ACR BI-RADS Assessment Category 4 Subdivisions in Diagnostic Mammography: Utilization and Outcomes in the National Mammography Database.

Purpose To determine the utilization and positive predictive value (PPV) of the American College of Radiology (ACR) Breast Imaging Data and Reporting System (BI-RADS) category 4 subdivisions in diagnostic mammography in the National Mammography Database (NMD). Materials and Methods This study involved retrospective review of diagnostic mammography data submitted to the NMD from January 1, 2008 to December 30, 2014. Utilization rates of BI-RADS category 4 subdivisions were compared by year, facility (type, location, census region), and examination (indication, finding type) characteristics. PPV3 (positive predictive value for biopsies performed) was calculated overall and according to category 4 subdivision. The χ2 test was used to test for significant associations. Results Of 1 309 950 diagnostic mammograms, 125 447 (9.6%) were category 4, of which 33.3% (41 841 of 125 447) were subdivided. Subdivision utilization rates were higher (P < .001) in practices that were community, suburban, or in the West; for examination indication of prior history of breast cancer; and for the imaging finding of architectural distortion. Of 41 841 category 4 subdivided examinations, 4A constituted 55.6% (23 258 of 41 841) of the examinations; 4B, 31.8% (13 302 of 41 841) of the examinations; and 4C, 12.6% (5281 of 41 841) of the examinations. Pathologic outcomes were available in 91 563 examinations, and overall category 4 PPV3 was 21.1% (19 285 of 91 563). There was a statistically significant difference in PPV3 according to category 4 subdivision (P < .001): The PPV of 4A was 7.6% (1274 of 16 784), that of 4B was 22% (2317 of 10 408), and that of 4C was 69.3% (2839 of 4099). Conclusion Although BI-RADS suggests their use, subdivisions were utilized in the minority (33.3% [41 841 of 125 447]) of category 4 diagnostic mammograms, with variability based on facility and examination characteristics. When subdivisions were used, PPV3s were in BI-RADS-specified malignancy ranges. This analysis supports the use of subdivisions in broad practice and, given benefits for patient care, should motivate increased utilization. © RSNA, 2018 Online supplemental material is available for this article.

Utility of BI-RADS Assessment Category 4 Subdivisions for Screening Breast MRI.

OBJECTIVE: BI-RADS for mammography and ultrasound subdivides category 4 assessments by likelihood of malignancy into categories 4A (> 2% to ≤ 10%), 4B (> 10% to ≤ 50%), and 4C (> 50% to < 95%). Category 4 is not subdivided for breast MRI because of a paucity of data. The purpose of the present study is to determine the utility of categories 4A, 4B, and 4C for MRI by calculating their positive predictive values (PPVs) and comparing them with BI-RADS-specified rates of malignancy for mammography and ultrasound. MATERIALS AND METHODS: All screening breast MRI examinations performed from July 1, 2010, through June 30, 2013, were included in this study. We identified in medical records prospectively assigned MRI BI-RADS categories, including category 4 subdivisions, which are used routinely in our practice. Benign versus malignant outcomes were determined by pathologic analysis, findings from 12 months or more clinical or imaging follow-up, or a combination of these methods. Distribution of BI-RADS categories and positive predictive value level 2 (PPV2; based on recommendation for tissue diagnosis) for categories 4 (including its subdivisions) and 5 were calculated. RESULTS: Of 860 screening breast MRI examinations performed for 566 women (mean age, 47 years), 82 with a BI-RADS category 4 assessment were identified. A total of 18 malignancies were found among 84 category 4 and 5 assessments, for an overall PPV2 of 21.4% (18/84). For category 4 subdivisions, PPV2s were as follows: for category 4A, 2.5% (1/40); for category 4B, 27.6% (8/29); for category 4C, 83.3% (5/6); and for category 4 (not otherwise specified), 28.6% (2/7). CONCLUSION: Category 4 subdivisions for MRI yielded malignancy rates within BI-RADS-specified ranges, supporting their use for benefits to patient care and more meaningful practice audits.

Breast MRI in the Diagnostic and Preoperative Workup Among Medicare Beneficiaries With Breast Cancer.

PURPOSE: We compared the frequency and sequence of breast imaging and biopsy use for the diagnostic and preoperative workup of breast cancer according to breast magnetic resonance imaging (MRI) use among older women. MATERIALS AND METHODS: Using SEER-Medicare data from 2004 to 2010, we identified women with and without breast MRI as part of their diagnostic and preoperative breast cancer workup and measured the number and sequence of breast imaging and biopsy events per woman. RESULTS: A total of 10,766 (20%) women had an MRI in the diagnostic/preoperative period, 32,178 (60%) had mammogram and ultrasound, and 10,669 (20%) had mammography alone. MRI use increased across study years, tripling from 2005 to 2009 (9%-29%). Women with MRI had higher rates of breast imaging and biopsy compared with those with mammogram and ultrasound or those with mammography alone (5.8 vs. 4.1 vs. 2.8, respectively). There were 4254 unique sequences of breast events; the dominant patterns for women with MRI were an MRI occurring at the end of the care pathway. Among women receiving an MRI postdiagnosis, 26% had a subsequent biopsy compared with 51% receiving a subsequent biopsy in the subgroup without MRI. CONCLUSIONS: Older women who receive breast MRI undergo additional breast imaging and biopsy events. There is much variability in the diagnostic/preoperative work-up in older women, demonstrating the opportunity to increase standardization to optimize care for all women.

Costs of diagnostic and preoperative workup with and without breast MRI in older women with a breast cancer diagnosis.

BACKGROUND: Breast cancer in the U.S. - estimated at 232,670 incident cases in 2014 - has the highest aggregate economic burden of care relative to other female cancers. Yet, the amount of cost attributed to diagnostic/preoperative work up has not been characterized. We examined the costs of imaging and biopsy among women enrolled in Medicare who did and did not receive diagnostic/preoperative Magnetic Resonance Imaging (MRI). METHODS: Using Surveillance, Epidemiology and End Results (SEER)- Medicare data, we compared the per capita costs (PCC) based on amount paid, between diagnosis date and primary surgical treatment for a breast cancer diagnosis (2005-2009) with and without diagnostic/preoperative MRI. We compared the groups with and without MRI using multivariable models, adjusting for woman and tumor characteristics. RESULTS: Of the 53,653 women in the cohort, within the diagnostic/preoperative window, 20 % (N = 10,776) received diagnostic/preoperative MRI. Total unadjusted median costs were almost double for women with MRI vs. without ($2,251 vs. $1,152). Adjusted costs were higher among women receiving MRI, with significant differences in total costs ($1,065), imaging costs ($928), and biopsies costs ($138). CONCLUSION: Costs of diagnostic/preoperative workups among women with MRI are higher than those without. Using these cost estimates in comparative effectiveness models should be considered when assessing the benefits and harms of diagnostic/preoperative MRI.

Availability of Advanced Breast Imaging at Screening Facilities Serving Vulnerable Populations.

OBJECTIVE: Among vulnerable women, unequal access to advanced breast imaging modalities beyond screening mammography may lead to delays in cancer diagnosis and unfavourable outcomes. We aimed to compare on-site availability of advanced breast imaging services (ultrasound, magnetic resonance imaging [MRI], and image-guided biopsy) between imaging facilities serving vulnerable patient populations and those serving non-vulnerable populations. SETTING: 73 imaging facilities across five Breast Cancer Surveillance Consortium regional registries in the United States during 2011 and 2012. METHODS: We examined facility and patient characteristics across a large, national sample of imaging facilities and patients served. We characterized facilities as serving vulnerable populations based on the proportion of mammograms performed on women with lower educational attainment, lower median income, racial/ethnic minority status, and rural residence.We performed multivariable logistic regression to determine relative risks of on-site availability of advanced imaging at facilities serving vulnerable women versus facilities serving non-vulnerable women. RESULTS: Facilities serving vulnerable populations were as likely (Relative risk [RR] for MRI = 0.71, 95% Confidence Interval [CI] 0.42, 1.19; RR for MRI-guided biopsy = 1.07 [0.61, 1.90]; RR for stereotactic biopsy = 1.18 [0.75, 1.85]) or more likely (RR for ultrasound = 1.38 [95% CI 1.09, 1.74]; RR for ultrasound-guided biopsy = 1.67 [1.30, 2.14]) to offer advanced breast imaging services as those serving non-vulnerable populations. CONCLUSIONS: Advanced breast imaging services are physically available on-site for vulnerable women in the United States, but it is unknown whether factors such as insurance coverage or out-of-pocket costs might limit their use.

Factors Associated with Preoperative Magnetic Resonance Imaging Use among Medicare Beneficiaries with Nonmetastatic Breast Cancer.

Preoperative breast magnetic resonance imaging (MRI) use among Medicare beneficiaries with breast cancer has substantially increased from 2005 to 2009. We sought to identify factors associated with preoperative breast MRI use among women diagnosed with ductal carcinoma in situ (DCIS) or stage I-III invasive breast cancer (IBC). Using Surveillance, Epidemiology, and End Results and Medicare data from 2005 to 2009 we identified women ages 66 and older with DCIS or stage I-III IBC who underwent breast-conserving surgery or mastectomy. We compared preoperative breast MRI use by patient, tumor and hospital characteristics stratified by DCIS and IBC using multivariable logistic regression. From 2005 to 2009, preoperative breast MRI use increased from 5.9% to 22.4% of women diagnosed with DCIS and 7.0% to 24.3% of women diagnosed with IBC. Preoperative breast MRI use was more common among women who were younger, married, lived in higher median income zip codes and had no comorbidities. Among women with IBC, those with lobular disease, smaller tumors (<1 cm) and those with estrogen receptor negative tumors were more likely to receive preoperative breast MRI. Women with DCIS were more likely to receive preoperative MRI if tumors were larger (>2 cm). The likelihood of receiving preoperative breast MRI is similar for women diagnosed with DCIS and IBC. Use of MRI is more common in women with IBC for tumors that are lobular and smaller while for DCIS MRI is used for evaluation of larger lesions.

Accuracy of 3 T versus 1.5 T breast MRI for pre-operative assessment of extent of disease in newly diagnosed DCIS.

OBJECTIVES: While 3T breast magnetic resonance imaging has increased in use over the past decade, there is little data comparing its use for assessing ductal carcinoma in situ (DCIS) versus 1.5 T. We sought to compare the accuracies of DCIS extent of disease measures on pre-operative 3T versus 1.5 T MRI. METHODS: This institutional review board-approved prospective study included 20 patients with ductal carcinoma in situ diagnosed by core needle biopsy (CNB) who underwent pre-operative breast MRI at both 3T (resolution=0.5 mm×0.5 mm×1.3 mm) and 1.5 T (0.85 mm×0.85 mm×1.6 mm). All patients provided informed consent, and the study was HIPPA compliant. Lesion sizes and imaging characteristics (morphologic and kinetic enhancement) were recorded for the 3 T and 1.5 T examinations. Lesion size measures at both field strengths were correlated to final pathology, and imaging characteristics also were compared. RESULTS: Of the initial cohort of 20 patients with CNB-diagnosed DCIS, 19 underwent definitive surgery. Median DCIS sizes of these 19 patients were 6mm (range: 0-67 mm) on 3T, 13 mm (0-60 mm) on 1.5 T, and 6mm (0-55 mm) on surgical pathology. Size correlation between MRI and pathology was higher for 3T (Spearman's ρ=0.66, p=0.002) than 1.5 T (ρ=0.36, p=0.13). In 10 women in which a residual area of suspicious enhancement was identified on both field strengths, there was agreement of morphologic description (NME vs. mass) in nine, and no significant difference in dynamic contrast enhanced kinetics at 3T compared to 1.5 T. CONCLUSIONS: Pre-operative breast MRI at 3T provided higher correlation with final pathology size of DCIS lesions compared to 1.5 T, and may be more accurate for assessment of disease extent prior to definitive surgery.

Geographic access to breast imaging for US women.

PURPOSE: The breast imaging modalities of mammography, ultrasound, and MRI are widely used for screening, diagnosis, treatment, and surveillance of breast cancer. Geographic access to breast imaging services in various modalities is not known at a national level overall or for population subgroups. METHODS: A retrospective study of 2004-2008 Medicare claims data was conducted to identify ZIP codes in which breast imaging occurred, and data were mapped. Estimated travel times were made for each modality for 215,798 census block groups in the contiguous United States. Using Census 2010 data, travel times were characterized by sociodemographic factors for 92,788,909 women aged ≥30 years, overall, and by subgroups of age, race/ethnicity, rurality, education, and median income. RESULTS: Overall, 85% of women had travel times of ≤20 minutes to nearest mammography or ultrasound services, and 70% had travel times of ≤20 minutes for MRI with little variation by age. Native American women had median travel times 2-3 times longer for all 3 modalities, compared to women of other racial/ethnic groups. For rural women, median travel times to breast imaging services were 4-8-fold longer than they were for urban women. Black and Asian women had the shortest median travel times to services for all 3 modalities. CONCLUSIONS: Travel times to mammography and ultrasound breast imaging facilities are short for most women, but for breast MRI, travel times are notably longer. Native American and rural women are disadvantaged in geographic access based on travel times to breast imaging services. This work informs potential interventions to reduce inequities in access and utilization.

In vivo assessment of ductal carcinoma in situ grade: a model incorporating dynamic contrast-enhanced and diffusion-weighted breast MR imaging parameters.

PURPOSE: To develop a model incorporating dynamic contrast material-enhanced (DCE) and diffusion-weighted (DW) magnetic resonance (MR) imaging features to differentiate high-nuclear-grade (HNG) from non-HNG ductal carcinoma in situ (DCIS) in vivo. MATERIALS AND METHODS: This HIPAA-compliant study was approved by the institutional review board and requirement for informed consent was waived. A total of 55 pure DCIS lesions (19 HNG, 36 non-HNG) in 52 women who underwent breast MR imaging at 1.5 T with both DCE and DW imaging (b = 0 and 600 sec/mm(2)) were retrospectively reviewed. The following lesion characteristics were recorded or measured: DCE morphology, DCE maximum lesion size, peak initial enhancement at 90 seconds, worst-curve delayed enhancement kinetics, apparent diffusion coefficient (ADC), contrast-to-noise ratio (CNR) at DW imaging with b values of 0 and 600 sec/mm(2), and T2 signal effects (measured with CNR at b = 0 sec/mm(2)). Univariate and stepwise multivariate logistic regression modeling was performed to identify MR imaging features that optimally discriminated HNG from non-HNG DCIS. Discriminative abilities of models were compared by using the area under the receiver operating characteristic curve (AUC). RESULTS: HNG lesions exhibited larger mean maximum lesion size (P = .02) and lower mean CNR for images with b value of 600 sec/mm(2) (P = .004), allowing discrimination of HNG from non-HNG DCIS (AUC = 0.71 for maximum lesion size, AUC = 0.70 for CNR at b = 600 sec/mm(2)). Differences in CNR for images with b value of 0 sec/mm(2) (P = .025) without corresponding differences in ADC values were observed between HNG and non-HNG lesions. Peak initial enhancement was the only kinetic variable to approach significance (P = .05). No differences in lesion morphology (P = .11) or worst-curve delayed enhancement kinetics (P = .97) were observed. A multivariate model combining CNR for images with b value of 600 sec/mm(2) and maximum lesion size most significantly discriminated HNG from non-HNG (AUC = 0.81). CONCLUSION: The preliminary findings suggest that DCE and DW MR imaging features may aid in identifying patients with high-risk DCIS. Further study may yield a model combining MR characteristics with histopathologic data to facilitate lesion-specific targeted therapies. © RSNA, 2012.

Computer-aided detection applied to breast MRI: assessment of CAD-generated enhancement and tumor sizes in breast cancers before and after neoadjuvant chemotherapy.

RATIONALE AND OBJECTIVES: MRI has shown promise in assessing breast cancer patients undergoing neoadjuvant chemotherapy. Computer-aided detection (CAD) for MRI can automatically display tumor enhancement parameters. This study was performed to determine the utility of CAD applied to breast MRI in this patient population. MATERIALS AND METHODS: Fifteen patients with 16 newly diagnosed locally advanced breast cancers were evaluated with MRI before and after neoadjuvant chemotherapy. CAD assessments, including presence or absence of significant enhancement, enhancement profiles, and maximum sizes, were recorded. Pre-chemotherapy and post-chemotherapy enhancement profiles were compared. Sizes were compared to those measured by the radiologist and at final pathology. RESULTS: Prior to chemotherapy, all tumors demonstrated CAD-assessed significant enhancement. Following chemotherapy, 7/16 tumors showed no residual significant enhancement, but all had residual disease at pathology. In those patients with residual enhancement, comparison of the post-chemotherapy to pre-chemotherapy CAD enhancement profiles showed a significant decrease in percentage of washout enhancement (P = 0.0147) in patients with less than 5 mm of residual microscopic disease. Radiologist-measured tumor sizes demonstrated better correlation with sizes at pathology (r = 0.60) than did CAD-generated tumor sizes (r = 0.32). CONCLUSION: CAD may be helpful in assessing changes in MRI enhancement profiles of tumors following chemotherapy. However, CAD-assessed significant enhancement following chemotherapy can be falsely negative for residual malignancy, and CAD tumor sizes are less accurate than those measured by the radiologist in predicting size of residual malignancy. CAD may complement but should not replace the radiologist's assessment of tumors in this patient population.