Purpose To determine if the change in tumor apparent diffusion coefficient (ADC) at diffusion-weighted (DW) MRI is predictive of pathologic complete response (pCR) to neoadjuvant chemotherapy for breast cancer. Materials and Methods In this prospective multicenter study, 272 consecutive women with breast cancer were enrolled at 10 institutions (from August 2012 to January 2015) and were randomized to treatment with 12 weekly doses of paclitaxel (with or without an experimental agent), followed by 12 weeks of treatment with four cycles of anthracycline. Each woman underwent breast DW MRI before treatment, at early treatment (3 weeks), at midtreatment (12 weeks), and after treatment. Percentage change in tumor ADC from that before treatment (ΔADC) was measured at each time point. Performance for predicting pCR was assessed by using the area under the receiver operating characteristic curve (AUC) for the overall cohort and according to tumor hormone receptor (HR)/human epidermal growth factor receptor 2 (HER2) disease subtype. Results The final analysis included 242 patients with evaluable serial imaging data, with a mean age of 48 years ± 10 (standard deviation); 99 patients had HR-positive (hereafter, HR+)/HER2-negative (hereafter, HER2-) disease, 77 patients had HR-/HER2- disease, 42 patients had HR+/HER2+ disease, and 24 patients had HR-/HER2+ disease. Eighty (33%) of 242 patients experienced pCR. Overall, ΔADC was moderately predictive of pCR at midtreatment/12 weeks (AUC = 0.60; 95% confidence interval [CI]: 0.52, 0.68; P = .017) and after treatment (AUC = 0.61; 95% CI: 0.52, 0.69; P = .013). Across the four disease subtypes, midtreatment ΔADC was predictive only for HR+/HER2- tumors (AUC = 0.76; 95% CI: 0.62, 0.89; P < .001). In a test subset, a model combining tumor subtype and midtreatment ΔADC improved predictive performance (AUC = 0.72; 95% CI: 0.61, 0.83) over ΔADC alone (AUC = 0.57; 95% CI: 0.44, 0.70; P = .032.). Conclusion After 12 weeks of therapy, change in breast tumor apparent diffusion coefficient at MRI predicts complete pathologic response to neoadjuvant chemotherapy. © RSNA, 2018 Online supplemental material is available for this article.

The use of neoadjuvant systemic therapy in the treatment of breast cancer patients is increasing beyond the scope of locally advanced disease. Imaging provides important information in assessing response to therapy as a complement to conventional tumor measurements via physical examination. The purpose of this article is to discuss the advantages and limitations of current assessment methods, as well as review functional and molecular imaging approaches being investigated as emerging techniques for evaluating neoadjuvant therapy response for patients with primary breast cancer. RSNA, 2017.

Purpose: Conventional breast MRI is highly sensitive for cancer detection but prompts some false-positives. We performed a prospective, multicenter study to determine whether apparent diffusion coefficients (ADCs) from diffusion weighted imaging (DWI) can decrease MRI false-positives. Experimental Design: 107 women with MRI-detected BI-RADS 3, 4, or 5 lesions were enrolled from March 2014 to April 2015. ADCs were measured both centrally and at participating sites. Receiver operating characteristic (ROC) analysis was employed to assess diagnostic performance of centrally-measured ADCs and identify optimal ADC thresholds to reduce unnecessary biopsies. Lesion reference standard was based on either definitive biopsy result or at least 337 days of follow-up after the initial MRI procedure. Results: Of 107 women enrolled, 67 patients (median age 49, range 24–75 years) with 81 lesions with confirmed reference standard (28 malignant, 53 benign) and evaluable DWI were analyzed. 67/81 lesions were BI-RADS 4 (n=63) or 5 (n=4) and recommended for biopsy. Malignancies exhibited lower mean centrally-measured ADCs (mm2/s) than benign lesions (1.21×10−3 vs.1.47×10−3, p<0.0001, area under ROC curve=0.75, 95% confidence interval [CI] 0.65–0.84). In centralized analysis, application of an ADC threshold (1.53×10−3 mm2/s) lowered the biopsy rate by 20.9% (14/67; 95% CI 11.2–31.2%) without affecting sensitivity. Application of a more conservative threshold (1.68×10−3mm2/s) to site-derived ADCs reduced the biopsy rate by 26.2%(16/61) but missed three cancers. Conclusion: DWI can re-classify a substantial fraction of suspicious breast MRI findings as benign and thereby decrease unnecessary biopsies. ADC thresholds identified in this trial should be validated in future Phase III studies.

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The histogram method is far more sensitive than the 10-HU threshold method for diagnosis of adrenal adenomas at enhanced CT, with specificity maintained at 100%.

Background Quantitative diffusion‐weighted imaging (DWI) MRI is a promising technique for cancer characterization and treatment monitoring. Knowledge of the reproducibility of DWI metrics in breast tumors is necessary to apply DWI as a clinical biomarker. Purpose To evaluate the repeatability and reproducibility of breast tumor apparent diffusion coefficient (ADC) in a multi‐institution clinical trial setting, using standardized DWI protocols and quality assurance (QA) procedures. Study Type Prospective. Subjects In all, 89 women from nine institutions undergoing neoadjuvant chemotherapy for invasive breast cancer. Field Strength/Sequence DWI was acquired before and after patient repositioning using a four b‐value, single‐shot echo‐planar sequence at 1.5T or 3.0T. Assessment A QA procedure by trained operators assessed artifacts, fat suppression, and signal‐to‐noise ratio, and determine study analyzability. Mean tumor ADC was measured via manual segmentation of the multislice tumor region referencing DWI and contrast‐enhanced images. Twenty cases were evaluated multiple times to assess intra‐ and interoperator variability. Segmentation similarity was assessed via the Sørenson–Dice similarity coefficient. Statistical Tests Repeatability and reproducibility were evaluated using within‐subject coefficient of variation (wCV), intraclass correlation coefficient (ICC), agreement index (AI), and repeatability coefficient (RC). Correlations were measured by Pearson's correlation coefficients. Results In all, 71 cases (80%) passed QA evaluation: 44 at 1.5T, 27 at 3.0T; 60 pretreatment, 11 after 3 weeks of taxane‐based treatment. ADC repeatability was excellent: wCV = 4.8% (95% confidence interval [CI] 4.0, 5.7%), ICC = 0.97 (95% CI 0.95, 0.98), AI = 0.83 (95% CI 0.76, 0.87), and RC = 0.16 * 10−3 mm2/sec (95% CI 0.13, 0.19). The results were similar across field strengths and timepoint subgroups. Reproducibility was excellent: interreader ICC = 0.92 (95% CI 0.80, 0.97) and intrareader ICC = 0.91 (95% CI 0.78, 0.96). Data Conclusion Breast tumor ADC can be measured with excellent repeatability and reproducibility in a multi‐institution setting using a standardized protocol and QA procedure. Improvements to DWI image quality could reduce loss of data in clinical trials. Level of Evidence: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;49:1617–1628.

All of the 73 seeds placed in the first 4 months of clinical use were successfully placed and all were successfully retrieved intraoperatively. The mean time from seed placement to surgery was 3 days. Early clinical experience suggests that Magseed is an effective and accurate means of preoperative breast lesion localization.

In anticipation of breast density notification legislation in the state of California, which would require notification of women with heterogeneously and extremely dense breast tissue, a working group of breast imagers and breast cancer risk specialists was formed to provide a common response framework. The California Breast Density Information Group identified key elements and implications of the law, researching scientific evidence needed to develop a robust response. In particular, issues of risk associated with dense breast tissue, masking of cancers by dense tissue on mammograms, and the efficacy, benefits, and harms of supplementary screening tests were studied and consensus reached. National guidelines and peer-reviewed published literature were used to recommend that women with dense breast tissue at screening mammography follow supplemental screening guidelines based on breast cancer risk assessment. The goal of developing educational materials for referring clinicians and patients was reached with the construction of an easily accessible Web site that contains information about breast density, breast cancer risk assessment, and supplementary imaging. This multi-institutional, multidisciplinary approach may be useful for organizations to frame responses as similar legislation is passed across the United States. Online supplemental material is available for this article.