Mammographic breast density and the risk of breast cancer: A systematic review and meta-analysis

[The possible benefit of artificial intelligence in an organized population-related screening program : Initial results and perspective]

BACKGROUND

Mammography screening programs (MSP) have shown that breast cancer can be detected at an earlier stage enabling less invasive treatment and leading to a better survival rate. The considerable numbers of interval breast cancer (IBC) and the additional examinations required, the majority of which turn out not to be cancer, are critically assessed.

OBJECTIVE

In recent years companies and universities have used machine learning (ML) to develop powerful algorithms that demonstrate astonishing abilities to read mammograms. Can such algorithms be used to improve the quality of MSP?

METHOD

The original screening mammographies of 251 cases with IBC were retrospectively analyzed using the software ProFound AI® (iCAD) and the results were compared (case score, risk score) with a control group. The relevant current literature was also studied.

RESULTS

The distributions of the case scores and the risk scores were markedly shifted to higher risks compared to the control group, comparable to the results of other studies.

CONCLUSION

Retrospective studies as well as our own data show that artificial intelligence (AI) could change our approach to MSP in the future in the direction of personalized screening and could enable a significant reduction in the workload of radiologists, fewer additional examinations and a reduced number of IBCs; however, the results of prospective studies are needed before implementation.

Digital breast tomosynthesis for breast cancer diagnosis in women with dense breasts and additional breast cancer risk factors: A systematic review

INTRODUCTION

Digital breast tomosynthesis (DBT) may improve sensitivity in population screening. However, evidence is currently limited on the performance of DBT in patients at a higher risk of breast cancer. This systematic review compares the clinical effectiveness and cost-effectiveness of DBT, digital mammography (DM), and ultrasound, for breast cancer detection in women with dense breasts and additional risk factors.

METHODS

Medline, Embase, and Evidence-Based Medicine Reviews via OvidSP were searched to identify literature from 2010 to August 21, 2023. Selection of studies, data extraction, and quality assessment (using QUADAS-2 and CHEERS) were completed in duplicate. Findings were summarised descriptively and narratively.

RESULTS

Twenty-six studies met pre-specified inclusion criteria. In women with breast symptoms or recalled for investigation of screen-detected findings (19 studies), DBT may be more accurate than DM. For example, in symptomatic women, the sensitivity of DBT + DM ranged from 82.8 % to 92.5 % versus 56.8 %-81.3 % for mammography (DM/synthesised images). However, most studies had a high risk of bias due to participant selection. Evidence regarding DBT in women with a personal or family history of breast cancer, for DBT versus ultrasound alone, and cost-effectiveness of DBT was limited.

CONCLUSIONS

In women with dense breasts and additional risk factors for breast cancer, evidence is limited about the accuracy of DBT compared to other imaging modalities, particularly in those with personal or family history of breast cancer. Future research in this population should consider head-to-head comparisons of imaging modalities to determine the relative effectiveness of these imaging tests.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO registration number CRD42021236470.

Hormone therapy in women with benign breast disease - What little is known and suggestions for clinical implementation

Benign breast disease encompasses a spectrum of lesions within the breast. While some lesions pose no increase in risk, others may elevate the likelihood of developing breast cancer by four- to five-fold. This necessitates a personalized approach to screening and lifestyle optimization for women. The menopausal transition is a critical time for the development of benign breast lesions. Increased detection can be attributed to the heightened precision and utilization of screening mammography, with or without the use of supplemental imaging. While it is widely acknowledged that combined hormone therapy involving estrogen and progesterone may elevate the risk of breast cancer, data from the Women's Health Initiative (WHI) indicates that estrogen-alone therapies may actually reduce the overall risk of cancer. Despite this general understanding, there is a notable gap in information regarding the impact of hormone therapy on the risk profile of women with specific benign breast lesions. This review comprehensively examines various benign breast lesions, delving into their pathophysiology and management. The goal is to enhance our understanding of when and how to judiciously prescribe hormone therapy, particularly in the context of specific benign breast conditions. By bridging this knowledge gap, the review provides valuable insights into optimizing healthcare strategies for women with benign breast disease, and offers a foundation for more informed decision-making regarding hormone therapy.

Artificial Intelligence for Breast Cancer Risk Assessment

Breast cancer risk prediction models based on common clinical risk factors are used to identify women eligible for high-risk screening and prevention. Unfortunately, these models have only modest discriminatory accuracy with disparities in performance in underrepresented race and ethnicity groups. The field of artificial intelligence (AI) and deep learning are rapidly advancing the field of breast cancer risk prediction with the development of mammography-based AI breast cancer risk models. Early studies suggest mammography-based AI risk models may perform better than traditional risk factor-based models with more equitable performance.

Breast Density: Where Are We Now?

Breast density refers to the amount of fibroglandular tissue relative to fat on mammography and is determined either qualitatively through visual assessment or quantitatively. It is a heritable and dynamic trait associated with age, race/ethnicity, body mass index, and hormonal factors. Increased breast density has important clinical implications including the potential to mask malignancy and as an independent risk factor for the development of breast cancer. Breast density has been incorporated into breast cancer risk models. Given the impact of dense breasts on the interpretation of mammography, supplemental screening may be indicated.

Imaging the dense breast

The sensitivity of mammography reduces as breast density increases, which impacts breast screening and locoregional staging in breast cancer. Supplementary imaging with other modalities can offer improved cancer detection, but this often comes at the cost of more false positives. Magnetic resonance imaging and contrast-enhanced mammography, which assess tumour enhancement following contrast administration, are more sensitive than digital breast tomosynthesis and ultrasound, which predominantly rely on the assessment of tumour morphology.

TGF-β signaling: critical nexus of fibrogenesis and cancer

The transforming growth factor-beta (TGF-β) signaling pathway is a vital regulator of cell proliferation, differentiation, apoptosis, and extracellular matrix production. It functions through canonical SMAD-mediated processes and noncanonical pathways involving MAPK cascades, PI3K/AKT, Rho-like GTPases, and NF-κB signaling. This intricate signaling system is finely tuned by interactions between canonical and noncanonical pathways and plays key roles in both physiologic and pathologic conditions including tissue homeostasis, fibrosis, and cancer progression. TGF-β signaling is known to have paradoxical actions. Under normal physiologic conditions, TGF-β signaling promotes cell quiescence and apoptosis, acting as a tumor suppressor. In contrast, in pathological states such as inflammation and cancer, it triggers processes that facilitate cancer progression and tissue remodeling, thus promoting tumor development and fibrosis. Here, we detail the role that TGF-β plays in cancer and fibrosis and highlight the potential for future theranostics targeting this pathway.

Limited impact of adding digital breast tomosynthesis to full field digital mammography in an elevated breast cancer risk population

PURPOSE

To investigate the impact of adding digital breast tomosynthesis (DBT) to full field digital mammography (FFDM) in screening asymptomatic women with an elevated breast cancer life time risk (BCLTR) but without known genetic mutation.

METHODS

This IRB-approved single-institution multi-reader study on prospectively acquired FFDM + DBT images included 429 asymptomatic women (39-69y) with an elevated BC risk on their request form. The BCLTR was calculated for each patient using the IBISrisk calculator v8.0b. The screening protocol and reader study consisted of 4-view FFDM + DBT, which were read by four independent radiologists using the BI-RADS lexicon. Standard of care (SOC) included ultrasound (US) and magnetic resonance imaging (MRI) for women with > 30 % BCLTR. Breast cancer detection rate (BCDR), sensitivity and positive predictive value were assessed for FFDM and FFDM + DBT and detection outcomes were compared with McNemar-test.

RESULTS

In total 7/429 women in this clinically elevated breast cancer risk group were diagnosed with BC using SOC (BCDR 16.3/1000) of which 4 were detected with FFDM. Supplemental DBT did not detect additional cancers and BCDR was the same for FFDM vs FFDM + DBT (9.3/1000, McNemar p = 1). Moderate inter-reader agreement for diagnostic BI-RADS score was found for both study arms (ICC for FFDM and FFDM + DBT was 0.43, resp. 0.46).

CONCLUSION

In this single institution study, supplemental screening with DBT in addition to standard FFDM did not increase BCDR in this higher-than-average BC risk group, objectively documented using the IBISrisk calculator.

Dual role of pregnancy in breast cancer risk

Reproductive history is one of the strongest risk factors for breast cancer in women. Pregnancy can promote short-term breast cancer risk, but also reduce a woman's lifetime risk of breast cancer. Changes in hormone levels before and after pregnancy are one of the key factors in breast cancer risk. This article summarizes the changes in hormone levels before and after pregnancy, and the roles of hormones in mammary gland development and breast cancer progression. Other factors, such as changes in breast morphology and mammary gland differentiation, changes in the proportion of mammary stem cells (MaSCs), changes in the immune and inflammatory environment, and changes in lactation before and after pregnancy, also play key roles in the occurrence and development of breast cancer. This review discusses the dual effects and the potential mechanisms of pregnancy on breast cancer risk from the above aspects, which is helpful to understand the complexity of female breast cancer occurrence.

Patient Experience of Women With Dense Breasts Undergoing Screening Contrast-Enhanced Mammography

OBJECTIVE

We investigated patient experience with screening contrast-enhanced mammography (CEM) to determine whether a general population of women with dense breasts would accept CEM in a screening setting.

METHODS

In this institutional review board-approved prospective study, patients with heterogeneous and extremely dense breasts on their mammogram were invited to undergo screening CEM and complete pre-CEM and post-CEM surveys. On the pre-CEM survey, patients were asked about their attitudes regarding supplemental screening in general. On the post-CEM survey, patients were asked about their experience undergoing screening CEM, including causes and severity of any discomfort and whether they would consider undergoing screening CEM again in the future or recommend it to a friend.

RESULTS

One hundred sixty-three women were surveyed before and after screening CEM. Most patients, 97.5% (159/163), reported minimal or no unpleasantness associated with undergoing screening CEM. In addition, 91.4% (149/163) said they would probably or very likely undergo screening CEM in the future if it cost the same as a traditional screening mammogram, and 95.1% (155/163) said they would probably or very likely recommend screening CEM to a friend. Patients in this study, who were all willing to undergo CEM, more frequently reported a family history of breast cancer than a comparison cohort of women with dense breasts (58.2% vs 47.1%, P = .027).

CONCLUSION

Patients from a general population of women with dense breasts reported a positive experience undergoing screening CEM, suggesting screening CEM might be well received by this patient population, particularly if the cost was comparable with traditional screening mammography.

The emerging role and mechanism of HMGA2 in breast cancer

High mobility group AT-hook 2 (HMGA2) is a member of the non-histone chromosomal high mobility group (HMG) protein family, which participate in embryonic development and other biological processes. HMGA2 overexpression is associated with breast cancer (BC) cell growth, proliferation, metastasis, and drug resistance. Furthermore, HMGA2 expression is positively associated with poor prognosis of patients with BC, and inhibiting HMGA2 signaling can stimulate BC cell progression and metastasis. In this review, we focus on HMGA2 expression changes in BC tissues and multiple BC cell lines. Wnt/β-catenin, STAT3, CNN6, and TRAIL-R2 proteins are upstream mediators of HMGA2 that can induce BC invasion and metastasis. Moreover, microRNAs (miRNAs) can suppress BC cell growth, invasion, and metastasis by inhibiting HMGA2 expression. Furthermore, long noncoding RNAs (LncRNAs) and circular RNAs (CircRNAs) mainly regulate HMGA2 mRNA and protein expression levels by sponging miRNAs, thereby promoting BC development. Additionally, certain small molecule inhibitors can suppress BC drug resistance by reducing HMGA2 expression. Finally, we summarize findings demonstrating that HMGA2 siRNA and HMGA2 siRNA-loaded nanoliposomes can suppress BC progression and metastasis.

Association of area- and volumetric-mammographic density and breast cancer risk in women of Asian descent: a case control study

BACKGROUND

Mammographic density (MD) has been shown to be a strong and independent risk factor for breast cancer in women of European and Asian descent. However, the majority of Asian studies to date have used BI-RADS as the scoring method and none have evaluated area and volumetric densities in the same cohort of women. This study aims to compare the association of MD measured by two automated methods with the risk of breast cancer in Asian women, and to investigate if the association is different for premenopausal and postmenopausal women.

METHODS

In this case-control study of 531 cases and 2297 controls, we evaluated the association of area-based MD measures and volumetric-based MD measures with breast cancer risk in Asian women using conditional logistic regression analysis, adjusting for relevant confounders. The corresponding association by menopausal status were assessed using unconditional logistic regression.

RESULTS

We found that both area and volume-based MD measures were associated with breast cancer risk. Strongest associations were observed for percent densities (OR (95% CI) was 2.06 (1.42-2.99) for percent dense area and 2.21 (1.44-3.39) for percent dense volume, comparing women in highest density quartile with those in the lowest quartile). The corresponding associations were significant in postmenopausal but not premenopausal women (premenopausal versus postmenopausal were 1.59 (0.95-2.67) and 1.89 (1.22-2.96) for percent dense area and 1.24 (0.70-2.22) and 1.96 (1.19-3.27) for percent dense volume). However, the odds ratios were not statistically different by menopausal status [p difference = 0.782 for percent dense area and 0.486 for percent dense volume].

CONCLUSIONS

This study confirms the associations of mammographic density measured by both area and volumetric methods and breast cancer risk in Asian women. Stronger associations were observed for percent dense area and percent dense volume, and strongest effects were seen in postmenopausal individuals.

Performance of an Artificial Intelligence System for Breast Cancer Detection on Screening Mammograms from BreastScreen Norway

Purpose To explore the stand-alone breast cancer detection performance, at different risk score thresholds, of a commercially available artificial intelligence (AI) system. Materials and Methods This retrospective study included information from 661 695 digital mammographic examinations performed among 242 629 female individuals screened as a part of BreastScreen Norway, 2004-2018. The study sample included 3807 screen-detected cancers and 1110 interval breast cancers. A continuous examination-level risk score by the AI system was used to measure performance as the area under the receiver operating characteristic curve (AUC) with 95% CIs and cancer detection at different AI risk score thresholds. Results The AUC of the AI system was 0.93 (95% CI: 0.92, 0.93) for screen-detected cancers and interval breast cancers combined and 0.97 (95% CI: 0.97, 0.97) for screen-detected cancers. In a setting where 10% of the examinations with the highest AI risk scores were defined as positive and 90% with the lowest scores as negative, 92.0% (3502 of 3807) of the screen-detected cancers and 44.6% (495 of 1110) of the interval breast cancers were identified with AI. In this scenario, 68.5% (10 987 of 16 040) of false-positive screening results (negative recall assessment) were considered negative by AI. When 50% was used as the cutoff, 99.3% (3781 of 3807) of the screen-detected cancers and 85.2% (946 of 1110) of the interval breast cancers were identified as positive by AI, whereas 17.0% (2725 of 16 040) of the false-positive results were considered negative. Conclusion The AI system showed high performance in detecting breast cancers within 2 years of screening mammography and a potential for use to triage low-risk mammograms to reduce radiologist workload. Keywords: Mammography, Breast, Screening, Convolutional Neural Network (CNN), Deep Learning Algorithms Supplemental material is available for this article. © RSNA, 2024 See also commentary by Bahl and Do in this issue.

Following the High-Risk Patient: Breast Cancer Risk-Based Screening

Breast cancer (BC) is the most common cancer occurring in women in the USA today, and accounts for more than 40,000 deaths annually (Giaquinto in CA Cancer J Clin 72: 524-541, 2022). While breast cancer survival has improved over the past decades, incidence has increased, and diagnoses are being made at younger ages. This emphasizes the importance of risk evaluation, accurate prediction, and effective mitigation and risk reduction strategies. Enhanced screening can help detect cancers at an earlier stage, thus improving morbidity and mortality. This review addresses the recognition of women at high-risk for BC and monitoring strategies for those at high risk.

Implementing supplementary breast cancer screening in women with dense breasts: Insights from European radiographers and radiologists

INTRODUCTION

In response to the critical need for enhancing breast cancer screening for women with dense breasts, this study explored the understanding of challenges and requirements for implementing supplementary breast cancer screening for such women among clinical radiographers and radiologists in Europe.

METHOD

Fourteen (14) semi-structured online interviews were conducted with European clinical radiologists (n = 5) and radiographers (n = 9) specializing in breast cancer screening from 8 different countries: Denmark, Finland, Greece, Italy, Malta, the Netherlands, Switzerland, United Kingdom. The interview schedule comprised questions regarding professional background and demographics and 13 key questions divided into six subgroups, namely Supplementary Imaging, Training, Resources and Guidelines, Challenges, Implementing supplementary screening and Women's Perspective. Data analysis followed the six phases of reflexive thematic analysis.

RESULTS

Six significant themes emerged from the data analysis: Understanding and experiences of supplementary imaging for women with dense breasts; Challenges and requirements related to training among clinical radiographers and radiologists; Awareness among radiographers and radiologists of guidelines on imaging women with dense breasts; Challenges to implement supplementary screening; Predictors of Implementing Supplementary screening; Views of radiologists and radiographers on women's perception towards supplementary screening.

CONCLUSION

The interviews with radiographers and radiologists provided valuable insights into the challenges and potential strategies for implementing supplementary breast cancer screening. These challenges included patient and staff related challenges. Implementing multifaceted solutions such as Artificial Intelligence integration, specialized training and resource investment can address these challenges and promote the successful implementation of supplementary screening. Further research and collaboration are needed to refine and implement these strategies effectively.

IMPLICATIONS FOR PRACTICE

This study highlights the urgent need for specialized training programs and dedicated resources to enhance supplementary breast cancer screening for women with dense breasts in Europe. These resources include advanced imaging technologies, such as MRI or ultrasound, and specialized software for image analysis. Moreover, further research is imperative to refine screening protocols and evaluate their efficacy and cost-effectiveness, based on the findings of this study.

The incidence of breast cancer in Egyptian females in correlation to different mammographic ACR densities

INTRODUCTION

The density of breast tissue, radiologically referred to as fibroglandular mammary tissue, was found to be a predisposing factor for breast cancer (BC). However, the stated degree of elevated BC risk varies widely in the literature.

Breast Tomographic Ultrasound: The Spectrum from Current Dense Breast Cancer Screenings to Future Theranostic Treatments

This review provides unique insights to the scientific scope and clinical visions of the inventors and pioneers of the SoftVue breast tomographic ultrasound (BTUS). Their >20-year collaboration produced extensive basic research and technology developments, culminating in SoftVue, which recently received the Food and Drug Administration's approval as an adjunct to breast cancer screening in women with dense breasts. SoftVue's multi-center trial confirmed the diagnostic goals of the tissue characterization and localization of quantitative acoustic tissue differences in 2D and 3D coronal image sequences. SoftVue mass characterizations are also reviewed within the standard cancer risk categories of the Breast Imaging Reporting and Data System. As a quantitative diagnostic modality, SoftVue can also function as a cost-effective platform for artificial intelligence-assisted breast cancer identification. Finally, SoftVue's quantitative acoustic maps facilitate noninvasive temperature monitoring and a unique form of time-reversed, focused US in a single theranostic device that actually focuses acoustic energy better within the highly scattering breast tissues, allowing for localized hyperthermia, drug delivery, and/or ablation. Women also prefer the comfort of SoftVue over mammograms and will continue to seek out less-invasive breast care, from diagnosis to treatment.

Screening mammography frequency following dense breast notification among a predominantly Hispanic/Latina screening cohort

PURPOSE

Nationally legislated dense breast notification (DBN) informs women of their breast density (BD) and the impact of BD on breast cancer risk and detection, but consequences for screening participation are unclear. We evaluated the association of DBN in New York State (NYS) with subsequent screening mammography in a largely Hispanic/Latina cohort.

METHODS

Women aged 40-60 were surveyed in their preferred language (33% English, 67% Spanish) during screening mammography from 2016 to 2018. We used clinical BD classification from mammography records from 2013 (NYS DBN enactment) through enrollment (baseline) to create a 6-category variable capturing prior and new DBN receipt (sent only after clinically dense mammograms). We used this variable to compare the number of subsequent mammograms (0, 1, ≥ 2) from 10 to 30 months after baseline using ordinal logistic regression.

RESULTS

In a sample of 728 women (78% foreign-born, 72% Hispanic, 46% high school education or less), first-time screeners and women who received DBN for the first time after prior non-dense mammograms had significantly fewer screening mammograms within 30 months of baseline (Odds Ratios range: 0.33 (95% Confidence Interval (CI) 0.12-0.85) to 0.38 (95% CI 0.17-0.82)) compared to women with prior mammography but no DBN. There were no differences in subsequent mammogram frequency between women with multiple DBN and those who never received DBN. Findings were consistent across age, language, health literacy, and education groups.

CONCLUSION

Women receiving their first DBN after previous non-dense mammograms have lower mammography participation within 2.5 years. DBN has limited influence on screening participation of first-time screeners and those with persistent dense mammograms.

Cyclin-dependent kinase 4/6 inhibitors in the treatment of advanced or metastatic breast cancer

OBJECTIVE

Despite the relatively high cure rates in early-stage breast cancer, advanced and metastatic breast cancer cases are associated with more inauspicious patient outcomes. Fortunately, with the advent of cyclin-dependent kinase (CDK)4/6 inhibitors (e.g. palbociclib, ribociclib, and abemaciclib) with endocrine therapy, survival in advanced and metastatic breast cancer has appreciably improved. In the current review, we discuss these distinctions and the concomitant implications associated with the individual CDK4/6 inhibitors.

DATA SOURCES

We conducted an extensive PubMed search comprising several review articles on the topic of advanced or metastatic breast cancer treatment, with specific terms that included CDK4/6 inhibitors, treatment, and breast cancer.

DATA SUMMARY

Palbociclib, ribociclib, and abemaciclib have exhibited superior progression-free survival differences compared to endocrine therapy alone. However, there are differences among the various CDK4/6 inhibitors with regard to overall survival, tolerability and quality of life.

CONCLUSIONS

Ribociclib may be indicated for pre/perimenopausal patients, whereas abemaciclib is potentially recommended to address endocrine-resistant or visceral disease. Alternatively, palbociclib is associated with lower discontinuation rates than abemaciclib and unlike ribociclib, QTc prolongation is not observed with palbociclib.

The impact of breast density notification on psychosocial outcomes in racial and ethnic minorities: A systematic review

BACKGROUND

High breast density is an independent risk factor for breast cancer and decreases the sensitivity of mammography. This systematic review synthesizes the evidence on the impact of breast density (BD) information and/or notification on women's psychosocial outcomes among women from racial and ethnic minority groups.

METHODS

A systematic search was performed in March 2023, and the articles were identified using CINHAL, Embase, Medline, and PsychInfo databases. The search strategy combined the terms "breast", "density", "notification" and synonyms. The authors specifically kept the search terms broad and did not include terms related to race and ethnicity. Full-text articles were reviewed for analysis by race, ethnicity and primary language of participants. Two authors evaluated the eligibility of studies with verification from the study team, extracted and crosschecked data, and assessed the risk of bias.

RESULTS

Of 1784 articles, 32 articles published from 2003 to 2023 were included. Thirty-one studies were conducted in the United States and one in Australia, with 28 quantitative and four qualitative methodologies. The overall results in terms of breast density awareness, knowledge, communication with healthcare professionals, screening intentions and supplemental screening practice were heterogenous across studies. Barriers to understanding BD notifications and intentions/access to supplemental screening among racial and ethnic minorities included socioeconomic factors, language, health literacy and medical mistrust.

CONCLUSIONS

A one-size approach to inform women about their BD may further disadvantage racial and ethnic minority women. BD notification and accompanying information should be tailored and translated to ensure readability and understandability by all women.

LncRNAs in necroptosis: Deciphering their role in cancer pathogenesis and therapy

Necroptosis, a controlled type of cell death that is different from apoptosis, has become a key figure in the aetiology of cancer and offers a possible target for treatment. A growing number of biological activities, including necroptosis, have been linked to long noncoding RNAs (lncRNAs), a varied family of RNA molecules with limited capacity to code for proteins. The complex interactions between LncRNAs and important molecular effectors of necroptosis, including mixed lineage kinase domain-like pseudokinase (MLKL) and receptor-interacting protein kinase 3 (RIPK3), will be investigated. We will explore the many methods that LncRNAs use to affect necroptosis, including protein-protein interactions, transcriptional control, and post-transcriptional modification. Additionally, the deregulation of certain LncRNAs in different forms of cancer will be discussed, highlighting their dual function in influencing necroptotic processes as tumour suppressors and oncogenes. The goal of this study is to thoroughly examine the complex role that LncRNAs play in controlling necroptotic pathways and how that regulation affects the onset and spread of cancer. In the necroptosis for cancer treatment, this review will also provide insight into the possible therapeutic uses of targeting LncRNAs. Techniques utilising LncRNA-based medicines show promise in controlling necroptotic pathways to prevent cancer from spreading and improve the effectiveness of treatment.

A novel PD-1/PD-L1 pathway-related seven-gene signature for the development and validation of the prognosis prediction model for breast cancer

Background

Breast cancer (BC/BRCA) is the most common carcinoma in women. The average 5-year survival rate of BC patients with stage IV disease is 26%. A considerable proportion of patients still do not receive effective therapy. It is an unmet need to identify novel biomarkers for BC patients. Herein, we evaluated whether the programmed cell death protein 1/programmed cell death ligand 1 (PD-1/PD-L1) status is associated with the clinical outcomes of BC, based on data from The Cancer Genome Atlas (TCGA).

Methods

Clinical and transcriptome data of BC patients were obtained from TCGA dataset, and prognostic genes in BC patients were identified, as well as the PD-1/PD-L1 pathway mainly associating with the BC patients. Following the execution of the consensus clustering algorithm, BC patients were segregated into two clusters, and subsequent investigation of the potential mechanisms between them was carried out. A comparison of ferroptosis and N6-methyladenosine (m6A) was conducted between the two groups with the greatest difference in prognosis. Based on least absolute shrinkage and selection operator (LASSO) analysis, a signature associated with the PD-1/PD-L1 pathway was developed, and the prognosis outcome and the predictive accuracy of the signature model were further assessed.

Results

Prognostic genes in BC patients were studied using TCGA data and it was found that the PD-1/PD-L1 pathway was most associated with the BC patients. Then, a low-risk (C1) group and a high-risk (C2) group of BC patients were constructed based on a PD-1/PD-L1 pathway-related signature. The functional analyses suggested that the underlying mechanisms between these groups were mainly associated with immune-related pathways. We found that ferroptosis and m6A were significantly different between the two groups. A PD-1/PD-L1 pathway-related gene signature was further developed to predict survival of BC patients, including 7 genes [mitogen-activated protein kinase kinase 6 (MAP2K6), NF-kappa-B inhibitor alpha (NFKBIA), NFKB Inhibitor Epsilon (NFKBIE), Interferon gamma (IFNG), Toll/interleukin-1 receptor domain-containing adapter protein (TIRAP), IkappaB kinase (CHUK), and Casein kinase 2 alpha 3 gene (CSNK2A3)]. The receiver operating characteristic (ROC) curves were analyzed to further assess the prognostic values of these 7 genes. The 1-, 3-, and 5-year values of the areas under the curve (AUCs) for overall survival were 0.651, 0.658, and 0.653 in this seven gene signature model, respectively.

Conclusions

PD-1/PD-L1 pathway-related subtypes of BC were identified, which were closely associated with the immune microenvironment, the ferroptosis status, and m6A in BC patients. The gene signature involved in the PD-1/PD-L1 pathway might help to make a distinction and predict prognosis in BC patients.

Liposuction-Only Breast Reduction: A Systematic Review of Outcomes

INTRODUCTION

Over the past few decades, there have been multiple reports of liposuction assisted breast reduction. This technique appeals to patients due to the limited scars and complication profile, compared to traditional reduction mammaplasty techniques. We aimed to systematically review the literature, to elucidate the outcomes and safety of liposuction-only breast reduction.

METHODS

A systematic review was performed using the Ovid (Medline/PubMed) database, in accordance with the PRISMA checklist.

RESULTS

In total 7 articles were included within this systematic review. A total of 652 patients were included. Liposuction-only breast reduction appears to lead to improvements in subjective outcome measures, patient satisfaction, and objective outcomes such as moderate breast volume reduction and reduction in breast ptosis. Overall, the procedure had a low complication profile. Liposuction did not preclude further surgery. No evidence of malignancy or difficulty in future breast cancer screening was noted.

CONCLUSION

Macromastia leads to a considerable health burden, especially in health-related costs. From the current evidence base, liposuction-only breast reduction appears to be a safe and effective procedure, especially in patients requiring a mild-moderate breast volume reduction and mild ptosis correction. More research is required, with standardised subjective and objective outcome measures, and longer follow-up periods to confirm the effectiveness and safety of this technique. Level of Evidence III This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine Ratings, please refer to Table of Contents or online Instructions to Authors www.springer.com/00266 .

A Public Health Emergency: Breast Cancer Among Black Communities in the United States

While Black people have a similar incidence of breast cancer compared to White people, they have a 40% increased death rate. Black people are more likely to be diagnosed with aggressive subtypes such as triple-negative breast cancer. However, despite biological factors, systemic racism and social determinants of health create delays in care and barriers to treatment. While genetic testing holds incredible promise for Black people, uptake remains low and results may be challenging to interpret. There is a need for more robust, multidisciplinary, and antiracist interventions to reverse breast cancer-related racial disparities.

miR-125 in Breast Cancer Etiopathogenesis: An Emerging Role as a Biomarker in Differential Diagnosis, Regenerative Medicine, and the Challenges of Personalized Medicine

Breast Cancer (BC) is one of the most common cancer types worldwide, and it is characterized by a complex etiopathogenesis, resulting in an equally complex classification of subtypes. MicroRNA (miRNA or miR) are small non-coding RNA molecules that have an essential role in gene expression and are significantly linked to tumor development and angiogenesis in different types of cancer. Recently, complex interactions among coding and non-coding RNA have been elucidated, further shedding light on the complexity of the roles these molecules fulfill in cancer formation. In this context, knowledge about the role of miR in BC has significantly improved, highlighting the deregulation of these molecules as additional factors influencing BC occurrence, development and classification. A considerable number of papers has been published over the past few years regarding the role of miR-125 in human pathology in general and in several types of cancer formation in particular. Interestingly, miR-125 family members have been recently linked to BC formation as well, and complex interactions (competing endogenous RNA networks, or ceRNET) between this molecule and target mRNA have been described. In this review, we summarize the state-of-the-art about research on this topic.

Suspicious Ultrasound-Occult Non-Calcified Mammographic Masses, Asymmetries, and Architectural Distortions Are Moderate Probability for Malignancy

Suspicious non-calcified mammographic findings have not been evaluated with modern mammographic technique, and the purpose of this work is to compare the likelihood of malignancy for those findings. To do this, 5018 consecutive mammographically guided biopsies performed during 2016-2019 at a large metropolitan, community-based hospital system were retrospectively reviewed. In total, 4396 were excluded for targeting calcifications, insufficient follow-up, or missing data. Thirty-seven of 126 masses (29.4%) were malignant, 44 of 194 asymmetries (22.7%) were malignant, and 77 of 302 architectural distortions (AD, 25.5%) were malignant. The combined likelihood of malignancy was 25.4%. Older age was associated with a higher likelihood of malignancy for each imaging finding type (all p ≤ 0.006), and a possible ultrasound correlation was associated with a higher likelihood of malignancy when all findings were considered together (p = 0.012). Two-view asymmetries were more frequently malignant than one-view asymmetries (p = 0.03). There were two false-negative biopsies (98.7% sensitivity and 100% specificity). In conclusion, the 25.4% likelihood of malignancy confirms the recommendation for biopsy of suspicious, ultrasound-occult, mammographic findings. Mammographically guided biopsies were highly sensitive and specific in this study. Older patient age and a possible ultrasound correlation should raise concern given the increased likelihood of malignancy in those scenarios.

Association between Family History of Breast Cancer and Breast Density in Saudi Premenopausal Women Participating in Mammography Screening

BACKGROUND

Mammographic density and family history of breast cancer (FHBC) are well-established independent factors affecting breast cancer risk; however, the association between these two risk factors in premenopausal-screened women remains unclear. The aim of this study is to investigate the relationship between mammographic density and FHBC among Saudi premenopausal-screened women.

METHODS

A total of 446 eligible participants were included in the study. Mammographic density was assessed qualitatively using the Breast Imaging Reporting and Data System (BIRADS 4th edition). Logistic regression models were built to investigate the relationship between mammographic density and FHBC.

RESULTS

Women with a family history of breast cancer demonstrated an 87% greater chance of having dense tissue than women without a family history of breast cancer (95% CI: 1.14-3.08; p = 0.01). Having a positive family history for breast cancer in mothers was significantly associated with dense tissue (adjusted odds ratio (OR): 5.6; 95% CI: 1.3-24.1; p = 0.02).

CONCLUSION

Dense breast tissue in Saudi premenopausal women undergoing screening may be linked to FHBC. If this conclusion is replicated in larger studies, then breast cancer risk prediction models must carefully consider these breast cancer risk factors.

Breast cancer risk association with postmenopausal hormone therapy: Health Insurance Database in South Korea-based cohort study

CONTEXT

Although many physicians have been concerned that the menopausal hormones used currently in clinical practice may affect the risk of breast cancer, there are currently few informative updated studies about the associations between menopausal hormone therapy (MHT) and the risk of breast cancer.

OBJECTIVE

This study aims to evaluate the association between the risk of breast cancer and MHT using the National Health Insurance Database in South Korea (HISK) cohort between 2002 and 2019 retrospectively.

METHODS

Postmenopausal women over 40 years of age from 2003 to 2011 were selected as the subject population, and their follow-up data were collected until 2019. We analyzed the risk and mortality of breast cancer according to the type of MHT received, namely, tibolone, combined estrogen plus progestin by manufacturer (CEPM), oral estrogen, combined estrogen plus progestin by physician (CEPP), or topical estrogen.

RESULTS

The risk of breast cancer increased in the CEPM group [hazard ratio (HR) 1.439, 95% CI 1.374-1.507, P-value < .001] in comparison with the non-MHT group. However, no significant associations were found between the use of tibolone, oral estrogen, CEPP, or topical estrogen and breast cancer risk in comparison with the non-MHT group (HR 0.968, 95% CI 0.925-1.012; HR 1.002, 95% CI 0.929-1.081; HR 0.929, 95% CI 0.75-1.15; HR 1.139, 95% CI 0.809-1.603). The mortality rate from breast cancer is lower in the MHT group in comparison with the non-MHT group, indicating that significant associations were found for tibolone, CEPM, and oral estrogen (HR 0.504, 95% CI 0.432-0.588; HR 0.429, 95% CI 0.352-0.522; HR 0.453 95% CI 0.349-0.588, P-value < .001).

CONCLUSIONS

This study suggests that the risk of breast cancer is increased by drugs in the CEPM group but not by tibolone, oral estrogen, CEPP, or topical estrogen. The mortality rate from breast cancer is lower with MHT (tibolone, CEPM, oral estrogen) than without MHT.

Knowledge of Non-Invasive Biomarkers of Breast Cancer, Risk Factors, and BSE Practices Among Nursing Undergraduates in Farasan Island, KSA

Background of the Study

Mammograms are sometimes met with issues of overdiagnosis and underdiagnosis; therefore, they are less reliable in identifying cancer in women with dense breasts. As a result, it is critical to be aware of other sensitive screening techniques for the early diagnosis of breast cancer.

Aim

The ultimate objective of this study was to assess the knowledge of nursing undergraduates regarding non-invasive biomarkers, such as volatile organic compounds in breath, nipple aspirate fluid, sweat, urine, and tears, for the early detection of breast cancer to help improve patient care, determine the risk factors, and encourage practice of breast self-examination.

Methods

Cross-sectional research was done in the Department of Nursing at Farasan campus using a self-structured questionnaire as the study tool. A total of 260 students willingly participated. The study tool had evaluation questions focused on the non-invasive biomarkers of breast cancer, risk factors, and breast self-examination practices to collect data. The data were subjected to descriptive and inferential statistics. The statistical significance was calculated at P < .05. Data analyses were done using Microsoft Excel (2013).

Results

A significant knowledge gap existed among the study participants about the non-invasive biomarkers of breast cancer. A lesser percentage of students (25%) stated that they do breast self-examination on a monthly basis. The most common reasons for not doing the breast self-examination were "not knowing how to do the breast self-examination" (77.3%), fear of a positive diagnosis (53.9%), thinking that they are not at risk as all were in their teens and hence not required (44.7%), and lack of time (48.7%). Age and frequency of breast self-examination were significantly associated (P < .05) as those few students (22.7%) who were doing breast self-examination practices every 2-4 months belonged to a higher study year. Furthermore, knowledge regarding incidence rates and health care expenditure by the government on breast cancer was also significantly low (P < .05).

Conclusions

Outcomes would help prioritize actions to help future nurses better understand breast cancer, allowing them to extend patient care in the best way possible.

Knowledge, attitudes, and practices related to breast cancer screening among female Jordanian university employees: A cross-sectional study

INTRODUCTION

To improve participation in breast screening programs, the level of knowledge about BC, attitudes, and practices of women in different sections of society must be understood. This study aimed to measure the level of knowledge of BC risk factors, signs and symptoms and determine current mammography practices among female employees at Jordanian universities.

METHODS

A cross-sectional descriptive study was conducted on female employees at Jordanian government universities. Data was collected using a structured questionnaire that included: sociodemographic characteristics, knowledge of BC risk factors, knowledge of BC symptoms and knowledge, attitude and practice of mammography as an early detection method.

RESULTS

A total of 362 participants completed the questionnaire. Overall, 174 scored ≥50% correct answers regarding BC risk factors, while 231 scored ≥50% correct answers regarding BC signs and symptoms. Half of the participants (n = 184, 50.8%) understood mammography to be an early BC detection method. Among those participants, 95 (51.6%) were eligible for screening and 39 (21.2%) had had a previous mammogram. The main reason for not engaging in mammography was the absence of BC signs and symptoms (37.2%). Profession, educational level and family history of BC were associated with increased knowledge of BC risk factors, signs and symptoms (p = 0.01). Lecturers in medical faculties exhibited the highest level of knowledge about mammography compared to participants in other professions (p = 0.02).

CONCLUSION

Only 79 participants had good to excellent knowledge about BC. Participants' profession was the major indicator for awareness of BC and mammography as an early detection method.

IMPLICATIONS FOR PRACTICE

The findings of this study reinforce the importance of providing BC educational programs for university employees in Jordan to increase awareness of BC and mammography.

Nanomedicine-Based Drug-Targeting in Breast Cancer: Pharmacokinetics, Clinical Progress, and Challenges

Breast cancer (BC) is a malignant neoplasm that begins in the breast tissue. After skin cancer, BC is the second most common type of cancer in women. At the end of 2040, the number of newly diagnosed BC cases is projected to increase by over 40%, reaching approximately 3 million worldwide annually. The hormonal and chemotherapeutic approaches based on conventional formulations have inappropriate therapeutic effects and suboptimal pharmacokinetic responses with nonspecific targeting actions. To overcome such issues, the use of nanomedicines, including liposomes, nanoparticles, micelles, hybrid nanoparticles, etc., has gained wider attention in the treatment of BC. Smaller dimensional nanomedicine (especially 50-200 nm) exhibited improved in vivo effectiveness, such as better tissue penetration and more effective tumor suppression through enhanced retention and permeation, as well as active targeting of the drug. Additionally, nanotechnology, which further extended and developed theranostic nanomedicine by incorporating diagnostic and imaging agents in one platform, has been applied to BC. Furthermore, hybrid and theranostic nanomedicine has also been explored for gene delivery as anticancer therapeutics in BC. Moreover, the nanocarriers' size, shape, surface charge, chemical compositions, and surface area play an important role in the nanocarriers' stability, cellular absorption, cytotoxicity, cellular uptake, and toxicity. Additionally, nanomedicine clinical translation for managing BC remains a slow process. However, a few cases are being used clinically, and their progress with the current challenges is addressed in this Review. Therefore, this Review extensively discusses recent advancements in nanomedicine and its clinical challenges in BC.

Tibolone and Breast Cancer

Tibolone, a selective tissue estrogenic activity regulator, is a synthetic steroid with distinct pharmacological and clinical characteristics in contrast to conventional menopausal hormone therapy. Tibolone induces estrogenic activity in the brain, vagina, and bone but remains inactive in the endometrium and breast. In particular, several studies have investigated whether tibolone usage increases the risk of breast cancer. This study aims to determine the effects of tibolone on the breast by focusing on the relation between tibolone use and breast cancer. Our investigation emphasizes recent studies, particularly those based on Asian populations.

Breast cancer risk prediction using Tyrer-Cuzick algorithm with an 18-SNPs polygenic risk score in a European population with below-average breast cancer incidence

GOALS

To determine whether an 18 single nucleotide polymorphisms (SNPs) polygenic risk score (PRS18) improves breast cancer (BC) risk prediction for women at above-average risk of BC, aged 40-49, in a Central European population with BC incidence below EU average.

METHODS

502 women aged 40-49 years at the time of BC diagnosis completed a questionnaire on BC risk factors (as per Tyrer-Cuzick algorithm) with data known at age 40 and before BC diagnosis. Blood samples were collected for DNA isolation. 250 DNA samples from healthy women aged 50 served as a control cohort. 18 BC-associated SNPs were genotyped in both groups and PRS18 was calculated. The predictive power of PRS18 to detect BC was evaluated using a ROC curve. 10-year BC risk was calculated using the Tyrer-Cuzick algorithm adapted to the Slovenian incidence rate (S-IBIS): first based on questionnaire-based risk factors and, second, including PRS18.

RESULTS

The AUC for PRS18 was 0.613 (95 % CI 0.570-0.657). 83.3 % of women were classified at above-average risk for BC with S-IBIS without PRS18 and 80.7 % when PRS18 was included.

CONCLUSION

BC risk prediction models and SNPs panels should not be automatically used in clinical practice in different populations without prior population-based validation. In our population the addition of an 18SNPs PRS to questionnaire-based risk factors in the Tyrer-Cuzick algorithm in general did not improve BC risk stratification, however, some improvements were observed at higher BC risk scores and could be valuable in distinguishing women at intermediate and high risk of BC.

Pathological macroscopic evaluation of breast density versus mammographic breast density in breast cancer conserving surgery

Correlation between imaging and anatomopathological breast density has been superficially explored and is heterogeneous in current medical literature. It is possible that mammographic and pathological findings are divergent. The aim of this study is to evaluate the association between breast density classified by mammography and breast density of pathological macroscopic examination in specimens of breast cancer conservative surgeries. Post-hoc, exploratory analysis of a prospective randomized clinical trial of patients with breast cancer candidates for breast conservative surgery. Breast mammographic density (MD) was analyzed according to ACR BI-RADS® criteria, and pathologic macroscopic evaluation of breast density (PMBD) was estimated by visually calculating the ratio between stromal and fatty tissue. From 412 patients, MD was A in 291 (70,6%), B in 80 (19,4%) B, C in 35 (8,5%), and D in 6 (1,5%). Ninety-nine percent (201/203) of patients classified as A+B in MD were correspondently classified in PMBD. Conversely, only 18.7% (39/209) of patients with MD C+D were classified correspondently in PMBD (p < 0.001). Binary logistic regression showed age (OR 1.06, 1.01-1.12 95% CI, p 0.013) and nulliparity (OR 0.39, 0.17-0.96 95% CI, p 0.039) as predictors of A+B PMBD.

Conclusion

Mammographic and pathologic macroscopic breast density showed no association in our study for breast C or D in breast image. The fatty breast was associated with older patients and the nulliparity decreases the chance of fatty breasts nearby 60%.

Implementing the National Dense Breast Reporting Standard, Expanding Supplemental Screening Using Current Guidelines, and the Proposed Find It Early Act

Thirty-eight states and the District of Columbia (DC) have dense breast notification laws that mandate varying levels of patient notification about breast density after a mammogram, and these cover over 90% of American women. On March 10, 2023, the Food and Drug Administration issued a final rule amending regulations under the Mammography Quality Standards Act for a national dense breast reporting standard for both patient results letters and mammogram reports. Effective September 10, 2024, letters will be required to tell a woman her breasts are "dense" or "not dense," that dense tissue makes it harder to find cancers on a mammogram, and that it increases the risk of developing cancer. Women with dense breasts will also be told that other imaging tests in addition to a mammogram may help find cancers. The specific density category can be added (eg, if mandated by a state "inform" law). Reports to providers must include the Breast Imaging Reporting and Data System density category. Implementing appropriate supplemental screening should be based on patient risk for missed breast cancer on mammography; such assessment should include consideration of breast density and other risk factors. This article discusses strategies for implementation. Currently 21 states and DC have varying insurance laws for supplemental breast imaging; in addition, Oklahoma requires coverage for diagnostic breast imaging. A federal insurance bill, the Find It Early Act, has been introduced that would ensure no-cost screening and diagnostic imaging for women with dense breasts or at increased risk and close loopholes in state laws.

Protocol for a pragmatic stepped wedge cluster randomized clinical trial testing behavioral economic implementation strategies to increase supplemental breast MRI screening among patients with extremely dense breasts

BACKGROUND

Increased breast density augments breast cancer risk and reduces mammography sensitivity. Supplemental breast MRI screening can significantly increase cancer detection among women with dense breasts. However, few women undergo this exam, and screening is consistently lower among racially minoritized populations. Implementation strategies informed by behavioral economics ("nudges") can promote evidence-based practices by improving clinician decision-making under conditions of uncertainty. Nudges directed toward clinicians and patients may facilitate the implementation of supplemental breast MRI.

METHODS

Approximately 1600 patients identified as having extremely dense breasts after non-actionable mammograms, along with about 1100 clinicians involved with their care at 32 primary care or OB/GYN clinics across a racially diverse academically based health system, will be enrolled. A 2 × 2 randomized pragmatic trial will test nudges to patients, clinicians, both, or neither to promote supplemental breast MRI screening. Before implementation, rapid cycle approaches informed by clinician and patient experiences and behavioral economics and health equity frameworks guided nudge design. Clinicians will be clustered into clinic groups based on existing administrative departments and care patterns, and these clinic groups will be randomized to have the nudge activated at different times per a stepped wedge design. Clinicians will receive nudges integrated into the routine mammographic report or sent through electronic health record (EHR) in-basket messaging once their clinic group (i.e., wedge) is randomized to receive the intervention. Independently, patients will be randomized to receive text message nudges or not. The primary outcome will be defined as ordering or scheduling supplemental breast MRI. Secondary outcomes include MRI completion, cancer detection rates, and false-positive rates. Patient sociodemographic information and clinic-level variables will be examined as moderators of nudge effectiveness. Qualitative interviews conducted at the trial's conclusion will examine barriers and facilitators to implementation.

DISCUSSION

This study will add to the growing literature on the effectiveness of behavioral economics-informed implementation strategies to promote evidence-based interventions. The design will facilitate testing the relative effects of nudges to patients and clinicians and the effects of moderators of nudge effectiveness, including key indicators of health disparities. The results may inform the introduction of low-cost, scalable implementation strategies to promote early breast cancer detection.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05787249. Registered on March 28, 2023.

Breast density analysis of digital breast tomosynthesis

Mammography shifted to digital breast tomosynthesis (DBT) in the US. An automated percentage of breast density (PD) technique designed for two-dimensional (2D) applications was evaluated with DBT using several breast cancer risk prediction measures: normalized-volumetric; dense volume; applied to the volume slices and averaged (slice-mean); and applied to synthetic 2D images. Volumetric measures were derived theoretically. PD was modeled as a function of compressed breast thickness (CBT). The mean and standard deviation of the pixel values were investigated. A matched case-control (CC) study (n = 426 pairs) was evaluated. Odd ratios (ORs) were estimated with 95% confidence intervals. ORs were significant for PD: identical for volumetric and slice-mean measures [OR = 1.43 (1.18, 1.72)] and [OR = 1.44 (1.18, 1.75)] for synthetic images. A 2nd degree polynomial (concave-down) was used to model PD as a function of CBT: location of the maximum PD value was similar across CCs, occurring at 0.41 × CBT, and PD was significant [OR = 1.47 (1.21, 1.78)]. The means from the volume and synthetic images were also significant [ORs ~ 1.31 (1.09, 1.57)]. An alternative standardized 2D synthetic image was constructed, where each pixel value represents the percentage of breast density above its location. Several measures were significant and an alternative method for constructing a standardized 2D synthetic image was produced.

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.

Analytic Hierarchy Process Analysis of Patient Preferences for Contrast-Enhanced Mammography Versus MRI as Supplemental Screening Options for Breast Cancer

OBJECTIVE

To guide implementation of supplemental breast screening by assessing patient preferences for contrast-enhanced mammography (CEM) versus MRI using analytic hierarchy process (AHP) methodology.

METHODS

In an institutional review board-approved, HIPAA-compliant protocol, from March 23 to June 3, 2022, we contacted 579 women who had both CEM screening and MRI. Women were e-mailed an invitation to complete an online survey developed using an AHP-based model to elicit preferences for CEM or MRI. Methods for categorical data analysis were used to evaluate factors affecting preferences, under the Bonferroni correction for multiplicity.

RESULTS

Complete responses were received from 222 (38.3%) women; the 189 women with a personal history of breast cancer had a mean age 61.8 years, and the 34 women without a personal history of breast cancer had a mean age of 53.6 years. Of 222 respondents, 157 (70.7%, confidence interval [CI]: 64.7-76.7) were determined to prefer CEM to MRI. Breast positioning was the most important criterion for 74 of 222 (33.3%) respondents, with claustrophobia, intravenous line placement, and overall stress most important for 38, 37, and 39 women (17.1%, 16.7%, and 17.6%), respectively, and noise level, contrast injection, and indifference being emphasized least frequently (by 10 [4.5%], 11 [5.0%], and 13 [5.9%] women, respectively). CEM preference was most prevalent (MRI least prevalent) for respondents emphasizing claustrophobia (37 of 38 [97%], CI: 86.2-99.9); CEM preference was least prevalent (MRI most prevalent) for respondents emphasizing breast positioning (40 of 74 [54%], CI: 42.1-65.7).

CONCLUSIONS

AHP-based modeling reveals strong patient preferences for CEM over MRI, with claustrophobia favoring preference for CEM and breast positioning relatively favoring preference for MRI. Our results should help guide implementation of screening CEM and MRI.

Deep Learning Analysis of Mammography for Breast Cancer Risk Prediction in Asian Women

The purpose of this study was to develop a mammography-based deep learning (DL) model for predicting the risk of breast cancer in Asian women. This retrospective study included 287 examinations in 153 women in the cancer group and 736 examinations in 447 women in the negative group, obtained from the databases of two tertiary hospitals between November 2012 and March 2022. All examinations were labeled as either dense breast or nondense breast, and then randomly assigned to either training, validation, or test sets. DL models, referred to as image-level and examination-level models, were developed. Both models were trained to predict whether or not the breast would develop breast cancer with two datasets: the whole dataset and the dense-only dataset. The performance of DL models was evaluated using the accuracy, precision, sensitivity, specificity, F1 score, and area under the receiver operating characteristic curve (AUC). On a test set, performance metrics for the four scenarios were obtained: image-level model with whole dataset, image-level model with dense-only dataset, examination-level model with whole dataset, and examination-level model with dense-only dataset with AUCs of 0.71, 0.75, 0.66, and 0.67, respectively. Our DL models using mammograms have the potential to predict breast cancer risk in Asian women.

Menopausal Hormone Therapy in Older Women: Examining the Current Balance of Evidence

Menopause occurs in all women. During the menopause transition, 80% of women experience vasomotor symptoms that can last an average of 7-10 years or longer, sometimes into the seventh and eighth decades of life. Understanding how to manage vasomotor symptoms (VMS) in older menopausal women is important since these symptoms can negatively impact quality of life. This review provides a practical guide on how to approach VMS treatment either with menopausal hormone therapy or non-hormone options. When initiating, as well as continuing hormone therapy, the factors clinicians should consider as they weigh risks and benefits include assessing a woman's risks related to cardiovascular disease, breast cancer, and osteoporosis. Utilizing a shared decision-making approach in regard to menopausal symptom management should aim to support women and help them maintain health and quality of life.

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.

Mammographic density and interval cancers in mammographic screening: Moving towards more personalized screening

PURPOSE

The European Society on Breast Imaging has recommended supplemental magnetic resonance imaging (MRI) every two to four years for women with mammographically dense breasts. This may not be feasible in many screening programs. Also, the European Commission Initiative on Breast Cancer suggests not implementing screening with MRI. By analyzing interval cancers and time from screening to diagnosis by density, we present alternative screening strategies for women with dense breasts.

METHODS

Our BreastScreen Norway cohort included 508 536 screening examinations, including 3125 screen-detected and 945 interval breast cancers. Time from screening to interval cancer was stratified by density measured by an automated software and classified into Volpara Density Grades (VDGs) 1-4. Examinations with volumetric density ≤3.4% were categorized as VDG1, 3.5%-7.4% as VDG2, 7.5%-15.4% as VDG3, and ≥15.5% as VDG4. Interval cancer rates were also determined by continuous density measures.

RESULTS

Median time from screening to interval cancer was 496 (IQR: 391-587) days for VDG1, 500 (IQR: 350-616) for VDG2, 482 (IQR: 309-595) for VDG3 and 427 (IQR: 266-577) for VDG4. A total of 35.9% of the interval cancers among VDG4 were detected within the first year of the biennial screening interval. For VDG2, 26.3% were detected within the first year. The highest annual interval cancer rate (2.7 per 1000 examinations) was observed for VDG4 in the second year of the biennial interval.

CONCLUSIONS

Annual screening of women with extremely dense breasts may reduce the interval cancer rate and increase program-wide sensitivity, especially in settings where supplemental MRI screening is not feasible.

Breast Density Analysis Using Digital Breast Tomosynthesis

We evaluated an automated percentage of breast density (BD) technique (PDa) with digital breast tomosynthesis (DBT) data. The approach is based on the wavelet expansion followed by analyzing signal dependent noise. Several measures were investigated as risk factors: normalized volumetric; total dense volume; average of the DBT slices (slice-mean); a two-dimensional (2D) metric applied to the synthetic images; and the mean and standard deviations of the pixel values. Volumetric measures were derived theoretically, and PDa was modeled as a function of compressed breast thickness. An alternative method for constructing synthetic 2D mammograms was investigated using the volume results. A matched case-control study (n = 426 pairs) was analyzed. Conditional logistic regression modeling, controlling body mass index and ethnicity, was used to estimate odds ratios (ORs) for each measure with 95% confidence intervals provided parenthetically. There were several significant findings: volumetric measure [OR = 1.43 (1.18, 1.72)], which produced an identical OR as the slice-mean measure as predicted; [OR =1.44 (1.18, 1.75)] when applied to the synthetic images; and mean of the pixel values (volume or 2D synthetic) [ORs ~ 1.31 (1.09, 1.57)]. PDa was modeled as 2nd degree polynomial (concave-down): its maximum value occurred at 0.41×(compressed breast thickness), which was similar across case-control groups, and was significant from this position [OR = 1.47 (1.21, 1.78)]. A standardized 2D synthetic image was produced, where each pixel value represents the percentage of BD above its location. The significant findings indicate the validity of the technique. Derivations supported by empirical analyses produced a new synthetic 2D standardized image technique. Ancillary to the objectives, the results provide evidence for understanding the percentage of BD measure applied to 2D mammograms. Notwithstanding the findings, the study design provides a template for investigating other measures such as texture.