Motion artifacts, lesion type, and parenchymal enhancement in breast MRI: what does really influence diagnostic accuracy?

BACKGROUND: Motion artifacts can reduce image quality of breast magnetic resonance imaging (MRI). There is a lack of data regarding their effect on diagnostic estimates. PURPOSE: To evaluate factors that potentially influence readers' diagnostic estimates in breast MRI: motion artifacts; amount of fibroglandular tissue; background parenchymal enhancement; lesion size; and lesion type. MATERIAL AND METHODS: This Institutional Review Board-approved, retrospective, cross-sectional, single-center study included 320 patients (mean age = 55.1 years) with 334 histologically verified breast lesions (139 benign, 195 malignant) who underwent breast MRI. Two expert breast radiologists evaluated the images considering: motion artifacts (1 = minimal to 4 = marked); fibroglandular tissue (BI-RADS FGT); background parenchymal enhancement (BI-RADS BPE); lesion size; lesion type; and BI-RADS score. Univariate (Chi-square) and multivariate (Generalized Estimation Equations [GEE]) statistics were used to identify factors influencing sensitivity, specificity, and accuracy. RESULTS: Lesions were: 230 mass (68.9%) and 59 non-mass (17.7%), no foci. Forty-five lesions (13.5%) did not enhance in MRI but were suspicious or unclear in conventional imaging. Sensitivity, specificity, and accuracy were 93.8%, 83.4%, and 89.8% for Reader 1 and 95.4%, 87.8%, and 91.9% for Reader 2. Lower sensitivity was observed in case of increased motion artifacts ( P = 0.007), non-mass lesions ( P < 0.001), and small lesions ≤ 10 mm ( P < 0.021). No further factors (e.g. BPE, FGT) significantly influenced diagnostic estimates. At multivariate analysis, lesion type and size were retained as independent factors influencing the diagnostic performance ( P < 0.033). CONCLUSION: Motion artifacts can impair lesion characterization with breast MRI, but lesion type and small size have the strongest influence on diagnostic estimates.

Differentiation of ductal carcinoma in situ versus fibrocystic changes by magnetic resonance imaging: are there pathognomonic imaging features?

Background In breast magnetic resonance imaging (MRI), the diagnosis of ductal carcinoma in situ (DCIS) remains controversial; the most challenging cause of false-positive DCIS diagnosis is fibrocystic changes (FC). Purpose To search for typical and pathognomonic patterns of DCIS and FC using a standard clinical MRI protocol. Material and Methods Consecutive patients scheduled for breast MRI (standardized protocols @ 1.5T: dynamic-T1-GRE before/after Gd-DTPA [0.1 mmol/kg body weight (BW)]; T1-TSE), with subsequent pathological sampling, were investigated. Sixteen MRI descriptors were prospectively assessed by two experienced radiologists in consensus (blinded to pathology) and explored in patients with DCIS (n = 77) or FC (n = 219). Univariate and multivariate statistics were performed to identify the accuracy of descriptors (alone, combined). Furthermore, pathognomonic descriptor-combinations with an accuracy of 100% were explored (χ2 statistics; decision trees). Results Six breast MRI descriptors significantly differentiated DCIS from FC ( Pcorrected < 0.05; odds ratio < 7.9). Pathognomonic imaging features were present in 33.8% (n = 100) of all cases allowing the identification of 42.9% of FC (n = 94). Conclusion Pathognomonic patterns of DCIS and FC were frequently observed in a standard clinical MRI protocol. Such imaging patterns could decrease the false-positive rate of breast MRI and hence might help to decrease the number of unnecessary biopsies in this clinically challenging subgroup.

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.

Diffusion-Weighted Imaging With Apparent Diffusion Coefficient Mapping for Breast Cancer Detection as a Stand-Alone Parameter: Comparison With Dynamic Contrast-Enhanced and Multiparametric Magnetic Resonance Imaging.

PURPOSE: The aims of this study were to compare dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) with diffusion-weighted imaging (DWI) with apparent diffusion coefficient mapping as a stand-alone parameter without any other supportive sequence for breast cancer detection and to assess its combination as multiparametric MRI (mpMRI) of the breast. MATERIALS AND METHODS: In this institutional review board-approved single-center study, prospectively acquired data of 106 patients who underwent breast MRI from 12/2010 to 09/2014 for an imaging abnormality (Breast Imaging Reporting and Data System 0, 4/5) were retrospectively analyzed. Four readers independently assessed DWI and DCE as well as combined as mpMRI. Breast Imaging Reporting and Data System categories, lesion size, and mean apparent diffusion coefficient values were recorded. Histopathology was used as the gold standard. Appropriate statistical tests were used to compare diagnostic values. RESULTS: There were 69 malignant and 41 benign tumors in 106 patients. Four patients presented with bilateral lesions. Dynamic contrast-enhanced MRI was the most sensitive test for breast cancer detection, with an average sensitivity of 100%. Diffusion-weighted imaging alone was less sensitive (82%; P < 0.001) but more specific than DCE-MRI (86.8% vs 76.6%; P = 0.002). Diagnostic accuracy was 83.7% for DWI and 90.6% for DCE-MRI. Multiparametric MRI achieved a sensitivity of 96.8%, not statistically different from DCE-MRI (P = 0.12) and with a similar specificity as DWI (83.8%; P = 0.195), maximizing diagnostic accuracy to 91.9%. There was almost perfect interreader agreement for DWI (κ = 0.864) and DCE-MRI (κ = 0.875) for differentiation of benign and malignant lesions. CONCLUSION: Dynamic contrast-enhanced MRI is most sensitive for breast cancer detection and thus still indispensable. Multiparametric MRI using DCE-MRI and DWI maintains a high sensitivity, increases specificity, and maximizes diagnostic accuracy, often preventing unnecessary breast biopsies. Diffusion-weighted imaging should not be used as a stand-alone parameter because it detects significantly fewer cancers in comparison with DCE-MRI and mpMRI.