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Objective To report the latest UK mammography dose survey results and to compare radiation doses from digital breast tomosynthesis (DBT) and full-field digital mammography (FFDM) in UK breast screening. Methods Anonymized exposure factors were collected for 111 152 screening cases and 5113 assessment cases from 405 x-ray sets across the United Kingdom using an online submission system linked to a national database of mammography quality control data. Output and beam quality measurements from each set were combined with exposure data to estimate mean glandular doses (MGD). Results FFDM doses increased by ∼10% compared to the 2016-2019 national survey but compressed breast thicknesses (CBT) remained similar. DBT doses were 34%-40% higher than FFDM overall and 34% higher than FFDM for breasts 50-60 mm thick. We found a possible overestimation of PMMA breast equivalent thicknesses at low CBTs, but the evidence was not conclusive. Conclusion Recent changes to the mix of x-ray models in use in UK breast screening have resulted in higher FFDM breast doses. DBT doses in the NHSBSP are on average higher than FFDM by ∼34%-40%. Advances in knowledge This is the first national study to report DBT and FFDM MGDs in UK breast screening. [ABSTRACT FROM AUTHOR]

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To record the radiation doses involved in UK breast screening and to identify any changes since previous publications related to technical factors and the population screened. Mammographic exposure factors for 68,998 women imaged using 411 X-ray sets spread across the UK were compiled. Local output and half value layer measurements for each X-ray set were used to estimate mean glandular dose (MGD) using the standard UK method. Mean MGDs in digital mammography have increased by 11% since 2010–12 for both medio-lateral oblique (MLO) and cranio-caudal (CC) views. The mean compressed breast thickness (CBT) has increased (4.8% CC, 5.2% MLO) over the same period. The mean MLO CBT value of 62.4 ± 0.1 mm is outside the 50 to 60 mm range used for diagnostic reference levels. The increase in MGD is consistent with the CBT changes. The mean MGD in the 50 to 60 mm CBT range is 1.44 ± 0.03 mGy for MLO views. CBT varies with age and peaks at 51. Mean CBT has increased with time, and this has increased mean MGDs for digital mammography. CBT also varies with age. Updated average MGDs in the UK are provided. There is evidence that breast size is increasing in the UK and that mean CBT is affected by age-related changes in the breast. [ABSTRACT FROM AUTHOR]

Objectives: To assess the performance of breast cancer screening by category of breast density and age in a UK screening cohort.Raw full-field digital mammography data from a single site in the UK, forming a consecutive 3-year cohort of women aged 50 to 70 years from 2016 to 2018, were obtained retrospectively. Breast density was assessed using Volpara software. Examinations were grouped by density category and age group (50–60 and 61–70 years) to analyse screening performance. Statistical analysis was performed to determine the association between density categories and age groups. Volumetric breast density was assessed as a binary classifier of interval cancers (ICs) to find an optimal density threshold.Forty-nine thousand nine-hundred forty-eight screening examinations (409 screen-detected cancers (SDCs) and 205 ICs) were included in the analysis. Mammographic sensitivity, SDC/(SDC + IC), decreased with increasing breast density from 75.0% for density a (p = 0.839, comparisons made to category b), to 73.5%, 59.8% (p = 0.001), and 51.3% (p < 0.001) in categories b, c, and d, respectively. IC rates were highest in the densest categories with rates of 1.8 (p = 0.039), 3.2, 5.7 (p < 0.001), and 7.9 (p < 0.001) per thousand for categories a, b, c, and d, respectively. The recall rate increased with breast density, leading to more false positive recalls, especially in the younger age group. There was no significant difference between the optimal density threshold found, 6.85, and that Volpara defined as the b/c boundary, 7.5.The performance of screening is significantly reduced with increasing density with IC rates in the densest category four times higher than in women with fatty breasts. False positives are a particular issue for the younger subgroup without prior examinations.In women attending screening there is significant underdiagnosis of breast cancer in those with dense breasts, most marked in the highest density category but still three times higher than in women with fatty breasts in the second highest category.Breast density can mask cancers leading to underdiagnosis on mammography.Interval cancer rate increased with breast density categories ‘a’ to ‘d’; 1.8 to 7.9 per thousand.Recall rates increased with increasing breast density, leading to more false positive recalls.Breast density can mask cancers leading to underdiagnosis on mammography.Interval cancer rate increased with breast density categories ‘a’ to ‘d’; 1.8 to 7.9 per thousand.Recall rates increased with increasing breast density, leading to more false positive recalls.Methods: To assess the performance of breast cancer screening by category of breast density and age in a UK screening cohort.Raw full-field digital mammography data from a single site in the UK, forming a consecutive 3-year cohort of women aged 50 to 70 years from 2016 to 2018, were obtained retrospectively. Breast density was assessed using Volpara software. Examinations were grouped by density category and age group (50–60 and 61–70 years) to analyse screening performance. Statistical analysis was performed to determine the association between density categories and age groups. Volumetric breast density was assessed as a binary classifier of interval cancers (ICs) to find an optimal density threshold.Forty-nine thousand nine-hundred forty-eight screening examinations (409 screen-detected cancers (SDCs) and 205 ICs) were included in the analysis. Mammographic sensitivity, SDC/(SDC + IC), decreased with increasing breast density from 75.0% for density a (p = 0.839, comparisons made to category b), to 73.5%, 59.8% (p = 0.001), and 51.3% (p < 0.001) in categories b, c, and d, respectively. IC rates were highest in the densest categories with rates of 1.8 (p = 0.039), 3.2, 5.7 (p < 0.001), and 7.9 (p < 0.001) per thousand for categories a, b, c, and d, respectively. The recall rate increased with breast density, leading to more false positive recalls, especially in the younger age group. There was no significant difference between the optimal density threshold found, 6.85, and that Volpara defined as the b/c boundary, 7.5.The performance of screening is significantly reduced with increasing density with IC rates in the densest category four times higher than in women with fatty breasts. False positives are a particular issue for the younger subgroup without prior examinations.In women attending screening there is significant underdiagnosis of breast cancer in those with dense breasts, most marked in the highest density category but still three times higher than in women with fatty breasts in the second highest category.Breast density can mask cancers leading to underdiagnosis on mammography.Interval cancer rate increased with breast density categories ‘a’ to ‘d’; 1.8 to 7.9 per thousand.Recall rates increased with increasing breast density, leading to more false positive recalls.Breast density can mask cancers leading to underdiagnosis on mammography.Interval cancer rate increased with breast density categories ‘a’ to ‘d’; 1.8 to 7.9 per thousand.Recall rates increased with increasing breast density, leading to more false positive recalls.Results: To assess the performance of breast cancer screening by category of breast density and age in a UK screening cohort.Raw full-field digital mammography data from a single site in the UK, forming a consecutive 3-year cohort of women aged 50 to 70 years from 2016 to 2018, were obtained retrospectively. Breast density was assessed using Volpara software. Examinations were grouped by density category and age group (50–60 and 61–70 years) to analyse screening performance. Statistical analysis was performed to determine the association between density categories and age groups. Volumetric breast density was assessed as a binary classifier of interval cancers (ICs) to find an optimal density threshold.Forty-nine thousand nine-hundred forty-eight screening examinations (409 screen-detected cancers (SDCs) and 205 ICs) were included in the analysis. Mammographic sensitivity, SDC/(SDC + IC), decreased with increasing breast density from 75.0% for density a (p = 0.839, comparisons made to category b), to 73.5%, 59.8% (p = 0.001), and 51.3% (p < 0.001) in categories b, c, and d, respectively. IC rates were highest in the densest categories with rates of 1.8 (p = 0.039), 3.2, 5.7 (p < 0.001), and 7.9 (p < 0.001) per thousand for categories a, b, c, and d, respectively. The recall rate increased with breast density, leading to more false positive recalls, especially in the younger age group. There was no significant difference between the optimal density threshold found, 6.85, and that Volpara defined as the b/c boundary, 7.5.The performance of screening is significantly reduced with increasing density with IC rates in the densest category four times higher than in women with fatty breasts. False positives are a particular issue for the younger subgroup without prior examinations.In women attending screening there is significant underdiagnosis of breast cancer in those with dense breasts, most marked in the highest density category but still three times higher than in women with fatty breasts in the second highest category.Breast density can mask cancers leading to underdiagnosis on mammography.Interval cancer rate increased with breast density categories ‘a’ to ‘d’; 1.8 to 7.9 per thousand.Recall rates increased with increasing breast density, leading to more false positive recalls.Breast density can mask cancers leading to underdiagnosis on mammography.Interval cancer rate increased with breast density categories ‘a’ to ‘d’; 1.8 to 7.9 per thousand.Recall rates increased with increasing breast density, leading to more false positive recalls.Conclusions: To assess the performance of breast cancer screening by category of breast density and age in a UK screening cohort.Raw full-field digital mammography data from a single site in the UK, forming a consecutive 3-year cohort of women aged 50 to 70 years from 2016 to 2018, were obtained retrospectively. Breast density was assessed using Volpara software. Examinations were grouped by density category and age group (50–60 and 61–70 years) to analyse screening performance. Statistical analysis was performed to determine the association between density categories and age groups. Volumetric breast density was assessed as a binary classifier of interval cancers (ICs) to find an optimal density threshold.Forty-nine thousand nine-hundred forty-eight screening examinations (409 screen-detected cancers (SDCs) and 205 ICs) were included in the analysis. Mammographic sensitivity, SDC/(SDC + IC), decreased with increasing breast density from 75.0% for density a (p = 0.839, comparisons made to category b), to 73.5%, 59.8% (p = 0.001), and 51.3% (p < 0.001) in categories b, c, and d, respectively. IC rates were highest in the densest categories with rates of 1.8 (p = 0.039), 3.2, 5.7 (p < 0.001), and 7.9 (p < 0.001) per thousand for categories a, b, c, and d, respectively. The recall rate increased with breast density, leading to more false positive recalls, especially in the younger age group. There was no significant difference between the optimal density threshold found, 6.85, and that Volpara defined as the b/c boundary, 7.5.The performance of screening is significantly reduced with increasing density with IC rates in the densest category four times higher than in women with fatty breasts. False positives are a particular issue for the younger subgroup without prior examinations.In women attending screening there is significant underdiagnosis of breast cancer in those with dense breasts, most marked in the highest density category but still three times higher than in women with fatty breasts in the second highest category.Breast density can mask cancers leading to underdiagnosis on mammography.Interval cancer rate increased with breast density categories ‘a’ to ‘d’; 1.8 to 7.9 per thousand.Recall rates increased with increasing breast density, leading to more false positive recalls.Breast density can mask cancers leading to underdiagnosis on mammography.Interval cancer rate increased with breast density categories ‘a’ to ‘d’; 1.8 to 7.9 per thousand.Recall rates increased with increasing breast density, leading to more false positive recalls.Clinical relevance statement: To assess the performance of breast cancer screening by category of breast density and age in a UK screening cohort.Raw full-field digital mammography data from a single site in the UK, forming a consecutive 3-year cohort of women aged 50 to 70 years from 2016 to 2018, were obtained retrospectively. Breast density was assessed using Volpara software. Examinations were grouped by density category and age group (50–60 and 61–70 years) to analyse screening performance. Statistical analysis was performed to determine the association between density categories and age groups. Volumetric breast density was assessed as a binary classifier of interval cancers (ICs) to find an optimal density threshold.Forty-nine thousand nine-hundred forty-eight screening examinations (409 screen-detected cancers (SDCs) and 205 ICs) were included in the analysis. Mammographic sensitivity, SDC/(SDC + IC), decreased with increasing breast density from 75.0% for density a (p = 0.839, comparisons made to category b), to 73.5%, 59.8% (p = 0.001), and 51.3% (p < 0.001) in categories b, c, and d, respectively. IC rates were highest in the densest categories with rates of 1.8 (p = 0.039), 3.2, 5.7 (p < 0.001), and 7.9 (p < 0.001) per thousand for categories a, b, c, and d, respectively. The recall rate increased with breast density, leading to more false positive recalls, especially in the younger age group. There was no significant difference between the optimal density threshold found, 6.85, and that Volpara defined as the b/c boundary, 7.5.The performance of screening is significantly reduced with increasing density with IC rates in the densest category four times higher than in women with fatty breasts. False positives are a particular issue for the younger subgroup without prior examinations.In women attending screening there is significant underdiagnosis of breast cancer in those with dense breasts, most marked in the highest density category but still three times higher than in women with fatty breasts in the second highest category.Breast density can mask cancers leading to underdiagnosis on mammography.Interval cancer rate increased with breast density categories ‘a’ to ‘d’; 1.8 to 7.9 per thousand.Recall rates increased with increasing breast density, leading to more false positive recalls.Breast density can mask cancers leading to underdiagnosis on mammography.Interval cancer rate increased with breast density categories ‘a’ to ‘d’; 1.8 to 7.9 per thousand.Recall rates increased with increasing breast density, leading to more false positive recalls.Key Points: To assess the performance of breast cancer screening by category of breast density and age in a UK screening cohort.Raw full-field digital mammography data from a single site in the UK, forming a consecutive 3-year cohort of women aged 50 to 70 years from 2016 to 2018, were obtained retrospectively. Breast density was assessed using Volpara software. Examinations were grouped by density category and age group (50–60 and 61–70 years) to analyse screening performance. Statistical analysis was performed to determine the association between density categories and age groups. Volumetric breast density was assessed as a binary classifier of interval cancers (ICs) to find an optimal density threshold.Forty-nine thousand nine-hundred forty-eight screening examinations (409 screen-detected cancers (SDCs) and 205 ICs) were included in the analysis. Mammographic sensitivity, SDC/(SDC + IC), decreased with increasing breast density from 75.0% for density a (p = 0.839, comparisons made to category b), to 73.5%, 59.8% (p = 0.001), and 51.3% (p < 0.001) in categories b, c, and d, respectively. IC rates were highest in the densest categories with rates of 1.8 (p = 0.039), 3.2, 5.7 (p < 0.001), and 7.9 (p < 0.001) per thousand for categories a, b, c, and d, respectively. The recall rate increased with breast density, leading to more false positive recalls, especially in the younger age group. There was no significant difference between the optimal density threshold found, 6.85, and that Volpara defined as the b/c boundary, 7.5.The performance of screening is significantly reduced with increasing density with IC rates in the densest category four times higher than in women with fatty breasts. False positives are a particular issue for the younger subgroup without prior examinations.In women attending screening there is significant underdiagnosis of breast cancer in those with dense breasts, most marked in the highest density category but still three times higher than in women with fatty breasts in the second highest category.Breast density can mask cancers leading to underdiagnosis on mammography.Interval cancer rate increased with breast density categories ‘a’ to ‘d’; 1.8 to 7.9 per thousand.Recall rates increased with increasing breast density, leading to more false positive recalls.Breast density can mask cancers leading to underdiagnosis on mammography.Interval cancer rate increased with breast density categories ‘a’ to ‘d’; 1.8 to 7.9 per thousand.Recall rates increased with increasing breast density, leading to more false positive recalls. [ABSTRACT FROM AUTHOR]

• The first study comparing breast screening performance on a test before, during and after COVID-19. • High sensitivity and low specificity were only observed in the test administered during lockdown. • Readers' over-recalling could be due to changes to national breast screening over lockdown. In the UK, the COVID-19 pandemic and the resulting lockdown significantly impacted routine breast screening and led to reduced case volumes for breast screening readers. The aim of the study was to evaluate whether breast screening performance on a test-set based assessment scheme (PERFORMS) varied over time, in association with the lockdown period. In this retrospective study, performance data were obtained for all breast cancer screening readers in England who completed the PERFORMS schemes based on digital mammography (from 2015 to 2022). Cancer detection (sensitivity), correct return to screen (specificity) and the difference between the sensitivity and specificity were calculated for each breast screener in each PERFORMS scheme. During the study period, 4906 readers participated in eight PERFORMS schemes. Both the cancer detection (H(7) = 775.56, p <.00001) and correct return to screen rate (H(7) = 401.13, p <.00001) varied significantly by scheme. The difference between cancer detection and correct return to screen rate in the scheme administered during the lockdown period was significantly higher than in all other schemes (p <.05, Bonferroni correction applied). The performance of breast screeners on the PERFORMS test-set based assessment scheme which was administered during the lockdown period, was characterised by markedly high sensitivity and low specificity when compared to their performance on other tests taken pre-COVID and following the lockdown. [ABSTRACT FROM AUTHOR]

Objectives: eDiaMoND is a next generation Internet ("Grid") multidisciplinary research project funded by the UK e-Science Programme with the following objectives; the development of a next generation Internet enabled prototype to demonstrate the potential benefits of a national infrastructure to support digital mammography; the exploration of potential benefits for digital mammography systems, with particular emphasis being placed on selected applications, namely, screening, training, computer-aided detection and appropriate support for epidemiological studies.Methods: EDiaMoND has worked in conjunction with selected clinical partners to enable the collection of valuable mammography information and the design of applications based upon extensive requirements gathering exercises. The clinical partners validated both the immediate needs and assisted with defining future needs of such an architecture to support the UK Health Service.Results: The project has succeeded in invoking the interest of clinical partners and representatives of the UK NHS Breast Screening Programme in our vision of a world without film, albeit a long way off. The project has also succeeded in identifying the barriers to adopting this approach with the current limitations within the NHS, and has developed a blueprint for working towards this strategy.Conclusions: A UK national digital mammography archive has the potential to provide major benefits for the UK. For example, such an archive could: ensure that previous mammograms are always available, and could link up seamlessly the screening, assessment and symptomatic clinics; it could provide a huge teaching and training resource; it could be a huge resource for epidemiological studies. [ABSTRACT FROM AUTHOR]

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. This multicentre study recruited 446 patients from UK breast clinics. Participants underwent both standard FFDM and DBT. A blinded retrospective multireader study involving 12 readers and 300 mammograms (152 malignant and 148 benign cases) was conducted. Sensitivity for cancer was 86.6% with FFDM [95% CI (85.2–88.0%)], 89.1% with DBT [95% CI (88.2–90%)], and 91.7% with FFDM+DBT [95% CI (90.7–92.6%)]. In the densest breasts, the maximum sensitivity increment with FFDM +DBT over FFDM alone was 10.3%, varying by density measurement method. Overall specificity was 81.4% with FFDM [95% CI (80.5–82.3%)], 84.6% with DBT [95% CI (83.9–85.3%)], and 79.6% with FFDM +DBT [95% CI (79.0–80.2%)]. No differences were detected in accuracy of tumour measurement in unifocal cases. Where available, DBT merits first-line use in the under 60 age group in symptomatic breast clinics, particularly in women known to have very dense breasts. This study is one of very few to address the accuracy of DBT in symptomatic rather than screening patients. It quantifies the diagnostic gains of DBT in direct comparison with standard digital mammography, supporting informed decisions on appropriate use of DBT in this population. [ABSTRACT FROM AUTHOR]