Population-based Breast Cancer Screening Program Research Articles

Australian healthcare workers’ views on artificial intelligence in BreastScreen: Results of a mixed method survey study

IntroductionThe evolving role of Artificial Intelligence (AI) in medicine, particularly in radiology and population-based breast cancer screening programs, offers potential accuracy gains and efficiency improvements. However, successful implementation requires understanding of healthcare workers’ views on AI, which this study aims to explore within the Australian BreastScreen program. MethodsAn online survey was distributed to clinical staff involved in breast imaging, collecting responses from November 2022 to April 2023. The survey encompassed demographic information, opinions, and experiences with AI in medical imaging, with questions covering various scenarios of AI integration in BreastScreen ResultsOut of an estimated 350 professionals contacted, 95 responded, with 84.2 % (80/95) being radiologists. Less than half of respondents (44.9 %, 40/89) had worked with artificial intelligence for image classification previously. The majority of radiologists 74.2 % (46/62) thought that the use of AI in reading mammograms for BreastScreen would improve workflow. However, radiologists thought they would behave with increasing caution with scenarios where AI was more autonomous, with the majority of radiologists (63.3 %, 38/60) uncomfortable with holding accountability when the AI was used to triage and remove cases from the workflow. Notably, 60 % of radiologists (36/60) expressed concerns about accountability. DiscussionThe findings suggest an optimistic attitude towards AI among Australian healthcare workers, although when given hypothetical scenarios for the way AI could be integrated into BreastScreen, there was increasing caution with scenarios where AI was more autonomous. This study highlights understanding and concerns of healthcare professionals working in population screening which are important to address when implementing AI into the healthcare system.

Random effects models of tumour growth for investigating interval breast cancer.

In Nordic countries and across Europe, breast cancer screening participation is high. However, a significant number of breast cancer cases are still diagnosed due to symptoms between screening rounds, termed "interval cancers". Radiologists use the interval cancer proportion as a proxy for the screening false negative rate (ie, 1-sensitivity). Our objective is to enhance our understanding of interval cancers by applying continuous tumour growth models to data from a study involving incident invasive breast cancer cases. Building upon previous findings regarding stationary distributions of tumour size and growth rate distributions in non-screened populations, we develop an analytical expression for the proportion of interval breast cancer cases among regularly screened women. Our approach avoids relying on estimated background cancer rates. We make specific parametric assumptions concerning tumour growth and detection processes (screening or symptoms), but our framework easily accommodates alternative assumptions. We also show how our developed analytical expression for the proportion of interval breast cancers within a screened population can be incorporated into an approach for fitting tumour growth models to incident case data. We fit a model on 3493 cases diagnosed in Sweden between 2001 and 2008. Our methodology allows us to estimate the distribution of tumour sizes at the most recent screening for interval cancers. Importantly, we find that our model-based expected incidence of interval breast cancers aligns closely with observed patterns in our study and in a large Nordic screening cohort. Finally, we evaluate the association between screening interval length and the interval cancer proportion. Our analytical expression represents a useful tool for gaining insights into the performance of population-based breast cancer screening programs.

Impact of real-life use of artificial intelligence as support for human reading in a population-based breast cancer screening program with mammography and tomosynthesis

ObjectivesTo evaluate the impact of using an artificial intelligence (AI) system as support for human double reading in a real-life scenario of a breast cancer screening program with digital mammography (DM) or digital breast tomosynthesis (DBT).Material and methodsWe analyzed the performance of double reading screening with mammography and tomosynthesis after implementarion of AI as decision support. The study group consisted of a consecutive cohort of 1 year screening between March 2021 and March 2022 where double reading was performed with concurrent AI support that automatically detects and highlights lesions suspicious of breast cancer in mammography and tomosynthesis. Screening performance was measured as cancer detection rate (CDR), recall rate (RR), and positive predictive value (PPV) of recalls. Performance in the study group was compared using a McNemar test to a control group that included a screening cohort of the same size, recorded just prior to the implementation of AI.ResultsA total of 11,998 women (mean age 57.59 years ± 5.8 [sd]) were included in the study group (5049 DM and 6949 DBT). Comparing global results (including DM and DBT) of double reading with vs. without AI support, we observed an increase in CDR, PPV, and RR by 3.2/‰ (5.8 vs. 9; p < 0.001), 4% (10.6 vs. 14.6; p < 0.001), and 0.7% (5.4 vs. 6.1; p < 0.001) respectively.ConclusionAI used as support for human double reading in a real-life breast cancer screening program with DM and DBT increases CDR and PPV of the recalled women.Clinical relevance statementArtificial intelligence as support for human double reading improves accuracy in a real-life breast cancer screening program both in digital mammography and digital breast tomosynthesis.Key Points• AI systems based on deep learning technology offer potential for improving breast cancer screening programs.• Using artificial intelligence as support for reading improves radiologists’ performance in breast cancer screening programs with mammography or tomosynthesis.• Artificial intelligence used concurrently with human reading in clinical screening practice increases breast cancer detection rate and positive predictive value of the recalled women.

Population-based breast cancer screening in Pavia (northern Italy) in 2016-2018: Key performance indicators and sensitivity estimate.

This study aims to assess the quality of the population-based breast cancer screening programme in Pavia, northern Italy computing its key performance indicators and estimating its sensitivity for the years 2016-2018. Invitation and examination coverage, participation rate, recall rate, detection rate and positive predictive values were computed on the basis of data provided yearly to the Italian Ministry of Health. Sensitivity was estimated identifying interval cancers in the local Cancer Registry and computed with the proportional incidence method. In 2016-2018 the adjusted invitation coverage was 90%, and the adjusted participation rate was 62%. Recall rate was 8.4% for first screenings and 3.9% for subsequent ones. The number of screen-detected cases was 268, corresponding to a detection rate of 6.6‰ for first screenings and 4.6‰ for subsequent screenings. The number of interval cancers observed was 110 over the study period; the proportional incidence was 22% for the first interval year and 50% for the second interval. The overall sensitivity of the screening program was 64%. The analysis of performance indicators and sensitivity estimates for the Pavia programme indicates that the programme performance is in line with the quality standards set by the European Union and the Italian reference scientific society (GISMa).

Carcinoma de intervalo en un programa de cribado de cáncer de mama (2007-2018). Características y pronóstico

Background and aimsTo analyze the radiologic and histologic characteristics of screening and interval cancers diagnosed in the period comprising 2007 through 2018 in a total of six rounds of a population-based breast cancer screening program. Material and methodsWe analyzed 1395 carcinomas detected at screening and 300 interval carcinomas diagnosed in women aged 50 to 69years old who underwent digital mammography every two years during the study period. Screening mammograms were read once.To classify the interval carcinomas, we retrospectively reviewed (blind reading followed by unblinded reading) at the end of each round, recording the radiologic findings, breast density, histologic characteristics, phenotype, and surgical treatment. ResultsThe interval carcinomas were classified as true interval cancers in 156 (52%) cases, false-negatives in 62 (20.5%), minimal signs in 39 (13%), occult lesions in 29 (9.5%), and impossible to classify in 14 (5%).Retrospectively, the most common radiologic findings in the false-negative cases were mass/asymmetry (64%), calcifications (16%), and distortion (13%); the most common radiologic findings in the cases with minimal signs were mass/asymmetry (58%) and calcifications (31%).There were significant differences in the histologic characteristics between cancers detected at screening and interval cancers: T1a-b (9% of the interval cancers vs. 34% of those detected at screening; P<.001); T1c (30% of the interval cancers vs. 44% of those detected at screening; P<.001); T2 or greater (61% of the interval cancers vs. 22% of those detected at screening; P<.001), and the degree of axillary involvement (45% of the interval cancers vs. 27% of those detected at screening; P<.001).There were also significant differences between cancers detected at screening and interval cancers in the proportion of cases with more aggressive subtypes (HER2+ and triple-negative): 38.5% of the interval cancers vs. 23% of those detected at screening; P<.001.A significantly higher proportion of interval cancers were treated with mastectomies (80% vs. 67% of those detected at screening; P<.001). ConclusionsAbout 20% of interval cancers were evident on screening mammograms. The most common radiologic finding in interval cancers was asymmetry/mass. Interval cancers are diagnosed at a more advanced stage than cancers identified at screening, so they are more often treated by mastectomy. Reviewing interval cancers is essential for quality control in screening programs.

Concurrent participation in breast, cervical, and colorectal cancer screening in the Netherlands

BackgroundMany European countries offer organised population-based breast, cervical, and colorectal cancer screening programmes. Around age 55 and 60, Dutch women are invited to all three screening programmes. We examined the extent to which participation concurs and identified factors influencing concurrent participation. Materials and methodsIndividual level data from breast, cervical, and colorectal cancer screening invitations between 2017 and 2019 were extracted from the Dutch screening registry. The percentages of women participating in all three, two, one, or none of the programmes around age 55 and 60, and before subsequent round invitation were determined. Multivariate ordinal regression analyses were performed to estimate whether population density, socio-economic status (SES) per postal code area, and time between the three invitations (<3, 3–6, >6 months) were associated with concurrent participation. ResultsData from 332,484 women were analysed. At age 55, 53.7% participated in all three programmes, 22.1% in two, 11.7% in one, and 12.6% did not participate at all. At age 60, a similar participation pattern was observed. Women living in areas with higher population density were less likely (odds ratios 0.75–0.94) and women in higher SES groups were more likely (odds ratios 1.12–1.60) to participate in more screening programmes, although this positive association was smaller for the highest SES group. No substantial association was found between concurrent participation and timing of invitations. ConclusionsMore than half of Dutch women participated in all three screening programmes and around 12% did not participate in any. Concurrent participation was lower in cities and lower SES groups.

Performance of artificial intelligence-based breast cancer screening in a community setting: a real-world evaluation study

Despite improvements in treatment strategies, breast cancer survival rates in India remain low because of poor awareness and advanced stages at presentation. Early diagnosis and treatment can improve the survival rates of patients with breast cancer. A population-based breast cancer screening programme with mammography is often not feasible in resource-constrained settings. Thermalytix, a novel breast cancer screening technology, applies artificial intelligence algorithms over thermal images to generate an automated interpretation report indicating breast health. The Thermalytix testing equipment is portable, requires minimal skills to operate, and operation is 20 times less expensive than a mammography. The test has been used to screen women in community settings in India. This study was done to assess the performance of the Thermalytix test in identifying women suspicious of breast cancer in community settings. Women who underwent Thermalytix tests in community-based screening camps in the Indian states of Karnataka and Maharashtra between Aug 12, 2017, and May 31, 2021, were included in this study. The Thermalytix test captured five thermal images in multiple views from each participant and the tool automatically generated a triage report. A more detailed report with annotations of probably abnormal regions and an overall breast health score ranging from 0 to 5 (B-score) was also generated. A B-score of 4 or 5 on triage indicates a high level of concern and prompts a recommendation to follow-up with breast ultrasonography. A B-score of 3 prompts a recommendation to repeat the Thermalytix test after 3 months. A B-score of 1 or 2 indicates thermal patterns of low level, usually prompting a recommendation to continue routine screening. Participants with B-scores of 4 or 5 on the Thermalytix test were followed-up with a telephone call to obtain information about their subsequent tests, such as mammography, ultrasonography, or histopathological examination. Women with a follow-up report were categorised as having "Normal", "Abnormal-Benign", or "Abnormal-Malignant" findings (as per their Breast Imaging Reporting and Data System score of 1, 2 or 3, or 4 or 5, respectively). 13 932 women were included in the analysis. 775 women complained of a breast lump, 625 (4·5%) of whom were given B-scores of 4 or 5 after Thermalytix testing and were referred for follow-up breast ultrasonography. 117 (18·7%) of these 625 women underwent standard follow-up investigations. Abnormalities were detected in 78 of the 117 followed-up women (74 benign and four malignant breast lesions), indicating that Thermalytix has a positive predictive value of 66·7% in detecting benign and malignant breast lesions. In resource-constrained countries where systematic screening programmes with mammography is not scalable or feasible, the portable, radiation-free Thermalytix test is a promising option for affordable and accessible breast cancer screening. This screening test is not resource-intensive and can be set up in remote locations and operated with minimal training. The Thermalytix test can be used to triage women for referral for further evaluation in secondary or tertiary health-care centres, which makes it a logistically and economically feasible option for breast cancer screening in low-income and middle-income countries. This programme was sponsored by Niramai Health Analytix and was executed in collaboration with National Health Mission, Maharashtra, India, and Bruhat Bengaluru Mahanagara Palike, Municipal Corporation of Bangalore City, Karnataka, India.

Costs and Effects of Implementing Digital Tomosynthesis in a Population-Based Breast Cancer Screening Program: Predictions Using Results from the To-Be Trial in Norway.

BackgroundAlthough several studies from Europe and the US have shown promising screening results favoring digital breast tomosynthesis compared with standard digital mammography (DM), both costs and effects of implementing tomosynthesis in routine screening programs remain uncertain. The cost effectiveness of using tomosynthesis in routine screening is debated in the literature, and model inputs from randomized trials are lacking. Using parameters mainly from a randomized controlled trial (the To-Be trial), we simulated costs and effects of implementing tomosynthesis in the national screening program BreastScreen Norway.MethodsThe To-Be trial was performed in Bergen from 2016 to 2017 within BreastScreen Norway, where females were randomized to either digital breast tomosynthesis including synthetic mammograms (DBT) or DM. The trial was followed by a cohort study offering all females DBT in 2018–2019. The trial included over 37,000 females, and allowed for estimation of short-term costs and effects related to screening, recall examinations and cancer detection. Using these and recent Norwegian estimates for 10-year stage-specific survival and treatment costs, the cost effectiveness of replacing DM with DBT in BreastScreen Norway was simulated in a decision tree model with probabilistic sensitivity analyses. Outcomes included false-positive screening results, screen-detected and interval cancers, stage at diagnosis, all-cause deaths, life-years gained, costs at recall and treatment and incremental cost-effectiveness ratio.ResultsThe estimated additional cost of DBT was €8.10. Simulating ten rounds of screening from 2018 and 10-year survival and costs, 500 deaths were averted and 2300 life-years gained at an additional screening cost of €29 million for females screened with DBT versus DM. Taking over-diagnosis, recall and treatment costs into account, DBT was dominant in the deterministic analysis. The incremental cost-effectiveness ratio indicated cost savings of €1400 per life-year gained. Probabilistic sensitivity analyses showed that DBT was cost effective in over 50% of the simulations at all willingness-to-pay levels per life-year gained, and in 80% of the simulations at levels above €22,000. If willingness-to-pay levels up to €35,000 were assumed, DBT would be cost effective in over 50% of the simulations for additional costs of DBT of up to €32, almost four times the estimated additional cost of €8.10.ConclusionDBT may be cost effective if implemented in BreastScreen Norway. However, generalizability of results could depend on factors varying between countries, such as recall rates, program sensitivity and specificity, treatment cost and willingness-to-pay levels.Supplementary InformationThe online version contains supplementary material available at 10.1007/s41669-022-00343-5.

Impact of the COVID-19 pandemic on breast cancer screening indicators in a Spanish population-based program: a cohort study.

To assess the effect of the COVID-19 pandemic on performance indicators in the population-based breast cancer screening program of Parc de Salut Mar (PSMAR), Barcelona, Spain. We conducted a before-and-after, study to evaluate participation, recall, false positives, the cancer detection rate, and cancer characteristics in our screening population from March 2020 to March 2021 compared with the four previous rounds (2012-2019). Using multilevel logistic regression models, we estimated the adjusted odds ratios (aORs) of each of the performance indicators for the COVID-19 period, controlling by type of screening (prevalent or incident), socioeconomic index, family history of breast cancer, and menopausal status. We analyzed 144,779 invitations from 47,571women. During the COVID-19 period, the odds of participation were lower in first-time invitees (aOR = 0.90 [95% CI = 0.84-0.96]) and in those who had previously participated regularly and irregularly (aOR = 0.63 [95% CI = 0.59-0.67] and aOR = 0.95 [95% CI = 0.86-1.05], respectively). Participation showed a modest increase in women not attending any of the previous rounds (aOR = 1.10 [95% CI = 1.01-1.20]). The recall rate decreased in both prevalent and incident screening (aOR = 0.74 [95% CI = 0.56-0.99] and aOR = 0.80 [95% CI = 0.68-0.95], respectively). False positives also decreased in both groups (prevalent aOR = 0.92 [95% CI = 0.66-1.28] and incident aOR = 0.72 [95% CI = 0.59-0.88]). No significant differences were observed in compliance with recall (OR = 1.26, 95% CI = 0.76-2.23), cancer detection rate (aOR = 0.91 [95% CI = 0.69-1.18]), or cancer stages. The COVID-19 pandemic negatively affected screening attendance, especially in previous participants and newcomers. We found a reduction in recall and false positives and no marked differences in cancer detection, indicating the robustness of the program. There is a need for further evaluations of interval cancers and potential diagnostic delays. This study has received funding by grants PI19/00007 and PI21/00058, funded by Instituto de Salud Carlos III (ISCIII) and cofunded by the European Union and Grant RD21/0016/0020 funded by Instituto de Salud Carlos III and by the European Union NextGenerationEU, Mecanismo para la Recuperación y la Resiliencia (MRR).

Should tomosynthesis replace mammography for breast cancer screening?

A decade has passed since the first prospective trials showed that the mammography technology, digital breast tomosynthesis, increased the rate of cancer detection compared with digital mammography. 1 Ciatto S Houssami N Bernardi D et al. Integration of 3D digital mammography with tomosynthesis for population breast-cancer screening (STORM): a prospective comparison study. Lancet Oncol. 2013; 14: 583-589 Summary Full Text Full Text PDF PubMed Scopus (608) Google Scholar , 2 Skaane P Bandos AI Gullien R et al. Prospective trial comparing full-field digital mammography (FFDM) versus combined FFDM and tomosynthesis in a population-based screening programme using independent double reading with arbitration. Eur Radiol. 2013; 23: 2061-2071 Crossref PubMed Scopus (170) Google Scholar A large body of evidence, comprising prospective non-randomised studies and retrospective studies, 3 Marinovich ML Hunter KE Macaskill P Houssami N Breast cancer screening using tomosynthesis or mammography: a meta-analysis of cancer detection and recall. J Natl Cancer Inst. 2018; 110: 942-949 Crossref PubMed Scopus (108) Google Scholar has since accumulated; however, evidence from randomised controlled trials is scarce. In The Lancet Oncology, Walter Heindel and colleagues report the results of the TOmosynthesis plus SYnthesised MAmmography Study (TOSYMA), 4 Heindel W Weigel W Gerß J et al. Digital breast tomosynthesis plus synthesised mammography versus digital screening mammography for the detection of invasive breast cancer (TOSYMA): a multicentre, open-label, randomised, controlled, superiority trial. Lancet Oncol. 2022; (published online April 12.)https://doi.org/10.1016/S1470-2045(22)00194-2 Summary Full Text Full Text PDF PubMed Scopus (1) Google Scholar a multicentre trial embedded in the German population-wide mammography screening programme. TOSYMA is the largest of three randomised controlled trials providing evidence on breast tomosynthesis versus mammography screening. 4 Heindel W Weigel W Gerß J et al. Digital breast tomosynthesis plus synthesised mammography versus digital screening mammography for the detection of invasive breast cancer (TOSYMA): a multicentre, open-label, randomised, controlled, superiority trial. Lancet Oncol. 2022; (published online April 12.)https://doi.org/10.1016/S1470-2045(22)00194-2 Summary Full Text Full Text PDF PubMed Scopus (1) Google Scholar , 5 Hofvind S Holen AS Aase HS et al. Two-view digital breast tomosynthesis versus digital mammography in a population-based breast cancer screening programme (To-Be): a randomised, controlled trial. Lancet Oncol. 2019; 20: 795-805 Summary Full Text Full Text PDF PubMed Scopus (38) Google Scholar , 6 Pattacini P Nitrosi A Giorgi RP et al. A randomized trial comparing breast cancer incidence and interval cancers after tomosynthesis plus mammography versus mammography alone. Radiology. 2022; (published online Feb 1.)https://doi.org/10.1148/radiol.211132 Crossref PubMed Scopus (3) Google Scholar Heindel and colleagues persevered with TOSYMA despite the COVID-19 pandemic stalling recruitment, resulting in a marginally lower sample size than planned in their adaptive design. 4 Heindel W Weigel W Gerß J et al. Digital breast tomosynthesis plus synthesised mammography versus digital screening mammography for the detection of invasive breast cancer (TOSYMA): a multicentre, open-label, randomised, controlled, superiority trial. Lancet Oncol. 2022; (published online April 12.)https://doi.org/10.1016/S1470-2045(22)00194-2 Summary Full Text Full Text PDF PubMed Scopus (1) Google Scholar Digital breast tomosynthesis plus synthesised mammography versus digital screening mammography for the detection of invasive breast cancer (TOSYMA): a multicentre, open-label, randomised, controlled, superiority trialThe results from this study indicate that the detection rate for invasive breast cancer was significantly higher with digital breast tomosynthesis plus s2D mammography than digital mammography alone. Evaluation of interval cancer rates in the follow-up study will further help to investigate incremental long-term benefits of digital breast tomosynthesis screening. Full-Text PDF

Mammography classification model trained from image labels only

The Cancer Registry of Norway organises a population-based breast cancer screening program, where 250 000 women participate each year. The interpretation of the screening mammograms is a manual process, but deep neural networks are showing potential in mammographic screening. Most methods focus on methods trained from pixel-level annotations, but these require expertise and are time-consuming to produce. Through the screenings, image level annotations are however readily available. In this work we present a few models trained from image level annotations from the Norwegian dataset: a holistic model, an attention model and an ensemble model. We compared their performance with that of pretrained models based on pixel-level annotations, trained on international datasets. From this we found that models trained on our local data with image-level annotation gave considerably better performance than the pretrained models from external data, although based on pixel-level annotations.

Populatıon-based breast cancer screenıng program ın Turkey: Priliminary results

Introduction: In Turkey, a population-based breast cancer screening program for women aged 40 to 69 years old was recently introduced. The goal of this study was to document early outcomes and assess the program's success.Method: This study looked at the 348,638 women who were screened in 2016. For end results, all data was gathered from the national centralized reporting system and the Cancer Registry database. For benign discoveries, Breast Imaging-Reporting and Data System (BI-RADS) 1-2 were applied, and for recalls, BI-RADS 0, 4, or 5 were utilized, depending on the level of suspicion. The study looked at the age distribution, recall rate, cancer detection, and interval cancer rates. The stages of identified malignancies were examined and compared to those of the nonscreened group throughout the same time frame.Results: In the screening population, 43.2 percent of women were between the ages of 40 and 49, and 56.8% were between the ages of 50 and 69. The age range of 50–69 was responsible for 70% of screen-detected malignancies. The total recall rate (n = 19,607) was 5.6 percent. The malignancy rate for BI-RADS 5 recalls was 70.2 percent, 19.2 percent for BI-RADS 4, and 1.7 percent for BI-RADS 0 recalls. Screen-discovered malignancies were detected at a rate of 3.2 per 1000 screening exams (n = 1,120). When compared to the Non screened group, the screened group had a larger percentage of early-stage illness (54.3%). (46.7 percent). Interval cancers were discovered in 231 women (0.66 per 1000 screened women).Conclusion: Turkey's recently launched population-based breast cancer screening program appears to be viable and successful, according to preliminary results. According to this study, the breast cancer screening program should be sustained, with coverage of the target group rising.

Artificial Intelligence for Breast Cancer Screening in Mammography (AI-STREAM): A Prospective Multicenter Study Design in Korea Using AI-Based CADe/x.

PurposeArtificial intelligence (AI)-based computer-aided detection/diagnosis (CADe/x) has helped improve radiologists’ performance and provides results equivalent or superior to those of radiologists’ alone. This prospective multicenter cohort study aims to generate real-world evidence on the overall benefits and disadvantages of using AI-based CADe/x for breast cancer detection in a population-based breast cancer screening program comprising Korean women aged ≥ 40 years. The purpose of this report is to compare the diagnostic accuracy of radiologists with and without the use of AI-based CADe/x in mammography readings for breast cancer screening of Korean women with average breast cancer risk.MethodsApproximately 32,714 participants will be enrolled between February 2021 and December 2022 at 5 study sites in Korea. A radiologist specializing in breast imaging will interpret the mammography readings with or without the use of AI-based CADe/x. If recall is required, further diagnostic workup will be conducted to confirm the cancer detected on screening. The findings will be recorded for all participants regardless of their screening status to identify study participants with breast cancer diagnosis within both 1 year and 2 years of screening. The national cancer registry database will be reviewed in 2026 and 2027, and the results of this study are expected to be published in 2027. In addition, the diagnostic accuracy of general radiologists and radiologists specializing in breast imaging from another hospital with or without the use of AI-based CADe/x will be compared considering mammography readings for breast cancer screening.DiscussionThe Artificial Intelligence for Breast Cancer Screening in Mammography (AI-STREAM) study is a prospective multicenter study that aims to compare the diagnostic accuracy of radiologists with and without the use of AI-based CADe/x in mammography readings for breast cancer screening of women with average breast cancer risk. AI-STREAM is currently in the patient enrollment phase.Trial RegistrationClinicalTrials.gov Identifier: NCT05024591

Quality assured implementation of the Slovenian breast cancer screening programme.

The organised, population-based breast cancer screening programme in Slovenia began providing biennial mammography screening for women aged 50-69 in 2008. The programme has taken a comprehensive approach to quality assurance as recommended by the European guidelines for quality assurance in breast cancer screening and diagnosis (4th edition), including centralized assessment, training and supervision, and proactive monitoring of performance indicators. This report describes the progress of implementation and rollout from 2003 through 2019. The screening protocol and key quality assurance procedures initiated during the planning from 2003 and rollout from 2008 of the screening programme, including training of the professional staff, are described. The organisational structure, gradual geographical rollout, and coverage by invitation and examination are presented. The nationwide programme was up and running in all screening regions by the end of 2017, at which time the nationwide coverage by invitation and examination had reached 70% and 50%, respectively. Nationwide rollout of the population-based programme was complete by the end of 2019. By this time, coverage by invitation and examination had reached 98% and 76%, respectively. The participation rates consistently exceeded 70% from 2014 to 2019. The successful implementation of the screening programme can be attributed to an independent central management, external guidance, and strict adherence to quality assurance procedures, all of which contributed to increasing governmental and popular support. The benefits of quality assurance have influenced all aspects of breast care and have provided a successful model for multidisciplinary management of other diseases.

Risk-Stratified Approach to Breast Cancer Screening in Canada: Women's Knowledge of the Legislative Context and Concerns about Discrimination from Genetic and Other Predictive Health Data.

The success of risk-stratified approaches in improving population-based breast cancer screening programs depends in no small part on women’s buy-in. Fear of genetic discrimination (GD) could be a potential barrier to genetic testing uptake as part of risk assessment. Thus, the objective of this study was twofold. First, to evaluate Canadian women’s knowledge of the legislative context governing GD. Second, to assess their concerns about the possible use of breast cancer risk levels by insurance companies or employers. We use a cross-sectional survey of 4293 (age: 30–69) women, conducted in four Canadian provinces (Alberta, British Colombia, Ontario and Québec). Canadian women’s knowledge of the regulatory framework for GD is relatively limited, with some gaps and misconceptions noted. About a third (34.7%) of the participants had a lot of concerns about the use of their health information by employers or insurers; another third had some concerns (31.9%), while 20% had no concerns. There is a need to further educate and inform the Canadian public about GD and the legal protections that exist to prevent it. Enhanced knowledge could facilitate the implementation and uptake of risk prediction informed by genetic factors, such as the risk-stratified approach to breast cancer screening that includes risk levels.

The Development and Testing of Balanced Communication Material for a Population-Based Breast Cancer Screening Program

Organized breast cancer screening (BCS) programs rely on written communication materials for achieving participation and informing women about screening-related benefits and limits. In order to achieve informed decisions and to maximize reader acceptance, the Agency for Health Protection of the metropolitan area of Milan aimed at improving the communication materials of the local BCS program through a multiphase, mixed-method process. Multidisciplinary working groups drafted three sets of materials: postal letters, an informative leaflet, and a question-and-answer online set. Readability was assessed using the Italian language-tailored Gulpease index. Suitability and Comprehensibility were assessed using the SAM + CAM instrument. User perception was investigated through “think aloud” interviews in two consecutive purposive samples. Participants’ intention to participate in the program was also assessed. After each phase was completed, materials were readapted, and previous phases were repeated, to maintain the pre-defined Gulpease and SAM + CAM targets. During the quality improvement process, the overall mean Gulpease and SAM + CAM scores increased from 65.5 (s. d. 10.4) to 67.7 (s. d. 8.2) and from 78 (s. d. 5.6) to 83 (s. d. 4.1), respectively. In light of the results of the first round of interviews, materials underwent rewriting and layout revision, which was generally appreciated during the second round, with a non-significant increase in the intention to participate in the program. However, negative emotions and miscomprehension concerning overdiagnosis were frequently reported, although less frequent in the second round, after rewording of the text. The mixed-method multistep process involving all the relevant key players allowed a balance among the multifaceted aspects of communication.

Effect of an information leaflet on breast cancer screening participation: A cluster randomized controlled trial

ObjectiveTo evaluate the impact of an information leaflet about the risk-benefit balance of breast cancer screening on women’s participation.MethodsThis cluster randomized controlled trial was conducted within a population-based breast cancer screening program and included women from the catchment areas of two hospitals in Barcelona, Spain. We evaluated women aged 50–69 years invited to screening between September 2019 and January 2020. The intervention group received an information leaflet on the benefits and harms of mammography screening. The control group received the usual invitation letter. The clusters consisted of the processing days of the invitation letter, assigned to the intervention with a simple random allocation scheme. We compared the participation rate at the individual level between groups, stratified by hospital and by per-protocol and intention-to-treat analyses.ResultsWe included 11,119 women (137 clusters): 5416 in the intervention group (66 clusters) and 5703 in the control group (71 clusters). A total of 36% (1964/5393) of the women in the intervention group and 37% (2135/5694) of those in the control group attended screening, respectively. Overall, we found no differences in participation among groups (difference in participation − 1.1%; 95%CI; − 2.9 to 0.7%). In a hospital attending a population with a low socioeconomic status, attendance was lower in the intervention group (− 1.4, 95%CI: − 5.7% to − 0.03%).ConclusionsOverall participation in our program was unaffected by a new information leaflet on the risk-benefit balance of breast cancer screening. However, participation was lower in certain populations with lower socioeconomic statusTrial registrationTrial registration number ISRCTN13848929.

Screening of women with aesthetic prostheses in dedicated sessions of a population-based breast cancer screening programme

BackgroundWomen with aesthetic prostheses must be included in the target population of mammography screening programmes. Breast implants are radiopaque and partially obscure the breast tissue. This can be avoided with the use of the Eklund technique, which causes an increased radiation exposure. In this study, augmented women undergoing a dedicated protocol within a population-based screening programme were compared according to selected indicators with the standard screening population. Essential dosimetric parameters and their time trend were also assessed.Materials and methodsThe study was conducted in a screening centre in Milan in the years 2009–2016. The screening protocol for women with breast implants included a double-read mammography with the Eklund views, ultrasound and clinical breast examination.ResultsA total of 28,794 women were enrolled, including 588 (2%) women with breast implants and 28,206 (98%) undergoing the standard screening protocol. The invasive assessment rate was 9.0‰ for women with breast implants vs. 15‰ in the standard cohort. The surgical referral rate was 2.2% vs. 0.9%. The detection rate was similar in the two groups (4.0 and 4.5‰, respectively). There were significant differences in the average glandular dose according to the mammography equipment. The use of the Eklund views increased over time.ConclusionsScreening of augmented women according to a specific protocol in the contexts of population-based programmes is feasible. Observed differences in screening indicators relative to the standard screening population require further research. The increasing use of Eklund views probably results from quality assurance measures associated with screening programmes.

Are artificial intelligence systems useful in breast cancer screening programmes?

Population-based breast cancer screening programmes are efficacious in reducing the mortality due to breast cancer. These programmes use mammography to screen the women who are invited to participate. Digital mammography makes it possible to develop computer-assisted diagnosis (CAD) systems that promise to reduce the workload of radiologists participating in screening programmes. However, various studies have shown that CAD results in a high rate of false positive diagnoses. Systems based on artificial intelligence are being more widely implemented, and studies have shown that these systems have better diagnostic performance than traditional CAD systems.This article explains the fundamentals of artificial intelligence systems and an overview of possible applications of these systems within the framework of breast cancer screening programmes.

The Role of Socio-Demographic Factors in the Coverage of Breast Cancer Screening: Insights From a Quantile Regression Analysis.

Background: In Flanders, breast cancer (BC) screening is performed in a population-based breast cancer screening program (BCSP), as well as in an opportunistic setting. Women with different socio-demographic characteristics are not equally covered by BC screening.Objective: To evaluate the role of socio-demographic characteristics on the lowest 10th and highest 90th quantile levels of BC screening coverage.Methods: The 2017 neighborhood-level coverage rates of 8,690 neighborhoods with women aged 50–69 and eligible for BCSP and opportunistic screening were linked to socio-demographic data. The association between socio-demographic characteristics and the coverage rates of BCSP and opportunistic screening was evaluated per quantile of coverage using multivariable quantile regression models, with specific attention to the lowest 10th and highest 90th quantiles.Results: The median coverage in the BCSP was 50%, 33.5% in the 10th quantile, and 64.5% in the 90th quantile. The median coverage of the opportunistic screening was 12, 4.2, and 24.8% in the 10th and 90th quantile, respectively. A lower coverage of BCSP was found in neighborhoods with more foreign residents and larger average household size, which were considered indicators for a lower socioeconomic status (SES). However, a higher average personal annual income, which was considered an indicator for a higher SES, was also found in neighborhoods with lower coverage of BCSP. For these neighborhoods, that have a relatively low and high SES, the negative association between the percentage of foreign residents, average household size, and average personal annual income and the coverage in the BCSP had the smallest regression coefficient and 95% confidence interval (CI) values were −0.75 (95% CI: −0.85, −0.65), −13.59 (95% CI: −15.81, −11.37), and −1.05 (95% CI: −1.18, −0.92), respectively, for the 10th quantile. The neighborhoods with higher coverage of opportunistic screening had a relatively higher average personal annual income, with the largest regression coefficient of 1.72 (95% CI: 1.59, 1.85) for the 90th quantile.Conclusions: Women from relatively low and high SES neighborhoods tend to participate less in the BCSP, whereas women with a relatively high SES tend to participate more in opportunistic screening. For women from low SES neighborhoods, tailored interventions are needed to improve the coverage of BCSP.