients (43 %). Of the nine patients whose differing histologic findings would have led to different clinical management, 4/9 had a high-risk lesion (atypical ductal hyperplasia n = 3, papilloma with epithelial atypia n = 1) vs benign changes (adenosis n = 4), 2/9 had high-grade DCIS vs benign changes (adenosis n = 1, fat necrosis n = 1), and 3/9 had invasive cancer (luminal A n = 2, luminal B n = 1) with high-grade DCIS vs pure high-grade DCIS. ConclusionsMultiple sites of calcifications within the same breast, even when morphologically similar or equally suspicious, may represent different histopathologic findings with different clinical management implications. Accordingly, in the presence of suspicious calcifications at multiple distinct sites within the same breast, biopsy of more than one site of calcification should be considered.

Successful Stereotactic-Guided Vacuum-Assisted Biopsy in the Evaluation of Breast Microcalcifications: A Study in a Single Tertiary Referral Center in the Middle East

Background: Breast microcalcifications are a category of lesions that can lead to malignancies. They remain a major concern in imaging of suspected cases. Vacuum-assisted biopsy (VAB) has been proposed as a safe and effective measure to evaluate microcalcifications. Objectives: The present study aimed to assess the results of VAB for breast microcalcifications. Patients and Methods: This cross-sectional study was conducted on patients with microcalcifications detected on mammograms. Patients were recruited through simple random sampling during 2019 - 2020, based on the inclusion criteria. The inclusion criteria were microcalcifications on mammography, classified as the breast imaging-reporting and data system (BI-RADS) categories 3, 4B, 4C, and 5, and undergoing mammography-guided VAB for the microcalcifications. Patients with missing data and those who could not be followed-up for at least six months were excluded from the study. They were assessed regarding different imaging characteristics of lesions, including the breast density, BI-RADS classification, microcalcification distribution and morphology, and other demographic and clinical features before biopsy. Additionally, the results of stereotactic-guided VAB were assessed for various benign and malignant pathologies of microcalcifications. The results of descriptive and analytical tests for various radiological and pathological features of lesions were reported. Results: A total of 257 patients, with a mean age of 50.3 ± 8.3 yars, were included in this study. Almost half of the patients (n = 125, 48.6%) had a C-grade breast composition. Regarding the BI-RADS classification, 206 (80.2%) patients were diagnosed with 4B lesions, followed by 44 (17.1%) patients with 4C lesions. The assessment of the pattern of microcalcification distribution in imaging showed that more than half of the patients (n = 148, 57.6%) had lesions in multiple groups. The most prevalent morphology of microcalcifications was punctate amorphous (n = 109, 42.4%). The majority of patients (n = 180, 70%) had benign findings in the pathological assessment, and only 69 (26.8%) had malignant features in pathology. The distribution of malignancies differed among various BI-RADS categories. In the 4B category of lesions, there were 166 benign lesions versus 32 malignant lesions, while in the 4C category, there were 10 benign lesions versus 34 malignant lesions (P &lt; 0.001). Conclusion: This study described the findings of successful stereotactic-guided VAB for breast microcalcifications. VAB can be implemented as a promising assessment tool to evaluate suspected breast microcalcifications effectively.

Concerns About Breast Pain: How Useful Is Imaging?

Background: Breast pain is one of the most common reasons for referral to breast imaging. Objectives: This study aimed to determine the diagnostic yield of mammography and sonomammography in women complaining of breast pain in a teaching hospital in Southeast Nigeria. Methods: This descriptive study analyzed the mammographic/sonomammographic images and records of 241 consecutive adult women aged 18 - 81 years with breast pain who presented to the radiology department over three years. A non-random sampling method was employed to select the participants. The extracted variables were patient’s age, positive clinical history of breast pain, laterality of breast pain, type of imaging, presence or absence of lesion, type, and laterality of lesions if present, and Breast Imaging Reporting and Data System (BI-RADS) assignment of imaging findings on mammography and sonomammography. The descriptive analysis of continuous variables and inferential statistics of ordinal data were performed with Microsoft Excel and chi-squared test, respectively. In this study, P &lt; 0.05 was set as the significance level. Results: Most women (20%) with a complaint of breast pain were in the 40 - 44-year age group. Moreover, 32.3%, 33.2%, and 34.4% of the participants had left-sided, right-sided, and bilateral breast pain, respectively. Among the participants, 118 and 123 women had mammography and sonomammography, respectively. Furthermore, 76.3% had normal findings on mammography or sonomammography, and only 23.7% had positive imaging findings on breast imaging. These lesions were mostly observed among the women in the age group of 45 - 49 years. Of those with lesions detected on imaging, 79.2% and 20.8% demonstrated benign and malignant attributes, respectively. Masses with definite benign attributes assigned BI-RADS II were mostly fibroadenomata and cysts. Inferential statistics indicated that unilateral mastalgia was more likely to be associated with a breast lesion, while bilateral mastalgia usually resulted in normal breast imaging findings. Conclusions: Women referring to the Radiology Department with a complaint of breast pain alone are unlikely to have any significant breast imaging finding; hence, imaging serves as a tool for assuaging the anxiety of these patients and reassuring the referring physician. Unilateral but not bilateral mastalgia is likely to yield positive imaging findings, which are largely benign.

Accuracy of ultrasonographic changes during neoadjuvant chemotherapy to predict axillary lymph node response in clinical node-positive breast cancer patients.

PurposeTo evaluate whether changes in ultrasound features during neoadjuvant chemotherapy (NAC) could predict axillary node response in clinically node-positive breast cancer patients.MethodsPatients with biopsy-proven node-positive disease receiving NAC between February 2009 and March 2021 were included. Ultrasound (US) images were obtained using a 5-12-MHz linear array transducer before NAC, after two cycles, and at the completion of NAC. Long and short diameter, cortical thickness, vascularity, and hilum status of the metastatic node were retrospectively reviewed according to breast imaging-reporting and data system (BI-RADS). The included population was randomly divided into a training set and a validation set at a 2:1 ratio using a simple random sampling method. Factors associated with node response were identified through univariate and multivariate analyses. A nomogram combining clinical and changes in ultrasonographic (US) features was developed and validated. The receiver operating characteristic (ROC) and calibration plots were applied to evaluate nomogram performance and discrimination.ResultsA total of 296 breast cancer patients were included, 108 (36.5%) of whom achieved axillary pathologic complete response (pCR) and 188 (63.5%) had residual nodal disease. Multivariate regression indicated that independent predictors of node pCR contain ultrasound features in addition to clinical features, clinical features including neoadjuvant HER2-targeted therapy and clinical response, ultrasound features after NAC including cortical thickness, hilum status, and reduction in short diameter ≥50%. The nomogram combining clinical features and US features showed better diagnostic performance compared to clinical-only model in the training cohort (AUC: 0.799 vs. 0.699, P=0.001) and the validation cohort (AUC: 0.764 vs. 0.638, P=0.027).ConclusionsUltrasound changes during NAC could improve the accuracy to predict node response after NAC in clinically node-positive breast cancer patients.

Radiomics in photon-counting dedicated breast CT: potential of texture analysis for breast density classification

BackgroundWe investigated whether features derived from texture analysis (TA) can distinguish breast density (BD) in spiral photon-counting breast computed tomography (PC-BCT).MethodsIn this retrospective single-centre study, we analysed 10,000 images from 400 PC-BCT examinations of 200 patients. Images were categorised into four-level density scale (a–d) using Breast Imaging Reporting and Data System (BI-RADS)-like criteria. After manual definition of representative regions of interest, 19 texture features (TFs) were calculated to analyse the voxel grey-level distribution in the included image area. ANOVA, cluster analysis, and multinomial logistic regression statistics were used. A human readout then was performed on a subset of 60 images to evaluate the reliability of the proposed feature set.ResultsOf the 19 TFs, 4 first-order features and 7 second-order features showed significant correlation with BD and were selected for further analysis. Multinomial logistic regression revealed an overall accuracy of 80% for BD assessment. The majority of TFs systematically increased or decreased with BD. Skewness (rho -0.81), as a first-order feature, and grey-level nonuniformity (GLN, -0.59), as a second-order feature, showed the strongest correlation with BD, independently of other TFs. Mean skewness and GLN decreased linearly from density a to d. Run-length nonuniformity (RLN), as a second-order feature, showed moderate correlation with BD, but resulted in redundant being correlated with GLN. All other TFs showed only weak correlation with BD (range -0.49 to 0.49, p < 0.001) and were neglected.ConclusionTA of PC-BCT images might be a useful approach to assess BD and may serve as an observer-independent tool.