INTRODUCTION: Breast cancer is a leading cause of cancer death among women, and its age-standardised incidence rate is one of the highest in Asia. We aimed to review studies on barriers to breast cancer screening to inform future policies in Singapore. METHOD: This was a literature review of both quantitative and qualitative studies published between 2012 and 2020 using PubMed, Google Scholar and Cochrane databases, which analysed the perceptions and behaviours of women towards breast cancer screening in Singapore. RESULTS: Through a thematic analysis based on the Health Belief Model, significant themes associated with low breast cancer screening uptake in Singapore were identified. The themes are: (1) high perceived barriers versus benefits, including fear of the breast cancer screening procedure and its possible outcomes, (2) personal challenges that impede screening attendance and paying for screening and treatment, and (3) low perceived susceptibility to breast cancer. CONCLUSION Perceived costs/barriers vs benefits of screening appear to be the most common barriers to breast cancer screening in Singapore. Based on the barriers identified, increasing convenience to get screened, reducing mammogram and treatment costs, and improving engagement with support groups are recommended to improve the screening uptake rate in Singapore.
Breast Neoplasms/epidemiology* ; Early Detection of Cancer ; Female ; Health Knowledge, Attitudes, Practice ; Humans ; Mammography ; Mass Screening ; Singapore/epidemiology*

In order to overcome the shortcomings of high false positive rate and poor generalization in the detection of microcalcification clusters regions, this paper proposes a method combining discriminative deep belief networks (DDBNs) to automatically and quickly locate the regions of microcalcification clusters in mammograms. Firstly, the breast region was extracted and enhanced, and the enhanced breast region was segmented to overlapped sub-blocks. Then the sub-block was subjected to wavelet filtering. After that, DDBNs model for breast sub-block feature extraction and classification was constructed, and the pre-trained DDBNs was converted to deep neural networks (DNN) using a softmax classifier, and the network is fine-tuned by back propagation. Finally, the undetected mammogram was inputted to complete the location of suspicious lesions. By experimentally verifying 105 mammograms with microcalcifications from the Digital Database for Screening Mammography (DDSM), the method obtained a true positive rate of 99.45% and a false positive rate of 1.89%, and it only took about 16 s to detect a 2 888 × 4 680 image. The experimental results showed that the algorithm of this paper effectively reduced the false positive rate while ensuring a high positive rate. The detection of calcification clusters was highly consistent with expert marks, which provides a new research idea for the automatic detection of microcalcification clusters area in mammograms.
Algorithms ; Breast Neoplasms/diagnostic imaging* ; Calcinosis/diagnostic imaging* ; Early Detection of Cancer ; Humans ; Mammography ; Neural Networks, Computer

Diagnosis, Differential ; Female ; Granulomatous Mastitis/drug therapy* ; Humans ; Mammography

Mammography is the primary screening method for breast cancers. However, the sensitivity of mammographic screening is lower for dense breasts, which are an independent risk factor for breast cancers. Automated breast ultrasound (ABUS) is used as an adjunct to mammography for screening breast cancers in asymptomatic women with dense breasts. It is an effective screening modality with diagnostic accuracy comparable to that of handheld ultrasound (HHUS). Radiologists should be familiar with the unique display mode, imaging features, and artifacts in ABUS, which differ from those in HHUS. The purpose of this study was to provide a comprehensive review of the clinical significance of dense breasts and ABUS screening, describe the unique features of ABUS, and introduce the method of use and interpretation of ABUS.]]>
Artifacts ; Breast Neoplasms ; Breast ; Early Detection of Cancer ; Female ; Humans ; Mammography ; Mass Screening ; Methods ; Risk Factors ; Ultrasonography

OBJECTIVE: To evaluate the interpretive performance and inter-observer agreement on digital mammographs among radiologists and to investigate whether radiologist characteristics affect performance and agreement. MATERIALS AND METHODS: The test sets consisted of full-field digital mammograms and contained 12 cancer cases among 1000 total cases. Twelve radiologists independently interpreted all mammograms. Performance indicators included the recall rate, cancer detection rate (CDR), positive predictive value (PPV), sensitivity, specificity, false positive rate (FPR), and area under the receiver operating characteristic curve (AUC). Inter-radiologist agreement was measured. The reporting radiologist characteristics included number of years of experience interpreting mammography, fellowship training in breast imaging, and annual volume of mammography interpretation. RESULTS: The mean and range of interpretive performance were as follows: recall rate, 7.5% (3.3–10.2%); CDR, 10.6 (8.0–12.0 per 1000 examinations); PPV, 15.9% (8.8–33.3%); sensitivity, 88.2% (66.7–100%); specificity, 93.5% (90.6–97.8%); FPR, 6.5% (2.2–9.4%); and AUC, 0.93 (0.82–0.99). Radiologists who annually interpreted more than 3000 screening mammograms tended to exhibit higher CDRs and sensitivities than those who interpreted fewer than 3000 mammograms (p = 0.064). The inter-radiologist agreement showed a percent agreement of 77.2–88.8% and a kappa value of 0.27–0.34. Radiologist characteristics did not affect agreement. CONCLUSION: The interpretative performance of the radiologists fulfilled the mammography screening goal of the American College of Radiology, although there was inter-observer variability. Radiologists who interpreted more than 3000 screening mammograms annually tended to perform better than radiologists who did not.
Area Under Curve ; Breast ; Fellowships and Scholarships ; Mammography ; Mass Screening ; Medical Audit ; Observer Variation ; ROC Curve ; Sensitivity and Specificity

Breast magnetic resonance imaging (MRI) has been increasingly utilized, especially in screening for high-risk cases, because of its high sensitivity and superior ability to detect cancers as compared with mammography and ultrasound. Several limitations such as higher cost, longer examination time, longer interpretation time, and low availability have hindered the wider application of MRI, especially for screening of average-risk women. To overcome some of these limitations and increase access to MRI screening, an abbreviated breast MRI protocol has been introduced. Abbreviated breast MRI is becoming popular and challenges the status quo. This review aims to present an overview of abbreviated MRI, discuss the current findings, and introduce ongoing prospective trials.
Breast Neoplasms ; Breast ; Female ; Humans ; Magnetic Resonance Imaging ; Mammography ; Mass Screening ; Prospective Studies ; Ultrasonography

PURPOSE: Women with dense breast are known to be at high risk for breast cancer, but their prevalence and number of Korean women are unknown. The current study was to investigate the distribution of mammographic breast density by age of women undergoing screening mammography, and to estimate the prevalence of Korean women with dense breasts, quantitatively. MATERIALS AND METHODS: For obtaining a nationwide representative sample, 6,481 mammograms were collected from 86 screening units participated in the National Cancer Screening Program for breast cancer. Based on the American College of Radiology Breast Imaging Reporting and Data System classification, breast density was evaluated by six breast radiologists, qualitatively. We applied these breast density distributions to age-specific counts of the Korean women population derived to mid-year 2017 to estimate the number of Korean women with dense breasts. RESULTS: Overall, 54.4% (95% confidence interval [CI], 52.9% to 55.8%) of women 40 to 69 years of age had heterogeneously or extremely dense breasts, and this proportion was inversely associated with age. Based on the age distribution of Korean women, we estimated that 6,083,000 women (95% CI, 5,919,600 to 6,245,600) age 40-69 years in Korean have dense breasts. Women aged 40-49 years (n=3,450,000) accounted for 56.7% of this group. CONCLUSION: More than half of Korean women aged 40 and over have dense breasts. To prevent breast cancer effectively and efficiently, it is necessary to develop a new personalized prevention strategy considering her status of breast density.
Age Distribution ; Breast Neoplasms ; Breast ; Classification ; Cross-Sectional Studies ; Early Detection of Cancer ; Female ; Humans ; Information Systems ; Korea ; Mammography ; Mass Screening ; Prevalence

OBJECTIVE: To evaluate the value of digital breast tomosynthesis (DBT) in diagnosis of dense breast lesions. METHODS: Clinical and pathological data of 163 patients (58 benign lesions, 122 malignant lesions, and 180 lesions in total) with breast lesions undergoing surgical treatment in Shaoxing Central Hospital from January 2017 to December 2018 were retrospectively analyzed. The lesions were classified into non-homogeneous dense gland type and extremely dense gland type according to BI-RADS creterion. Breast MRI and DBT examinations were performed before the surgery. ROC curve was generated and the diagnostic efficacy of two examination methods for dense breast lesions was evaluated with pathological results as the gold standard. The detection rate, diagnostic accuracy of benign and malignant breast lesions were compared between two methods using chi-square test. The accuracy of lesion size preoperatively evaluated by MRI and DBT was analyzed by Pearson correlation. RESULTS: The detection rate and diagnostic accuracy for benign breast lesions by MRI were higher than those by DBT (91.4% vs. 75.9%, =5.098, <0.05 and 89.7% vs. 67.2%, =8.617, <0.01). But there were no significant differences in detection rate and accuracy for malignant lesions by MRI and DBT (98.4% vs. 95.1%, =2.068, >0.05 and 94.3% vs. 91.8%, =0.569, >0.05). The areas under the ROC curves of MRI, DBT based on BI-RADS classification were 0.910 and 0.832, respectively (=1.860, >0.05). The sensitivities of MRI, DBT to breast lesions were 93.3% and 86.7%, and the specificities were 68.3% and 79.1%. DBT and MRI measurements were positively correlated with pathological measurements (=0.887 and 0.949, all <0.01). CONCLUSIONS DBT can effectively diagnose benign and malignant breast lesions under dense gland background, and it has similar diagnostic efficacy with MRI for breast malignant lesions.
Breast Neoplasms ; Female ; Humans ; Magnetic Resonance Imaging ; Mammography ; ROC Curve ; Retrospective Studies

Objective To compare the values of dynamic enhanced magnetic resonance imaging(DCE-MRI),digital breast tomosynthesis(DBT),and digital mammography(DM)in the early detection and diagnosis of breast cancer.Methods We retrospectively analyzed the clinical and imaging data of 65 cases with early breast cancer confirmed by surgical pathology from June 2017 to December 2018.All patients underwent breast DCE-MRI,DM and DBT before surgery.The receiver operating characteristic(ROC)curves were drawn,with the pathological results as the gold standard,to evaluate the diagnostic performance of different examination methods.The areas under ROC curves(AUCs)were compared using test.The differences among DCE-MRI,DBT and DM in detecting early breast cancer were compared using chi-square test in terms of positive rates,accuracy,sensitivity,and specificity.Pearson correlation analysis was performed to assess the accuracy of these imaging methods in detecting the size of early breast cancer.Results The AUCs of DCE-MRI,DBT,and DM based on the BI-RADS classification for early diagnosis of breast cancer were 0.910,0.832,and 0.700,respectively(=2.132,=0.001);the sensitivity of DCE-MRI,DBT,and DM for early breast cancer was 92.3%,70.8%,and 52.5%,the specificity was 65.0%,85.0%,and 79.3%,and the accuracy was 83.1%,70.8%,and 50.8%,indicating that DCE-MRI(=15.330,=0.0001) and DBT(=5.450,=0.020) had significantly higher diagnostic accuracy than DM.The measurement results of DM,DBT,and DCE-MRI were positively correlated with the pathological measurements(=0.781,=0.847,=0.946;all <0.01). Conclusions DCE-MRI and DBT have higher positive rates and accuracies than DM in detecting early breast cancer.Medical institutions where DCE-MRI is still not available can use DBT to improve the early detection of breast cancer.
Breast ; diagnostic imaging ; Breast Neoplasms ; diagnostic imaging ; Female ; Humans ; Magnetic Resonance Imaging ; Mammography ; methods ; Retrospective Studies

OBJECTIVE: To develop a digital breast tomosynthesis (DBT) imaging system with optimizes imaging chain. METHODS: Based on 3D tomography and DBT imaging scanning, we analyzed the methods for projection data correction, geometric correction, projection enhancement, filter modulation, and image reconstruction, and established a hardware testing platform. In the experiment, the standard ACR phantom and high-resolution phantom were used to evaluate the system stability and noise level. The patient projection data of commercial equipment was used to test the effect of the imaging algorithm. RESULTS: In the high-resolution phantom study, the line pairs were clear without confusing artifacts in the images reconstructed with the geometric correction parameters. In ACR phantom study, the calcified foci, cysts, and fibrous structures were more clearly defined in the reconstructed images after filtering and modulation. The patient data study showed a high contrast between tissues, and the lesions were more clearly displayed in the reconstructed image. CONCLUSIONS This DBT imaging system can be used for mammary tomography with an image quality comparable to that of commercial DBT systems to facilitate imaging diagnosis of breast diseases.
Algorithms ; Artifacts ; Breast ; diagnostic imaging ; Female ; Humans ; Mammography ; methods ; Phantoms, Imaging ; Radiographic Image Enhancement ; methods