Mammographic breast density: How it affects performance indicators in screening programmes?

How do AI markings on screening mammograms correspond to cancer location? An informed review of 270 breast cancer cases in BreastScreen Norway

OBJECTIVES

To compare the location of AI markings on screening mammograms with cancer location on diagnostic mammograms, and to classify interval cancers with high AI score as false negative, minimal sign, or true negative.

METHODS

In a retrospective study from 2022, we compared the performance of an AI system with independent double reading according to cancer detection. We found 93% (880/949) of the screen-detected cancers, and 40% (122/305) of the interval cancers to have the highest AI risk score (AI score of 10). In this study, four breast radiologists reviewed mammograms from 126 randomly selected screen-detected cancers and all 120 interval cancers with an AI score of 10. The location of the AI marking was stated as correct/not correct in craniocaudal and mediolateral oblique view. Interval cancers with an AI score of 10 were classified as false negative, minimal sign significant/non-specific, or true negative.

RESULTS

All screen-detected cancers and 78% (93/120) of the interval cancers with an AI score of 10 were correctly located by the AI system. The AI markings matched in both views for 79% (100/126) of the screen-detected cancers and 22% (26/120) of the interval cancers. For interval cancers with an AI score of 10, 11% (13/120) were correctly located and classified as false negative, 10% (12/120) as minimal sign significant, 26% (31/120) as minimal sign non-specific, and 31% (37/120) as true negative.

CONCLUSION

AI markings corresponded to cancer location for all screen-detected cancers and 78% of the interval cancers with high AI score, indicating a potential for reducing the number of interval cancers. However, it is uncertain whether interval cancers with subtle findings in only one view are actionable for recall in a true screening setting.

CLINICAL RELEVANCE STATEMENT

In this study, AI markings corresponded to the location of the cancer in a high percentage of cases, indicating that the AI system accurately identifies the cancer location in mammograms with a high AI score.

KEY POINTS

• All screen-detected and 78% of the interval cancers with high AI risk score (AI score of 10) had AI markings in one or two views corresponding to the location of the cancer on diagnostic images. • Among all 120 interval cancers with an AI score of 10, 21% (25/120) were classified as a false negative or minimal sign significant and had AI markings matching the cancer location, suggesting they may be visible on prior screening. • Most of the correctly located interval cancers matched only in one view, and the majority were classified as either true negative or minimal sign non-specific, indicating low potential for being detected earlier in a real screening setting.

Clinical Significance of Combined Density and Deep-Learning-Based Texture Analysis for Stratifying the Risk of Short-Term and Long-Term Breast Cancer in Screening

Assessing a woman's risk of breast cancer is important for personalized screening. Mammographic density is a strong risk factor for breast cancer, but parenchymal texture patterns offer additional information which cannot be captured by density. We aimed to combine BI-RADS density score 4th Edition and a deep-learning-based texture score to stratify women in screening and compare rates among the combinations. This retrospective study cohort study included 216,564 women from a Danish populations-based screening program. Baseline mammograms were evaluated using BI-RADS density scores (1-4) and a deep-learning texture risk model, with scores categorized into four quartiles (1-4). The incidence rate ratio (IRR) for screen-detected, interval, and long-term cancer were adjusted for age, year of screening and screening clinic. Compared with subgroup B1-T1, the highest IRR for screen-detected cancer were within the T4 category (3.44 (95% CI: 2.43-4.82)-4.57 (95% CI: 3.66-5.76)). IRR for interval cancer was highest in the BI-RADS 4 category (95% CI: 5.36 (1.77-13.45)-16.94 (95% CI: 9.93-30.15)). IRR for long-term cancer increased both with increasing BI-RADS and increasing texture reaching 5.15 (4.31-6.16) for the combination of B4-T4 compared with B1-T1. Deep-learning-based texture analysis combined with BI-RADS density categories can reveal subgroups with increased rates beyond what density alone can ascertain, suggesting the potential of combining texture and density to improve risk stratification in breast cancer screening.

Mammographic Texture versus Conventional Cumulus Measure of Density in Breast Cancer Risk Prediction: A Literature Review

Mammographic textures show promise as breast cancer risk predictors, distinct from mammographic density. Yet, there is a lack of comprehensive evidence to determine the relative strengths as risk predictor of textures and density and the reliability of texture-based measures. We searched the PubMed database for research published up to November 2023, which assessed breast cancer risk associations [odds ratios (OR)] with texture-based measures and percent mammographic density (PMD), and their discrimination [area under the receiver operating characteristics curve (AUC)], using same datasets. Of 11 publications, for textures, six found stronger associations (P < 0.05) with 11% to 508% increases on the log scale by study, and four found weaker associations (P < 0.05) with 14% to 100% decreases, compared with PMD. Risk associations remained significant when fitting textures and PMD together. Eleven of 17 publications found greater AUCs for textures than PMD (P < 0.05); increases were 0.04 to 0.25 by study. Discrimination from PMD and these textures jointly was significantly higher than from PMD alone (P < 0.05). Therefore, different textures could capture distinct breast cancer risk information, partially independent of mammographic density, suggesting their joint role in breast cancer risk prediction. Some textures could outperform mammographic density for predicting breast cancer risk. However, obtaining reliable texture-based measures necessitates addressing various issues. Collaboration of researchers from diverse fields could be beneficial for advancing this complex field.

Test-set results can predict participants' development in breast-screen cancer detection: An observational cohort study

Background and Aim

Test-sets are standardized assessments used to evaluate reader performance in breast screening. Understanding how test-set results affect real-world performance can help refine their use as a quality improvement tool. The aim of this study is to explore if mammographic test-set results could identify breast-screening readers who improved their cancer detection in association with test-set training.

Methods

Test-set results of 41 participants were linked to their annual cancer detection rate change in two periods oriented around their first test-set participation year. Correlation tests and a multiple linear regression model investigated the relationship between each metric in the test-set results and the change in detection rates. Additionally, participants were divided based on their improvement status between the two periods, and Mann-Whitney U test was used to determine if the subgroups differed in their test-set metrics.

Results

Test-set records indicated multiple significant correlations with the change in breast cancer detection rate: a moderate positive correlation with sensitivity (0.688, p < 0.001), a moderate negative correlation with specificity (-0.528, p < 0.001), and a low to moderate positive correlation with lesion sensitivity (0.469, p = 0.002), and the number of years screen-reading mammograms (0.365, p = 0.02). In addition, the overall regression was statistically significant (F (2,38) = 18.456 p < 0.001), with an R² of 0.493 (adjusted R² = 0.466) based on sensitivity (F = 27.132, p < 0.001) and specificity (F = 9.78, p = 0.003). Subgrouping the cohort based on the change in cancer detection indicated that the improved group is significantly higher in sensitivity (p < 0.001) and lesion sensitivity (p = 0.02) but lower in specificity (p = 0.003).

Conclusion

Sensitivity and specificity are the strongest test-set performance measures to predict the change in breast cancer detection in real-world breast screening settings following test-set participation.

A scoping review of programme specific mammographic breast density related guidelines and practices within breast screening programmes

Introduction

High mammographic breast density (MBD) is an independent breast cancer risk factor. In organised breast screening settings, discussions are ongoing regarding the optimal clinical role of MBD to help guide screening decisions. The aim of this scoping review was to provide an overview of current practices incorporating MBD within population-based breast screening programmes and from professional organisations internationally.

Methods

This scoping review was conducted in accordance with the framework proposed by the Joanna Briggs Institute. The electronic databases, MEDLINE (PubMed), EMBASE, CINAHL Plus, Scopus, and Web of Science were systematically searched. Grey literature sources, websites of international breast screening programmes, and relevant government organisations were searched to identify further relevant literature. Data from identified materials were extracted and presented as a narrative summary.

Results

The search identified 78 relevant documents. Documents were identified for breast screening programmes in 18 countries relating to screening intervals for women with dense breasts, MBD measurement, reporting, notification, and guiding supplemental screening. Documents were identified from 18 international professional organisations with the majority of material relating to supplemental screening guidance for women with dense breasts. Key factors collated during the data extraction process as relevant considerations for MBD practices included the evidence base needed to inform decision-making processes and resources (healthcare system costs, radiology equipment, and workforce planning).

Conclusions

This scoping review summarises current practices and guidelines incorporating MBD in international population-based breast screening settings and highlights the absence of consensus between organised breast screening programmes incorporating MBD in current breast screening protocols.

Predicting Breast Cancer Risk Using Radiomics Features of Mammography Images

Mammography images contain a lot of information about not only the mammary glands but also the skin, adipose tissue, and stroma, which may reflect the risk of developing breast cancer. We aimed to establish a method to predict breast cancer risk using radiomics features of mammography images and to enable further examinations and prophylactic treatment to reduce breast cancer mortality. We used mammography images of 4000 women with breast cancer and 1000 healthy women from the 'starting point set' of the OPTIMAM dataset, a public dataset. We trained a Light Gradient Boosting Machine using radiomics features extracted from mammography images of women with breast cancer (only the healthy side) and healthy women. This model was a binary classifier that could discriminate whether a given mammography image was of the contralateral side of women with breast cancer or not, and its performance was evaluated using five-fold cross-validation. The average area under the curve for five folds was 0.60122. Some radiomics features, such as 'wavelet-H_glcm_Correlation' and 'wavelet-H_firstorder_Maximum', showed distribution differences between the malignant and normal groups. Therefore, a single radiomics feature might reflect the breast cancer risk. The odds ratio of breast cancer incidence was 7.38 in women whose estimated malignancy probability was ≥0.95. Radiomics features from mammography images can help predict breast cancer risk.

New Approaches and Recommendations for Risk-Adapted Breast Cancer Screening

Population-based breast cancer screening using mammography as the gold standard imaging modality has been in clinical practice for over 40 years. However, the limitations of mammography in terms of sensitivity and high false-positive rates, particularly in high-risk women, challenge the indiscriminate nature of population-based screening. Additionally, in light of expanding research on new breast cancer risk factors, there is a growing consensus that breast cancer screening should move toward a risk-adapted approach. Recent advancements in breast imaging technology, including contrast material-enhanced mammography (CEM), ultrasound (US) (automated-breast US, Doppler, elastography US), and especially magnetic resonance imaging (MRI) (abbreviated, ultrafast, and contrast-agent free), may provide new opportunities for risk-adapted personalized screening strategies. Moreover, the integration of artificial intelligence and radiomics techniques has the potential to enhance the performance of risk-adapted screening. This review article summarizes the current evidence and challenges in breast cancer screening and highlights potential future perspectives for various imaging techniques in a risk-adapted breast cancer screening approach. EVIDENCE LEVEL: 1. TECHNICAL EFFICACY: Stage 5.

Mammographic density in relation to breast cancer recurrence and survival in women receiving neoadjuvant chemotherapy

Objective

The association between mammographic density (MD) and breast cancer (BC) recurrence and survival remains unclear. Patients receiving neoadjuvant chemotherapy (NACT) are in a vulnerable situation with the tumor within the breast during treatment. This study evaluated the association between MD and recurrence/survival in BC patients treated with NACT.

Methods

Patients with BC treated with NACT in Sweden (2005-2016) were retrospectively included (N=302). Associations between MD (Breast Imaging-Reporting and Data System (BI-RADS) 5^th Edition) and recurrence-free/BC-specific survival at follow-up (Q1 2022) were addressed. Hazard ratios (HRs) for recurrence/BC-specific survival (BI-RADS a/b/c vs. d) were estimated using Cox regression analysis and adjusted for age, estrogen receptor status, human epidermal growth factor receptor 2 status, axillary lymph node status, tumor size, and complete pathological response.

Results

A total of 86 recurrences and 64 deaths were recorded. The adjusted models showed that patients with BI-RADS d vs. BI-RADS a/b/c had an increased risk of recurrence (HR 1.96 (95% confidence interval (CI) 0.98-3.92)) and an increased risk of BC-specific death (HR 2.94 (95% CI 1.43-6.06)).

Conclusion

These findings raise questions regarding personalized follow-up for BC patients with extremely dense breasts (BI-RADS d) pre-NACT. More extensive studies are required to confirm our findings.

Test-set training improves the detection rates of invasive cancer in screening mammography

AIM

To investigate if mammographic test-set participation affects routine breast cancer screening performance.

MATERIALS AND METHODS

Clinical audit data between 2008 and 2018 were collected for 35 breast screen readers who participated in the BreastScreen Reader Assessment Strategy (BREAST) and 22 readers with no history of test-set participation. For BREAST readers, the annual audit data were divided according to the year they completed their first test set, and the same years were used randomly to align and divide the data of non-BREAST readers into pre- and post-test set periods. Multiple audit parameters were inspected retrospectively for the two cohorts to identify how their reading performance has evolved in screening mammography.

RESULTS

Investigating 2 calendar years before and after test-set participation, BREAST and non-BREAST readers recalled lower rates of women in the latter period (p=0.03 and p=0.02, respectively). They also improved their positive predictive value (PPV; p=0.01 and p=0.02, respectively). BREAST readers additionally improved their detection rates of invasive cancer (p=0.02) and all cancers (p=0.01). In an extended 3-year comparison, similar improvements occurred in the recall rate for BREAST (p=0.02) and non-BREAST readers (p=0.02) and in PPV (p=0.001, 0.01, respectively); however, improvements in detection rates also occurred exclusively in BREAST readers' performance for invasive cancer (p=0.04), DCIS (p=0.05), and all cancers (p=0.02); however, significant improvements in detection did not involve <15 mm invasive cancers in both periods. Meanwhile, non-BREAST readers demonstrated a decrease in sensitivity (p=0.02).

CONCLUSION

Participation in test sets is linked to over-time improvements in most audit-measured cancer detection rates.

Chemical Effects on Breast Development, Function, and Cancer Risk: Existing Knowledge and New Opportunities

Population studies show worrisome trends towards earlier breast development, difficulty in breastfeeding, and increasing rates of breast cancer in young women. Multiple epidemiological studies have linked these outcomes with chemical exposures, and experimental studies have shown that many of these chemicals generate similar effects in rodents, often by disrupting hormonal regulation. These endocrine-disrupting chemicals (EDCs) can alter the progression of mammary gland (MG) development, impair the ability to nourish offspring via lactation, increase mammary tissue density, and increase the propensity to develop cancer. However, current toxicological approaches to measuring the effects of chemical exposures on the MG are often inadequate to detect these effects, impairing our ability to identify exposures harmful to the breast and limiting opportunities for prevention. This paper describes key adverse outcomes for the MG, including impaired lactation, altered pubertal development, altered morphology (such as increased mammographic density), and cancer. It also summarizes evidence from humans and rodent models for exposures associated with these effects. We also review current toxicological practices for evaluating MG effects, highlight limitations of current methods, summarize debates related to how effects are interpreted in risk assessment, and make recommendations to strengthen assessment approaches. Increasing the rigor of MG assessment would improve our ability to identify chemicals of concern, regulate those chemicals based on their effects, and prevent exposures and associated adverse health effects.

Reducing Unnecessary Biopsies Using Digital Breast Tomosynthesis and Ultrasound in Dense and Nondense Breasts

Aim: To compare digital breast tomosynthesis (DBT) and ultrasound in women recalled for assessment after a positive screening mammogram and assess the potential for each of these tools to reduce unnecessary biopsies. Methods: This data linkage study included 538 women recalled for assessment from January 2017 to December 2019. The association between the recalled mammographic abnormalities and breast density was analysed using the chi-square independence test. Relative risks and the number of recalled cases requiring DBT and ultrasound assessment to prevent one unnecessary biopsy were compared using the McNemar test. Results: Breast density significantly influenced recall decisions (p < 0.001). Ultrasound showed greater potential to decrease unnecessary biopsies than DBT: in entirely fatty (21% vs. 5%; p = 0.04); scattered fibroglandular (23% vs. 10%; p = 0.003); heterogeneously dense (34% vs. 7%; p < 0.001) and extremely dense (39% vs. 9%; p < 0.001) breasts. The number of benign cases needing assessment to prevent one unnecessary biopsy was significantly lower with ultrasound than DBT in heterogeneously dense (1.8 vs. 7; p < 0.001) and extremely dense (1.9 vs. 5.1; p = 0.03) breasts. Conclusion: Women with dense breasts are more likely to be recalled for assessment and have a false-positive biopsy. Women with dense breasts benefit more from ultrasound assessment than from DBT.

Quantitative Breast Density in Contrast-Enhanced Mammography

Contrast-enhanced mammography (CEM) demonstrates a potential role in personalized screening models, in particular for women at increased risk and women with dense breasts. In this study, volumetric breast density (VBD) measured in CEM images was compared with VBD obtained from digital mammography (DM) or tomosynthesis (DBT) images. A total of 150 women who underwent CEM between March 2019 and December 2020, having at least a DM/DBT study performed before/after CEM, were included. Low-energy CEM (LE-CEM) and DM/DBT images were processed with automatic software to obtain the VBD. VBDs from the paired datasets were compared by Wilcoxon tests. A multivariate regression model was applied to analyze the relationship between VBD differences and multiple independent variables certainly or potentially affecting VBD. Median VBD was comparable for LE-CEM and DM/DBT (12.73% vs. 12.39%), not evidencing any statistically significant difference (p = 0.5855). VBD differences between LE-CEM and DM were associated with significant differences of glandular volume, breast thickness, compression force and pressure, contact area, and nipple-to-posterior-edge distance, i.e., variables reflecting differences in breast positioning (coefficient of determination 0.6023; multiple correlation coefficient 0.7761). Volumetric breast density was obtained from low-energy contrast-enhanced spectral mammography and was not significantly different from volumetric breast density measured from standard mammograms.

Diagnostic efficacy of contrast-enhanced breast MRI versus X-ray mammography in women with different degrees of breast density

BACKGROUND

Detection of breast cancer in women with high breast densities is a clinical challenge.

PURPOSE

To study the influence of different degrees of breast density on the sensitivity of contrast-enhanced breast magnetic resonance imaging (CE-BMRI) versus X-ray mammography (XRM).

MATERIAL AND METHODS

We performed an additional analysis of two large Phase III clinical trials (G1; G2) which included women with histologically proven breast cancers, called "index cancers." Additional cancers were detected during image reading. We compared the sensitivity of CE-BMRI and XRM in women with different breast densities (ACR A→D; Version 5). For each study, six blinded readers evaluated the images. Results are given as the "Median Reader."

RESULTS

A total of 774 patients were included, 169 had additional cancers. While sensitivity of CE-BMRI for detecting all index cancers was independent of breast density (ACR A→D) (G1: 83%→83%; G2: 91%→91%) the sensitivity of XRM declined (ACR A→D) (G1: 79%→62%; G2: 82%→64%). Thus, the sensitivity difference between both imaging modalities in ACR A breasts of 3% (G1) and 9% (G2) increased to 21% (G1) and 26% (G2) in ACR D breasts. Sensitivity of CE-BMRI for detecting at least one additional cancer increased with increasing breast density (ACR A→D) (G1: 50%→73%, G2: 57%→81%). XRM's sensitivity decreased (G1: 34%→20%) or remained stable (G2: 24%→25%).

CONCLUSION

CE-BMRI showed significantly higher sensitivity compared to XRM.

Breast Cancer Knowledge and Practice of Breast Self-Examination among Female University Students, Gaza

Breast cancer is the highest public detected cancer among female population in the majority of countries worldwide. Breast self-examination (BSE) is a useful screening tool to empower women and raise awareness about their breast tissues and help detect any breast abnormalities when they occur. This study aimed to assess the level of female university students' knowledge and practice of BSE. A self-administered questionnaire was used to assess the knowledge about breast cancer and related items, and an observation checklist was used to test practicing BSE using a breast simulator. Eighty-six students participated in the study, 58.1% studying nursing and 41.9% studying clinical nutrition in the third (40.7%) or the fourth level (59.3%). Of them, 24.4% had previous family history of breast cancer. The majority of the students (80.2%) had previous information about breast cancer acquired from different sources, university studies (57%), the Internet (45%), and social media (41%). Findings showed good scores (≥70%) regarding signs and symptoms and risk factors of breast cancer; however, low knowledge scores (<70%) were detected regarding general knowledge about breast cancer disease, methods of early detection and management, and applying steps of practicing BSE. Roughly all the students (96.5%) have heard about BSE, and 69.8% knew the time to do BSE; however, only 31.4% practice it regularly. Three barriers to practice were dominant among students who do not have a breast problem (39.7%), do not know how to do it (37.9%), and being busy 31%. On the other hand, breast cancer early detection purpose and the presence of family history of breast cancer were considered facilitators to regular practice BSE. A statistically significant relationship existed between knowledge about the steps of applying the BSE and regular practicing. A training program should be implemented to increase the level of awareness about BC and practicing BSE.

A Practical, Clinical User-Friendly Format for Breast Ultrasound Report

Objective

Breast ultrasound (BUS) is often performed as an adjunct to mammography in breast cancer screening or for evaluating breast lesions. Our aim was to design a practical and user-friendly format for BUS that could include the details of the Breast Imaging Reporting and Data System.

Materials and Methods

As a team of radiologists and surgeons trained in the management of breast diseases, we gathered and carried out the project in four phases-literature search and collection of present report formats, summarizing key points and preparing the first draft, seeking expert opinion and preparing the final format, and pilot testing-followed by a survey was answered by the research team's radiologists and surgeons.

Results

It produced a list of items to be stated in the BUS report, the final BUS report format, and the pilot format guide. Then, the radiologists used the format in three active ultrasound units in university-affiliated centers, and reports were referred to the surgeons. At the end of the project, the survey showed a high degree of ease of use, clarity, conciseness, comprehensiveness, and well-classified structure of the report format; but radiologists believed that the new organization took more time.

Conclusion

We propose our design as a user-friendly and practical format for BUS reports. It should be used for a longer time and by various ultrasound centers in order to ascertain its benefits.

Developing and validating an individualized breast cancer risk prediction model for women attending breast cancer screening

BACKGROUND

Several studies have proposed personalized strategies based on women's individual breast cancer risk to improve the effectiveness of breast cancer screening. We designed and internally validated an individualized risk prediction model for women eligible for mammography screening.

METHODS

Retrospective cohort study of 121,969 women aged 50 to 69 years, screened at the long-standing population-based screening program in Spain between 1995 and 2015 and followed up until 2017. We used partly conditional Cox proportional hazards regression to estimate the adjusted hazard ratios (aHR) and individual risks for age, family history of breast cancer, previous benign breast disease, and previous mammographic features. We internally validated our model with the expected-to-observed ratio and the area under the receiver operating characteristic curve.

RESULTS

During a mean follow-up of 7.5 years, 2,058 women were diagnosed with breast cancer. All three risk factors were strongly associated with breast cancer risk, with the highest risk being found among women with family history of breast cancer (aHR: 1.67), a proliferative benign breast disease (aHR: 3.02) and previous calcifications (aHR: 2.52). The model was well calibrated overall (expected-to-observed ratio ranging from 0.99 at 2 years to 1.02 at 20 years) but slightly overestimated the risk in women with proliferative benign breast disease. The area under the receiver operating characteristic curve ranged from 58.7% to 64.7%, depending of the time horizon selected.

CONCLUSIONS

We developed a risk prediction model to estimate the short- and long-term risk of breast cancer in women eligible for mammography screening using information routinely reported at screening participation. The model could help to guiding individualized screening strategies aimed at improving the risk-benefit balance of mammography screening programs.

The mammographic breast density distribution of Finnish women with breast cancer and comparison of breast density reporting using the 4th and 5th editions of the Breast Imaging-Reporting and Data System

PURPOSE

To examine the breast density distribution in patients diagnosed with breast cancer in an eastern Finnish population and to examine the changes in breast density reporting patterns between the 4^th and 5^th editions of the Breast Imaging-Reporting and Data System (BI-RADS).

METHOD

821 women (mean age 62.8 ± 12.2 years, range 28-94 years) with breast cancer were included in this retrospective study and their digital mammographic examinations were assessed semi-automatically and then visually by two radiologists in accordance with the 4^th and 5^th editions of the BI-RADS. Intraclass correlation coefficients (ICCs) were used to evaluate interobserver reproducibility. Chi-square tests were used to examine the associations between the breast density distribution and age or body mass index (BMI).

RESULTS

Interobserver reproducibility of the visual assessment was excellent, with an ICCr = 0.93. The majority of breast cancers occurred in fatty breasts (93.8 %) when density was assessed according to the 4^th edition of the BI-RADS. The distributions remained constant after correction for age and BMI. Using the 5^th edition, there was an overall 50.2 % decrease in almost entirely fatty (p <  0.001), 19.4 % increase in scattered fibroglandular (p <  0.001), 28.7 % increase in heterogeneously dense (p <  0.001), and 2.1 % increase in extremely dense (p <  0.001) categories.

CONCLUSIONS

Most breast cancers in eastern Finland occur in fatty breasts with an area density of < 50 %. Assessing breast density using the 5^th edition of the BI-RADS greatly increased denser assessments.

The effect of breast density on the missed lesion rate in screening digital mammography determined using an adjustable-density breast phantom tailored to Japanese women

OBJECTIVE

Despite the high risk of missing lesions in mammography, the missed lesion rate is yet to be clinically established. Further, no breast phantoms with adjustable breast density currently exist. We developed a novel, adjustable-density breast phantom with a composition identical to that of actual breasts, and determined the quantitative relationship between breast density and the missed lesion rate in mammography.

METHODS

An original breast phantom consisting of adipose- and fibroglandular-equivalent materials was developed, and a receiver operating characteristic (ROC) study was performed. Breast density, which is the fraction by weight of fibroglandular to total tissue, was adjusted to 25%, 50%, and 75% by arbitrarily mixing the two materials. Microcalcification, mass lesions, and spiculated lesions, each with unique characteristics, were inserted into the phantom. For the above-mentioned fibroglandular densities, 50 positive and 50 negative images for each lesion type were used as case samples for the ROC study. Five certified radiological technologists participated in lesion detection.

RESULTS

The mass-lesion detection rate, according to the area under the curve, decreased by 18.0% (p = 0.0001, 95% Confidence intervals [CI] = 0.1258 to 0.1822) and 37.8% (p = 0.0003, 95% CI = 0.2453 to 0.4031) for breast densities of 50% and 75%, respectively, compared to that for a 25% breast density. A similar tendency was observed with microcalcification; however, spiculated lesions did not follow this tendency.

CONCLUSIONS

We quantified the missed lesion rate in different densities of breast tissue using a novel breast phantom, which is imperative for advancing individualized screening mammography.

Automated breast ultrasound: Supplemental screening for average-risk women with dense breasts

OBJECTIVE

We review ultrasound (US) options for supplemental breast cancer screening of average risk women with dense breasts.

CONCLUSION

Performance data of physician-performed handheld US (HHUS), technologist-performed HHUS, and automated breast ultrasound (AUS) indicate that all are appropriate for adjunctive screening. Volumetric 3D acquisitions, reduced operator dependence, protocol standardization, reliable comparison with previous studies, independence of performance and interpretation, and whole breast depiction on coronal view may favor selection of AUS. Important considerations are workflow adjustments for physicians and staff.

The implications of increased mammographic breast density for breast screening in Jordan

INTRODUCTION

Mammographic breast density is associated with a four to six times increased risk for breast cancer. Mammographic breast density varies by ethnicity, geographical region and age. The aim of this study was to document for the first time the mammographic breast density of Jordanian women and to explore its relationship with age.

METHODS

Mammograms completed at King Abdullah University Hospital (Irbid, Jordan) between January 2016 and August 2018 were retrospectively reviewed and classified for breast density using the American College of Radiology (ACR) Breast Imaging-Reporting and Data System (BI-RADS). Descriptive analyses and Kurskal-Wallis test were used to examine the association between age and mammographic breast density.

RESULTS

A total of 659 mammograms were reviewed. A significant inverse relationship was observed between age and breast density (P < 0.001). In women aged 40-49 years, 83.2% had dense breasts (ACR BI-RADS (c) and (d)). This percentage decreased to 59.8% of women aged 50-59 years; 38.4% of women in their 60s and 37.9% of women aged 70 years or older (ACR BI-RADS (c) only).

CONCLUSION

The mammographic breast density of Jordanian women has been shown to be high across all age groups. Increased mammographic breast density is associated with increased breast cancer risk and renders mammography a less effective technique for the early detection of breast cancer. Breast cancer screening of Jordanian women should be individualised to develop screening protocols and include additional adjunct imaging to best manage women at high risk.

Environmental Influences on Mammographic Breast Density in California: A Strategy to Reduce Breast Cancer Risk

State legislation in many U.S. states, including California, mandates informing women if they have dense breasts on screening mammography, meaning over half of their breast tissue is comprised of non-adipose tissue. Breast density is important to interpret screening sensitivity and is an established breast cancer risk factor. Environmental chemical exposures may play an important role in this, especially during key windows of susceptibility for breast development: in utero, during puberty, pregnancy, lactation, and the peri-menopause. There is a paucity of research, however, examining whether environmental chemical exposures are associated with mammographic breast density, and even less is known about environmental exposures during windows of susceptibility. Now, with clinical breast density scoring being reported routinely for mammograms, it is possible to find out, especially in California, where there are large study populations that can link environmental exposures during windows of susceptibility to breast density. Density scores are now available throughout the state through electronic medical records. We can link these with environmental chemical exposures via state-wide monitoring. Studying the effects of environmental exposure on breast density may provide valuable monitoring and etiologic data to inform strategies to reduce breast cancer risk.