Breast density: clinical implications and assessment methods

Physical Activity and Mammographic Density in Japanese Women

BACKGROUND

Dense breast is one of the strong risk factors for breast cancer among women. While it has been established that physical activity is associated with decreased risk for breast cancer, results have been inconsistent in terms of mammographic density. Thus, we examined physical activity in relation to mammographic density among Japanese women in Tokyo.

METHODS

We used 123,026 records from 33,698 Japanese women without a history of breast cancer who got mammograms at St. Luke's International Hospital in Tokyo, Japan from 2004 to 2019. Mammographic density was classified according to the Breast Imaging Reporting and Data System (BI-RADS), and women self-reported their physical activity level over the past year. ORs were estimated using logistic generalized estimating equations after adjusting for age, body mass index, menopausal status, parity, family history of breast or ovarian cancer, hormone therapy use, smoking status, alcohol consumption, and year.

RESULTS

We observed inverse associations of physical activity with dense breasts. Adjusted ORs were 0.96 (95% confidence interval: 0.91-1.00) for women with physical exercise for 1-2 days per week, 0.94 (0.88-0.99) for those with physical exercise for 3-5 days per week, and 0.91 (0.84-0.99) for those with daily physical exercise when compared with those reported seldom physical exercise.

CONCLUSIONS

Higher levels of physical activity may be associated with decreased mammographic density levels in Japanese women.

IMPACT

Increasing physical activity may serve as a reasonable intervention to reduce mammographic density, and thereby, to mitigate the risk of breast cancer in Asian women.

Pathological macroscopic evaluation of breast density versus mammographic breast density in breast cancer conserving surgery

Correlation between imaging and anatomopathological breast density has been superficially explored and is heterogeneous in current medical literature. It is possible that mammographic and pathological findings are divergent. The aim of this study is to evaluate the association between breast density classified by mammography and breast density of pathological macroscopic examination in specimens of breast cancer conservative surgeries. Post-hoc, exploratory analysis of a prospective randomized clinical trial of patients with breast cancer candidates for breast conservative surgery. Breast mammographic density (MD) was analyzed according to ACR BI-RADS® criteria, and pathologic macroscopic evaluation of breast density (PMBD) was estimated by visually calculating the ratio between stromal and fatty tissue. From 412 patients, MD was A in 291 (70,6%), B in 80 (19,4%) B, C in 35 (8,5%), and D in 6 (1,5%). Ninety-nine percent (201/203) of patients classified as A+B in MD were correspondently classified in PMBD. Conversely, only 18.7% (39/209) of patients with MD C+D were classified correspondently in PMBD (p < 0.001). Binary logistic regression showed age (OR 1.06, 1.01-1.12 95% CI, p 0.013) and nulliparity (OR 0.39, 0.17-0.96 95% CI, p 0.039) as predictors of A+B PMBD.

Conclusion

Mammographic and pathologic macroscopic breast density showed no association in our study for breast C or D in breast image. The fatty breast was associated with older patients and the nulliparity decreases the chance of fatty breasts nearby 60%.

Breast Cancer in Dense Breasts: Detection Challenges and Supplemental Screening Opportunities

Dense breast tissue at mammography is associated with higher breast cancer incidence and mortality rates, which have prompted new considerations for breast cancer screening in women with dense breasts. The authors review the definition and classification of breast density, density assessment methods, breast cancer risk, current legislation, and future efforts and summarize trials and key studies that have affected the existing guidelines for supplemental screening. Cases of breast cancer in dense breasts are presented, highlighting a variety of modalities and specific imaging findings that can aid in cancer detection and staging. Understanding the current state of breast cancer screening in patients with dense breasts and its challenges is important to shape future considerations for care. Shifting the paradigm of breast cancer detection toward early diagnosis for women with dense breasts may be the answer to reducing the number of deaths from this common disease. ©RSNA, 2023 Online supplemental material is available for this article. Quiz questions for this article are available through the Online Learning Center. See the invited commentary by Yeh in this issue.

Advances in PET/CT Imaging for Breast Cancer

One out of eight women will be affected by breast cancer during her lifetime. Imaging plays a key role in breast cancer detection and management, providing physicians with information about tumor location, heterogeneity, and dissemination. In this review, we describe the latest advances in PET/CT imaging of breast cancer, including novel applications of 18F-FDG PET/CT and the development and testing of new agents for primary and metastatic breast tumor imaging and therapy. Ultimately, these radiopharmaceuticals may guide personalized approaches to optimize treatment based on the patient's specific tumor profile, and may become a new standard of care. In addition, they may enhance the assessment of treatment efficacy and lead to improved outcomes for patients with a breast cancer diagnosis.

International Interobserver Variability of Breast Density Assessment

PURPOSE

The aim of this study was to determine variability in visually assessed mammographic breast density categorization among radiologists practicing in Indonesia, the Netherlands, South Africa, and the United States.

METHODS

Two hundred consecutive 2-D full-field digital screening mammograms obtained from September to December 2017 were selected and retrospectively reviewed from four global locations, for a total of 800 mammograms. Three breast radiologists in each location (team) provided consensus density assessments of all 800 mammograms using BI-RADS® density categorization. Interreader agreement was compared using Gwet's AC2 with quadratic weighting across all four density categories and Gwet's AC1 for binary comparison of combined not dense versus dense categories. Variability of distribution among teams was calculated using the Stuart-Maxwell test of marginal homogeneity across all four categories and using the McNemar test for not dense versus dense categories. To compare readers from a particular country on their own 200 mammograms versus the other three teams, density distribution was calculated using conditional logistic regression.

RESULTS

For all 800 mammograms, interreader weighted agreement for distribution among four density categories was 0.86 (Gwet's AC2 with quadratic weighting; 95% confidence interval, 0.85-0.88), and for not dense versus dense categories, it was 0.66 (Gwet's AC1; 95% confidence interval, 0.63-0.70). Density distribution across four density categories was significantly different when teams were compared with one another and one team versus the other three teams combined (P < .001). Overall, all readers placed the largest number of mammograms in the scattered and heterogeneous categories.

CONCLUSIONS

Although reader teams from four different global locations had almost perfect interreader agreement in BI-RADS density categorization, variability in density distribution across four categories remained statistically significant.

Breast Density Evaluation According to BI-RADS 5th Edition on Digital Breast Tomosynthesis: AI Automated Assessment Versus Human Visual Assessment

Background: The assessment of breast density is one of the main goals of radiologists because the masking effect of dense fibroglandular tissue may affect the mammographic identification of lesions. The BI-RADS 5th Edition has revised the mammographic breast density categories, focusing on a qualitative evaluation rather than a quantitative one. Our purpose is to compare the concordance of the automatic classification of breast density with the visual assessment according to the latest available classification. Methods: A sample of 1075 digital breast tomosynthesis images from women aged between 40 and 86 years (58 ± 7.1) was retrospectively analyzed by three independent readers according to the BI-RADS 5th Edition. Automated breast density assessment was performed on digital breast tomosynthesis images with the Quantra software version 2.2.3. Interobserver agreement was assessed with kappa statistics. The distributions of breast density categories were compared and correlated with age. Results: The agreement on breast density categories was substantial to almost perfect between radiologists (κ = 0.63–0.83), moderate to substantial between radiologists and the Quantra software (κ = 0.44–0.78), and the consensus of radiologists and the Quantra software (κ = 0.60–0.77). Comparing the assessment for dense and non-dense breasts, the agreement was almost perfect in the screening age range without a statistically significant difference between concordant and discordant cases when compared by age. Conclusions: The categorization proposed by the Quantra software has shown a good agreement with the radiological evaluations, even though it did not completely reflect the visual assessment. Thus, clinical decisions regarding supplemental screening should be based on the radiologist’s perceived masking effect rather than the data produced exclusively by the Quantra software.

Multicenter, Multivendor Validation of an FDA-approved Algorithm for Mammography Triage

OBJECTIVE

Artificial intelligence (AI)-based triage algorithms may improve cancer detection and expedite radiologist workflow. To this end, the performance of a commercial AI-based triage algorithm on screening mammograms was evaluated across breast densities and lesion types.

METHODS

This retrospective, IRB-exempt, multicenter, multivendor study examined 1255 screening 4-view mammograms (400 positive and 855 negative studies). Images were anonymized by providing institutions and analyzed by a commercially available AI algorithm (cmTriage, CureMetrix, La Jolla, CA) that performed retrospective triage at the study level by flagging exams as "suspicious" or not. Sensitivities and specificities with confidence intervals were derived from area under the curve (AUC) calculations.

RESULTS

The algorithm demonstrated an AUC of 0.95 (95% CI: 0.94-0.96) for case identification. Area under the curve held across densities (0.95) and lesion types (masses: 0.94 [95% CI: 0.92-0.96] or microcalcifications: 0.97 [95% CI: 0.96-0.99]). The algorithm has a default sensitivity of 93% (95% CI: 95.6%-90.5%) with specificity of 76.3% (95% CI: 79.2%-73.4%). To evaluate real-world performance, a sensitivity of 86.9% (95% CI: 83.6%-90.2%) was tested, as observed for practicing radiologists by the Breast Cancer Surveillance Consortium (BCSC) study. The resulting specificity was 88.5% (95% CI: 86.4%-90.7%), similar to the BCSC specificity of 88.9%, indicating performance comparable to real-world results.

CONCLUSION

When tested for lesion detection, an AI-based triage software can perform at the level of practicing radiologists. Drawing attention to suspicious exams may improve reader specificity and help streamline radiologist workflow, enabling faster turnaround times and improving care.

Combining the strengths of radiologists and AI for breast cancer screening: a retrospective analysis

BACKGROUND

We propose a decision-referral approach for integrating artificial intelligence (AI) into the breast-cancer screening pathway, whereby the algorithm makes predictions on the basis of its quantification of uncertainty. Algorithmic assessments with high certainty are done automatically, whereas assessments with lower certainty are referred to the radiologist. This two-part AI system can triage normal mammography exams and provide post-hoc cancer detection to maintain a high degree of sensitivity. This study aimed to evaluate the performance of this AI system on sensitivity and specificity when used either as a standalone system or within a decision-referral approach, compared with the original radiologist decision.

METHODS

We used a retrospective dataset consisting of 1 193 197 full-field, digital mammography studies carried out between Jan 1, 2007, and Dec 31, 2020, from eight screening sites participating in the German national breast-cancer screening programme. We derived an internal-test dataset from six screening sites (1670 screen-detected cancers and 19 997 normal mammography exams), and an external-test dataset of breast cancer screening exams (2793 screen-detected cancers and 80 058 normal exams) from two additional screening sites to evaluate the performance of an AI algorithm on sensitivity and specificity when used either as a standalone system or within a decision-referral approach, compared with the original individual radiologist decision at the point-of-screen reading ahead of the consensus conference. Different configurations of the AI algorithm were evaluated. To account for the enrichment of the datasets caused by oversampling cancer cases, weights were applied to reflect the actual distribution of study types in the screening programme. Triaging performance was evaluated as the rate of exams correctly identified as normal. Sensitivity across clinically relevant subgroups, screening sites, and device manufacturers was compared between standalone AI, the radiologist, and decision referral. We present receiver operating characteristic (ROC) curves and area under the ROC (AUROC) to evaluate AI-system performance over its entire operating range. Comparison with radiologists and subgroup analysis was based on sensitivity and specificity at clinically relevant configurations.

FINDINGS

The exemplary configuration of the AI system in standalone mode achieved a sensitivity of 84·2% (95% CI 82·4-85·8) and a specificity of 89·5% (89·0-89·9) on internal-test data, and a sensitivity of 84·6% (83·3-85·9) and a specificity of 91·3% (91·1-91·5) on external-test data, but was less accurate than the average unaided radiologist. By contrast, the simulated decision-referral approach significantly improved upon radiologist sensitivity by 2·6 percentage points and specificity by 1·0 percentage points, corresponding to a triaging performance at 63·0% on the external dataset; the AUROC was 0·982 (95% CI 0·978-0·986) on the subset of studies assessed by AI, surpassing radiologist performance. The decision-referral approach also yielded significant increases in sensitivity for a number of clinically relevant subgroups, including subgroups of small lesion sizes and invasive carcinomas. Sensitivity of the decision-referral approach was consistent across the eight included screening sites and three device manufacturers.

INTERPRETATION

The decision-referral approach leverages the strengths of both the radiologist and AI, demonstrating improvements in sensitivity and specificity surpassing that of the individual radiologist and of the standalone AI system. This approach has the potential to improve the screening accuracy of radiologists, is adaptive to the requirements of screening, and could allow for the reduction of workload ahead of the consensus conference, without discarding the generalised knowledge of radiologists.

FUNDING

Vara.

Obesity and breast cancer: Preventive and therapeutic possibilities for bariatric surgery

Breast cancer is the most common and second deadliest malignancy in women. With rising obesity rates and building evidence for a strong association with obesity, the incidence of breast cancer can be expected to increase. Weight loss reduces breast cancer risk, the mechanisms of which are still poorly understood. As an effective therapy for obesity, bariatric surgery may be a powerful tool in breast cancer prevention and treatment. This review details the potential physiologic mechanisms that may underlie this association, as well as recently published studies that reinforce the link between bariatric surgery and a reduction in incident breast cancer. The use of bariatric surgery as an adjunct therapy in endometrial cancer also raises the potential for similar use in select breast cancer patients. Despite the expanding potential applications of bariatric surgery in this field, publications to date have been strictly observational, highlighting a need for future clinical trials.

Persistent inter-observer variability of breast density assessment using BI-RADS® 5th edition guidelines

OBJECTIVES

Due to most states' legislation, mammographic density categorization has potentially far-reaching implications, but remains subjective based on BIRADS® guidelines. We aimed to determine 1) effect of BI-RADS® 5th edition (5th-ed) vs 4th-edition (4th-ed) guidelines on reader agreement regarding density assessment; 2) 5th-ed vs 4th-ed density distribution, and visual vs quantitative assessment agreement; 3) agreement between experienced vs less experienced readers.

METHODS

In a retrospective review, six breast imaging radiologists (BIR) (23-30 years' experience) visually assessed density of 200 screening mammograms performed September 2012-January 2013 using 5th-ed guidelines. Results were compared to 2016 data of the same readers evaluating the same mammograms using 4th-ed guidelines after a training module. 5th-ed density categorization by seven junior BIR (1-5 years' experience) was compared to eight experienced BIR. Nelson et al.'s kappas (κ_m, κ_w), Fleiss' κ_F, and Cohen's κ were calculated. Quantitative density using Volpara was compared with reader assessments.

RESULTS

Inter-reader weighted agreement using 5th-ed is moderately strong, 0.73 (κ_w, s.e. = 0.01), similar to 4th-ed, 0.71 (κ_w, s.e. = 0.03). Intra-reader Cohen's κ is 0.23-0.34, similar to 4th-ed. Binary not-dense vs dense categorization, using 5th-ed results in higher dense categorization vs 4th-ed (p < 0.001). 5th-ed density distribution results in higher numbers in categories B/C vs 4th-ed (p < 0.001). Distribution for 5th-ed does not differ based on reader experience (p = 0.09). Reader vs quantitative weighted agreement is similar (5th-ed, Cohen's κ = 0.76-0.85; 4th-ed, Cohen's κ = 0.68-0.83).

CONCLUSION

There is persistent subjectivity of visually assessed mammographic density using 5th-ed guidelines; experience does not correlate with better inter-reader agreement.

Evaluation of the Value of Multiplex MicroRNA Analysis as a Breast Cancer Screening in Korean Women under 50 Years of Age with a High Proportion of Dense Breasts

This study was conducted to confirm the performance of the microRNA (miRNA) biomarker combination as a new breast cancer screening method in Korean women under the age of 50 with a high percentage of dense breasts. To determine the classification performance of a set of miRNA biomarkers (miR-1246, 202, 21, and 219B) useful for breast cancer screening, we determined whether there was a significant difference between the breast cancer and healthy control groups through box plots and the Mann–Whitney U-test, which was further examined in detail by age group. To verify the classification performance of the 4 miRNA biomarker set, 4 classification methods (logistic regression, random forest, XGBoost, and generalized linear model plus random forest) were applied, and 10-fold cross-validation was used as a validation method to improve performance stability. We confirmed that the best breast cancer detection performance was achievable in patients under 50 years of age when the set of 4 miRNAs were used. Under the age of 50, the 4 miRNA biomarkers showed the highest performance with a sensitivity of 85.29%, specificity of 93.33%, and area under the curve (AUC) of 0.961. Examining the results of 4 miRNA biomarkers was found to be an effective strategy for diagnosing breast cancer in Korean women under 50 years of age with dense breasts, and hence has the potential as a new breast cancer screening tool. Further validation in an appropriate screening population with large-scale clinical trials is required.

Malignancy risk of indeterminate mammographic calcification in symptomatic breast clinics

BACKGROUND

To explore the potential risk factors predicting malignancy in patients with indeterminate incidental mammographic microcalcification and to evaluate the short-term risk of developing malignancy.

METHODS

Between January 2011 and December 2015, one hundred and fifty (150) consecutive patients with indeterminate mammographic microcalcifications who had undergone stereotactic biopsy were evaluated. Clinical and mammographic features were recorded and compared with histopathological biopsy results. In patients with malignancy, postsurgical findings and surgical upgrade, if any, were recorded. Linear regression analysis (SPSS V.25) was used to evaluate significant variables predicting malignancy. OR with 95% CIs was calculated for all variables. All patients were followed up for a maximum of 10 years. The mean age of the patients was 52 years (range 33-79 years).

RESULTS

There were a total of 55 (37%) malignant results in this study cohort. Age was an independent predictor of breast malignancy with an OR (95% CI) of 1.10 (1.03 to 1.16). Mammographic microcalcification size, pleomorphic morphology, multiple clusters and linear/segmental distribution were significantly associated with malignancy with OR (CI) of 1.03 (1.002 to 1.06), 6.06 (2.24 to 16.66), 6.35 (1.44 to 27.90) and 4.66 (1.07 to 20.19). The regional distribution of microcalcification had an OR of 3.09 (0.92 to 10.3), but this was not statistically significant. Patients with previous breast biopsies had a lower risk of breast malignancy than patients with no prior biopsy (p=0.034).

CONCLUSION

Multiple clusters, linear/segmental distribution, pleomorphic morphology, size of mammographic microcalcifications and increasing age were independent predictors of malignancy. Having a previous breast biopsy did not increase malignancy risk.

ACR Appropriateness Criteria® Transgender Breast Cancer Screening

Breast cancer screening recommendations for transgender and gender nonconforming individuals are based on the sex assigned at birth, risk factors, and use of exogenous hormones. Insufficient evidence exists to determine whether transgender people undergoing hormone therapy have an overall lower, average, or higher risk of developing breast cancer compared to birth-sex controls. Furthermore, there are no longitudinal studies evaluating the efficacy of breast cancer screening in the transgender population. In the absence of definitive data, current evidence is based on data extrapolated from cisgender studies and a limited number of cohort studies and case reports published on the transgender community. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

Quantitative breast density measurement based on three-dimensional images: a study on cone-beam breast computed tomography

BACKGROUND

Breast density is an independent predictor of breast cancer risk. Quantitative volumetric breast density (QVBD) is expected to provide more information on the prediction of breast cancer risk.

PURPOSE

To evaluate the reliability of QVBD measurements based on cone-beam breast computed tomography (CBBCT) images.

MATERIAL AND METHODS

A total of 216 breasts were used to evaluate the stability of QVBD measurements based on CBBCT images and the correlations between this volumetric measurement and visual and area-based measurement methods. The intra- and inter-observer consistency of QVBD measurements were compared. Visual breast density (VBD) was evaluated with Breast Imaging Reporting and Data System (BI-RADS) standard on CBBCT images. The correlation between QVBD and VBD was evaluated by Spearman correlation coefficient. Receiver operating characteristic (ROC) curve was used to assess the sensitivity and specificity of the volumetric method in distinguishing dense and non-dense breasts. The correlation between QVBD and quantitative area-based breast density (QABD) was determined with Pearson correlation coefficient. Then, the breast volume measured with CBBCT images was compared with the breast specimen obtained during nipple-sparing mastectomy (NSM) by Pearson correlation coefficient and linear regression.

RESULTS

Excellent intra- and inter-observer consistency was found from QVBD measurements. The volumetric method distinguished dense and non-dense breasts at a cutoff value of 9.5%, with 94.5% sensitivity and 77.1% specificity. Positive correlations were found between QVBD and QABD (r=0.890; P<0.001) and between the volume measured with CBBCT images and Archimedes method (r=0.969; P<0.001).

CONCLUSION

CBBCT images can evaluate breast density reliably on a continuous scale.

The Role of Imaging in Health Screening: Screening for Specific Conditions

There are well-established and emerging screening examinations aimed at identifying malignant and nonmalignant conditions at early, treatable stages. The Radiology Research Alliance's "Role of Imaging in Health Screening" Task Force provides a comprehensive review of specific imaging-based screening examinations. This work reviews and serves as a reference for screening examinations for breast and colon cancer in a healthy population along with screening for lung cancer, hepatocellular carcinoma, and the use of whole body magnetic resonance imaging in at-risk individuals. American College of Radiology scoring systems, along with case-based examples, are included to illustrate the different disease entities. The future of screening is discussed, particularly in the context of artificial intelligence.

Circulating carotenoids and breast cancer among high-risk individuals

BACKGROUND

Carotenoids represent 1 of few modifiable factors to reduce breast cancer risk. Elucidation of interactions between circulating carotenoids and genetic predispositions or mammographic density (MD) may help inform more effective primary preventive strategies in high-risk populations.

OBJECTIVES

We tested whether women at high risk for breast cancer due to genetic predispositions or high MD would experience meaningful and greater risk reduction from higher circulating levels of carotenoids in a nested case-control study in the Nurses' Health Studies (NHS and NHSII).

METHODS

This study included 1919 cases and 1695 controls in a nested case-control study in the NHS and NHSII. We assessed both multiplicative and additive interactions. RR reductions and 95% CIs were calculated using unconditional logistic regressions, adjusting for matching factors and breast cancer risk factors. Absolute risk reductions (ARR) were calculated based on Surveillance, Epidemiology, and End Results incidence rates.

RESULTS

We showed that compared with women at low genetic risk or low MD, those with higher genetic risk scores or high MD had greater ARRs for breast cancer as circulating carotenoid levels increase (additive P-interaction = 0.05). Among women with a high polygenic risk score, those in the highest quartile of circulating carotenoids had a significant ARR (28.6%; 95% CI, 14.8-42.1%) compared to those in the lowest quartile of carotenoids. For women with a high percentage MD (≥50%), circulating carotenoids were associated with a 37.1% ARR (95% CI, 21.7-52.1%) when comparing the highest to the lowest quartiles of circulating carotenoids.

CONCLUSIONS

The inverse associations between circulating carotenoids and breast cancer risk appeared to be more pronounced in high-risk women, as defined by germline genetic makeup or MD.

The mammographic breast density distribution of Finnish women with breast cancer and comparison of breast density reporting using the 4th and 5th editions of the Breast Imaging-Reporting and Data System

PURPOSE

To examine the breast density distribution in patients diagnosed with breast cancer in an eastern Finnish population and to examine the changes in breast density reporting patterns between the 4^th and 5^th editions of the Breast Imaging-Reporting and Data System (BI-RADS).

METHOD

821 women (mean age 62.8 ± 12.2 years, range 28-94 years) with breast cancer were included in this retrospective study and their digital mammographic examinations were assessed semi-automatically and then visually by two radiologists in accordance with the 4^th and 5^th editions of the BI-RADS. Intraclass correlation coefficients (ICCs) were used to evaluate interobserver reproducibility. Chi-square tests were used to examine the associations between the breast density distribution and age or body mass index (BMI).

RESULTS

Interobserver reproducibility of the visual assessment was excellent, with an ICCr = 0.93. The majority of breast cancers occurred in fatty breasts (93.8 %) when density was assessed according to the 4^th edition of the BI-RADS. The distributions remained constant after correction for age and BMI. Using the 5^th edition, there was an overall 50.2 % decrease in almost entirely fatty (p <  0.001), 19.4 % increase in scattered fibroglandular (p <  0.001), 28.7 % increase in heterogeneously dense (p <  0.001), and 2.1 % increase in extremely dense (p <  0.001) categories.

CONCLUSIONS

Most breast cancers in eastern Finland occur in fatty breasts with an area density of < 50 %. Assessing breast density using the 5^th edition of the BI-RADS greatly increased denser assessments.

Routine use of both mammography and MRI surveillance in patients with previous 'mammogram occult' breast cancer: experience from a tertiary centre

BACKGROUND

To evaluate the role of combined MRI and mammogram follow-up in patients with previous 'mammographically occult' breast cancer.

METHODS

Between 2011 and 2016, examinations of all patients undergoing routine surveillance following previous 'mammogram occult' breast cancer were evaluated. Patients had both MRI and mammograms on the same day with an interval of 12-18 months between consecutive pairs. Total number of recalls on both imaging modalities and the outcome of those recalls was recorded. There were six median examinations per patient.

RESULTS

There were a total of 325 examinations of 54 patients. There were 96 mammograms/MRI pairs and 87 lone MRI and 46 lone mammograms. There were a total of 26 recalls in 21 patients. MRI had specificity (95% CI) of 89.99 (85.67 to 93.11) compared to mammograms 96.27 (92.53 to 98.25). The diagnostic OR with 95% CI was 19.40 (3.70 to 101.57) vs 6.72 (1.43 to 31.58) of mammograms and MRI, respectively. Three of seven cancers presented symptomatically.

CONCLUSIONS

MRI surveillance leads to higher recalls and false positives compared to mammograms in this specific subgroup of high-risk patients. Large proportion of cancers presented symptomatically, stressing the importance of remaining vigilant of breast symptoms despite imaging surveillance.

Evaluation of automated volumetric breast density software in comparison with visual assessments in an Asian population: A retrospective observational study

This study aims to compare Quantra, as an automated volumetric breast density (Vbd) tool, with visual assessment according to ACR BI-RADS density categories and to determine its potential usage in clinical practice.Five hundred randomly selected screening and diagnostic mammograms were included in this retrospective study. Three radiologists independently assigned qualitative ACR BI-RADS density categories to the mammograms. Quantra automatically calculates the volumetric density data into the system. The readers were blinded to the Quantra and other readers assessment. Inter-reader agreement and agreement between Quantra and each reader were tested. Region under the curve (ROC) analysis was performed to obtain the cut-off value to separate dense from a non-dense breast. Results with P value <.05 was taken as significant.There were 40.4% Chinese, 27% Malays, 19% Indian and 3.6% represent other ethnicities. The mean age of the patients was 57. 15%, 45.6%, 30.4%, and 9% of patients fall under BI-RADS A, B, C and D density category respectively. Fair agreement with Kappa (κ) value: 0.49, 0.38, and 0.30 were seen for Reader 1, 2 and 3 versus Quantra. Moderate agreement with κ value: 0.63, 0.64, 0.51 was seen when the data were dichotomized (density A and B to "non-dense", C and D to "dense"). The cut-off Vbd value was 13.5% to stratify dense from non-dense breasts with a sensitivity of 86.2% and specificity of 83.1% (AUC 91.4%; confidence interval: 88.8, 94.1).Quantra showed moderate agreement with radiologists visual assessment. Hence, this study adds to the available evidence to support the potential use of Quantra as an adjunct tool for breast density assessment in routine clinical practice in the Asian population. We found 13.5% is the best cut-off value to stratify dense to non-dense breasts in our study population. Its application will provide an objective, consistent and reproducible results as well as aiding clinical decision-making on the need for supplementary breast ultrasound in our screening population.

"Are changes in breast density during the menstrual cycle relevant? To what?"

PURPOSE

Cancers can be hidden by high breast density (BDen)- the masking effect (ME). BDen is also a modifiable and highly prevalent breast cancer risk (BCR) factor. The purposes of this study were to determine how much glandular volume (GVol), breast volume (BVol) and their ratio: BDen change during the menstrual cycle, and if these changes could affect ME or be relevant to results of interventional studies aiming to diminish BCR using these parameters as surrogates.

METHODS

We retrieved GVol, BVol and BDen data values obtained from 39,997 right mammograms performed with photon counting technique of 19,904 premenopausal women who reported their first day of last menses (FDLM). Many women had more than one study included over the years (with a different FDLM) but were not studied longitudinally. We segregated women by age (yearly), divided the menstrual cycle in 4 weeks, and assigned results with respect to the FDLM.

RESULTS

All parameters vary cyclically, with higher values in week 4 (GVol and BDen) or week 1 (BVol). Mean inter-week differences were very small for the three parameters, and diminished with age. However, especially in the youngest women, inter-week differences could be more than 10% for BDen, 15% for GVol, and 50% for BVol.

CONCLUSION

Small inter-week mean differences almost certainly rule out relevant changes to ME directly attributable to BDen. However, the possibility of large differences during the menstrual cycle in younger women, who are the ideal targets of interventional studies to diminish BCR, might distort results and should be accounted for.

Mammographic density and breast cancer screening

Mammographic density, which is determined by the relative amounts of fibroglandular tissue and fat in the breast, varies between women. Mammographic density is associated with a range of factors, including age and body mass index. The description of mammographic density has been transformed by the digitalization of mammography, which has allowed automation of the assessment of mammographic density, rather than using visual inspection by a radiologist. High mammographic density is important because it is associated with reduced sensitivity for the detection of breast cancer at the time of mammographic screening. High mammographic density is also associated with an elevated risk of developing breast cancer. Mammographic density appears to be on the causal pathway for some breast cancer risk factors, but not others. Mammographic density needs to be considered in the context of a woman's background risk of breast cancer. There is intense debate about the use of supplementary imaging for women with high mammographic density. Should supplementary imaging be used in women with high mammographic density and a clear mammogram? If so, what modalities of imaging should be used and in which women? Trials are underway to address the risks and benefits of supplementary imaging.

Supplemental breast cancer-screening ultrasonography in women with dense breasts: a systematic review and meta-analysis

Background

Mammography is not effective in detecting breast cancer in dense breasts.

Methods

A search in Medline, Cochrane, EMBASE and Google Scholar databases was conducted from January 1, 1980 to April 10, 2019 to identify women with dense breasts screened by mammography (M) and/or ultrasound (US). Meta-analysis was performed using the random-effect model.

Results

A total of 21 studies were included. The pooled sensitivity values of M alone and M + US in patients were 74% and 96%, while specificity of the two methods were 93% and 87%, respectively. Screening sensitivity was significantly higher in M + US than M alone (risk ratio: M alone vs. M + US = 0.699, P < 0.001), but the slight difference in specificity was statistically significant (risk ratio = 1.060, P = 0.001). Pooled diagnostic performance of follow-up US after initial negative mammography demonstrated a high pooled sensitivity (96%) and specificity (88%). The findings were supported by subgroup analysis stratified by study country, US method and timing of US.

Conclusions

Breast cancer screening by supplemental US among women with dense breasts shows added detection sensitivity compared with M alone. However, US slightly decreased the diagnostic specificity for breast cancer. The cost-effectiveness of supplemental US in detecting malignancy in dense breasts should be considered additionally.

Subjective Versus Quantitative Methods of Assessing Breast Density

In order to find a consistent, simple and time-efficient method of assessing mammographic breast density (MBD), different methods of assessing density comparing subjective, quantitative, semi-subjective and semi-quantitative methods were investigated. Subjective MBD of anonymized mammographic cases (n = 250) from a national breast-screening programme was rated by 49 radiologists from two countries (UK and USA) who were voluntarily recruited. Quantitatively, three measurement methods, namely VOLPARA, Hand Delineation (HD) and ImageJ (IJ) were used to calculate breast density using the same set of cases, however, for VOLPARA only mammographic cases (n = 122) with full raw digital data were included. The agreement level between methods was analysed using weighted kappa test. Agreement between UK and USA radiologists and VOLPARA varied from moderate (κw = 0.589) to substantial (κw = 0.639), respectively. The levels of agreement between USA, UK radiologists, VOLPARA with IJ were substantial (κw = 0.752, 0.768, 0.603), and with HD the levels of agreement varied from moderate to substantial (κw = 0.632, 0.680, 0.597), respectively. This study found that there is variability between subjective and objective MBD assessment methods, internationally. These results will add to the evidence base, emphasising the need for consistent, simple and time-efficient MBD assessment methods. Additionally, the quickest method to assess density is the subjective assessment, followed by VOLPARA, which is compatible with a busy clinical setting. Moreover, the use of a more limited two-scale system improves agreement levels and could help minimise any potential country bias.

Placental morphometry in relation to daughters' percent mammographic breast density at midlife

Intrauterine and early-life exposures, including intrauterine smoke exposures and infant growth are associated with mammographic breast density (MBD), a strong breast cancer risk factor. We investigated whether placental morphometry, which is affected by intrauterine smoke exposure and also influences infant growth, predicts %MBD at ages 37-47. In 247 daughters in the Child Health and Development Studies, we found that larger placental surface area and placental thickness were associated with lower %MBD (-0.32 per cm², 95% CI -0.6, -0.05; -37.8 per 0.5 cm, 95% CI= -73.3, -2.3 respectively) independent of mothers' smoking, age, weight, parity and daughters' birthweight and age at mammogram. We also observed a positive interaction between placental surface area and thickness (p < 0.05) such that the highest breast dense area was observed for offspring with the thickest and largest placentas. Factors that impact placental morphometry, in addition to in utero smoke exposure, may influence adult breast architecture and breast cancer risk.

The impact of bariatric surgery on qualitative and quantitative breast density

BACKGROUND

Obesity and breast density are associated with breast cancer in postmenopausal women. Bariatric surgery effectively treats morbid obesity, with sustainable weight loss and reductions in cancer incidence. We evaluated changes in qualitative and quantitative density; hypothesizing breast density would increase following bariatric surgery.

METHODS

Women undergoing bariatric surgery from 1990 to 2015 were identified, excluding patients without a mammogram performed both before and after surgery. Changes in body mass index (BMI), time between mammograms and surgery, and American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) scores were assessed. VolparaDensity™ automated software calculated volumetric breast density (VBD), fibroglandular volume (FGV), and total breast volume for the 82 women with digital data available. Differences between pre- and postsurgery values were assessed.

RESULTS

One hundred eighty women were included. Median age at surgery was 50.0 years, with 8.8 months between presurgery mammogram and surgery and 62.3 months between surgery and postsurgery mammogram. Median BMI significantly decreased over the study period (46.0 vs 35.4 kg/m² ; P < 0.001). No change in BI-RADS scores was seen between the pre- and postsurgery mammograms. Eighty-two women had VolparaDensity™ data available. While VBD increased in these patients, FGV and total breast volume both decreased following bariatric surgery.

CONCLUSIONS

Increased VBD, decreased FGV, and decreased total breast volume were seen following bariatric surgery-induced weight loss. There was no difference in qualitative breast density, highlighting the discrepancy between BI-RADS and VolparaDensity™ measurements. Further investigation will be required to determine how differential changes in components of breast density may affect breast cancer risk.

Comparison of a personalized breast dosimetry method with standard dosimetry protocols

Average glandular dose (AGD) in digital mammography crucially depends on the estimation of breast glandularity. In this study we compared three different methods of estimating glandularities according to Wu, Dance and Volpara with respect to resulting AGDs. Exposure data from 3050 patient images, acquired with a GE Senographe Essential constituted the study population of this work. We compared AGD (1) according to Dance et al. applying custom g, c, and s factors using HVL, breast thickness, patient age and incident air kerma (IAK) from the DICOM headers; (2) according to Wu et al. as determined by the GE system; and (3) AGD derived with the Dance model with personalized c factors using glandularity determined with the Volpara (Volpara Solutions, Wellington, New Zealand) software (Volpare AGD). The ratios of the resulting AGDs were analysed versus parameters influencing dose. The highest deviation between the resulting AGDs was found in the ratio of GE AGD to Volpara AGD for breast thicknesses between 20 and 40 mm (ratio: 0.80). For thicker breasts this ratio is close to one (1 ± 0.02 for breast thicknesses >60 mm). The Dance to Volpara ratio was between 0.86 (breast thickness 20–40 mm) and 0.99 (>80 mm), and Dance/GE AGD was between 1.07 (breast thickness 20–40 mm) and 0.98 (41–60, and >80 mm). Glandularities by Volpara were generally smaller than the one calculated with the Dance method. This effect is most pronounced for small breast thickness and older ages. Taking the considerable divergences between the AGDs from different methods into account, the selection of the method should by done carefully. As the Volpara method provides an analysis of the individual breast tissue, while the Wu and the Dance methods use look up tables and custom parameter sets, the Volpara method might be more appropriate if individual ADG values are sought. For regulatory purposes and comparison with diagnostic reference values, the method to be used needs to be defined exactly and clearly be stated. However, it should be accepted that dose values calculated with standardized models, like AGD and also effective dose, are afflicted with a considerable uncertainty budgets that need to be accounted for in the interpretation of these values.

Association of advanced hepatic fibrosis and sonographic visualization score: a dual-center study using ACR US LI-RADS

PURPOSE

To evaluate the association between imaging and clinical features and visualization scores, as specified by American College of Radiology (ACR) Ultrasound Liver Imaging Reporting and Data System (LI-RADS), on hepatocellular carcinoma (HCC) screening ultrasound examinations.

METHODS

In this dual-center retrospective study, HCC screening ultrasound reports containing ultrasound elastography measurements (January to September, 2017) were reviewed. Ultrasound point shear wave elastography and 2-dimensional shear wave elastography were used to assess liver stiffness; median shear wave velocity was translated to METAVIR fibrosis scoring, per previously published data. Reports were analyzed for subject age, sex, reason for HCC screening, spleen size, fibrosis scores, and assigned ultrasound visualization scores. Jonckheere-Terpstra trend and Kendall's tau-b coefficient analyses were performed.

RESULTS

714 subjects (mean age 55; 51% male, 49% female) were included. 308 (43%) subjects had clinically declared cirrhosis; 406 (57%) did not. Majority (535, 75%) of exams were adequate (Visualization Score A), 156 (22%) moderately limited (Visualization Score B), and 23 (3%) severely limited (Visualization Score C). Increasing spleen size and patient age were associated with worsening visualization scores (p < 0.001). Suboptimal visualization was also associated with clinically significant fibrosis (≥ F2) by elastography (Kendall's tau-b = 0.181, p < 0.001) and clinically declared cirrhosis (Kendall's tau-b = 0.433, p < 0.001). There was no association with patient sex.

CONCLUSION

Using ACR Ultrasound LI-RADS visualization score assessment, majority (75%) of HCC screening exams were diagnostically adequate, and only 3% were severely limited. Sonoelastographic diagnosis of clinically significant fibrosis, as well as clinical cirrhosis, increased patient age, and spleen size, were associated with greater diagnostic limitations.

Breast tomosynthesis: state of the art

Breast tomosynthesis is a continually improving tool for diagnostic radiologists. This update about tomosynthesis reviews the advantages of the technique both in patients with suspected or known disease and in screening, as well as its limitations, of which the dose of radiation is the most important. The more recent advent of synthesized mammography, computer-assisted detection, and tomosynthesis-guided biopsy have helped to reduce the dose of radiation used and have improved the diagnostic performance of tomosynthesis, so they are also discussed in this review.

Multimodality Imaging of Breast Parenchymal Density and Correlation with Risk Assessment

Purpose of Review

Breast density, or the amount of fibroglandular tissue in the breast, has become a recognized and independent marker for breast cancer risk. Public awareness of breast density as a possible risk factor for breast cancer has resulted in legislation for risk stratification purposes in many US states. This review will provide a comprehensive overview of the currently available imaging modalities for qualitative and quantitative breast density assessment and the current evidence on breast density and breast cancer risk assessment.

Recent Findings

To date, breast density assessment is mainly performed with mammography and to some extent with magnetic resonance imaging. Data indicate that computerized, quantitative techniques in comparison with subjective visual estimations are characterized by higher reproducibility and robustness.

Summary

Breast density reduces the sensitivity of mammography due to a masking effect and is also a recognized independent risk factor for breast cancer. Standardized breast density assessment using automated volumetric quantitative methods has the potential to be used for risk prediction and stratification and in determining the best screening plan for each woman.

Breast cancer diagnosis in a specialised breast clinic: Are cancers detected by ultrasound alone less aggressive?

INTRODUCTION

The aim of this study was to determine the relationship between the way breast cancer is diagnosed and its prognostic features.

METHODS

We studied new primary invasive and non-invasive breast cancers (670) diagnosed between 2013 and 2015 where detection included at least clinical examination, mammography and breast ultrasound (BUS). The cancers were classified into six Diagnostic Groups according to the results of each modality.

RESULTS

Overall, 79% of cancers were positive on mammography, but another 20% were diagnosed on BUS after a negative mammogram. The largest group (37.6% of cases), had all three modalities positive (Group 1). BUS was the only modality positive in 14.6% (Group 4). Mammography alone was positive in 21.2%, of which 73.9% were ductal carcinoma in situ (DCIS). Invasive lobular carcinoma comprised 9.6% of the groups where mammography was positive, but 16.5% of the groups where mammography was negative and BUS positive. Dense breast tissue was more common in the groups where mammography was negative and BUS positive. Invasive cancers comprised 82.7% of Group 4 and 95.2% of Group 1. For those in Group 4, the average size (10.2 mm) and the percentages with lymphovascular invasion (11.1%), lymph node involvement (17.3%) and poor differentiation (12.3%) were less than half the corresponding figures for Group 1 (27.3 mm, 35%, 44%, 44%).

CONCLUSION

This study illustrates the complementary benefits of mammography and BUS, especially where breast density is high. Tumours diagnosed by BUS alone had better prognostic features in terms of size, lymphovascular invasion, lymph node status, differentiation and hormone receptors, compared with cancers where all three modalities were positive.

Liver Imaging Reporting and Data System (LI-RADS) Version 2018: Imaging of Hepatocellular Carcinoma in At-Risk Patients

The Liver Imaging Reporting and Data System (LI-RADS) is composed of four individual algorithms intended to standardize the lexicon, as well as reporting and care, in patients with or at risk for hepatocellular carcinoma in the context of surveillance with US; diagnosis with CT, MRI, or contrast material-enhanced US; and assessment of treatment response with CT or MRI. This report provides a broad overview of LI-RADS, including its historic development, relationship to other imaging guidelines, composition, aims, and future directions. In addition, readers will understand the motivation for and key components of the 2018 update.

Density and tailored breast cancer screening: practice and prediction - an overview

Mammography, as the primary screening modality, has facilitated a substantial decrease in breast cancer-related mortality in the general population. However, the sensitivity of mammography for breast cancer detection is decreased in women with higher breast densities, which is an independent risk factor for breast cancer. With increasing public awareness of the implications of a high breast density, there is an increasing demand for supplemental screening in these patients. Yet, improvements in breast cancer detection with supplemental screening methods come at the expense of increased false-positives, recall rates, patient anxiety, and costs. Therefore, breast cancer screening practice must change from a general one-size-fits-all approach to a more personalized, risk-based one that is tailored to the individual woman’s risk, personal beliefs, and preferences, while accounting for cost, potential harm, and benefits.

This overview will provide an overview of the available breast density assessment modalities, the current breast density screening recommendations for women at average risk of breast cancer, and supplemental methods for breast cancer screening. In addition, we will provide a look at the possibilities for a risk-adapted breast cancer screening.

Measuring breast density: Comparing computer-automated breast density quantification with an observer-based method in a South African academic context

BACKGROUND

Dense breast tissue may not only 'mask' small, non-calcified cancers but also represents an independent risk factor for the development of breast cancer. Computer-automated breast density quantification (CABD) software tools have been developed for the calculation of volumetric breast density.

OBJECTIVES

This study sought: (1) to compare observer-based breast density scores, using the fifth edition of the Breast Imaging Reporting and Data System (BI-RADS), with the breast density scores calculated using CABD quantification software tools, (2) to determine inter-reader variability in breast density scoring between qualified radiologists, between radiologists in training (registrars) and between these two groups and (3) to determine intra-reader reliability in breast density scoring.

METHODS

A cross-sectional study was performed using the data of 100 patients (200 breasts). Three qualified radiologists and three registrars were asked to review the mammograms in question and to assign a breast density score according to the fifth edition of the Breast Imaging Reporting and Data System (BI-RADS) reporting system. Two readings took place at a minimum of 30 days apart. The percentage agreement between the automated and observer-based scores was calculated and intra-reader and inter-reader reliability values were determined.

RESULTS

The study found that there was poor agreement between the breast densities calculated by CABD and the more subjective observer-based BI-RADS density scores. These results further reflect a statistically significant degree of inter-reader and intra-reader variability in the evaluation of breast density.

CONCLUSION

We conclude that the use of automated breast density quantification (i.e. CABD) is a valuable tool for the reduction of variability in breast density ratings.

Comparison of Breast Density Between Synthesized Versus Standard Digital Mammography

PURPOSE

To evaluate perceptual difference in breast density classification using synthesized mammography (SM) compared with standard or full-field digital mammography (FFDM) for screening.

MATERIALS AND METHODS

This 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.

RESULTS

For 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).

CONCLUSION

Overall subjective breast density assignment by radiologists on SM is similar to density assignment on standard 2-D mammogram.

Comparison of variability in breast density assessment by BI-RADS category according to the level of experience

Background Only few studies have assessed variability in the results obtained by the readers with different experience levels in comparison with automated volumetric breast density measurements. Purpose To examine the variations in breast density assessment according to BI-RADS categories among readers with different experience levels and to compare it with the results of automated quantitative measurements. Material and Methods Density assignment was done for 1000 screening mammograms by six readers with three different experience levels (breast-imaging experts, general radiologists, and students). Agreement level between the results obtained by the readers and the Volpara automated volumetric breast density measurements was assessed. The agreement analysis using two categories-non-dense and dense breast tissue-was also performed. Results Intra-reader agreement for experts, general radiologists, and students were almost perfect or substantial (k = 0.74-0.95). The agreement between visual assessments of the breast-imaging experts and volumetric assessments by Volpara was substantial (k = 0.77). The agreement was moderate between the experts and general radiologists (k = 0.67) and slight between the students and Volpara (k = 0.01). The agreement for the two category groups (nondense and dense) was almost perfect between the experts and Volpara (k = 0.83). The agreement was substantial between the experts and general radiologists (k = 0.78). Conclusion We observed similar high agreement levels between visual assessments of breast density performed by radiologists and the volumetric assessments. However, agreement levels were substantially lower for the untrained readers.

Malignancy Detection on Mammography Using Dual Deep Convolutional Neural Networks and Genetically Discovered False Color Input Enhancement

Breast cancer is the most prevalent malignancy in the US and the third highest cause of cancer-related mortality worldwide. Regular mammography screening has been attributed with doubling the rate of early cancer detection over the past three decades, yet estimates of mammographic accuracy in the hands of experienced radiologists remain suboptimal with sensitivity ranging from 62 to 87% and specificity from 75 to 91%. Advances in machine learning (ML) in recent years have demonstrated capabilities of image analysis which often surpass those of human observers. Here we present two novel techniques to address inherent challenges in the application of ML to the domain of mammography. We describe the use of genetic search of image enhancement methods, leading us to the use of a novel form of false color enhancement through contrast limited adaptive histogram equalization (CLAHE), as a method to optimize mammographic feature representation. We also utilize dual deep convolutional neural networks at different scales, for classification of full mammogram images and derivative patches combined with a random forest gating network as a novel architectural solution capable of discerning malignancy with a specificity of 0.91 and a specificity of 0.80. To our knowledge, this represents the first automatic stand-alone mammography malignancy detection algorithm with sensitivity and specificity performance similar to that of expert radiologists.

A review of mammographic positioning image quality criteria for the craniocaudal projection

Detection of breast cancer is reliant on optimal breast positioning and the production of quality images. Two projections, the mediolateral oblique and craniocaudal (CC), are routinely performed. Determination of successful positioning and inclusion of all breast tissue is achieved through meeting stated image quality criteria. For the CC view, current image quality criteria are inconsistent. Absence of reliable anatomical markers, other than the nipple, further contribute to difficulties in assessing the quality of CC views. The aim of this paper was to explore published international quality standards to identify and find the origin of any CC positioning criteria which might provide for quantitative assessment. The pectoralis major (pectoral) muscle was identified as a key posterior anatomical structure to establish optimum breast tissue inclusion on mammographic projections. It forms the first two of the three main CC metrics that are frequently reported (1) visualization of the pectoral muscle, (2) measurement of the posterior nipple line and (3) depiction of retroglandular fat. This literature review explores the origin of the three metrics, and discusses three key publications, spanning 1992 to 1994, on which subsequent image quality standards have been based. The evidence base to support published CC metrics is sometimes not specified and more often, the same set of publications are cited, most often without critical evaluation. To conclude, there remains uncertainty if the metrics explored for the CC view support objective evaluation and reproducibility to confirm optimal breast positioning and quality images.

Automated Breast Density Computation in Digital Mammography and Digital Breast Tomosynthesis: Influence on Mean Glandular Dose and BIRADS Density Categorization

RATIONALE AND OBJECTIVES

The study aimed to compare the breast density estimates from two algorithms on full-field digital mammography (FFDM) and digital breast tomosynthesis (DBT) and to analyze the clinical implications.

MATERIALS AND METHODS

We selected 561 FFDM and DBT examinations from patients without breast pathologies. Two versions of a commercial software (Quantra 2D and Quantra 3D) calculated the volumetric breast density automatically in FFDM and DBT, respectively. Other parameters such as area breast density and total breast volume were evaluated. We compared the results from both algorithms using the Mann-Whitney U non-parametric test and the Spearman's rank coefficient for data correlation analysis. Mean glandular dose (MGD) was calculated following the methodology proposed by Dance et al.

RESULTS

Measurements with both algorithms are well correlated (r ≥ 0.77). However, there are statistically significant differences between the medians (P < 0.05) of most parameters. The volumetric and area breast density median values from FFDM are, respectively, 8% and 77% higher than DBT estimations. Both algorithms classify 35% and 55% of breasts into BIRADS (Breast Imaging-Reporting and Data System) b and c categories, respectively. There are no significant differences between the MGD calculated using the breast density from each algorithm. DBT delivers higher MGD than FFDM, with a lower difference (5%) for breasts in the BIRADS d category. MGD is, on average, 6% higher than values obtained with the breast glandularity proposed by Dance et al.

CONCLUSIONS

Breast density measurements from both algorithms lead to equivalent BIRADS classification and MGD values, hence showing no difference in clinical outcomes. The median MGD values of FFDM and DBT examinations are similar for dense breasts (BIRADS d category).

The Effect of California's Breast Density Notification Legislation on Breast Cancer Screening

Purpose: Half of US states mandate women be notified if they have dense breasts on their mammogram, yet guidelines and data on supplemental screening modalities are limited. Breast density (BD) refers to the extent that breast tissue appears radiographically dense on mammograms. High BD reduces the sensitivity of screening mammography and increases breast cancer risk. The aim of this study was to determine the potential impact of California’s 2013 BD notification legislation on breast cancer screening patterns. Methods: We conducted a cohort study of women aged 40 to 74 years who were members of a large Northern California integrated health plan (approximately 3.9 million members) in 2011-2015. We calculated pre- and post-legislation rates of screening mammography and magnetic resonance imaging (MRI). We also examined whether women with dense breasts (defined as BI-RADS density c or d) had higher MRI rates than women with nondense breasts (defined as BI-RADS density a or b). Results: After adjustment for race/ethnicity, age, body mass index, medical facility, neighborhood median income, and cancer history, there was a relative 6.6% decrease (relative risk [RR] 0.934, confidence interval [CI] 0.92-0.95) in the rate of screening mammography, largely driven by a decrease among women <50 years. While infrequent, there was a relative 16% increase (RR 1.16, CI 1.07-1.25) in the rate of screening MRI, with the greatest increase among the youngest women. In the postlegislation period, women with extremely dense breasts (BI-RADS d) had 2.77 times (CI 1.93-3.95) the odds of a MRI within 9 months of a screening mammogram compared with women with nondense breasts (BI-RADS b). Conclusions: In this setting, MRI rates increased in the postlegislation period. In addition, women with higher BD were more likely to have supplementary MRI. The decrease in mammography rates seen primarily among younger women may have been due to changes in national screening guidelines.

What we need to know about dense breasts: implications for breast cancer screening

High breast density and its relationship to the risk of breast cancer has become a hot topic in the medical literature and in the lay press, especially in the United States, where it has brought about changes in the legal framework that require radiologists to inform clinicians and patients about breast density. Radiologists, who are mainly responsible for this information, need to know the scientific evidence and controversies regarding this subject. The discussion is centered on the real importance of the risk, the limitation that not having standardized methods of measurement represents, and the possible application of complementary screening techniques (ultrasound, magnetic resonance imaging, or tomosynthesis) for which clear recommendations have yet to be established. We need controlled studies that evaluate the application of these techniques in women with dense breasts, including the possibility that they can lead to overdiagnosis.