Breast Cancer Screening: The Debate that Never Ends

Artificial Intelligence (AI) in Breast Imaging: A Scientometric Umbrella Review

Artificial intelligence (AI), a rousing advancement disrupting a wide spectrum of applications with remarkable betterment, has continued to gain momentum over the past decades. Within breast imaging, AI, especially machine learning and deep learning, honed with unlimited cross-data/case referencing, has found great utility encompassing four facets: screening and detection, diagnosis, disease monitoring, and data management as a whole. Over the years, breast cancer has been the apex of the cancer cumulative risk ranking for women across the six continents, existing in variegated forms and offering a complicated context in medical decisions. Realizing the ever-increasing demand for quality healthcare, contemporary AI has been envisioned to make great strides in clinical data management and perception, with the capability to detect indeterminate significance, predict prognostication, and correlate available data into a meaningful clinical endpoint. Here, the authors captured the review works over the past decades, focusing on AI in breast imaging, and systematized the included works into one usable document, which is termed an umbrella review. The present study aims to provide a panoramic view of how AI is poised to enhance breast imaging procedures. Evidence-based scientometric analysis was performed in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guideline, resulting in 71 included review works. This study aims to synthesize, collate, and correlate the included review works, thereby identifying the patterns, trends, quality, and types of the included works, captured by the structured search strategy. The present study is intended to serve as a "one-stop center" synthesis and provide a holistic bird's eye view to readers, ranging from newcomers to existing researchers and relevant stakeholders, on the topic of interest.

Women's Breast Cancer Screening Confidence by Screening Modality and Breast Density: A Breast Cancer Surveillance Consortium Survey Study

Objective: Little is known about women's confidence in their breast cancer screening. We sought to characterize breast cancer screening confidence by imaging modality and clinically assessed breast density. Materials and Methods: We undertook a cross-sectional survey of women ages 40-74 years who received digital mammography (DM), digital breast tomosynthesis (DBT), and/or breast magnetic resonance imaging (MRI) with a normal screening exam in the prior year. The main outcome was women's confidence (Very, Somewhat, A little, Not at all) in their breast cancer screening detecting any cancer. Multivariable logistic regression identified correlates of being very confident in breast cancer screening by screening modality group: Group 1) DM vs. DBT and Group 2) DM or DBT alone vs. with supplemental MRI. Results: Overall, 2329 of 7439 (31.3%) invitees participated, with 30%-61% being very confident in their screening across modality and density subgroups. Having dense versus nondense breasts was associated with lower odds of being very confident (Group 1: odds ratio [OR]: 0.58; 95% confidence interval [CI]: 0.46-0.79; Group 2: OR: 0.56; 95% CI: 0.40-0.79). There were no differences by modality within Group 1, but for Group 2, women undergoing MRI had higher odds of being very confident (OR: 1.69; 95% CI: 1.21-2.37). Other correlates of greater screening confidence were as follows: Group 1-being offered a screening test choice and cost not influencing modality received, and Group 2-decision satisfaction and worry. Conclusions: Women with dense breasts had lower screening confidence regardless of screening modality and those undergoing MRI had higher confidence regardless of density. The importance of informing women about screening options is underscored by observed associations between screening choice, decision satisfaction, and screening confidence. ClinicalTrials.gov: NCT02980848.

Prevalence of Molecular Subtypes in Operated Cases of Breast Cancer and Its Clinicopathological Correlation: A Single Institute Study from a Tertiary Cancer Centre in North India

Breast cancer has emerged as a major health problem among women in India. There are few Indian studies which have looked at prevalence of molecular subtypes of breast cancer in Indian population. The primary objective of our study was to find out the prevalence of various molecular subtypes in operated cases of breast cancer patients presenting to us. Three hundred sixty patients who were operated in our department were analysed. Clinicopathological features of all cases were recorded. Classification into various molecular subtypes was done using St. Gallen 2013 criteria. Luminal B HER2 negative was the predominant molecular subtype in our study population constituting 30.3% of patients. The percentage of aggressive subtypes, viz. triple negative breast cancer and HER2 enriched, were 21.7% and 11.4% respectively. Only 19.4% of patients in our study population had tumour size ≤ 2 cm with nodes being positive in 56.9% of our patients at presentation. Data from our study and other studies published from India show that the two most aggressive subtypes of, viz. triple negative breast cancer and HER2 enriched, may be more prevalent in our population as compared to western population.

Estimating the Breast Cancer Burden in Germany and Implications for Risk-based Screening

In Germany, it is currently recommended that women start mammographic breast cancer screening at age 50. However, recently updated guidelines state that for women younger than 50 and older than 70 years of age, screening decisions should be based on individual risk. International clinical guidelines recommend starting screening when a woman's 5-year risk of breast cancer exceeds 1.7%. We thus compared the performance of the current age-based screening practice with an alternative risk-adapted approach using data from a German population representative survey. We found that 10,498,000 German women ages 50-69 years are eligible for mammographic screening based on age alone. Applying the 5-year risk threshold of 1.7% to individual breast cancer risk estimated from a model that considers a woman's reproductive and personal characteristics, 39,000 German women ages 40-49 years would additionally be eligible. Among those women, the number needed to screen to detect one breast cancer case, NNS, was 282, which was close to the NNS = 292 among all 50- to 69-year-old women. In contrast, NNS = 703 for the 113,000 German women ages 50-69 years old with 5-year breast cancer risk <0.8%, the median 5-year breast cancer risk for German women ages 45-49 years, which we used as a low-risk threshold. For these low-risk women, longer screening intervals might be considered to avoid unnecessary diagnostic procedures. In conclusion, we show that risk-adapted mammographic screening could benefit German women ages 40-49 years who are at elevated breast cancer risk and reduce cost and burden among low-risk women ages 50-69 years. PREVENTION RELEVANCE: We show that a risk-based approach to mammography screening for German women can help detect breast cancer in women ages 40-49 years with increased risk and reduce screening costs and burdens for low-risk women ages 50-69 years. However, before recommending a particular implementation of a risk-based mammographic screening approach, further investigations of models and thresholds used are needed.

A review of various modalities in breast imaging: technical aspects and clinical outcomes

Background

Nowadays, breast cancer is the second cause of death after cardiovascular diseases. In general, about one out of eight women (about 12%) suffer from this disease during their life in the USA and European countries. If breast cancer is detected at an early stage, its survival rate will be very high. Several methods have been introduced to diagnose breast cancer with their clinical advantages and disadvantages.

Main text

In this review, various methods of breast imaging have been introduced. Furthermore, the sensitivity and specificity of each of these methods have been investigated. For each of the imaging methods, articles that were relevant to the past 10 years were selected through electronic search engines, and then the most relevant papers were selected. Finally, about 40 articles were studied and their results were categorized and presented in the form of a report as follows. Various breast cancer imaging techniques were extracted as follows: mammography, contrast-enhanced mammography, digital tomosynthesis, sonography, sonoelastography, magnetic resonance imaging, magnetic elastography, diffusion-weighted imaging, magnetic spectroscopy, nuclear medicine, optical imaging, and microwave imaging.

Conclusion

The choice of these methods depends on the patient’s state and stage, the age of the individual and the density of the breast tissue. Hybrid imaging techniques appear to be an acceptable way to improve detection of breast cancer. This review article can be useful in choosing the right method for imaging in people suspected of breast cancer.

Mammographic Screening in Older Women: When Is It Time to Stop?

Mammographic screening guidelines in women aged 75 and older are inconsistent due to a lack of data from prospective randomized controlled trials, such as those that exist for women between 40-74 years of age. In addition, older women are perceived as less likely to benefit from early detection due to increased comorbidities and a greater proportion of biologically favorable cancers. With increasing life expectancy and quality of life in the elderly, the question of when to stop mammographic screening merits renewed discussion. Observational data support a survival benefit from regular screening in older women with no severe comorbidities. In addition, screening mammography in this age group has been shown to perform better than in younger age groups, tipping the balance toward greater benefits than harms. Early studies of digital breast tomosynthesis (DBT) in older women suggest that performance metrics are further improved with DBT screening. While a biennial schedule in older women preserves some of the benefit of screening, annual mammography achieves the greatest reductions in breast cancer mortality and morbidity. As the medical community strives to offer personalized care for all age groups, health care providers are well positioned to offer shared decision-making based on existing data and tailored to each woman's individual risk profile, comorbid conditions, and personal values.