Improving State-Mandated Breast Density Notifications

PurposeEffective written communication directly affects health care outcomes. Since 2016, the complex language of state-mandated breast density notifications (BDNs) has been challenged, because it is perceived to be beyond the comprehension of most patients. The aim of this study was to assess whether a revised BDN written at a lower reading grade level improves understanding compared with the current state-mandated BDN.MethodsA revised notification with similar content to the current state-mandated BDN was developed. Both notifications were presented to patients for direct comparison, using a paper survey asking questions that evaluated patients’ perceptions and convictions associated with breast density. Surveys were distributed at four outpatient imaging centers to screening mammography patients.ResultsThe current BDN’s mean readability metric was 13.4, and that of the revised BDN was 6.6. Five hundred surveys were analyzed. Survey data demonstrated that 56.6% of all women perceived that dense breast tissue results indicated a “high” associated lifetime breast cancer risk from the current state-mandated BDN compared with only 2.2% with the revised notification (P < .001). Nearly all women were more likely to initiate discussions with their providers regarding their breast tissue density after reading the revised notification (96.0%) as opposed to the current state-mandated BDN (32.8%; P < .001).ConclusionsA significant portion of women misinterpret the intended messages of the current state-mandated BDN. Thus, a revised notification at a lower reading grade level may improve understanding of breast density, leading to improved individualized breast cancer screening for women with dense breasts.     

Impact of the New Jersey Breast Density Law on Imaging and Intervention Volumes and Breast Cancer Diagnosis

PurposeIncreased breast density is acknowledged as an independent risk factor for breast cancer and may obscure malignancy on mammography. Approximately half of all mammograms depict dense breasts. Legislation related to mandatory breast density notification was first enacted in Connecticut in 2009. On May 1, 2014, New Jersey joined other states with similar legislation. The New Jersey breast density law (NJBDL) mandates that mammography reports acknowledge the relevance and masking effect of mammographic breast density. The aim of this study was to assess the impact of the NJBDL at one of the state’s largest ACR-accredited breast centers.MethodsA retrospective chart review was performed to determine changes in imaging and intervention utilization and modality of cancer diagnosis after enactment of the legislation. Data for the present study were extracted from a review of all patients with core biopsy–proven malignancy at a large outpatient breast center between November 1, 2012, and October 31, 2015. Data were divided into the 18-month period before the implementation of the NJBDL (November 1, 2012 to April 30, 2014) and the 18-month period after passage of the law (May 1, 2014 to October 31, 2015).ResultsScreening ultrasound increased significantly after the implementation of the NJBDL, by 651% (1,530 vs 11,486). MRI utilization increased by 59.3% (2,595 vs 4,134). A total of 1,213 cancers were included in the final analysis, 592 in the first time period and 621 after law implementation. Breast cancer was most commonly detected on screening mammography, followed by diagnostic mammography with ultrasound for palpable concern, in both time periods. Of the 621 cancers analyzed, 26.1% (n = 162) were found in patients 50 years of age or younger. Results demonstrated that with respect to how malignancies were detected, age and average mammographic density were both statistically significant (P = .002).ConclusionsThe NJBDL succeeded in publicizing the masking effect of dense breasts. The number of supplemental screening ultrasound and MRI examinations increased after the implementation of this legislation. An efficacy analysis affirmed the high sensitivity of screening MRI compared with other modalities. The use of MRI increased core biopsy efficiency and reduced the number of biopsies needed per cancer diagnosed.     

Patient Awareness of Breast Density and Interest in Supplemental Screening Tests: Comparison of an Academic Facility and a County Hospital

PurposeThe aim of this study was to measure women’s knowledge of breast density and their attitudes toward supplemental screening tests in the setting of the California Breast Density Notification Law at an academic facility and a county hospital, serving women with higher and lower socioeconomic status, respectively.MethodsInstitutional review board exemptions were obtained. A survey was administered during screening mammography at two facilities, assessing women’s awareness of and interest in knowing their breast density and interest in and willingness to pay for supplemental whole breast ultrasound and contrast-enhanced spectral mammography (CEMG). The results were compared by using Fisher exact tests between groups.ResultsA total of 105 of 130 and 132 of 153 women responded to the survey at the academic and county facilities, respectively. Among respondents at the academic and county facilities, 23% and 5% were aware of their breast density, and 94% and 79% wanted to know their density. A majority were interested in supplemental ultrasonography and CEMG at both sites; however, fewer women had a willingness to pay for the supplemental tests at the county hospital compared with those at the academic facility (22% and 70%, respectively, for ultrasound, P < .0001; 20% and 65%, respectively, for CEMG, P < .0001).ConclusionsBoth groups of women were interested in knowing their breast density and in supplemental screening tests. However, women at the county hospital were less willing to incur out-of-pocket expenses, suggesting a potential for a disparity in health care access for women of lower socioeconomic status after the enactment of breast density notification legislation.     

Impact of a Deep Learning Model for Predicting Mammographic Breast Density in Routine Clinical Practice

ObjectiveLegislation in 38 states requires patient notification of dense mammographic breast tissue because increased density is a marker of breast cancer risk and can limit mammographic sensitivity. Because radiologist density assessments vary widely, our objective was to implement and measure the impact of a deep learning (DL) model on mammographic breast density assessments in clinical practice.MethodsThis institutional review board–approved prospective study identified consecutive screening mammograms performed across three clinical sites over two periods: 2017 period (January 1, 2017, through September 30, 2017) and 2019 period (January 1, 2019, through September 30, 2019). The DL model was implemented at sites A (academic practice) and B (community practice) in 2018 for all screening mammograms. Site C (community practice) was never exposed to the DL model. Prospective densities were evaluated, and multivariable logistic regression models evaluated the odds of a dense mammogram classification as a function of time and site.ResultsWe identified 85,124 consecutive screening mammograms across the three sites. Across time intervals, odds of a dense classification decreased at sites exposed to the DL model, site A (adjusted odds ratio [aOR], 0.93; 95% confidence interval [CI], 0.86-0.99; P = .024) and site B (aOR, 0.81 [95% CI, 0.70-0.93]; P = .003), and odds increased at the site unexposed to the model (site C) (aOR, 1.13 [95% CI, 1.01-1.27]; P = .033).DiscussionA DL model reduces the odds of screening mammograms categorized as dense. Accurate density assessments could help health care systems more appropriately use limited supplemental screening resources and help better inform traditional clinical risk models.     

The Impact of Breast Density Reporting Laws on Women’s Awareness of Density-Associated Risks and Conversations Regarding Supplemental Screening With Providers

Objective

We conducted a national survey to understand the impact of state-level density reporting laws on women’s level of density risk awareness and their engagement in conversations with providers regarding supplemental screening.

Comparison of Breast Density Between Synthesized Versus Standard Digital Mammography

PurposeTo evaluate perceptual difference in breast density classification using synthesized mammography (SM) compared with standard or full-field digital mammography (FFDM) for screening.Materials and MethodsThis institutional review board–approved, retrospective, multireader study evaluated breast density on 200 patients who underwent baseline screening mammogram during which both SM and FFDM were obtained contemporaneously from June 1, 2016, through November 30, 2016. Qualitative breast density was independently assigned by seven readers initially evaluating FFDM alone. Then, in a separate session, these same readers assigned breast density using synthetic views alone on the same 200 patients. The readers were again blinded to each other’s assignment. Qualitative density assessment was based on BI-RADS fifth edition. Interreader agreement was evaluated with κ statistic using 95% confidence intervals. Testing for homogeneity in paired proportions was performed using McNemar’s test with a level of significance of .05.ResultsFor patients across the SM and standard 2-D data set, diagnostic testing with McNemar’s test with P = 0.32 demonstrates that the minimal density transitions across FFDM and SM are not statistically significant density shifts. Taking clinical significance into account, only 8 of 200 (4%) patients had clinically significant transition (dense versus not dense). There was substantial interreader agreement with overall κ in FFDM of 0.71 (minimum 0.53, maximum 0.81) and overall SM κ average of 0.63 (minimum 0.56, maximum 0.87).ConclusionOverall subjective breast density assignment by radiologists on SM is similar to density assignment on standard 2-D mammogram.     

Staying abreast of imaging – Current status of breast cancer detection in high density breast

ObjectivesThe aim of this paper is to illustrate the current status of imaging in high breast density as we enter a new decade of advancing medicine and technology to diagnose breast lesions.Key findingsEarly detection of breast cancer has become the chief focus of research from governments to individuals. However, with varying breast densities across the globe, the explosion of breast density information related to imaging, phenotypes, diet, computer aided diagnosis and artificial intelligence has witnessed a dramatic shift in new screening recommendations in mammography, physical examination, screening younger women and women with comorbid conditions, screening women at high risk, and new screening technologies. Breast density is well known to be a risk factor in patients with suspected/known breast neoplasia. Extensive research in the field of qualitative and quantitative analysis on different tissue characteristics of the breast has rapidly become the chief focus of breast imaging. A summary of the available guidelines and modalities of breast imaging, as well as new emerging techniques under study that can potentially provide an augmentation or even a replacement of those currently available.ConclusionDespite all the advances in technology and all the research directed towards breast cancer, detection of breast cancer in dense breasts remains a dilemma.Implications for practiceIt is of utmost importance to develop highly sensitive screening modalities for early detection of breast cancer.     

Primary Care Providers Underutilize Breast Screening MRI for High-Risk Women

ObjectiveSupplemental MRI screening for women at high risk for breast cancer is underutilized. Our study assessed how primary care providers in our healthcare network identify high-risk women and recommend high-risk screening breast MRI.MethodsAn electronic survey was distributed to providers in OB/GYN, family, and internal medicine departments between 1/14/19 and 3/22/19. The survey inquired about methods used to assess breast cancer risk, familiarity with the American Cancer Society's definition of high-risk, and whether screening breast MRI is recommended for high-risk women.ResultsResponse rate was 17% (89/524). After excluding providers who ordered ≤10 mammograms per year, the study included 75 respondents, who mostly ordered 10-1000 mammograms per year and supported annual/biennial screening mammogram starting at age 40-50 years. More providers reported estimating breast cancer risk qualitatively (with family, clinical history, and/or breast density) than quantitatively with risk calculators (73/75, 97% vs 22/75, 29%). A minority of providers (23/75, 31%) correctly defined high lifetime risk. Only 9/75 (12%) providers recommended screening MRI for high-risk women. Use of quantitative risk calculators or ability to correctly define high-risk were not associated with likelihood of recommending MRI screening. More providers had recommended MRI for screening in the setting of dense breasts than for high-risk screening (23/75, 31% vs 9/75, 12%).ConclusionPrimary care providers at our institution did not routinely recommend screening MRI for high-risk women. Risk assessment and reporting at the time of mammography may improve MRI utilization and is an opportunity for radiologists to add value and directly participate in patient-centered care.     

Effect of Training on Qualitative Mammographic Density Assessment

PurposeThe aim of this study was to evaluate the accuracy of visual mammographic breast density assessment and determine if training can improve this assessment, to compare the accuracy of qualitative density assessment before and after training with a quantitative assessment tool, and to evaluate agreement between qualitative and quantitative density assessment methods.MethodsConsecutive screening mammograms performed over a 4-month period were visually assessed by two study breast radiologists (the leads), who selected 200 cases equally distributed among the four BI-RADS density categories. These 200 cases were shown to 20 other breast radiologists (the readers) before and after viewing a training module on visual density assessment. Agreement between reader assessment and lead radiologist assessment was calculated for both reading sessions. Quantitative volumetric density of the 200 mammograms, determined using a commercially available tool, was compared with both sets of reader assessment and with lead radiologist assessment.ResultsCompared with lead radiologist assessment, reader accuracy of breast density assessment increased from 65% before training to 72% after training (odds ratio, 1.41; P < .0001). Training specifically improved assignment to BI-RADS categories 1 (P < .0001) and 4 (P < .10). Compared with quantitative assessment, reader accuracy showed statistically nonsignificant improvement with training (odds ratio, 1.1; P = .26). Substantial agreement between qualitative and quantitative breast density assessment was demonstrated (κ = 0.78).ConclusionsTraining may improve the accuracy of mammographic breast density assessment. Substantial agreement between qualitative and quantitative breast density assessment exists.     

CTLM as an adjunct to mammography in the diagnosis of patients with dense breast

PurposeThe purpose was to evaluate the utility of computed tomographic laser mammography (CTLM) as an adjunct examination to mammography in women with dense breast tissue.MethodsWe retrospectively compared the findings of mammography, CTLM, and adjunct CTLM to mammography with pathology of 155 women scheduled for biopsy or surgery.ResultsPositive lesions were observed more significantly in malignant than benign lesions. The sensitivity of mammography vs. mammography+CTLM was 34.4% vs. 81.57% among extremely dense breasts and 68.29% vs. 95.34% among heterogeneously dense breasts.ConclusionCTLM could distinguish benign lesions from malignant lesions and is not affected by breast density.     

Preoperative breast MR imaging in newly diagnosed breast cancer: Comparison of outcomes based on mammographic modality,breast density and breast parenchymal enhancement

PurposeTo compare the role of MR for assessment of extent of disease in women newly diagnosed with breast cancer imaged with digital mammography (DM) alone versus digital breast tomosynthesis (DBT).MethodsRetrospective review was conducted of 401 consecutive breast MR exams (10/1/2013–7/31/2015) from women who underwent preoperative MR for newly diagnosed breast cancer by either DM or DBT, leaving 388 exams (201 DM and 187 DBT). MR detection of additional, otherwise occult, disease was stratified by modality, breast density, and background parenchymal enhancement. A true-positive finding was defined as malignancy in the ipsilateral-breast >2 cm away from the index-lesion or in the contralateral breast.Results50 additional malignancies were detected in 388 exams (12.9%), 37 ipsilateral and 13 contralateral. There was no difference in the MR detection of additional disease in women imaged by either DM versus DBT (p = 0.53). In patients with DM, there was no significant difference in the rate of MR additional cancer detection in dense versus non-dense breasts (p = 0.790). However, in patients with DBT, MR detected significantly more additional sites of malignancy in dense compared to non-dense breasts (p = 0.017). There was no difference in false-positive MR exams (p = 0.470) for DM versus DBT. For both DM and DBT cohorts, higher MR background parenchymal enhancement was associated with higher false-positive (p = 0.040) but no significant difference in true-positive exams.ConclusionsAmong patients with DBT imaging at cancer diagnosis, women with dense breasts appear to benefit more from preoperative MR than non-dense women. In women imaged only with DM, MR finds additional malignancy across all breast densities.     

Comparison of the performance of screening mammography,physical examination,and breast US and evaluation of factors that influence them: an analysis of 27,825 patient evaluations

PURPOSE: To (a) determine the performance of screening mammography, ultrasonography (US), and physical examination (PE); (b) analyze the influence of age, hormonal status, and breast density; (c) compare the size and stage of tumors detected with each modality; and (d) determine which modality or combination of modalities optimize cancer detection. MATERIALS AND METHODS: A total of 11,130 asymptomatic women underwent 27,825 screening sessions, (mammography and subsequent PE). Women with dense breasts subsequently underwent screening US. Abnormalities were deemed positive if biopsy findings revealed malignancy and negative if findings from biopsy or all screening examinations were negative. RESULTS: In 221 women, 246 cancers were found. Sensitivity, specificity, negative and positive predictive values, and accuracy of mammography were 77.6%, 98.8%, 99.8%, 35.8%, and 98.6%, respectively; those of PE, 27.6%, 99.4%, 99.4%, 28.9%, and 98.8%, respectively; and those of US, 75.3%, 96.8%, 99.7%, 20.5%, and 96.6%, respectively. Screening breast US increased the number of women diagnosed with nonpalpable invasive cancers by 42% (30 of 71). Mammographic sensitivity declined significantly with increasing breast density (P <.01) (48% for the densest breasts) and in younger women with dense breasts (P =.02); the effects were independent. Mammography and US together had significantly higher sensitivity (97%) than did mammography and PE together (74%) (P <.001). Tumors detected at mammography and/or US were significantly smaller (P =.01) and of lower stage (P =.01) than those detected at PE. CONCLUSION: Mammographic sensitivity for breast cancer declines significantly with increasing breast density and is independently higher in older women with dense breasts. Addition of screening US significantly increases detection of small cancers and depicts significantly more cancers and at smaller size and lower stage than does PE, which detects independently extremely few cancers. Hormonal status has no significant effect on effectiveness of screening independent of breast density.     

Breast Density Awareness,Knowledge, and Attitudes Among US Women: National Survey Results Across 5 Years

PurposeTo assess changes in breast density (BD) awareness, knowledge, and attitudes among US women over a period of 5 years.MethodsUsing a probability-based web panel representative of the US population, we administered an identical BD survey in 2012 and 2017 to women aged 40 to 74 years.ResultsIn 2017, 65.8% had heard of BD (versus 57.5% in 2012; P = .0002). BD awareness in both 2012 and 2017 was significantly associated with race, income, and education. Among women aware of BD in 2017, 76.5% had knowledge of BD’s relationship to masking (versus 71.5% in 2012; P = .04); 65.5% had knowledge of BD’s relationship to cancer risk (versus 58.5%; P = .009); and 47.3% had discussed BD with a provider (versus 43.1% in 2012; P = .13). After multivariable adjustment, residence in a state with BD legislation was associated in 2017 with knowledge of BD’s relationship to risk but not to masking. Most women wanted to know their BD (62.5% in 2017 versus 59.8% in 2012; P = .46); this information was anticipated to cause anxiety in 44.8% (versus 44.9% in 2012; P = .96); confusion in 35.9% (versus 43.0%; P = .002); and feeling informed in 89.7% (versus 90.4%; P = .64). Over three-quarters supported federal BD legislation in both surveys. Response rate to the 2017 survey was 55% (1,502 of 2,730) versus 65% (1,506 of 2,311) in 2012.ConclusionAlthough BD awareness has increased, important disparities persist. Knowledge of BD’s impact on risk has increased; knowledge about masking and BD discussions with providers have not. Most women want to know their BD, would not feel anxious or confused as a result of knowing, and would feel empowered to make decisions. The federal BD notification legislation presents an opportunity to improve awareness and knowledge and encourage BD conversations with providers.     

The incremental contribution of clinical breast examination to invasive cancer detection in a mammography screening program

OBJECTIVE: The objective of this study was to determine the potential added contribution of clinical breast examination (CBE) to invasive breast cancer detection in a mammography screening program, by categories of age and breast density. SUBJECTS AND METHODS: We prospectively followed 61,688 women aged 40 years or older who had undergone at least one screening examination with mammography and CBE between January 1, 1996, and December 31, 2000, for 1 year after their mammogram for invasive cancer. We computed the incremental sensitivity, specificity, and positive predictive value of CBE over mammography alone for combinations of age and breast density (predominantly fatty or dense). RESULTS: Mammography sensitivity was 78% and combined mammography-CBE sensitivity was 82%, thus CBE detected an additional 4% of invasive cancers. CBE detected a minority of invasive cancers compared with mammography for all age groups and all breast densities. Sensitivity increased from adding CBE to screening mammography for all ages, from 6.8% in women ages 50-59 with dense breasts to 1.8% in women ages 60-69 years with fatty breasts. CBE generally added incrementally more to sensitivity among women with dense breasts. Specificity and positive predictive value declined when CBE was used in conjunction with mammography, and this decrement was more pronounced in women with dense breasts. CONCLUSION: CBE had modest incremental benefit to invasive cancer detection over mammography alone in a screening program, but also led to greater risk of false-positive results. These risks and benefits were greater in women with dense breasts. The balance of risks and benefits must be weighed carefully when evaluating the inclusion of CBE in a screening examination.     

Recall rate of screening ultrasound with automated breast volumetric scanning (ABVS) in women with dense breasts: a first quarter experience

PurposeThe aim of this study was to determine the recall rate of screening ultrasound with automated breast volumetric scanning (ABVS) in women with dense breasts (BI-RADS density classification 3 or 4 on mammogram).Materials and MethodsIn this retrospective cohort study, at the end of the “first quarter” (August–October 2013) of use, our practice database was searched for all ABVS examinations performed and specifically, the positive examinations (defined as abnormal/BI-RADS 0) for which patients were recalled for additional imaging evaluation with handheld ultrasound (HHUS); the latter group was reviewed with respect to final BI-RADS and pathology if relevant.ResultsDuring the 3-month study time period, 558 ABVS studies were performed: 453 (81%) were initially BI-RADS 1 or 2 and 105 (19%) were BI-RADS 0-incomplete and recalled, corresponding with an overall recall rate of 19%; specifically, the recall rate trended down from 24.7% in August to 12.6% in October. To date, 98 of the 105 recalled women have returned for HHUS, with the resultant final BI-RADS as follows: 25/98=25% BI-RADS 1, 46/98=47% BI-RADS 2, 13/98=13% BI-RADS 3, 14/98=15% BI-RADS 4, and 0/98=0% BI-RADS 5. All biopsies performed to date of the ABVS-detected BI-RADS 4 lesions have yielded benign results, with the most common pathology being fibroadenoma.ConclusionThe recall rate of screening ABVS in women with dense breasts at our institution was under 20% overall during its first quarter of use, and trended down from nearly 25% in the first month to under 13% in the third. The clinical implication is that ABVS does have a learning curve, but that is a potentially feasible way to meet the increasing demands for screening ultrasound in women with dense breasts.     

Multi-Institutional Assessment and Crowdsourcing Evaluation of Deep Learning for Automated Classification of Breast Density

ObjectiveWe developed deep learning algorithms to automatically assess BI-RADS breast density.MethodsUsing a large multi-institution patient cohort of 108,230 digital screening mammograms from the Digital Mammographic Imaging Screening Trial, we investigated the effect of data, model, and training parameters on overall model performance and provided crowdsourcing evaluation from the attendees of the ACR 2019 Annual Meeting.ResultsOur best-performing algorithm achieved good agreement with radiologists who were qualified interpreters of mammograms, with a four-class κ of 0.667. When training was performed with randomly sampled images from the data set versus sampling equal number of images from each density category, the model predictions were biased away from the low-prevalence categories such as extremely dense breasts. The net result was an increase in sensitivity and a decrease in specificity for predicting dense breasts for equal class compared with random sampling. We also found that the performance of the model degrades when we evaluate on digital mammography data formats that differ from the one that we trained on, emphasizing the importance of multi-institutional training sets. Lastly, we showed that crowdsourced annotations, including those from attendees who routinely read mammograms, had higher agreement with our algorithm than with the original interpreting radiologists.ConclusionWe demonstrated the possible parameters that can influence the performance of the model and how crowdsourcing can be used for evaluation. This study was performed in tandem with the development of the ACR AI-LAB, a platform for democratizing artificial intelligence.     

Digital breast tomosynthesis: sensitivity for cancer in younger symptomatic women

Objective:Full-field digital mammography (FFDM) has limited sensitivity for cancer in younger women with denser breasts. Digital breast tomosynthesis (DBT) can reduce the risk of cancer being obscured by overlying tissue. The primary study aim was to compare the sensitivity of FFDM, DBT and FFDM-plus-DBT in women under 60 years old with clinical suspicion of breast cancer.Methods:This multicentre study recruited 446 patients from UK breast clinics. Participants underwent both standard FFDM and DBT. A blinded retrospective multireader study involving 12 readers and 300 mammograms (152 malignant and 148 benign cases) was conducted.Results:Sensitivity for cancer was 86.6% with FFDM [95% CI (85.2–88.0%)], 89.1% with DBT [95% CI (88.2–90%)], and 91.7% with FFDM+DBT [95% CI (90.7–92.6%)]. In the densest breasts, the maximum sensitivity increment with FFDM +DBT over FFDM alone was 10.3%, varying by density measurement method. Overall specificity was 81.4% with FFDM [95% CI (80.5–82.3%)], 84.6% with DBT [95% CI (83.9–85.3%)], and 79.6% with FFDM +DBT [95% CI (79.0–80.2%)]. No differences were detected in accuracy of tumour measurement in unifocal cases.Conclusions:Where available, DBT merits first-line use in the under 60 age group in symptomatic breast clinics, particularly in women known to have very dense breasts.Advances in knowledge:This study is one of very few to address the accuracy of DBT in symptomatic rather than screening patients. It quantifies the diagnostic gains of DBT in direct comparison with standard digital mammography, supporting informed decisions on appropriate use of DBT in this population.     

Mammographic Density Estimation with Automated Volumetric Breast Density Measurement

Objective

To compare automated volumetric breast density measurement (VBDM) with radiologists'' evaluations based on the Breast Imaging Reporting and Data System (BI-RADS), and to identify the factors associated with technical failure of VBDM.

Materials and Methods

In this study, 1129 women aged 19-82 years who underwent mammography from December 2011 to January 2012 were included. Breast density evaluations by radiologists based on BI-RADS and by VBDM (Volpara Version 1.5.1) were compared. The agreement in interpreting breast density between radiologists and VBDM was determined based on four density grades (D1, D2, D3, and D4) and a binary classification of fatty (D1-2) vs. dense (D3-4) breast using kappa statistics. The association between technical failure of VBDM and patient age, total breast volume, fibroglandular tissue volume, history of partial mastectomy, the frequency of mass > 3 cm, and breast density was analyzed.

Results

The agreement between breast density evaluations by radiologists and VBDM was fair (k value = 0.26) when the four density grades (D1/D2/D3/D4) were used and moderate (k value = 0.47) for the binary classification (D1-2/D3-4). Twenty-seven women (2.4%) showed failure of VBDM. Small total breast volume, history of partial mastectomy, and high breast density were significantly associated with technical failure of VBDM (p = 0.001 to 0.015).

Conclusion

There is fair or moderate agreement in breast density evaluation between radiologists and VBDM. Technical failure of VBDM may be related to small total breast volume, a history of partial mastectomy, and high breast density.     

Breast Density Notification Letters and Websites: Are They Too “Dense”?

PurposeTo evaluate grade-level readability of dense breast notification letters (DBNs) and popular websites.MethodsHIPAA-compliant, institutional review board–exempt study. As of April 2018, letter characteristics and grade-level readability were evaluated from states with mandated text using five readability metrics, one of which was the Flesch-Kincaid Grade Level. For states that had mandated DBNs in 2016, the 2016 data were compared with 2018. Readability was also assessed for common websites about dense breasts.ResultsThirty states had mandated text for DBNs. All were written above a Flesch-Kincaid sixth-grade level. Eight state DBNs were around or below a Flesch-Kincaid eighth-grade level. Connecticut was the highest (19.4) and Alabama and New York lowest (both at 7.2). For all states, the mean readability score using the five metrics exceeded an eighth-grade level. Of states that had updated DBNs since 2016, only one state significantly improved readability (Missouri 13.1 to 8.5). All DBNs discussed that breast density may mask cancer on a mammogram, 20 discussed the association with increased risk of breast cancer, and 23 discussed supplemental screening. For websites, the range of Flesch-Kincaid grade-level readability was 6 to 11.3. The lowest was the American Cancer Society dense breast website (6.0) followed by ACR dense breast patient pamphlet (7.2).ConclusionAs of 2018, the mean readability score using five metrics for all state-mandated DBNs exceeded an eighth-grade reading level. Compared with 2016, only one state significantly decreased DBN grade-level readability. Publicly available websites performed relatively better.