Percentage mammographic density or absolute breast density for risk stratification in breast screening: Possible implications for socioeconomic health disparity.

Objectives: Obesity levels and mortality from breast cancer are higher in more deprived areas of the UK, despite lower breast cancer incidence. Supplemental imaging for women with dense breasts has been proposed as a potential improvement to screening, but it is not clear how stratification by percentage mammographic density (%MD) would be reflected across socioeconomic groups. This study aims to clarify the associations between breast composition (dense and fatty tissue) and socioeconomic status in a multi-ethnic screening population.

Clinical Integration of Artificial Intelligence for Breast Imaging.

This article describes an approach to planning and implementing artificial intelligence products in a breast screening service. It highlights the importance of an in-depth understanding of the end-to-end workflow and effective project planning by a multidisciplinary team. It discusses the need for monitoring to ensure that performance is stable and meets expectations, as well as focusing on the potential for inadvertantly generating inequality.

Evidence-informed recommendations on managing breast screening atypia: perspectives from an expert panel consensus meeting reviewing results from the Sloane atypia project.

Evidence-based clinical guidelines are essential to maximize patient benefit and to reduce clinical uncertainty and inconsistency in clinical practice. Gaps in the evidence base can be addressed by data acquired in routine practice. At present, there is no international consensus on management of women diagnosed with atypical lesions in breast screening programmes.

Development and quality appraisal of a new English breast screening linked data set as part of the age, test threshold, and frequency of mammography screening (ATHENA-M) study.

Objectives: To build a data set capturing the whole breast cancer screening journey from individual breast cancer screening records to outcomes and assess data quality.

Methods: Routine screening records (invitation, attendance, test results) from all 79 English NHS breast screening centres between January 1, 1988 and March 31, 2018 were linked to cancer registry (cancer characteristics and treatment) and national mortality data. Data quality was assessed using comparability, validity, timeliness, and completeness.

Should we share breast density information during breast cancer screening in the United Kingdom? an integrative review.

Objective: Dense breasts are an established risk factor for breast cancer and also reduce the sensitivity of mammograms. There is increasing public concern around breast density in the UK, with calls for this information to be shared at breast cancer screening.

Methods: We searched the PubMed database, Cochrane Library and grey literature, using broad search terms in October 2022.

Are mammography image acquisition factors, compression pressure and paddle tilt, associated with breast cancer detection in screening?

Objectives: To assess the associations between objectively measured mammographic compression pressure and paddle tilt and breast cancer (BC) detected at the same ("contemporaneous") screen, subsequent screens, or in-between screens (interval cancers).

Methods: Automated pressure and paddle tilt estimates were derived for 80,495 mammographic examinations in a UK population-based screening programme. Adjusted logistic regression models were fitted to estimate the associations of compression parameters with BC detected at contemporaneous screen (777 cases).

To what extent are objectively measured mammographic imaging techniques associated with compression outcomes.

Objective: To describe the association between objectively measurable imaging techniques and the resulting compression thickness and dose.

Methods: The study included 80,495 routine screens from the South-West London Breast Screening Service between March 2013 and July 2017. Average compression force, paddle tilt and dose were calculated.

Quantitative background parenchymal enhancement and fibro-glandular density at breast MRI: Association with BRCA status.

Objectives: To investigate whether MRI-based measurements of fibro-glandular tissue volume, breast density (MRBD), and background parenchymal enhancement (BPE) could be used to stratify two cohorts of healthy women: BRCA carriers and women at population risk of breast cancer.

Methods: Pre-menopausal women aged 40-50 years old were scanned at 3 T, employing a standard breast protocol including a DCE-MRI (35 and 30 participants in high- and low-risk groups, respectively). The dynamic range of the DCE protocol was characterised and both breasts were masked and segmented with minimal user input to produce measurements of fibro-glandular tissue volume, MRBD, and voxelwise BPE.

Lessons learned from independent external validation of an AI tool to detect breast cancer using a representative UK data set.

Objective: To pilot a process for the independent external validation of an artificial intelligence (AI) tool to detect breast cancer using data from the NHS breast screening programme (NHSBSP).

Methods: A representative data set of mammography images from 26,000 women attending 2 NHS screening centres, and an enriched data set of 2054 positive cases were used from the OPTIMAM image database. The use case of the AI tool was the replacement of the first or second human reader.

Recommendations for the development and use of imaging test sets to investigate the test performance of artificial intelligence in health screening.

Rigorous evaluation of artificial intelligence (AI) systems for image classification is essential before deployment into health-care settings, such as screening programmes, so that adoption is effective and safe. A key step in the evaluation process is the external validation of diagnostic performance using a test set of images. We conducted a rapid literature review on methods to develop test sets, published from 2012 to 2020, in English.

UK National Screening Committee's approach to reviewing evidence on artificial intelligence in breast cancer screening.

Artificial intelligence (AI) could have the potential to accurately classify mammograms according to the presence or absence of radiological signs of breast cancer, replacing or supplementing human readers (radiologists). The UK National Screening Committee's assessments of the use of AI systems to examine screening mammograms continues to focus on maximising benefits and minimising harms to women screened, when deciding whether to recommend the implementation of AI into the Breast Screening Programme in the UK. Maintaining or improving programme specificity is important to minimise anxiety from false positive results.

Understanding and supporting peer relationships in adolescents with acquired brain injury: A stakeholder engagement study.

Peer relationship difficulties in adolescents with acquired brain injury (ABI) are under-recognized and targets for intervention are unclear. From a social constructionist position, this study aimed to engage with stakeholders to develop a collaborative understanding of peer relationship difficulties in adolescents with ABI and seek consultation on what might be required to improve them. Focus groups and semi-structured interviews were conducted with four stakeholder groups: adolescents with ABI ( = 4); parents of adolescents with ABI ( = 7); adults who sustained an ABI in adolescence ( = 2); and specialist practitioners ( = 3).

Understanding breast cancer as a global health concern.

Breast cancer is now the most commonly diagnosed cancer in the world. The most recent global cancer burden figures estimate that there were 2.26 million incident breast cancer cases in 2020 and the disease is the leading cause of cancer mortality in women worldwide.

Virtual clinical trial to compare cancer detection using combinations of 2D mammography, digital breast tomosynthesis and synthetic 2D imaging.

Objectives: This study was designed to compare the detection of subtle lesions (calcification clusters or masses) when using the combination of digital breast tomosynthesis (DBT) and synthetic mammography (SM) with digital mammography (DM) alone or combined with DBT.

Methods: A set of 166 cases without cancer was acquired on a DBT mammography system. Realistic subtle calcification clusters and masses in the DM images and DBT planes were digitally inserted into 104 of the acquired cases.

Quantitative breast density analysis to predict interval and node-positive cancers in pursuit of improved screening protocols: a case-control study.

Background: This study investigates whether quantitative breast density (BD) serves as an imaging biomarker for more intensive breast cancer screening by predicting interval, and node-positive cancers.

Methods: This case-control study of 1204 women aged 47-73 includes 599 cancer cases (302 screen-detected, 297 interval; 239 node-positive, 360 node-negative) and 605 controls. Automated BD software calculated fibroglandular volume (FGV), volumetric breast density (VBD) and density grade (DG).

Digital breast tomosynthesis: sensitivity for cancer in younger symptomatic women.

Objective: Full-field digital mammography (FFDM) has limited sensitivity for cancer in younger women with denser breasts. Digital breast tomosynthesis (DBT) can reduce the risk of cancer being obscured by overlying tissue. The primary study aim was to compare the sensitivity of FFDM, DBT and FFDM-plus-DBT in women under 60 years old with clinical suspicion of breast cancer.

Left-right breast asymmetry and risk of screen-detected and interval cancers in a large population-based screening population.

Objectives: To assess the associations between automated volumetric estimates of mammographic asymmetry and breast cancers detected at the same ("contemporaneous") screen, at subsequent screens, or in between (interval cancers).

Methods: Automated measurements from mammographic images ( = 79,731) were used to estimate absolute asymmetry in breast volume (BV) and dense volume (DV) in a large ethnically diverse population of attendees of a UK breast screening programme. Logistic regression models were fitted to assess asymmetry associations with the odds of a breast cancer detected at contemporaneous screen (767 cases), adjusted for relevant confounders.

Radiological audit of interval breast cancers: Estimation of tumour growth rates.

Introduction: This multicentre, retrospective study aimed to establish correlation between estimated tumour volume doubling times (TVDT) from a series of interval breast cancers with their clinicopathological features. The potential impact of delayed diagnosis on prognosis was also explored.

Materials And Methods: Interval cancers, where screening mammograms demonstrated changes that were retrospectively classified as either uncertain or suspicious, were reviewed from five screening units within the UK NHS Breast Screening Programme (NHSBSP).

An automated approach for the optimised estimation of breast density with Dixon methods.

Objective: To present and evaluate an automated method to correct scaling between Dixon water/fat images used in breast density (BD) assessments.

Methods: Dixon images were acquired in 14 subjects with different weightings (flip angles, FA, 4°/16°). Our method corrects intensity differences between water () and fat () images via the application of a uniform scaling factor (SF), determined subject-by-subject.

Ethnic and age differences in right-left breast asymmetry in a large population-based screening population.

Objective: Exposure to sex hormones is important in the pathogenesis of breast cancer and inability to tolerate such exposure may be reflected in increased asymmetrical growth of the breasts. This study aims to characterize, for the first time, asymmetry in breast volume (BV) and radiodense volume (DV) in a large ethnically diverse population.

Methods: Automated measurements from digital raw mammographic images of 54,591 cancer-free participants (aged 47-73) in a UK breast screening programme were used to calculate absolute (cm) and relative asymmetry in BV and DV.

Implementation of the SMART MOVE intervention in primary care: a qualitative study using normalisation process theory.

Background: Problematic translational gaps continue to exist between demonstrating the positive impact of healthcare interventions in research settings and their implementation into routine daily practice. The aim of this qualitative evaluation of the SMART MOVE trial was to conduct a theoretically informed analysis, using normalisation process theory, of the potential barriers and levers to the implementation of a mhealth intervention to promote physical activity in primary care.

Methods: The study took place in the West of Ireland with recruitment in the community from the Clare Primary Care Network.