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Objective: Mammography and MRI screening typically occur in combination or in alternating sequence. We compared multimodality screening performance accounting for the relative timing of mammography and MRI and overlapping follow-up periods., Methods: We identified 8,260 screening mammograms performed 2005 to 2017 in the Breast Cancer Surveillance Consortium, paired with screening MRIs within ±90 days (combined screening) or 91 to 270 days (alternating screening). Performance for combined screening (cancer detection rate [CDR] per 1,000 examinations and sensitivity) was calculated with 1-year follow-up for each modality, and with a single follow-up period treating the two tests as a single test. Alternating screening performance was calculated with 1-year follow-up for each modality and also with follow-up ending at the next screen if within 1 year (truncated follow-up)., Results: For 3,810 combined screening pairs, CDR per 1,000 screens was 6.8 (95% confidence interval [CI]: 4.6-10.0) for mammography and 12.3 (95% CI: 9.3-16.4) for MRI as separate tests compared with 13.1 (95% CI: 10.0-17.3) as a single combined test. Sensitivity of each test was 48.1% (35.0%-61.5%) for mammography and 79.7% (95% CI: 67.7%-88.0%) for MRI compared with 96.2% (95% CI: 85.9%-99.0%) for combined screening. For 4,450 alternating screening pairs, mammography CDR per 1,000 screens changed from 3.6 (95% CI: 2.2-5.9) to zero with truncated follow-up; sensitivity was incalculable (denominator = 0). MRI CDR per 1,000 screens changed from 12.1 (95% CI 9.3-15.8) to 11.7 (95% CI: 8.9-15.3) with truncated follow-up; sensitivity changed from 75.0% (95% CI 63.8%-83.6%) to 86.7% (95% CI 75.5%-93.2%)., Discussion: Updating auditing approaches to account for combined and alternating screening sequencing and to address outcome attribution issues arising from overlapping follow-up periods can improve the accuracy of multimodality screening performance evaluation., (Copyright © 2024 American College of Radiology. Published by Elsevier Inc. All rights reserved.)

Purpose: Cancer detection rate (CDR), an important metric in the mammography screening audit, is designed to ensure adequate sensitivity. Most practices use biopsy results as the reference standard; however, commonly ascertainment of biopsy results is incomplete. We used simulation to determine the relationship between the cancer ascertainment rate of biopsy (AR-biopsy), CDR estimation, and associated error rates in classifying whether practices and radiologists meet the established ACR benchmark of 2.5 per 1,000., Materials and Methods: We simulated screening mammography volume, number of cancers detected, and CDR, using negative binomial and beta-binomial distributions, respectively. Simulations were performed at both the practice and radiologist level. Average CDR was based on linearly rescaling a published CDR by the AR-biopsy. CDR distributions were simulated for AR-biopsy between 5% and 100% in steps of five percentage points and were summarized with boxplots and smoothed histograms over the range of AR-biopsy, to quantify the proportion of practices and radiologists meeting the ACR benchmark at each level of AR-biopsy., Results: Decreasing AR-biopsy led to an increasing probability of categorizing CDR performance as being below the ACR benchmark. Our simulation predicts that at the practice level, an AR-biopsy of 65% categorizes 17.6% below the benchmark (compared to 1.6% at an AR-biopsy of 100%), and at the radiologist level, an AR-biopsy of 65% categorizes 34.7% as being below the benchmark (compared to 11.6% at an AR-biopsy of 100%)., Conclusions: Our simulation demonstrates that decreasing the AR-biopsy (in currently clinically relevant ranges) has the potential to artifactually lower the assessed CDR on both the practice and radiologist levels and may, in turn, increase the chance of erroneous categorization of underperformance per the ACR benchmark., (Copyright © 2023 American College of Radiology. Published by Elsevier Inc. All rights reserved.)

Purpose: To summarize the literature regarding the performance of mammography-image based artificial intelligence (AI) algorithms, with and without additional clinical data, for future breast cancer risk prediction., Materials and Methods: A systematic literature review was performed using six databases (medRixiv, bioRxiv, Embase, Engineer Village, IEEE Xplore, and PubMed) from 2012 through September 30, 2022. Studies were included if they used real-world screening mammography examinations to validate AI algorithms for future risk prediction based on images alone or in combination with clinical risk factors. The quality of studies was assessed, and predictive accuracy was recorded as the area under the receiver operating characteristic curve (AUC)., Results: Sixteen studies met inclusion and exclusion criteria, of which 14 studies provided AUC values. The median AUC performance of AI image-only models was 0.72 (range 0.62-0.90) compared with 0.61 for breast density or clinical risk factor-based tools (range 0.54-0.69). Of the seven studies that compared AI image-only performance directly to combined image + clinical risk factor performance, six demonstrated no significant improvement, and one study demonstrated increased improvement., Conclusions: Early efforts for predicting future breast cancer risk based on mammography images alone demonstrate comparable or better accuracy to traditional risk tools with little or no improvement when adding clinical risk factor data. Transitioning from clinical risk factor-based to AI image-based risk models may lead to more accurate, personalized risk-based screening approaches., (Copyright © 2023 American College of Radiology. Published by Elsevier Inc. All rights reserved.)

Purpose: The aim of this study was to develop a prioritization strategy for scheduling immediate screening mammographic interpretation and possible diagnostic evaluation., Methods: A population-based cohort with screening mammograms performed from 2012 to 2020 at 126 radiology facilities from 7 Breast Cancer Surveillance Consortium registries was identified. Classification trees identified combinations of clinical history (age, BI-RADS® density, time since prior mammogram, history of false-positive recall or biopsy result), screening modality (digital mammography, digital breast tomosynthesis), and facility characteristics (profit status, location, screening volume, practice type, academic affiliation) that grouped screening mammograms by recall rate, with ≥12/100 considered high and ≥16/100 very high. An efficiency ratio was estimated as the percentage of recalls divided by the percentage of mammograms., Results: The study cohort included 2,674,051 screening mammograms in 925,777 women, with 235,569 recalls. The most important predictor of recall was time since prior mammogram, followed by age, history of false-positive recall, breast density, history of benign biopsy, and screening modality. Recall rates were very high for baseline mammograms (21.3/100; 95% confidence interval, 19.7-23.0) and high for women with ≥5 years since prior mammogram (15.1/100; 95% confidence interval, 14.3-16.1). The 9.2% of mammograms in subgroups with very high and high recall rates accounted for 19.2% of recalls, an efficiency ratio of 2.1 compared with a random approach. Adding women <50 years of age with dense breasts accounted for 20.3% of mammograms and 33.9% of recalls (efficiency ratio = 1.7). Results including facility-level characteristics were similar., Conclusions: Prioritizing women with baseline mammograms or ≥5 years since prior mammogram for immediate interpretation and possible diagnostic evaluation could considerably reduce the number of women needing to return for diagnostic imaging at another visit., (Copyright © 2022 American College of Radiology. Published by Elsevier Inc. All rights reserved.)

Objective: We sought to identify and characterize examinations in women with a personal history of breast cancer likely performed for asymptomatic surveillance., Methods: We included surveillance mammograms (1997-2017) in asymptomatic women with a personal history of breast cancer diagnosed at age ≥18 years (1996-2016) from 103 Breast Cancer Surveillance Consortium facilities. We examined facility-level variability in examination indication. We modeled the relative risk (RR) and 95% confidence intervals (CIs) at the examination level of a (1) nonscreening indication and (2) surveillance interval ≤9 months using Poisson regression with fixed effects for facility, stage, diagnosis age, surgery, examination year, and time since diagnosis., Results: Among 244,855 surveillance mammograms, 69.5% were coded with a screening indication, 12.7% short-interval follow-up, and 15.3% as evaluation of a breast problem. Within a facility, the proportion of examinations with a screening indication ranged from 6% to 100% (median 86%, interquartile range 79%-92%). Facilities varied the most for examinations in the first 5 years after diagnosis, with 39.4% of surveillance mammograms having a nonscreening indication. Within a facility, breast conserving surgery compared with mastectomy (RR = 1.64; 95% CI = 1.60-1.68) and less time since diagnosis (1 year versus 5 years; RR = 1.69; 95% CI = 1.66-1.72; 3 years versus 5 years = 1.20; 95% CI = 1.18-1.23) were strongly associated with a nonscreening indication with similar results for ≤9-month surveillance interval. Screening indication and >9-month surveillance intervals were more common in more recent years., Conclusion: Variability in surveillance indications across facilities in the United States supports including indications beyond screening in studies evaluating surveillance mammography effectiveness and demonstrates the need for standardization., (Copyright © 2020. Published by Elsevier Inc.)

Objective: The impact of mammography screening recall on quality-of-life (QOL) has been studied in women at average risk for breast cancer, but it is unknown whether these effects differ by breast cancer risk level. We used a vignette-based survey to evaluate how women across the spectrum of breast cancer risk perceive the experience of screening recall., Methods: Women participating in mammography or breast MRI screening were recruited to complete a vignette-based survey. Using a numerical rating scale (0-100), women rated QOL for hypothetical scenarios of screening recall, both before and after benign results were known. Lifetime breast cancer risk was calculated using Gail and BRCAPRO risk models. Risk perception, trait anxiety, and breast cancer worry were assessed using validated instruments., Results: The final study cohort included 162 women at low (n = 43, 26%), intermediate (n = 66, 41%), and high-risk (n = 53, 33%). Actual breast cancer risk was not a predictor of QOL for any of the presented scenarios. Across all risk levels, QOL ratings were significantly lower for the period during diagnostic uncertainty compared to after benign results were known (p < 0.05). In multivariable regression analyses, breast cancer worry was a significant predictor of decreased QoL for all screening scenarios while awaiting results, including scenarios with non-invasive imaging alone or with biopsy. High trait anxiety and family history predicted lower QOL scores after receipt of benign test results (p < 0.05)., Conclusions: Women with high trait anxiety and family history may particularly benefit from discussions about the risk of recall when choosing a screening regimen., Competing Interests: Declaration of competing interest JML and KPL receive research support from GE Healthcare. GSG was previously a consultant for GE Healthcare until 2018., (Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Purpose: To describe factors associated with screening ultrasound ordering and determine whether adoption of state-level breast density reporting laws was associated with changes in ordering rates., Materials and Methods: We performed a cohort study using National Ambulatory Medical Care Survey data for 2007 to 2015. We included preventive office visits for women aged 40 to 74 years without breast symptoms and signs or additional reasons requiring ultrasound ordering. Multivariate logistic regression was used to identify changes in ultrasound ordering rates pre- versus post-state-level density reporting laws, accounting for patient-, physician-, and practice-level characteristics. Analyses were weighted to account for the multistage probability sampling design of National Ambulatory Medical Care Survey., Results: Our sample included 12,787 visits over the 9-year study period. Overall, 28.9% (3,370 of 12,787) of women underwent a breast examination and 22.1% (2,442 of 12,787) had a screening mammogram ordered. Only 3.3% (379 of 12,787) had screening ultrasound ordered. Screening ultrasounds were ordered more frequently for younger women (rate ratio [RR] 0.8 per 10-year increase in age, 95% confidence interval [CI]: 0.6-0.9, P = .003) and at urban practices (RR 2.3, 95% CI: 1.1-5.0, P = .028), and less frequently in practices with computer reminders for ordering screening tests (RR 0.6, 95% CI: 0.3-0.9, P = .024). In multivariate analyses, the rate of ultrasound ordering did not change after adoption of density notification laws (RR 0.7, 95% CI: 0.3-2.0, P = .57)., Conclusion: The rate of screening ultrasound ordering remains low over time. There was no observed association between adoption of state-level density reporting laws and overall changes in ultrasound ordering., (Copyright © 2019 American College of Radiology. Published by Elsevier Inc. All rights reserved.)

Purpose: To evaluate the impact of double reading automated breast ultrasound (ABUS) when added to full field digital mammography (FFDM) or digital breast tomosynthesis (DBT) for breast cancer screening., Methods: From April 2014 to June 2015, 124 women with dense breasts and intermediate to high breast cancer risk were recruited for screening with FFDM, DBT, and ABUS. Readers used FFDM and DBT in clinical practice and received ABUS training prior to study initiation. FFDM or DBT were first interpreted alone by two independent readers and then with ABUS. All recalled women underwent diagnostic workup with at least one year of follow-up. Recall rates were compared using the sign test; differences in outcomes were evaluated using Fisher's exact test., Results: Of 121 women with complete follow-up, all had family (35.5%) or personal (20.7%) history of breast cancer, or both (43.8%). Twenty-four women (19.8%) were recalled by at least one modality. Recalls increased from 5.0% to 13.2% (p = 0.002) when ABUS was added to FFDM and from 3.3% to 10.7% (p = 0.004) when ABUS was added to DBT. Findings recalled by both readers were more likely to result in a recommendation for short term follow-up imaging or tissue biopsy compared to findings recalled by only one reader (100% vs. 42.1%, p = 0.041). The cancer detection rate was 8.3 per 1000 screens (1/121); mode of detection: FFDM and DBT., Conclusions: Adding ABUS significantly increased the recall rate of both FFDM and DBT screening. Double reading of ABUS during early phase adoption may reduce false positive recalls., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Purpose: Focusing on outcomes of care alone may be too restrictive. Patients can experience morbidity that is important to them from health care processes themselves. However, many processes, such as testing and screening, have been little evaluated. This study's purpose was to assess the construct validity of a new preference-based index, the Testing Morbidities Index (TMI), by comparing two common cancer-related procedures in prior publications: screening colonoscopy and core-needle breast biopsy., Methods: Women evaluating their breast biopsies (n = 100) were compared with men and women who had undergone screening colonoscopy (n = 109) after both groups completed the TMI. The TMI addresses physical and mental or emotional quality of life affected by test-specific aspects occurring before, during, or after any test. It has 7 domains and survey items. TMI scores can be scaled in various ways, including multi-attribute value theory-based patient or societal preferences, where 0 = dead and 1.0 = full health, as used here., Results: There was significantly greater morbidity from breast biopsy (mean, 0.84) than from screening colonoscopy (mean, 0.88) comparing overall TMI preference scores (P < .0001). Breast biopsy showed significantly worse morbidity (P = .005 to P < .0001) in most domains. Pain or discomfort before testing was worse for colonoscopy because of bowel preparation. The TMI showed no floor effect and an acceptable ceiling effect., Conclusions: The TMI provides the first objective evidence comparing the morbidity of one cancer-related testing procedure with another. The TMI may be useful in assessments of medical care processes informative to institutions and imaging departments, shared decision-making scenarios, and economic analyses., (Copyright © 2015 American College of Radiology. Published by Elsevier Inc. All rights reserved.)

There are potential benefits and harms of screening ultrasound (US) to supplement mammographic screening of women with dense breast tissue. We conducted a comprehensive literature review of studies assessing the efficacy of screening US to supplement mammography among women with dense breasts. From a total of 189 peer-reviewed publications on the performance of screening US, 12 studies were relevant to our analysis. The reporting of breast cancer risk factors varied across studies; however, the study populations tended to be at greater than average risk for developing breast cancer. Overall, US detected an additional 0.3-7.7 cancers per 1000 examinations (median, 4.2) and was associated with an additional 11.7-106.6 biopsies per 1000 examinations (median, 52.2). Significant improvements in cancer detection in dense breasts have been achieved with the transition from film to digital mammography. Thus adjunctive screening with ultrasound should be considered in the context of current screening mammography performance. Clinicians should discuss breast density as 1 of several important breast cancer risk factors, consider the potential harms of adjunctive screening, and arrive at a shared decision consistent with each woman's preferences and values., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Purpose: Breast MRI is increasingly used for both screening and diagnostic purposes. Although performance benchmarks for screening and diagnostic mammography have been published, performance benchmarks for breast MRI have yet to be established. The purpose of this study was to comprehensively evaluate breast MRI performance measures, stratified by screening and diagnostic indications, from a single academic institution., Methods: Institutional review board approval was acquired for this HIPAA-compliant study. Informed consent was not required. Retrospective review of the institutional database identified all breast MRI examinations performed from April 1, 2007, to March 31, 2008. After application of exclusion criteria, the following performance measures for screening and diagnostic indications were calculated: cancer detection rate, positive predictive value (PPV), and abnormal interpretation rates., Results: The study included 2,444 examinations, 1,313 for screening and 1,131 for diagnostic indications. The cancer detection rates were 14 per 1,000 screening breast MRI examinations and 47 per 1,000 diagnostic examinations (P < .00001). The abnormal interpretation rate was 12% (152 of 1,313) for screening and 17% (194 of 1,131) for diagnostic indications (P = .00008). The PPVs of MRI were lower for screening [PPV1 (abnormal findings) = 12%, PPV2 (biopsy recommended) = 24%, PPV3 (biopsy performed) = 27%] compared with diagnostic indications (PPV1 (abnormal findings) = 28%, PPV2 (biopsy recommended) = 36%, PPV3 (biopsy performed) = 38%]., Conclusions: Breast MRI performance measures differ significantly between screening and diagnostic MRI indications. Medical audits for breast MRI should calculate performance measures for screening and diagnostic breast MRI separately, as recommended for mammography., (Copyright © 2014 American College of Radiology. Published by Elsevier Inc. All rights reserved.)

Background: Recent changes in clinical guideline recommendations for age of breast cancer screening initiation highlighted the potential psychological ramifications associated with screening. This study examined the feasibility, acceptability, and preliminary efficacy of a brief Relaxation Response training (RRT) to decrease distress among women undergoing breast biopsy., Methods: Women scheduled for percutaneous core-needle biopsy were recruited into a single-arm RRT trial, including 3 individual sessions. Psychosocial assessments were completed pre- and postintervention., Results: Forty women were enrolled between 6/1/10 and 8/31/11. Among enrollees, 75% completed all 3 RRT sessions, and 75% completed the post-assessment. Participants showed significant reductions in acute distress following each RRT session. Qualitative feedback indicated a positive impact of RRT on clinic care experiences., Conclusions: RRT is a portable intervention that was feasible to implement, acceptable to patients and associated with significant decreases in acute emotional distress during the period of diagnostic uncertainty related to percutaneous breast biopsy., (Copyright © 2013 Elsevier Ltd. All rights reserved.)