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Retrospective studies have shown promising results using artificial intelligence (AI) to improve mammography screening accuracy and reduce screen-reading workload; however, to our knowledge, a randomised trial has not yet been conducted. We aimed to assess the clinical safety of an AI-supported screen-reading protocol compared with standard screen reading by radiologists following mammography. In this randomised, controlled, population-based trial, women aged 40–80 years eligible for mammography screening (including general screening with 1·5–2-year intervals and annual screening for those with moderate hereditary risk of breast cancer or a history of breast cancer) at four screening sites in Sweden were informed about the study as part of the screening invitation. Those who did not opt out were randomly allocated (1:1) to AI-supported screening (intervention group) or standard double reading without AI (control group). Screening examinations were automatically randomised by the Picture Archive and Communications System with a pseudo-random number generator after image acquisition. The participants and the radiographers acquiring the screening examinations, but not the radiologists reading the screening examinations, were masked to study group allocation. The AI system (Transpara version 1.7.0) provided an examination-based malignancy risk score on a 10-level scale that was used to triage screening examinations to single reading (score 1–9) or double reading (score 10), with AI risk scores (for all examinations) and computer-aided detection marks (for examinations with risk score 8–10) available to the radiologists doing the screen reading. Here we report the prespecified clinical safety analysis, to be done after 80 000 women were enrolled, to assess the secondary outcome measures of early screening performance (cancer detection rate, recall rate, false positive rate, positive predictive value [PPV] of recall, and type of cancer detected [invasive or in situ]) and screen-reading workload. Analyses were done in the modified intention-to-treat population (ie, all women randomly assigned to a group with one complete screening examination, excluding women recalled due to enlarged lymph nodes diagnosed with lymphoma). The lowest acceptable limit for safety in the intervention group was a cancer detection rate of more than 3 per 1000 participants screened. The trial is registered with ClinicalTrials.gov, NCT04838756, and is closed to accrual; follow-up is ongoing to assess the primary endpoint of the trial, interval cancer rate. Between April 12, 2021, and July 28, 2022, 80 033 women were randomly assigned to AI-supported screening (n=40 003) or double reading without AI (n=40 030). 13 women were excluded from the analysis. The median age was 54·0 years (IQR 46·7–63·9). Race and ethnicity data were not collected. AI-supported screening among 39 996 participants resulted in 244 screen-detected cancers, 861 recalls, and a total of 46 345 screen readings. Standard screening among 40 024 participants resulted in 203 screen-detected cancers, 817 recalls, and a total of 83 231 screen readings. Cancer detection rates were 6·1 (95% CI 5·4–6·9) per 1000 screened participants in the intervention group, above the lowest acceptable limit for safety, and 5·1 (4·4–5·8) per 1000 in the control group—a ratio of 1·2 (95% CI 1·0–1·5; p=0·052). Recall rates were 2·2% (95% CI 2·0–2·3) in the intervention group and 2·0% (1·9–2·2) in the control group. The false positive rate was 1·5% (95% CI 1·4–1·7) in both groups. The PPV of recall was 28·3% (95% CI 25·3–31·5) in the intervention group and 24·8% (21·9–28·0) in the control group. In the intervention group, 184 (75%) of 244 cancers detected were invasive and 60 (25%) were in situ; in the control group, 165 (81%) of 203 cancers were invasive and 38 (19%) were in situ. The screen-reading workload was reduced by 44·3% using AI. AI-supported mammography screening resulted in a similar cancer detection rate compared with standard double reading, with a substantially lower screen-reading workload, indicating that the use of AI in mammography screening is safe. The trial was thus not halted and the primary endpoint of interval cancer rate will be assessed in 100 000 enrolled participants after 2-years of follow up. Swedish Cancer Society, Confederation of Regional Cancer Centres, and the Swedish governmental funding for clinical research (ALF).

Artificial intelligence (AI) in mammography screening has shown promise in retrospective evaluations, but few prospective studies exist. PRAIM is an observational, multicenter, real-world, noninferiority, implementation study comparing the performance of AI-supported double reading to standard double reading (without AI) among women (50–69 years old) undergoing organized mammography screening at 12 sites in Germany. Radiologists in this study voluntarily chose whether to use the AI system. From July 2021 to February 2023, a total of 463,094 women were screened (260,739 with AI support) by 119 radiologists. Radiologists in the AI-supported screening group achieved a breast cancer detection rate of 6.7 per 1,000, which was 17.6% (95% confidence interval: +5.7%, +30.8%) higher than and statistically superior to the rate (5.7 per 1,000) achieved in the control group. The recall rate in the AI group was 37.4 per 1,000, which was lower than and noninferior to that (38.3 per 1,000) in the control group (percentage difference: −2.5% (−6.5%, +1.7%)). The positive predictive value (PPV) of recall was 17.9% in the AI group compared to 14.9% in the control group. The PPV of biopsy was 64.5% in the AI group versus 59.2% in the control group. Compared to standard double reading, AI-supported double reading was associated with a higher breast cancer detection rate without negatively affecting the recall rate, strongly indicating that AI can improve mammography screening metrics. In a large-scale prospective study run across 12 sites in Germany and involving 463,094 women and 119 radiologists, AI-supported screening increased breast cancer detection rates by a significant margin without affecting the recall rate.

Screening mammography reduces breast cancer mortality, but studies analyzing interval cancers diagnosed after negative screens have shown that many cancers are missed. Supplemental screening using magnetic resonance imaging (MRI) can reduce the number of missed cancers. However, as qualified MRI staff are lacking, the equipment is expensive to purchase and cost-effectiveness for screening may not be convincing, the utilization of MRI is currently limited. An effective method for triaging individuals to supplemental MRI screening is therefore needed. We conducted a randomized clinical trial, ScreenTrustMRI, using a recently developed artificial intelligence (AI) tool to score each mammogram. We offered trial participation to individuals with a negative screening mammogram and a high AI score (top 6.9%). Upon agreeing to participate, individuals were assigned randomly to one of two groups: those receiving supplemental MRI and those not receiving MRI. The primary endpoint of ScreenTrustMRI is advanced breast cancer defined as either interval cancer, invasive component larger than 15 mm or lymph node positive cancer, based on a 27-month follow-up time from the initial screening. Secondary endpoints, prespecified in the study protocol to be reported before the primary outcome, include cancer detected by supplemental MRI, which is the focus of the current paper. Compared with traditional breast density measures used in a previous clinical trial, the current AI method was nearly four times more efficient in terms of cancers detected per 1,000 MRI examinations (64 versus 16.5). Most additional cancers detected were invasive and several were multifocal, suggesting that their detection was timely. Altogether, our results show that using an AI-based score to select a small proportion (6.9%) of individuals for supplemental MRI after negative mammography detects many missed cancers, making the cost per cancer detected comparable with screening mammography. ClinicalTrials.gov registration: NCT04832594 . In an interim analysis, an artificial intelligence model was nearly four times more efficient in terms of cancers detected per number of magnetic resonance imaging tests, compared to traditional breast density measures used in a previous clinical trial.

It is not known which supplemental imaging technique is most beneficial for women with dense breasts attending breast screening. This study compares abbreviated MRI, automated whole breast ultrasound (ABUS), and contrast-enhanced mammography versus standard of care in women with dense breasts and a negative mammogram. We report on interim results from the first round of supplemental imaging. In this UK randomised controlled trial, at ten breast screening sites, women (aged 50–70 years) were independently allocated by batches (day/mobile screening van) to either abbreviated MRI, ABUS, or contrast-enhanced mammography or standard of care (full-field digital mammography) varied by modality availability at each centre. Women were invited if their mammogram was negative and they had dense breasts. Primary outcome was detection rate, defined as the percentage of women with a positive result on supplemental imaging that resulted in histologically confirmed breast cancer. Analysis was by imaging received (intention to treat) using network meta-analysis, treating each site as a study in the meta-analysis, with two analyses carried out: one using only the three active intervention arms (primary analysis) that compared the three supplemental imaging techniques with respect to cancer detection, recall, and biopsy rates in addition to those resulting from full-field digital mammography alone; and one with the addition of the observational data from Cambridge on full-field digital mammography alone. This trial is closed for recruitment and is registered with ClinicalTrials.gov, NCT04097366. From October 18, 2019, to March 30, 2024, 9361 eligible women were recruited and randomly assigned (2318 to abbreviated MRI, 2240 to ABUS, 2235 to contrast-enhanced mammography, and 2568 to standard of care). Of those, 6305 completed supplementary imaging (2130 in the abbreviated MRI, 2141 in the ABUS, and 2035 in the contrast-enhanced mammography) and were included in the outcome analysis. The cancer detection rate was 17·4 (95% CI 12·2–23·9, n=37) per 1000 examinations for abbreviated MRI, 4·2 (1·9–8·0, n=9) per 1000 examinations for ABUS, and 19·2 (13·7–26·1, n=39) per 1000 examinations for contrast-enhanced mammography, of which 15·0 (10·3–21·1, n=32) per 1000 women for abbreviated MRI, 4·2 (1·9–8·0, n=9) per 1000 examinations for ABUS, and 15·7 (10·8–22·1, n=32) per 1000 examinations for contrast-enhanced mammography were invasive cancers. The detection rates for abbreviated MRI were significantly higher than for ABUS (p=0·047) and non-significantly higher than for contrast-enhanced mammography (p=0·62). There was one case of extravasation in the abbreviated MRI arm (0·5 events per 1000 examinations), no adverse events in the ABUS arm, and 24 iodinated contrast reactions (17 minor [8·4 events per 1000 examinations], six moderate [2·9 events per 1000 examinations], and one severe [0·5 events per 1000 examinations]) and three extravasations (1·5 extravasations per 1000 examinations) in the contrast-enhanced mammography arm. Abbreviated MRI and contrast-enhanced mammography detected three times as many invasive cancers compared with ABUS, with cancers being half the size. This study shows that supplemental imaging could lead to earlier detection of cancer in women with dense breasts but does not estimate the level of overdiagnosis. Cancer Research UK, GE Healthcare, and Bayer Healthcare.

The frequency of mammographic surveillance for women after diagnosis of breast cancer varies globally. The aim of this study was to evaluate whether less than annual mammography was non-inferior in terms of breast cancer-specific survival in women aged 50 years or older. Mammo-50 was a multicentre, randomised, phase 3 trial of annual versus less frequent mammography (2-yearly after conservation surgery; 3-yearly after a mastectomy) for women aged 50 years or older at initial diagnosis of invasive or non-invasive breast cancer and who were recurrence free 3 years post curative surgery. The trial was conducted at 114 National Health Service hospitals in the UK. Participants were randomly assigned (1:1) to annual or less frequent mammograms at 3 years post curative surgery and were followed up for 6 years. The co-primary outcomes were breast cancer-specific survival and cost-effectiveness. The cost-effectiveness analysis will be reported elsewhere. Breast cancer-specific survival was assessed in the intention-to-treat population. Secondary outcomes were recurrence-free interval, overall survival, and referrals back to the hospital system. 5000 women provided 90% power to detect a 3% absolute non-inferiority margin for breast cancer-specific survival with 2·5% one-sided significance. The trial was registered with the ISRCTN registry, ISRCTN48534559; recruitment is complete but longer-term follow-up is ongoing. Between April 22, 2014, and Sept 28, 2018, 5235 women were randomly assigned to annual mammography (n=2618) or less frequent mammography (n=2617). 3858 (73·6%) women were aged 60 years or older, 4202 (80·3%) had undergone conservation surgery, 4576 (87·4%) had invasive disease, 1159 (22·1%) had node positive disease, and 4330 (82·7%) had oestrogen receptor-positive tumours. With a median of 5·7 years follow-up (IQR 5·0–6·0; 8·7 years post curative surgery), 343 women died, including 116 who died of breast cancer (61 in the annual mammography group and 55 in the less frequent mammography group). 5-year breast cancer-specific survival was 98·1% (95% CI 97·5–98·6) in the annual mammography group and 98·3% (97·8–98·8) in the less frequent mammography group (hazard ratio 0·92, 95% CI 0·64–1·32), demonstrating non-inferiority of less frequent mammography at the pre-specified 3% margin (non-inferiority p<0·0001). 5-year recurrence-free interval was 94·1% (95% CI 93·1–94·9) in the annual mammography group and 94·5% (93·5–95·3) in the less frequent mammography group. Overall survival at 5 years was 94·7% (95% CI 93·8–95·5%) and 94·5% (93·5–95·3), respectively. 224 (64·9%) of 345 breast cancer events were detected from emergency admissions or symptomatic referrals back to the hospital system, including 108 (61·7%) of 175 in the annual mammography group and 116 (68·2%) of 170 in the less frequent mammography group. For patients aged 50 years or older and at 3 years post diagnosis, less frequent mammograms were non-inferior compared with annual mammograms for breast cancer-specific survival, recurrence-free interval, and overall survival, and should be considered for this population. National Institute for Health Research Health Technology Assessment programme.

Two dimensional (2D) full-field digital mammography is the current standard of breast cancer screening. Digital breast tomosynthesis generates pseudo-three dimensional datasets of the breast from which synthesised 2D (s2D) mammograms can be reconstructed. This innovative approach reduces the likelihood of overlapping breast tissues that can conceal features of malignancy. We aimed to compare digital breast tomosynthesis plus s2D mammography with digital screening mammography for the detection of invasive breast cancer. TOSYMA was a randomised, open-label, superiority trial done at 17 screening units in two federal states of Germany. Eligible participants were women aged 50–69 years who had been invited to participate in a population-wide, quality-controlled mammography screening programme. Women were randomly assigned (1:1) to digital breast tomosynthesis plus s2D mammography or digital mammography alone using block randomisation (block size of 32), stratified by site. The primary endpoints were the detection rate of invasive breast cancer and invasive interval cancer rate at 24 months, analysed in the modified full analysis set, which included all randomly assigned participants who underwent either type of screening examination. Ten examinations, corresponding to a second study participation, were excluded. Analyses were done according to the intention-to-treat principle. Interval cancer rates will be reported in the follow-up study. Safety was assessed in the as-treated population, which included all participants who were randomly assigned. This trial is registered with ClinicalTrials.gov, NCT03377036, and is closed to accrual. Between July 5, 2018, and Dec 30, 2020, 99 689 women were randomly assigned to digital breast tomosynthesis plus s2D mammography (n=49 804) or digital mammography (n=49 830). Invasive breast cancers were detected in 354 of 49 715 women with evaluable primary endpoint data in the digital breast tomosynthesis plus s2D group (detection rate 7·1 cases per 1000 women screened) and in 240 of 49 762 women in the digital mammography group (4·8 cases per 1000 women screened; odds ratio 1·48 [95% CI 1·25–1·75]; p<0·0001). Adverse events and device deficiencies were rare (six adverse events in each group; 23 device deficiencies in the digital breast tomosynthesis plus s2D group vs five device deficiencies in the digital mammography group) and no serious adverse events were reported. The 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. Deutsche Forschungsgemeinschaft (German Research Foundation).

Objective To compare breast cancer incidence and mortality up to 25 years in women aged 40-59 who did or did not undergo mammography screening.Design Follow-up of randomised screening trial by centre coordinators, the study’s central office, and linkage to cancer registries and vital statistics databases.Setting 15 screening centres in six Canadian provinces,1980-85 (Nova Scotia, Quebec, Ontario, Manitoba, Alberta, and British Columbia).Participants 89 835 women, aged 40-59, randomly assigned to mammography (five annual mammography screens) or control (no mammography).Interventions Women aged 40-49 in the mammography arm and all women aged 50-59 in both arms received annual physical breast examinations. Women aged 40-49 in the control arm received a single examination followed by usual care in the community.Main outcome measure Deaths from breast cancer.Results During the five year screening period, 666 invasive breast cancers were diagnosed in the mammography arm (n=44 925 participants) and 524 in the controls (n=44 910), and of these, 180 women in the mammography arm and 171 women in the control arm died of breast cancer during the 25 year follow-up period. The overall hazard ratio for death from breast cancer diagnosed during the screening period associated with mammography was 1.05 (95% confidence interval 0.85 to 1.30). The findings for women aged 40-49 and 50-59 were almost identical. During the entire study period, 3250 women in the mammography arm and 3133 in the control arm had a diagnosis of breast cancer, and 500 and 505, respectively, died of breast cancer. Thus the cumulative mortality from breast cancer was similar between women in the mammography arm and in the control arm (hazard ratio 0.99, 95% confidence interval 0.88 to 1.12). After 15 years of follow-up a residual excess of 106 cancers was observed in the mammography arm, attributable to over-diagnosis.Conclusion Annual mammography in women aged 40-59 does not reduce mortality from breast cancer beyond that of physical examination or usual care when adjuvant therapy for breast cancer is freely available. Overall, 22% (106/484) of screen detected invasive breast cancers were over-diagnosed, representing one over-diagnosed breast cancer for every 424 women who received mammography screening in the trial.

Objectives To compare the diagnostic performance of contrast-enhanced spectral mammography (CESM) to digital mammography (MG) and magnetic resonance imaging (MRI) in a prospective two-centre, multi-reader study. Methods One hundred seventy-eight women (mean age 53 years) with invasive breast cancer and/or DCIS were included after ethics board approval. MG, CESM and CESM + MG were evaluated by three blinded radiologists based on amended ACR BI-RADS criteria. MRI was assessed by another group of three readers. Receiver-operating characteristic (ROC) curves were compared. Size measurements for the 70 lesions detected by all readers in each modality were correlated with pathology. Results Reading results for 604 lesions were available (273 malignant, 4 high-risk, 327 benign). The area under the ROC curve was significantly larger for CESM alone (0.84) and CESM + MG (0.83) compared to MG (0.76) (largest advantage in dense breasts) while it was not significantly different from MRI (0.85). Pearson correlation coefficients for size comparison were 0.61 for MG, 0.69 for CESM, 0.70 for CESM + MG and 0.79 for MRI. Conclusions This study showed that CESM, alone and in combination with MG, is as accurate as MRI but is superior to MG for lesion detection. Patients with dense breasts benefitted most from CESM with the smallest additional dose compared to MG. Key Points • CESM has comparable diagnostic performance (ROC-AUC) to MRI for breast cancer diagnostics . • CESM in combination with MG does not improve diagnostic performance . • CESM has lower sensitivity but higher specificity than MRI . • Sensitivity differences are more pronounced in dense and not significant in non-dense breasts . • CESM and MRI are significantly superior to MG, particularly in dense breasts .

Background: Chinese women tend to have small and dense breasts and ultrasound is a common method for breast cancer screening in China. However, its efficacy and cost comparing with mammography has not been evaluated in randomised trials. Methods: At 14 breast centres across China during 2008–2010, 13 339 high-risk women aged 30–65 years were randomised to be screened by mammography alone, ultrasound alone, or by both methods at enrolment and 1-year follow-up. Results: A total of 12 519 and 8692 women underwent the initial and second screenings, respectively. Among the 30 cancers (of which 15 were stage 0/I) detected, 5 (0.72/1000) were in the mammography group, 11 (1.51/1000) in the ultrasound group, and 14 (2.02/1000) in the combined group ( P =0.12). In the combined group, ultrasound detected all the 14 cancers, whereas mammography detected 8, making ultrasound more sensitive (100 vs 57.1%, P =0.04) with a better diagnostic accuracy (0.999 vs 0.766, P =0.01). There was no difference between mammography and ultrasound in specificity (100 vs 99.9%, P =0.51) and positive predictive value (72.7 vs 70.0%; P =0.87). To detect one cancer, the costs of ultrasound, mammography, and combined modality were $7876, $45 253, and $21 599, respectively. Conclusions: Ultrasound is superior to mammography for breast cancer screening in high-risk Chinese women.

Objective To assess the performance of one-view digital breast tomosynthesis (DBT) in breast cancer screening. Methods The Malmö Breast Tomosynthesis Screening Trial is a prospective population-based one-arm study with a planned inclusion of 15000 participants; a random sample of women aged 40–74 years eligible for the screening programme. This is an explorative analysis of the first half of the study population (n = 7500). Participants underwent one-view DBT and two-view digital mammography (DM), with independent double reading and scoring. Primary outcome measures were detection rate, recall rate and positive predictive value (PPV). McNemar's test with 95 % confidence intervals was used. Results Breast cancer was found in sixty-eight women. Of these, 46 cases were detected by both modalities, 21 by DBT alone and one by DM alone. The detection rate for one-view DBT was 8.9/1000 screens (95 % CI 6.9 to 11.3) and 6.3/1000 screens (4.6 to 8.3) for two-view DM (p < 0.0001). The recall rate after arbitration was 3.8 % (3.3 to 4.2) for DBT and 2.6 % (2.3 to 3.0) for DM (p < 0.0001). The PPV was 24 % for both DBT and DM. Conclusion Our results suggest that one-view DBT might be feasible as a stand-alone screening modality. Key Points • One-view DBT as a stand-alone breast cancer screening modality has not been investigated. • One-view DBT increased the cancer detection rate significantly. • The recall rate increased significantly but was still low. • Breast cancer screening with one-view DBT as a stand-alone modality seems feasible.