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Architectural and dynamic features are important in breast MR imaging interpretation. Multivariate models involving feature assessment have a diagnostic accuracy superior to that of qualitative characterization of the dynamic enhancement pattern.

AMMOGRAPHY IS THE PRImary imaging modality used to detect clinically occult breast cancer. However, mammography has limitations in both sensitivity and specificity that have led to exploration of other imaging techniques. Magnetic resonance imaging (MRI) has been evaluated for breast imaging because of its value for assessing soft tissues of the body. Breast MRI is performed before and after injection of a gadoliniumbased contrast agent. 1,2 Additional lesions seen by MRI that are not visible on the mammogram have been reported to be present in between 27% and 37% of patients. 3,4 The use of MRI to evaluate women with mammographically or clinically suspicious breast lesions who are undergoing biopsy has shown high potential, with the reported sensitivities of MRI for breast cancer from larger single center studies ranging from 88% to 95%. 5-12 Thus, there has been considerable enthusiasm for breast MRI and use of the procedure for Medicare patients increased almost 3-fold between 2001 (3440 examinations) and 2003 (10 115 examinations). 13 However, the reported specificity of MRI is variable, ranging from 30% to For editorial comment see p 2779.

To compare breast cancer detection performance of radiologists reading mammographic examinations unaided versus supported by an artificial intelligence (AI) system. Materials and Methods: An enriched retrospective, fully crossed, multireader, multicase, HIPAA-compliant study was performed. Screening digital mammographic examinations from 240 women (median age, 62 years; range, 39-89 years) performed between 2013 and 2017 were included. The 240 examinations (100 showing cancers, 40 leading to false-positive recalls, 100 normal) were interpreted by 14 Mammography Quality Standards Act-qualified radiologists, once with and once without AI support. The readers provided a Breast Imaging Reporting and Data System score and probability of malignancy. AI support provided radiologists with interactive decision support (clicking on a breast region yields a local cancer likelihood score), traditional lesion markers for computer-detected abnormalities, and an examination-based cancer likelihood score. The area under the receiver operating characteristic curve (AUC), specificity and sensitivity, and reading time were compared between conditions by using mixed-models analysis dof variance and generalized linear models for multiple repeated measurements. Results: On average, the AUC was higher with AI support than with unaided reading (0.89 vs 0.87, respectively; P = .002). Sensitivity increased with AI support (86% [86 of 100] vs 83% [83 of 100]; P = .046), whereas specificity trended toward improvement (79% [111 of 140]) vs 77% [108 of 140]; P = .06). Reading time per case was similar (unaided, 146 seconds; supported by AI, 149 seconds; P = .15). The AUC with the AI system alone was similar to the average AUC of the radiologists (0.89 vs 0.87). Conclusion: Radiologists improved their cancer detection at mammography when using an artificial intelligence system for support, without requiring additional reading time. Published under a CC BY 4.0 license.

This paper summarizes information about breast MRI to be provided to women and referring physicians. After listing contraindications, procedure details are described, stressing the need for correct scheduling and not moving during the examination. The structured report including BI-RADS® categories and further actions after a breast MRI examination are discussed. Breast MRI is a very sensitive modality, significantly improving screening in high-risk women. It also has a role in clinical diagnosis, problem solving, and staging, impacting on patient management. However, it is not a perfect test, and occasionally breast cancers can be missed. Therefore, clinical and other imaging findings (from mammography/ultrasound) should also be considered. Conversely, MRI may detect lesions not visible on other imaging modalities turning out to be benign (false positives). These risks should be discussed with women before a breast MRI is requested/performed. Because breast MRI drawbacks depend upon the indication for the examination, basic information for the most important breast MRI indications is presented. Seventeen notes and five frequently asked questions formulated for use as direct communication to women are provided. The text was reviewed by Europa Donna–The European Breast Cancer Coalition to ensure that it can be easily understood by women undergoing MRI.Key Points• Information on breast MRI concerns advantages/disadvantages and preparation to the examination• Claustrophobia, implantable devices, allergic predisposition, and renal function should be checked• Before menopause, scheduling on day 7–14 of the cycle is preferred• During the examination, it is highly important that the patient keeps still• Availability of prior examinations improves accuracy of breast MRI interpretationElectronic supplementary materialThe online version of this article (doi:10.1007/s00330-015-3807-z) contains supplementary material, which is available to authorized users.