Digital Breast Tomosynthesis: Potential Benefits in Routine Clinical Practice.

Purpose To determine whether the rates and tumor characteristics of screening-detected and interval cancers differ for two-dimensional digital mammography (DM) versus digital breast tomosynthesis (DBT) mammography. Materials and Methods Consecutive screening mammograms from January 2009 to February 2011 (DM group, before DBT integration) and from January 2013 to February 2015 (DBT group, after complete DBT integration) were reviewed. Cancers were considered screening detected if diagnosed within 365 days of a positive screening examination and interval if diagnosed within 365 days of a negative screening examination. Z tests were used to compare cancers on DM versus DBT examinations. Results A total of 948 breast cancers were diagnosed after 78 385 DM and 76 896 DBT examinations. Although the overall rate of screening-detected cancers was similar with DM and DBT (5.0 vs 5.0 per 1000 examinations, P = .98), a higher proportion of screening-detected cancers were invasive rather than in situ with DBT (74.2% [287 of 387] vs 66.0% [260 of 394], P = .01). There were no significant differences in tumor characteristics, including size at pathologic examination, grade, hormone receptor status, and nodal status, between the screening-detected invasive cancers on DM versus DBT (P = .09-.99). The rate of interval cancers was similar with DM and DBT (1.1 vs 1.1 per 1000 examinations, P = .84). Compared with symptomatic interval cancers, magnetic resonance imaging-detected interval cancers were more likely to be minimal cancers. Conclusion The overall rates of screening-detected and interval cancers are similar with DM and DBT, but a higher proportion of screening-detected cancers are invasive rather than in situ with DBT. © RSNA, 2017.

Time for Change in Digital Breast Tomosynthesis Research.

Evidence on screening outcomes with digital breast tomosynthesis (DBT) vs digital mammography (DM) in women with a family history of breast cancer is limited. To compare the performance of DBT and DM screening in women with a family history of breast cancer overall and subdivided by breast cancer family history category, breast density, age group, screening interval, and screening round, and to describe characteristics of cancers detected on screening vs interval cancers. In this comparative cohort study at imaging facilities affiliated with the Breast Cancer Surveillance Consortium, adult women 18 years and older with a self-reported family history of breast cancer who underwent DBT or DM from 2011 to 2018 were included, with a 1-year follow-up for breast carcinoma. Data analysis was performed between November 2023 and August 2024. DBT or DM. The main outcomes were absolute risk difference (ARD) between DBT and DM for recall rate, cancer detection rate, interval cancer rate, advanced cancer rate, biopsy rate, positive predictive values, sensitivity, and specificity, with inverse probability of treatment weighting. A total of 208 945 women with a family history of breast cancer undergoing 502 357 screening examinations were included in the sample. Median (IQR) age was 58 (50-66) and 57 (49-66) years for the DBT and DM groups, respectively. Adjusted ARDs (DBT vs DM) were significant for recall rate (-1.51%; 95% CI, -2.42% to -0.59%) and specificity (1.56%; 95% CI, 0.65%-2.46%) in the overall cohort of 121 698 DBT and 380 561 DM examinations and among women with 1 first-degree relative (recall rate ARD, -1.72%; 95% CI, -2.70% to -0.74%; specificity ARD, 1.75%; 95% CI, 0.81%-2.69%). Among those with only second-degree relatives, the biopsy rate for DBT was significantly higher (ARD, 0.39%; 95% CI, 0.18%-0.61%). Significant ARDs were observed for the ductal carcinoma in situ detection rate (-0.71 per 1000 examinations; 95% CI, -1.03 to -0.38 per 1000 examinations) in women with almost entirely fatty breasts; recall rate (-1.90%; 95% CI, -2.88% to -0.92%) and specificity (1.93%; 95% CI, 0.97%-2.89%) in women with scattered fibroglandular densities. Significant ARDs were also observed for the positive predictive value for recall (1.75%; 95% CI, 0.84%-2.67%) in heterogeneously dense breasts, as well as the biopsy rate (0.48%; 95% CI, 0.16%-0.80%) and advanced cancer rate (-0.61 per 1000 examinations; 95% CI, -1.02 to -0.20 per 1000 examinations) in extremely dense breasts. DBT screening had a higher proportion than DM of screen-detected early-stage, invasive cancers with favorable prognostic characteristics. In this cohort study of women with a family history of breast cancer, DBT screening reduced recall rates and increased specificity compared to DM, particularly in women with 1 first-degree relative with breast cancer and those with scattered fibroglandular breast density, and reduced advanced cancer rates in women with extremely dense breasts.

Many US radiologists have screening mammography recall rates above the expert-recommended threshold of 12%. The influence of digital breast tomosynthesis (DBT) on the distribution of radiologist recall rates is uncertain. To evaluate radiologists' recall and cancer detection rates before and after beginning interpretation of DBT examinations. This cohort study included 198 radiologists from 104 radiology facilities in the Breast Cancer Surveillance Consortium who interpreted 251 384 DBT and 2 000 681 digital mammography (DM) screening examinations from 2009 to 2017, including 126 radiologists (63.6%) who interpreted DBT examinations during the study period and 72 (36.4%) who exclusively interpreted DM examinations (to adjust for secular trends). Data were analyzed from April 2018 to July 2019. Digital breast tomosynthesis and DM screening examinations. Recall rate and cancer detection rate. A total of 198 radiologists interpreted 2 252 065 DM and DBT examinations (2 000 681 [88.8%] DM examinations; 251 384 [11.2%] DBT examinations; 710 934 patients [31.6%] aged 50-59 years; 1 448 981 [64.3%] non-Hispanic white). Among the 126 radiologists (63.6%) who interpreted DBT examinations, 83 (65.9%) had unadjusted DM recall rates of no more than 12% before using DBT, with a median (interquartile range) recall rate of 10.0% (7.5%-13.0%). On DBT examinations, 96 (76.2%) had an unadjusted recall rate of no more than 12%, with a median (interquartile range) recall rate of 8.8% (6.3%-11.3%). A secular trend in recall rate was observed, with the multivariable-adjusted risk of recall on screening examinations declining by 1.2% (95% CI, 0.9%-1.5%) per year. After adjusting for examination characteristics and secular trends, recall rates were 15% lower on DBT examinations compared with DM examinations interpreted before DBT use (relative risk, 0.85; 95% CI, 0.83-0.87). Adjusted recall rates were significantly lower on DBT examinations compared with DM examinations interpreted before DBT use for 45 radiologists (35.7%) and significantly higher for 18 (14.3%); 63 (50.0%) had no statistically significant change. The unadjusted cancer detection rate on DBT was 5.3 per 1000 examinations (95% CI, 5.0-5.7 per 1000 examinations) compared with 4.7 per 1000 examinations (95% CI, 4.6-4.8 per 1000 examinations) on DM examinations interpreted before DM use (multivariable-adjusted risk ratio, 1.21; 95% CI, 1.11-1.33). In this study, DBT was associated with an overall decrease in recall rate and an increase in cancer detection rate. However, our results indicated that there is wide variability among radiologists, including a subset of radiologists who experienced increased recall rates on DBT examinations. Radiology practices should audit radiologist DBT screening performance and consider additional DBT training for radiologists whose performance does not improve as expected.

BACKGROUND. Prior studies comparing cancer screening by digital breast tomosynthesis (DBT) and digital mammography (DM) have largely entailed prospective trials and investigations at tertiary academic centers, which may encounter high-risk patient populations and lack heterogeneity among interpreting radiologists. Thus, results may not generalize across real-world community settings in the United States. OBJECTIVE. The purpose of this study was to compare DBT and DM in terms of screening performance and tumor characteristics of screen-detected cancers in a community practice setting. METHODS. Data were retrospectively retrieved for all screening mammography examinations performed by DBT or DM at four outpatient private practice facilities from January 1, 2012, to July 10, 2019. Examinations were interpreted by one of 26 radiologists (21 breast radiologists, five general radiologists). Further detailed information was recorded from radiology and pathology reports for all screen-detected cancers. Statistical comparisons were performed between DBT and DM in terms of screening performance and tumor characteristics of screen-detected cancers. RESULTS. A total of 310 cancers were detected in 47,096 screening DBT examinations and 83,200 screening DM examinations. Cancer detection rate was higher (p < .001) for DBT (3.4 per 1000 women) than for DM (1.8 per 1000 women). PPV1 was higher (p < .001) for DBT (3.5% [161/4641]) than for DM (2.1% [149/7116]). Patients with DBT-detected cancer were younger than those with DM-detected cancer (mean age [range], 61 years [40-87 years] vs 64 years [37-88 years]; p = .02). A greater percentage of DBT-detected than DM-detected cancers were invasive (85.1% [137/161] vs 72.5% [108/149]; p = .006), grade 1 when invasive (27.9% [38/136] vs 17.8% [19/107]; p = .04), and node negative (92.2% [71/77] vs 78.4% [58/74]; p = .02). Cancers detected by DBT and DM were not significantly different in histologic subtype, molecular subtype, or mean size (all p > .05). CONCLUSION. DBT showed a higher cancer detection rate and PPV1 than DM, and patients were younger at cancer diagnosis with DBT. Cancers detected on DBT were more often invasive, grade 1, and node negative. CLINICAL IMPACT. The findings support the generalizability of insights into DBT-based screening, which previously have been investigated primarily in academic settings.

Invasive lobular carcinoma (ILC) is a distinct histological subtype of breast cancer that can make early detection with mammography challenging. We compared imaging performance of digital breast tomosynthesis (DBT) to digital mammography (DM) for diagnoses of ILC, invasive ductal carcinoma (IDC), and invasive mixed carcinoma (IMC) in a screening population. We included screening exams (DM; n = 1,715,249 or DBT; n = 414,793) from 2011 to 2018 among 839,801 women in the Breast Cancer Surveillance Consortium. Examinations were followed for one year to ascertain incident ILC, IDC, or IMC. We measured cancer detection rate (CDR) and interval invasive cancer rate/1000 screening examinations for each histological subtype and stratified by breast density and modality. We calculated relative risk (RR) for DM vs. DBT using log-binomial models to adjust for the propensity of receiving DBT vs. DM. Unadjusted CDR per 1000 mammograms of ILC overall was 0.33 (95%CI: 0.30-0.36) for DM; 0.45 (95%CI: 0.39-0.52) for DBT, and for women with dense breasts- 0.33 (95%CI: 0.29-0.37) for DM and 0.54 (95%CI: 0.43-0.66) for DBT. Similar results were noted for IDC and IMC. Adjusted models showed a significantly increased RR for cancer detection with DBT compared to DM among women with dense breasts for all three histologies (RR; 95%CI: ILC 1.53; 1.09-2.14, IDC 1.21; 1.02-1.44, IMC 1.76; 1.30-2.38), but no significant increase among women with non-dense breasts. DBT was associated with higher CDR for ILC, IDC, and IMC for women with dense breasts. Early detection of ILC with DBT may improve outcomes for this distinct clinical entity.

Introduction: Digital breast tomosynthesis (DBT) may decrease recall rates (RRs) and improve positive predictive values (PPVs) and cancer detection rates (CDRs) versus full-field digital mammography (FFDM). The value of DBT has not been assessed in New Mexico's rural and minority population. Objectives of this study were to compare RRs, CDRs, and PPVs using FFDM+DBT versus FFDM in screening mammograms at the University of New Mexico between 2013 and 2016 and to qualitatively evaluate patient decision-making regarding DBT. Materials and Methods: RRs, CDRs, and PPVs with 95% confidence intervals and relative risk were calculated from 35,147 mammograms. The association between relative risk and mammography approach was tested using Pearson's chi-square test. Twenty women undergoing screening were interviewed for qualitative evaluation of decision-making. Results: From 2013 to 2016, RRs were 8.4% and 11.1% for FFDM+DBT and FFDM, respectively. The difference in RRs became more pronounced with time. No significant difference was observed in PPVs or CDRs. Qualitative interviews revealed that the majority had limited prior knowledge of DBT and relied on provider recommendations. Conclusion: In New Mexico women undergoing screening mammography, a 30% relative risk reduction in RRs was observed with FFDM+DBT. Qualitative interviews suggest that women are aware of and receptive to DBT, assuming adequate educational support. Clinical Trials.gov ID: NCT03979729.

Purpose To examine the outcomes of a breast cancer screening program based on digital breast tomosynthesis (DBT) plus synthesized two-dimensional (2D) mammography compared with those after full-field digital mammography (FFDM). Materials and Methods This prospective study included 16 666 asymptomatic women aged 50-69 years who were recruited in April 2015 through March 2016 for DBT plus synthetic 2D screening in the Verona screening program. A comparison cohort of women screened with FFDM (n = 14 423) in the previous year was included. Screening detection measures for the two groups were compared by calculating the proportions associated with each outcome, and the relative rates (RRs) were estimated with multivariate logistic regression. Results Cancer detection rate (CDR) for DBT plus synthetic 2D imaging was 9.30 per 1000 screening examinations versus 5.41 per 1000 screening examinations with FFDM (RR, 1.72; 95% confidence interval [CI]: 1.30, 2.29). CDR was significantly higher in patients screened with DBT plus synthetic 2D imaging than in those screened with FFDM among women classified as having low breast density (RR, 1.53; 95% CI: 1.13, 2.10) or high breast density (RR, 2.86; 95% CI: 1.42, 6.25). The positive predictive value (PPV) for recall was almost doubled with DBT plus synthetic 2D imaging: 23.3% versus 12.9% of recalled patients who were screened with FFDM (RR, 1.81; 95% CI: 1.34, 2.47). The recall rate was similar between groups (RR, 0.95; 95% CI: 0.84, 1.06), whereas the recall rate with invasive assessment was higher for DBT plus synthetic 2D imaging than for FFDM (RR, 1.93; 95% CI: 1.31, 2.03). The mean number of screening studies interpreted per hour was significantly lower for screening examinations performed with DBT plus synthetic 2D imaging (38.5 screens per hour) than with FFDM (60 screens per hour) (P < .001). Conclusion DBT plus synthetic 2D imaging increases CDRs with recall rates comparable to those of FFDM. DBT plus synthetic 2D imaging increased image reading time and the time needed for invasive assessments. © RSNA, 2017.

With growing interest in applying artificial intelligence (AI) to population breast cancer screening, the evidence base has expanded rapidly. This systematic review aims to systematically review and summarise the published evidence on the use of AI in breast cancer screening. We conducted a systematic review of primary studies assessing AI for screening mammography, extracting test-accuracy metrics (sensitivity, specificity, recall and cancer detection rates) and workflow outcomes. We searched the Cochrane Breast Cancer Group Specialised Register, Cochrane CENTRAL, PubMed, Embase (Elsevier), Scopus, ClinicalTrials.gov and the WHO International Clinical Trials Registry Platform from January 2012 to June 2025; we also screened reference lists of included studies and relevant reviews. No language restrictions were applied. Primary studies evaluating AI for screening mammography (digital mammography or digital breast tomosynthesis) in asymptomatic women, assessing AI as a standalone reader or AI-assisted radiologist workflows versus radiologists alone. Eligible designs included randomised trials, prospective paired reader studies, real-world implementation/registry cohorts, retrospective cohorts and multireader-multicase reader studies conducted in population-based or opportunistic screening settings. Key outcomes included diagnostic accuracy metrics (eg, sensitivity, specificity, Area Under the Curve (AUC) and/or programme metrics (cancer detection rate (CDR), recall/abnormal interpretation rate, positive predictive value, arbitration/workload). We excluded protocols, pilot/feasibility studies, case reports, editorials and studies without relevant accuracy or screening outcomes. Two independent reviewers extracted data and assessed risk of bias. Study quality was appraised with Quality Assessment of Diagnostic Accuracy Studies-2 and an AI-specific critical appraisal tool, and findings were synthesised narratively with stratification by study design and AI integration role. 31 studies met the inclusion criteria, encompassing randomised controlled trials, prospective paired-reader studies, registry-based implementations and retrospective simulations, representing more than two million screening examinations across Europe, Asia, North America and Australia. When used as a second reader or within double-reading workflows, AI generally maintained or modestly increased sensitivity (up to +9 percentage points (PP)) while preserving or improving specificity. Triage and decision-referral configurations delivered the greatest operational benefit, reducing reading volumes by 40-90% while maintaining non-inferior cancer detection when thresholds were conservatively calibrated. Stand-alone AI achieved AUC values comparable to radiologists and similar cancer detection in real-world, non-enriched cohorts, although interval-cancer follow-up remains incomplete in several datasets. In prospective randomised evidence, including the Mammography Screening with Artificial Intelligence trial (MASAI) trial, AI-supported screening achieved higher CDRs (6.4 versus 5.0 per 1000; p=0.0021) with stable or reduced false-positive and recall rates. Across implementation and simulation settings, integration of AI reduced radiologist workload substantially, with triage and band-pass approaches reducing the number of reads by approximately 40-90%. Overall certainty is limited by heterogeneity across study designs, reliance on enriched datasets for some accuracy estimates and incomplete interval-cancer follow-up in several major studies. Contemporary AI systems show diagnostic performance that is broadly comparable to radiologists and can substantially reduce reading workload, particularly when used as a second reader or triage tool. Emerging prospective evidence supports their safe integration in these roles, although transparent reporting, standardised evaluation and long-term population studies are still required before considering AI as a stand-alone reader. AI may improve workflow efficiency and possibly cancer detection, but definitive evidence on safety, especially interval cancer outcomes, remains essential.

To compare the diagnostic performance of two-dimensional (2D) mammography, 2D mammography plus digital breast tomosynthesis (DBT), and synthetic 2D mammography plus DBT in depicting malignant radiographic features. In this multicenter, multireader, retrospective reading study (the TOMMY trial), after written informed consent was obtained, 8869 women (age range, 29-85 years; mean, 56 years) were recruited from July 2011 to March 2013 in an ethically approved study. From these women, a reading dataset of 7060 cases was randomly allocated for independent blinded review of (a) 2D mammography images, (b) 2D mammography plus DBT images, and (c) synthetic 2D mammography plus DBT images. Reviewers had no access to results of previous examinations. Overall sensitivities and specificities were calculated for younger women and those with dense breasts. Overall sensitivity was 87% for 2D mammography, 89% for 2D mammography plus DBT, and 88% for synthetic 2D mammography plus DBT. The addition of DBT was associated with a 34% increase in the odds of depicting cancer (odds ratio [OR] = 1.34, P = .06); however, this level did not achieve significance. For patients aged 50-59 years old, sensitivity was significantly higher (P = .01) for 2D mammography plus DBT than it was for 2D mammography. For those with breast density of 50% or more, sensitivity was 86% for 2D mammography compared with 93% for 2D mammography plus DBT (P = .03). Specificity was 57% for 2D mammography, 70% for 2D mammography plus DBT, and 72% for synthetic 2D mammography plusmDBT. Specificity was significantly higher than 2D mammography (P < .001in both cases) and was observed for all subgroups (P < .001 for all cases). The addition of DBT increased the sensitivity of 2D mammography in patients with dense breasts and the specificity of 2D mammography for all subgroups. The use of synthetic 2D DBT demonstrated performance similar to that of standard 2D mammography with DBT. DBT is of potential benefit to screening programs, particularly in younger women with dense breasts. (©) RSNA, 2015.

Why Patients Decline Digital Breast Tomosynthesis? Results From a Patient Survey in an Urban Academic Breast Center

Background Multiple studies showed digital breast tomosynthesis (DBT) has a higher cancer detection rate and a lower recall rate than full-field digital mammography (FFDM). However, there is a paucity of studies on whether the benign biopsy rate will be lower with DBT. Purpose To evaluate the benign biopsy rate of DBT versus that of FFDM in women recalled after breast screening within the National Health Service Breast Screening Programme. Materials and Methods This prospective single institution study included women who underwent screening FFDM or screening breast MRI between November 13, 2015, and July 29, 2016, and were recalled. Women who were recalled underwent a breast examination, additional imaging (mammography, US), and biopsy, if required. The number of interventions and the outcome of assessment were recorded. FFDM was performed at the screening appointment, and DBT images were acquired when participants attended a screening assessment within 3 weeks after screening FFDM. Two of four readers blinded to biopsy results analyzed DBT images in isolation and then in conjunction with FFDM images and any additional two-dimensional mammographic or US images. Two-tailed McNemar tests were used to test differences in sensitivity and specificity of the two conditions at 5% significance level. Results During the study period, 30 933 women underwent FFDM. A total of 1470 women were recalled (recall rate, 4.8%), and 827 were included after exclusion criteria were applied. Their mean age was 56.7 years ± 7.7 (standard deviation). A total of 145 breast cancers were detected (142 with FFDM, two with DBT only, one with surveillance MRI). Triple assessment without DBT resulted in 571 breast biopsies and enabled detection of 142 cancers. The addition of DBT would have resulted in 298 biopsies and detection of 142 cancers, reducing the number of biopsies from 571 of 827 (69.0%) to 298 of 827 (36.0%). Conclusion When compared with full-field digital mammography, digital breast tomosynthesis can reduce the benign biopsy rate while maintaining the cancer detection rate. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Skaane in this issue.

Over-diagnosis in screening by mammography: A follow-up of the Malmö Mammographic Screening Trial, MMST

Full-field digital mammography (FFDM), the standard of care for breast cancer screening, has some limitations. With the advent of digital breast tomosynthesis (DBT), improvements including decreased recall rates and increased cancer detection rates have been observed. The quasi-three-dimensional capability of DBT reduces breast tissue overlap, a significant limitation of FFDM. However, early studies demonstrate that a few cancers detected at FFDM may not be diagnosed at DBT-only screening, and lesions with calcifications as the dominant feature may look less suspicious at DBT or not be visible at all. These findings support the use of combined FFDM and DBT protocols to optimize screening performance. However, this combination would approximately double the patient's radiation exposure. The development of computer algorithms that generate two-dimensional synthesized mammography (SM) views from DBT has improved calcification conspicuity and sensitivity. Therefore, SM may substitute for FFDM in screening protocols, reducing radiation exposure. DBT plus SM demonstrates significantly better performance than that of FFDM alone, although there are reports of missed malignant calcifications. Thus, some centers continue to perform FFDM with DBT. Use of DBT in breast imaging has also necessitated the development of DBT-guided biopsy. DBT-guided biopsy may have a higher success rate than that of stereotactic biopsy, with a shorter procedure time. While DBT brings substantial improvements to breast cancer imaging, it is important to be aware of its strengths and limitations regarding detection of calcifications. This article reviews the imaging appearance of breast calcifications at DBT, discusses calcification biopsy techniques, and provides an overview of the current literature. Online supplemental material is available for this article. ©RSNA, 2019 An earlier incorrect version of this article appeared online. This article was corrected on February 13, 2019.

Digital breast tomosynthesis (DBT) is a relatively new X-ray technique that allows quasi–three-dimensional imaging of the breast to overcome limitations of conventional 2-D digital mammography (DM). Several early screening studies have shown that DBT reduces the number of false-positive recalls while simultaneously improving the cancer detection rate. Cost-effectiveness studies have shown that incorporating DBT in screening has the potential to save health care dollars due to lower recall rates as well as reduced treatment costs resulting from the earlier detection of breast cancer. In the diagnostic setting, DBT imaging may allow a more efficient work-up of breast lesions due to improved lesion conspicuity and the ability to better localize lesions within the breast.