Computerized detection of breast cancer on automated breast ultrasound imaging of women with dense breasts.
ABSTRACT: Develop a computer-aided detection method and investigate its feasibility for detection of breast cancer in automated 3D ultrasound images of women with dense breasts.The HIPAA compliant study involved a dataset of volumetric ultrasound image data, "views," acquired with an automated U-Systems Somo●V(®) ABUS system for 185 asymptomatic women with dense breasts (BI-RADS Composition/Density 3 or 4). For each patient, three whole-breast views (3D image volumes) per breast were acquired. A total of 52 patients had breast cancer (61 cancers), diagnosed through any follow-up at most 365 days after the original screening mammogram. Thirty-one of these patients (32 cancers) had a screening-mammogram with a clinically assigned BI-RADS Assessment Category 1 or 2, i.e., were mammographically negative. All software used for analysis was developed in-house and involved 3 steps: (1) detection of initial tumor candidates, (2) characterization of candidates, and (3) elimination of false-positive candidates. Performance was assessed by calculating the cancer detection sensitivity as a function of the number of "marks" (detections) per view.At a single mark per view, i.e., six marks per patient, the median detection sensitivity by cancer was 50.0% (16/32) ± 6% for patients with a screening mammogram-assigned BI-RADS category 1 or 2--similar to radiologists' performance sensitivity (49.9%) for this dataset from a prior reader study--and 45.9% (28/61) ± 4% for all patients.Promising detection sensitivity was obtained for the computer on a 3D ultrasound dataset of women with dense breasts at a rate of false-positive detections that may be acceptable for clinical implementation.
Project description:Twenty-one states have laws requiring that women be notified if they have dense breasts and that they be advised to discuss supplemental imaging with their provider.To better direct discussions of supplemental imaging by determining which combinations of breast cancer risk and Breast Imaging Reporting and Data System (BI-RADS) breast density categories are associated with high interval cancer rates.Prospective cohort.Breast Cancer Surveillance Consortium (BCSC) breast imaging facilities.365,426 women aged 40 to 74 years who had 831,455 digital screening mammography examinations.BI-RADS breast density, BCSC 5-year breast cancer risk, and interval cancer rate (invasive cancer ?12 months after a normal mammography result) per 1000 mammography examinations. High interval cancer rate was defined as more than 1 case per 1000 examinations.High interval cancer rates were observed for women with 5-year risk of 1.67% or greater and extremely dense breasts or 5-year risk of 2.50% or greater and heterogeneously dense breasts (24% of all women with dense breasts). The interval rate of advanced-stage disease was highest (>0.4 case per 1000 examinations) among women with 5-year risk of 2.50% or greater and heterogeneously or extremely dense breasts (21% of all women with dense breasts). Five-year risk was low to average (0% to 1.66%) for 51.0% of women with heterogeneously dense breasts and 52.5% with extremely dense breasts, with interval cancer rates of 0.58 to 0.63 and 0.72 to 0.89 case per 1000 examinations, respectively.The benefit of supplemental imaging was not assessed.Breast density should not be the sole criterion for deciding whether supplemental imaging is justified because not all women with dense breasts have high interval cancer rates. BCSC 5-year risk combined with BI-RADS breast density can identify women at high risk for interval cancer to inform patient-provider discussions about alternative screening strategies.National Cancer Institute.
Project description:BACKGROUND:Breast density is strongly related to breast cancer. Identifying associations between environmental exposures and density may elucidate relationships with breast cancer. Metals and polycyclic aromatic hydrocarbons (PAHs) may influence breast density via oxidative stress or endocrine disruption. METHODS:Study participants (n = 222,581) underwent a screening mammogram in 2011 at a radiology facility in the Breast Cancer Surveillance Consortium. Zip code residential levels of airborne PAHs and metals (arsenic, cadmium, chromium, cobalt, lead, manganese, mercury, nickel, and selenium) were assessed using the 2011 EPA National Air Toxics Assessment. Breast density was measured using the Breast Imaging-Reporting and Data System (BI-RADS) lexicon. Logistic regression was used to estimate adjusted odds ratios (ORs) and 95% confidence intervals (CI) for the individual air toxics and dense breasts (BI-RADS 3 or 4). Weighted quantile sum (WQS) regression was used to model the association between the air toxic mixture and density. RESULTS:Higher residential levels of arsenic, cobalt, lead, manganese, nickel, or PAHs were individually associated with breast density. Comparing the highest to the lowest quartile, higher odds of having dense breasts were observed for cobalt (OR = 1.60, 95% CI 1.56-1.64) and lead (OR = 1.56, 95% CI 1.52-1.64). Associations were stronger for premenopausal women. The WQS index was associated with density overall (OR = 1.22, 95% CI 1.20-1.24); the most heavily weighted air toxics were lead and cobalt. CONCLUSIONS:In this first study to evaluate the association between air toxics and breast density, women living in areas with higher concentrations of lead and cobalt were more likely to have dense breasts.
Project description:Extensive mammographic density (MD), a well-established breast cancer risk factor, is a radiological representation of stromal and epithelial breast tissue content. In studies conducted predominantly among Caucasian women, histologic measures of reduced terminal duct lobular unit (TDLU) involution have been correlated with extensive MD, but independently associated with breast cancer risk. We therefore examined associations between TDLU measures and MD among Chinese women, a low-risk population but with high prevalence of dense breasts. Diagnostic pre-treatment digital mammograms were obtained from 144 breast cancer cases at a tertiary hospital in Beijing and scored using the Breast Imaging Reporting and Data System (BI-RADS) density classification. TDLU features were assessed using three standardized measures (count/100 mm2 , span [?m], and acini count/TDLU) in benign tissues. Associations between each of TDLU measures and MD were examined using generalized linear models for TDLU count and span and polytomous logistic regression for acini count with adjustment for potential confounders stratified by age. Among women ?50 years, 63% had dense breasts; cases with dense breasts (BI-RADS, c-d) had greater TDLU count (21.1 [SE = 2.70] vs. 9.0 [SE = 1.83]; p = 0.0004), longer span (480.6 ?m [SE = 24.6] vs. 393.8 ?m [SE = 31.8]; p = 0.03), and greater acini count (ORtrend = 16.1; 95%CI = 4.08-63.1; ptrend < 0.0001) compared to those with non-dense breasts (BI-RADS, a-b). Among women <50 years, 91% had dense breasts, precluding our ability to detect associations. Our findings are consistent with previously reported associations between extensive MD and reduced TDLU involution, supporting the hypothesis that breast cancer risk associated with extensive MD may be related to the amount of "at-risk" epithelium.
Project description:Importance:Federal legislation proposes requiring that screening mammography reports to practitioners and women incorporate breast density information and that women with dense breasts discuss supplemental imaging with their practitioner given their increased risk of interval breast cancer. Instead of discussing supplemental imaging with all women with dense breasts, it may be more efficient to identify women at high risk of advanced breast cancer who may benefit most from supplemental imaging. Objective:To identify women at high risk of advanced breast cancer to target woman-practitioner discussions about the need for supplemental imaging. Design, Setting, and Participants:This prospective cohort study assessed 638?856 women aged 40 to 74 years who had 1?693?163 screening digital mammograms taken at Breast Cancer Surveillance Consortium (BCSC) imaging facilities from January 3, 2005, to December 31, 2014. Data analysis was performed from October 10, 2018, to March 20, 2019. Exposures:Breast Imaging Reporting and Data System (BI-RADS) breast density and BCSC 5-year breast cancer risk. Main Outcomes and Measures:Advanced breast cancer (stage IIB or higher) within 12 months of screening mammography; high advanced cancer rates (?0.61 cases per 1000 mammograms) defined as the top 25th percentile of advanced cancer rates, and discussions per potential advanced cancer prevented. Results:A total of 638?856 women (mean [SD] age, 56.5 [8.9] years) were included in the study. Women with dense breasts (heterogeneously or extremely dense) accounted for 47.0% of screened women and 60.0% of advanced cancers. Low advanced cancer rates (<0.61 per 1000 mammograms) occurred in 34.5% of screened women with dense breasts. High advanced breast cancer rates occurred in women with heterogeneously dense breasts and a 5-year risk of 2.5% or higher (6.0% of screened women) and those with extremely dense breasts and a 5-year risk of 1.0% or higher (6.5% of screened women). Density-risk subgroups at high advanced cancer risk comprised 12.5% of screened women and 27.1% of advanced cancers. Density-risk subgroups had the fewest supplemental imaging discussions per potential advanced cancer prevented compared with a strategy based on dense breasts (1097 vs 1866 discussions). Women with heterogeneously dense breasts and a 5-year risk less than 1.67% (21.7% of screened women) had high rates of false-positive short-interval follow-up recommendation without undergoing supplemental imaging. Conclusions and Relevance:The findings suggest that breast density notification should be combined with breast cancer risk so women at highest risk for advanced cancer are targeted for supplemental imaging discussions and women at low risk are not. BI-RADS breast density combined with BCSC 5-year risk may offer a more efficient strategy for supplemental imaging discussions than targeting all women with dense breasts.
Project description:Over 40% of women undergoing breast screening have mammographically dense breasts. Elevated mammographic breast density (MBD) is an established breast cancer risk factor and is known to mask tumors within the dense tissue. However, the association of MBD with high risk benign breast disease (BBD) is unknown.We analyzed data for 3400 women diagnosed with pathologically confirmed BBD in the Mayo Clinic BBD cohort from 1985-2001, with a clinical MBD measure (either parenchymal pattern (PP) or Breast Imaging Reporting and Data Systems (BI-RADS) density) and expert pathology review. Risk factor information was collected from medical records and questionnaires. MBD was dichotomized as dense (PP classification P2 or DY, or BI-RADS classification c or d) or non-dense (PP classification N1 or P1, or BI-RADS classification a or b). Associations of clinical and histologic characteristics with MBD were examined using logistic regression analysis to estimate odds ratios (ORs) with 95% confidence intervals (CIs).Of 3400 women in the study, 2163 (64%) had dense breasts. Adjusting for age and body mass index (BMI), there were positive associations of dense breasts with use of hormone therapy (HT), lack of lobular involution, presence of atypical lobular hyperplasia (ALH), histologic fibrosis, columnar cell hyperplasia/flat epithelia atypia (CCH/FEA), sclerosing adenosis (SA), cyst, usual ductal hyperplasia, and calcifications. In fully adjusted multivariate models, HT (1.3, 95% CI 1.1-1.5), ALH (1.5, 95% CI 1.0-2.2), lack of lobular involution (OR 1.6, 95% CI 1.2-2.1, compared to complete involution), fibrosis (OR 2.2, 95% CI 1.9-2.6) and CCH/FEA (OR 1.3, 95% CI 1.0-1.6) remained significantly associated with high MBD.Our findings support an association between high risk BBD and high MBD, suggesting that risks associated with the latter may act early in breast carcinogenesis.
Project description:BACKGROUND:Attention in the 2000s on the importance of mammographic density led us to study screening sensitivity, breast cancer incidence, and associations with risk factors by mammographic density in Danish breast cancer screening programs. Here, we summarise our approaches and findings. METHODS:Dichotomized density codes: fatty, equal to BI-RADS density code 1 and part of 2, and other mixed/dense data from the 1990s-were available from two counties, and BI-RADS density codes from one region were available from 2012/13. Density data were linked with data on vital status, incident breast cancer, and potential risk factors. We calculated screening sensitivity by combining data on screen-detected and interval cancers. We used cohorts to study high density as a predictor of breast cancer risk; cross-sectional data to study the association between life style factors and density, adjusting for age and body mass index (BMI); and time trends to study the prevalence of high density across birth cohorts. RESULTS:Sensitivity decreased with increasing density from 78% in women with BI-RADS 1 to 47% in those with BI-RADS 4. For women with mixed/dense compared with those with fatty breasts, the rate ratio of incident breast cancer was 2.45 (95% CI 2.14-2.81). The percentage of women with mixed/dense breasts decreased with age, but at a higher rate the later the women were born. Among users of postmenopausal hormone therapy, the percentage of women with mixed/dense breasts was higher than in non-users, but the patterns across birth cohorts were similar. The occurrence of mixed/dense breast at screening age decreased by a z-score unit of BMI at age 13-odds ratio (OR) 0.56 (95% CI 0.53-0.58)-and so did breast cancer risk and hazard ratio (HR) 0.92 (95% CI 0.84-1.00), but it changed to HR 1.01 (95% CI 0.93-1.11) when controlled for density. Age and BMI adjusted associations between life style factors and density were largely close to unity; physical activity OR 1.06 (95% CI 0.93-1.21); alcohol consumption OR 1.01 (95% CI 0.81-1.27); air pollution OR 0.96 (95% 0.93-1.01) per 20 ?g/m3; and traffic noise OR 0.94 (95% CI 0.86-1.03) per 10 dB. Weak negative associations were seen for diabetes OR 0.61 (95% CI 0.40-0.92) and cigarette smoking OR 0.86 (95% CI 0.75-0.99), and a positive association was found with hormone therapy OR 1.24 (95% 1.14-1.35). CONCLUSION:Our data indicate that breast tissue in middle-aged women is highly dependent on childhood body constitution while adult life-style plays a modest role, underlying the need for a long-term perspective in primary prevention of breast cancer.
Project description:<h4>Objectives</h4>To assess DWI for tumor visibility and breast cancer detection by the addition of different synthetic b-values.<h4>Methods</h4>Eighty-four consecutive women who underwent a breast-multiparametric-MRI (mpMRI) with enhancing lesions on DCE-MRI (BI-RADS 2-5) were included in this IRB-approved retrospective study from September 2018 to March 2019. Three readers evaluated DW acquired b-800 and synthetic b-1000, b-1200, b-1500, and b-1800 s/mm<sup>2</sup> images for lesion visibility and preferred b-value based on lesion conspicuity. Image quality (1-3 scores) and breast composition (BI-RADS) were also recorded. Diagnostic parameters for DWI were determined using a 1-5 malignancy score based on qualitative imaging parameters (acquired + preferred synthetic b-values) and ADC values. BI-RADS classification was used for DCE-MRI and quantitative ADC values + BI-RADS were used for mpMRI.<h4>Results</h4>Sixty-four malignant (average = 23 mm) and 39 benign (average = 8 mm) lesions were found in 80 women. Although b-800 achieved the best image quality score, synthetic b-values 1200-1500 s/mm<sup>2</sup> were preferred for lesion conspicuity, especially in dense breast. b-800 and synthetic b-1000/b-1200 s/mm<sup>2</sup> values allowed the visualization of 84-90% of cancers visible with DCE-MRI performing better than b-1500/b-1800 s/mm<sup>2</sup>. DWI was more specific (86.3% vs 65.7%, p < 0.001) but less sensitive (62.8% vs 90%, p < 0.001) and accurate (71% vs 80.7%, p = 0.003) than DCE-MRI for breast cancer detection, where mpMRI was the most accurate modality accounting for less false positive cases.<h4>Conclusion</h4>The addition of synthetic b-values enhances tumor conspicuity and could potentially improve tumor visualization particularly in dense breast. However, its supportive role for DWI breast cancer detection is still not definite.<h4>Key points</h4>• The addition of synthetic b-values (1200-1500 s/mm<sup>2</sup>) to acquired DWI afforded a better lesion conspicuity without increasing acquisition time and was particularly useful in dense breasts. • Despite the use of synthetic b-values, DWI was less sensitive and accurate than DCE-MRI for breast cancer detection. • A multiparametric MRI modality still remains the best approach having the highest accuracy for breast cancer detection and thus reducing the number of unnecessary biopsies.
Project description:The objective of this study is to compare different methods for measuring breast density, both visual assessments and automated volumetric density, in a breast cancer screening setting. These measures could potentially be implemented in future screening programmes, in the context of personalised screening or screening evaluation.Digital mammographic exams (N = 992) of women participating in the Dutch breast cancer screening programme (age 50-75y) in 2013 were included. Breast density was measured in three different ways: BI-RADS density (5th edition) and with two commercially available automated software programs (Quantra and Volpara volumetric density). BI-RADS density (ordinal scale) was assessed by three radiologists. Quantra (v1.3) and Volpara (v1.5.0) provide continuous estimates. Different comparison methods were used, including Bland-Altman plots and correlation coefficients (e.g., intraclass correlation coefficient [ICC]).Based on the BI-RADS classification, 40.8% of the women had 'heterogeneously or extremely dense' breasts. The median volumetric percent density was 12.1% (IQR: 9.6-16.5) for Quantra, which was higher than the Volpara estimate (median 6.6%, IQR: 4.4-10.9). The mean difference between Quantra and Volpara was 5.19% (95% CI: 5.04-5.34) (ICC: 0.64). There was a clear increase in volumetric percent dense volume as BI-RADS density increased. The highest accuracy for predicting the presence of BI-RADS c+d (heterogeneously or extremely dense) was observed with a cut-off value of 8.0% for Volpara and 13.8% for Quantra.Although there was no perfect agreement, there appeared to be a strong association between all three measures. Both volumetric density measures seem to be usable in breast cancer screening programmes, provided that the required data flow can be realized.
Project description:Mammographic density is a strong risk factor for breast cancer. Image acquisition technique varies across mammograms to limit radiation and produce a clinically useful image. We examined whether acquisition technique parameters at the time of mammography were associated with mammographic density and whether the acquisition parameters confounded the density and breast cancer association.We examined this question within the Mayo Mammography Health Study (MMHS) cohort, comprised of 19,924 women (51.2% of eligible) seen in the Mayo Clinic mammography screening practice from 2003 to 2006. A case-cohort design, comprising 318 incident breast cancers diagnosed through December 2009 and a random subcohort of 2,259, was used to examine potential confounding of mammogram acquisition technique parameters (x-ray tube voltage peak (kVp), milliampere-seconds (mAs), thickness and compression force) on the density and breast cancer association. The Breast Imaging Reporting and Data System four-category tissue composition measure (BI-RADS) and percent density (PD) (Cumulus program) were estimated from screen-film mammograms at time of enrollment. Spearman correlation coefficients (r) and means (standard deviations) were used to examine the relationship of density measures with acquisition parameters. Hazard ratios (HR) and C-statistics were estimated using Cox proportional hazards regression, adjusting for age, menopausal status, body mass index and postmenopausal hormones. A change in the HR of at least 15% indicated confounding.Adjusted PD and BI-RADS density were associated with breast cancer (p-trends < 0.001), with a 3 to 4-fold increased risk in the extremely dense vs. fatty BI-RADS categories (HR: 3.0, 95% CI, 1.7 - 5.1) and the ? 25% vs. ? 5% PD categories (HR: 3.8, 95% CI, 2.5 - 5.9). Of the acquisition parameters, kVp was not correlated with PD (r = 0.04, p = 0.07). Although thickness (r = -0.27, p < 0.001), compression force (r = -0.16, p < 0.001), and mAs (r = -0.06, p = 0.008) were inversely correlated with PD, they did not confound the PD or BI-RADS associations with breast cancer and their inclusion did not improve discriminatory accuracy. Results were similar for associations of dense and non-dense area with breast cancer.We confirmed a strong association between mammographic density and breast cancer risk that was not confounded by mammogram acquisition technique.