Purpose:To evaluate the diffusion-weighted (DW) imaging characteristics of nonmalignant lesion subtypes assessed as false-positive findings at conventional breast magnetic resonance (MR) imaging. Materials and Methods:This HIPAA-compliant retrospective study had institutional review board approval, and the need for informed patient consent was waived. Lesions assessed as Breast Imaging Reporting and Data System category 4 or 5 at clinical dynamic contrast material-enhanced MR imaging that subsequently proved nonmalignant at biopsy were retrospectively reviewed. One hundred seventy-five nonmalignant breast lesions in 165 women were evaluated. Apparent diffusion coefficients (ADCs) from DW imaging (b = 0, 600 sec/mm 2 ) were calculated for each lesion and were compared between subtypes and with an ADC threshold of 1.81 3 10 23 mm 2 /sec (determined in a prior study to achieve 100% sensitivity). Results:Eighty-one (46%) lesions exhibited ADCs greater than the predetermined threshold. /sec; n = 23) was the most common lesion subtype with ADC below the threshold. Lymph nodes exhibited the lowest mean ADC of all nonmalignant lesions ([1.28 6 0.23] 3 10 23 mm 2 /sec; n = 4). High-risk lesions (atypical ductal hyperplasia and lobular neoplasia) showed significantly lower ADCs than other benign lesions (P , .0001) and were the most common lesions with ADCs below the threshold. Conclusion:Assessing ADC along with dynamic contrast-enhanced MR imaging features may decrease the number of avoidable false-positive findings at breast MR imaging and reduce the number of preventable biopsies.

Background Diffusion-weighted imaging (DWI) can increase breast MRI diagnostic specificity due to the tendency of malignancies to restrict diffusion. Diffusion tensor imaging (DTI) provides further information over conventional DWI regarding diffusion directionality and anisotropy. Our study evaluates DTI features of suspicious breast lesions detected on MRI to determine the added diagnostic value of DTI for breast imaging . Methods With IRB approval, we prospectively enrolled patients over a 3-year period who had suspicious (BI-RADS category 4 or 5) MRI-detected breast lesions with histopathological results. Patients underwent multiparametric 3 T MRI with dynamic contrast-enhanced (DCE) and DTI sequences. Clinical factors (age, menopausal status, breast density, clinical indication, background parenchymal enhancement) and DCE-MRI lesion parameters (size, type, presence of washout, BI-RADS category) were recorded prospectively by interpreting radiologists. DTI parameters (apparent diffusion coefficient [ADC], fractional anisotropy [FA], axial diffusivity [ λ 1 ], radial diffusivity [( λ 2 + λ 3 )/2], and empirical difference [ λ 1 − λ 3 ]) were measured retrospectively. Generalized estimating equations (GEE) and least absolute shrinkage and selection operator (LASSO) methods were used for univariate and multivariate logistic regression, respectively. Diagnostic performance was internally validated using the area under the curve (AUC) with bootstrap adjustment. Results The study included 238 suspicious breast lesions (95 malignant, 143 benign) in 194 women. In univariate analysis, lower ADC, axial diffusivity, and radial diffusivity were associated with malignancy (OR = 0.37–0.42 per 1-SD increase, p < 0.001 for each), as was higher FA (OR = 1.45, p = 0.007). In multivariate analysis, LASSO selected only ADC (OR = 0.41) as a predictor for a DTI-only model, while both ADC (OR = 0.41) and FA (OR = 0.88) were selected for a model combining clinical and imaging parameters. Post-hoc analysis revealed varying association of FA with malignancy depending on the lesion type. The combined model (AUC = 0.81) had a significantly better performance than Clinical/DCE-MRI-only (AUC = 0.76, p < 0.001) and DTI-only (AUC = 0.75, p = 0.002) models. Conclusions DTI significantly improves diagnostic performance in multivariate modeling. ADC is the most important diffusion parameter for distinguishing benign and malignant breast lesions, while anisotropy measures may help further characterize tumor microstructure and microenvironment.

ImportanceDiagnostic delays in breast cancer detection may be associated with later-stage disease and higher anxiety, but data on multilevel factors associated with diagnostic delay are limited.ObjectiveTo evaluate individual-, neighborhood-, and health care–level factors associated with differences in time from abnormal screening to biopsy among racial and ethnic groups.Design, Setting, and ParticipantsThis prospective cohort study used data from women aged 40 to 79 years who had abnormal results in screening mammograms conducted in 109 imaging facilities across 6 US states between 2009 and 2019. Data were analyzed from February 21 to November 4, 2021.ExposuresIndividual-level factors included self-reported race and ethnicity, age, family history of breast cancer, breast density, previous breast biopsy, and time since last mammogram; neighborhood-level factors included geocoded education and income based on residential zip codes and rurality; and health care–level factors included mammogram modality, screening facility academic affiliation, and facility onsite biopsy service availability. Data were also assessed by examination year.Main Outcome and MeasuresThe main outcome was unadjusted and adjusted relative risk (RR) of no biopsy within 30, 60, and 90 days using sequential log-binomial regression models. A secondary outcome was unadjusted and adjusted median time to biopsy using accelerated failure time models.ResultsA total of 45 186 women (median [IQR] age at screening, 56 [48-65] years) with 46 185 screening mammograms with abnormal results were included. Of screening mammograms with abnormal results recommended for biopsy, 15 969 (34.6%) were not resolved within 30 days, 7493 (16.2%) were not resolved within 60 days, and 5634 (12.2%) were not resolved within 90 days. Compared with White women, there was increased risk of no biopsy within 30 and 60 days for Asian (30 days: RR, 1.66; 95% CI, 1.31-2.10; 60 days: RR, 1.58; 95% CI, 1.15-2.18), Black (30 days: RR, 1.52; 95% CI, 1.30-1.78; 60 days: 1.39; 95% CI, 1.22-1.60), and Hispanic (30 days: RR, 1.50; 95% CI, 1.24-1.81; 60 days: 1.38; 95% CI, 1.11-1.71) women; however, the unadjusted risk of no biopsy within 90 days only persisted significantly for Black women (RR, 1.28; 95% CI, 1.11-1.47). Sequential adjustment for selected individual-, neighborhood-, and health care–level factors, exclusive of screening facility, did not substantially change the risk of no biopsy within 90 days for Black women (RR, 1.27; 95% CI, 1.12-1.44). After additionally adjusting for screening facility, the increased risk for Black women persisted but showed a modest decrease (RR, 1.20; 95% CI, 1.08-1.34).Conclusions and RelevanceIn this cohort study involving a diverse cohort of US women recommended for biopsy after abnormal results on screening mammography, Black women were the most likely to experience delays to diagnostic resolution after adjusting for multilevel factors. These results suggest that adjustment for multilevel factors did not entirely account for differences in time to breast biopsy, but unmeasured factors, such as systemic racism and other health care system factors, may impact timely diagnosis.

Purpose To compare breast MRI B1 homogeneity at 3 Tesla with and without dual-source parallel radiofrequency (RF) excitation. Materials and Methods After institutional review board approval, we evaluated 14 consecutive breast MR examinations performed at 3 Tesla that included 3D B1 maps created separately with conventional single-source and dual-source parallel RF excitation techniques. We measured B1 values (expressed as % of intended B1) on each B1 map at nipple level in multiple bilateral locations: anterior, lateral, central, medial, and posterior. Mean whole breast and location specific B1 values were calculated and compared between right and left breasts using paired t-test. Results Mean whole breast B1 values differed significantly between right and left breasts with standard single-source RF excitation (difference L-R, Δ=9.2%; p<0.001) but not with dual-source parallel RF excitation (Δ=2.3%; p=0.085). Location specific B1 values differed significantly between right and left on single-source in the lateral (p=0.014), central (p=0.0001), medial (p=0.0013), and posterior (p<0.0001) locations. Conversely, mean B1 values differed significantly on dual-source parallel RF excitation for only the anterior (p=0.030) and lateral (p=0.0003) locations. Conclusion B1 homogeneity is improved with dual-source parallel RF excitation on 3T breast MRI when compared to standard single-source RF excitation technique.