Comparison of Contrast-enhanced Mammography with MRI Utilizing an Enriched Reader Study: A Breast Cancer Study (CONTRRAST Trial).

Background Despite growing interest in using contrast-enhanced mammography (CEM) for breast cancer screening as an alternative to breast MRI, limited literature is available. Purpose To determine whether CEM is noninferior to breast MRI or abbreviated breast MRI (AB MRI) and superior to two-dimensional mammography in an asymptomatic population simulating those who would present for screening and then undergo diagnostic work-up. Materials and Methods This enriched reader study used CEM and MRI data prospectively collected from asymptomatic individuals at a single institution from December 2014 to March 2020. Case sets were obtained at screening, as part of work-up for a screening-detected finding, or before biopsy of a screening-detected abnormality. All images were anonymized and randomized, and all 12 radiologists interpreted them. For CEM interpretation, readers were first shown low-energy images as a surrogate for digital mammography and asked to give a forced Breast Imaging Reporting and Data System score for up to three abnormalities. The highest score was used as the case score. Readers then reviewed the full CEM examination and scored it similarly. After a minimum 1-month washout, the readers similarly interpreted AB MRI and full MRI examinations. Receiver operating characteristic analysis, powered to test CEM noninferiority to full MRI, was performed. Results The study included 132 case sets (14 negative, 74 benign, and 44 malignant; all female participants; mean age, 54 years ± 12 [SD]). The mean areas under the receiver operating characteristic curve (AUCs) for digital mammography, CEM, AB MRI, and full MRI were 0.79, 0.91, 0.89, and 0.91, respectively. CEM was superior to digital mammography (P < .001). No evidence of a difference in AUC was found between CEM and AB MRI and MRI. Conclusion In an asymptomatic study sample, CEM was noninferior to full MRI and AB MRI and was superior to digital mammography. Clinical trial registration no. NCT03482557 and NCT02275871 © RSNA, 2023 Supplemental material is available for this article.

Discrimination of benign from malignant breast lesions in dense breasts with model-based analysis of regions-of-interest using directional diffusion-weighted images.

BACKGROUND: There is an increasing interest in non-contrast-enhanced magnetic resonance imaging (MRI) for detecting and evaluating breast lesions. We present a methodology utilizing lesion core and periphery region of interest (ROI) features derived from directional diffusion-weighted imaging (DWI) data to evaluate performance in discriminating benign from malignant lesions in dense breasts. METHODS: We accrued 55 dense-breast cases with 69 lesions (31 benign; 38 cancer) at a single institution in a prospective study; cases with ROIs exceeding 7.50 cm2 were excluded, resulting in analysis of 50 cases with 63 lesions (29 benign, 34 cancers). Spin-echo echo-planar imaging DWI was acquired at 1.5 T and 3 T. Data from three diffusion encoding gradient directions were exported and processed independently. Lesion ROIs were hand-drawn on DWI images by two radiologists. A region growing algorithm generated 3D lesion models on augmented apparent-diffusion coefficient (ADC) maps and defined lesion core and lesion periphery sub-ROIs. A lesion-core and a lesion-periphery feature were defined and combined into an overall classifier whose performance was compared to that of mean ADC using receiver operating characteristic (ROC) analysis. Inter-observer variability in ROI definition was measured using Dice Similarity Coefficient (DSC). RESULTS: The region-growing algorithm for 3D lesion model generation improved inter-observer variability over hand drawn ROIs (DSC: 0.66 vs 0.56 (p < 0.001) with substantial agreement (DSC > 0.8) in 46% vs 13% of cases, respectively (p < 0.001)). The overall classifier improved discrimination over mean ADC, (ROC- area under the curve (AUC): 0.85 vs 0.75 and 0.83 vs 0.74 respectively for the two readers). CONCLUSIONS: A classifier generated from directional DWI information using lesion core and lesion periphery information separately can improve lesion discrimination in dense breasts over mean ADC and should be considered for inclusion in computer-aided diagnosis algorithms. Our model-based ROIs could facilitate standardization of breast MRI computer-aided diagnostics (CADx).

MRI, Clinical Examination, and Mammography for Preoperative Assessment of Residual Disease and Pathologic Complete Response After Neoadjuvant Chemotherapy for Breast Cancer: ACRIN 6657 Trial.

OBJECTIVE: The objective of our study was to determine the accuracy of preoperative measurements for detecting pathologic complete response (CR) and assessing residual disease after neoadjuvant chemotherapy (NACT) in patients with locally advanced breast cancer. SUBJECTS AND METHODS: The American College of Radiology Imaging Network 6657 Trial prospectively enrolled women with ≥ 3 cm invasive breast cancer receiving NACT. Preoperative measurements of residual disease included longest diameter by mammography, MRI, and clinical examination and functional volume on MRI. The accuracy of preoperative measurements for detecting pathologic CR and the association with final pathology size were assessed for all lesions, separately for single masses and nonmass enhancements (NMEs), multiple masses, and lesions without ductal carcinoma in situ (DCIS). RESULTS: In the 138 women with all four preoperative measures, longest diameter by MRI showed the highest accuracy for detecting pathologic CR for all lesions and NME (AUC = 0.76 and 0.84, respectively). There was little difference across preoperative measurements in the accuracy of detecting pathologic CR for single masses (AUC = 0.69-0.72). Longest diameter by MRI and longest diameter by clinical examination showed moderate ability for detecting pathologic CR for multiple masses (AUC = 0.78 and 0.74), and longest diameter by MRI and longest diameter by mammography showed moderate ability for detecting pathologic CR for tumors without DCIS (AUC = 0.74 and 0.71). In subjects with residual disease, longest diameter by MRI exhibited the strongest association with pathology size for all lesions and single masses (r = 0.33 and 0.47). Associations between preoperative measures and pathology results were not significantly influenced by tumor subtype or mammographic density. CONCLUSION: Our results indicate that measurement of longest diameter by MRI is more accurate than by mammography and clinical examination for preoperative assessment of tumor residua after NACT and may improve surgical planning.

MR spectroscopy of breast cancer for assessing early treatment response: Results from the ACRIN 6657 MRS trial.

PURPOSE: To estimate the accuracy of predicting response to neoadjuvant chemotherapy (NACT) in patients with locally advanced breast cancer using MR spectroscopy (MRS) measurements made very early in treatment. MATERIALS AND METHODS: This prospective Health Insurance Portability and Accountability Act (HIPAA)-compliant protocol was approved by the American College of Radiology and local-site institutional review boards. One hundred nineteen women with invasive breast cancer of ≥3 cm undergoing NACT were enrolled between September 2007 and April 2010. MRS measurements of the concentration of choline-containing compounds ([tCho]) were performed before the first chemotherapy regimen (time point 1, TP1) and 20-96 h after the first cycle of treatment (TP2). The change in [tCho] was assessed for its ability to predict pathologic complete response (pCR) and radiologic response using the area under the receiver operating characteristic curve (AUC) and logistic regression models. RESULTS: Of the 119 subjects enrolled, only 29 cases (24%) with eight pCRs provided usable data for the primary analysis. Technical challenges in acquiring quantitative MRS data in a multi-site trial setting limited the capture of usable data. In this limited data set, the decrease in tCho from TP1 to TP2 had poor ability to predict either pCR (AUC = 0.53, 95% confidence interval [CI]: 0.27-0.79) or radiologic response (AUC = 0.51, 95% CI: 0.27-0.75). CONCLUSION: The technical difficulty of acquiring quantitative MRS data in a multi-site clinical trial setting led to a low yield of analyzable data, which was insufficient to accurately measure the ability of early MRS measurements to predict response to NACT. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:290-302.

Neoadjuvant Chemotherapy for Breast Cancer: Functional Tumor Volume by MR Imaging Predicts Recurrence-free Survival-Results from the ACRIN 6657/CALGB 150007 I-SPY 1 TRIAL.

PURPOSE: To evaluate volumetric magnetic resonance (MR) imaging for predicting recurrence-free survival (RFS) after neoadjuvant chemotherapy (NACT) of breast cancer and to consider its predictive performance relative to pathologic complete response (PCR). MATERIALS AND METHODS: This HIPAA-compliant prospective multicenter study was approved by institutional review boards with written informed consent. Women with breast tumors 3 cm or larger scheduled for NACT underwent dynamic contrast-enhanced MR imaging before treatment (examination 1), after one cycle (examination 2), midtherapy (examination 3), and before surgery (examination 4). Functional tumor volume (FTV), computed from MR images by using enhancement thresholds, and change from baseline (ΔFTV) were measured after one cycle and before surgery. Association of RFS with FTV was assessed by Cox regression and compared with association of RFS with PCR and residual cancer burden (RCB), while controlling for age, race, and hormone receptor (HR)/ human epidermal growth factor receptor type 2 (HER2) status. Predictive performance of models was evaluated by C statistics. RESULTS: Female patients (n = 162) with FTV and RFS were included. At univariate analysis, FTV2, FTV4, and ΔFTV4 had significant association with RFS, as did HR/HER2 status and RCB class. PCR approached significance at univariate analysis and was not significant at multivariate analysis. At univariate analysis, FTV2 and RCB class had the strongest predictive performance (C statistic = 0.67; 95% confidence interval [CI]: 0.58, 0.76), greater than for FTV4 (0.64; 95% CI: 0.53, 0.74) and PCR (0.57; 95% CI: 0.39, 0.74). At multivariate analysis, a model with FTV2, ΔFTV2, RCB class, HR/HER2 status, age, and race had the highest C statistic (0.72; 95% CI: 0.60, 0.84). CONCLUSION: Breast tumor FTV measured by MR imaging is a strong predictor of RFS, even in the presence of PCR and RCB class. Models combining MR imaging, histopathology, and breast cancer subtype demonstrated the strongest predictive performance in this study.

Men (and Women) in Academic Radiology: How Can We Reduce the Gender Discrepancy?

OBJECTIVE: There is a chronic gender imbalance in academic radiology departments, which could limit our field's ability to foster creative, productive, and innovative environments. We recently reviewed 51 major academic radiology faculty rosters and discovered that 34% of academic radiologists are women, but only 25% of vice chairs and section chiefs and 9% of department chairs are women. CONCLUSION: Active intervention is needed to correct this imbalance, which should start with awareness of the issue, exposing medical students to radiology early in their training, and implementing better mentorship programs for female radiologists.

Impact of computer-aided detection systems on radiologist accuracy with digital mammography.

OBJECTIVE: The purpose of this study was to assess the impact of computer-aided detection (CAD) systems on the performance of radiologists with digital mammograms acquired during the Digital Mammographic Imaging Screening Trial (DMIST). MATERIALS AND METHODS: Only those DMIST cases with proven cancer status by biopsy or 1-year follow-up that had available digital images were included in this multireader, multicase ROC study. Two commercially available CAD systems for digital mammography were used: iCAD SecondLook, version 1.4; and R2 ImageChecker Cenova, version 1.0. Fourteen radiologists interpreted, without and with CAD, a set of 300 cases (150 cancer, 150 benign or normal) on the iCAD SecondLook system, and 15 radiologists interpreted a different set of 300 cases (150 cancer, 150 benign or normal) on the R2 ImageChecker Cenova system. RESULTS: The average AUC was 0.71 (95% CI, 0.66-0.76) without and 0.72 (95% CI, 0.67-0.77) with the iCAD system (p = 0.07). Similarly, the average AUC was 0.71 (95% CI, 0.66-0.76) without and 0.72 (95% CI 0.67-0.77) with the R2 system (p = 0.08). Sensitivity and specificity differences without and with CAD for both systems also were not significant. CONCLUSION: Radiologists in our studies rarely changed their diagnostic decisions after the addition of CAD. The application of CAD had no statistically significant effect on radiologist AUC, sensitivity, or specificity performance with digital mammograms from DMIST.

The Importance of Outcomes Ascertainment for Accurate Assessment of the Mammography Screening Cancer Detection Rate: A Simulation Study.

PURPOSE: Cancer detection rate (CDR), an important metric in the mammography screening audit, is designed to ensure adequate sensitivity. Most practices use biopsy results as the reference standard; however, commonly ascertainment of biopsy results is incomplete. We used simulation to determine the relationship between the cancer ascertainment rate of biopsy (AR-biopsy), CDR estimation, and associated error rates in classifying whether practices and radiologists meet the established ACR benchmark of 2.5 per 1,000. MATERIALS AND METHODS: We simulated screening mammography volume, number of cancers detected, and CDR, using negative binomial and beta-binomial distributions, respectively. Simulations were performed at both the practice and radiologist level. Average CDR was based on linearly rescaling a published CDR by the AR-biopsy. CDR distributions were simulated for AR-biopsy between 5% and 100% in steps of five percentage points and were summarized with boxplots and smoothed histograms over the range of AR-biopsy, to quantify the proportion of practices and radiologists meeting the ACR benchmark at each level of AR-biopsy. RESULTS: Decreasing AR-biopsy led to an increasing probability of categorizing CDR performance as being below the ACR benchmark. Our simulation predicts that at the practice level, an AR-biopsy of 65% categorizes 17.6% below the benchmark (compared to 1.6% at an AR-biopsy of 100%), and at the radiologist level, an AR-biopsy of 65% categorizes 34.7% as being below the benchmark (compared to 11.6% at an AR-biopsy of 100%). CONCLUSIONS: Our simulation demonstrates that decreasing the AR-biopsy (in currently clinically relevant ranges) has the potential to artifactually lower the assessed CDR on both the practice and radiologist levels and may, in turn, increase the chance of erroneous categorization of underperformance per the ACR benchmark.

Prospective Evaluation of the Cost of Performing Breast Imaging Examinations Using a Time-Driven Activity-Based Costing Method: A Single-Center Study.

OBJECTIVE: Measuring the cost of performing breast imaging is difficult in healthcare systems. The purpose of our study was to evaluate this cost using time-driven activity-based costing (TDABC) and to evaluate cost drivers for different exams. METHODS: An IRB-approved, single-center prospective study was performed on 80 female patients presenting for breast screening, diagnostic or biopsy exams from July 2020 to April 2021. Using TDABC, data were collected for each exam type. Included were full-field digital mammography (FFDM), digital breast tomosynthesis (DBT), contrast-enhanced mammography (CEM), US and MRI exams, and stereotactic, US-guided and MRI-guided biopsies. For each exam type, mean cost and relative contributions of equipment, personnel and supplies were calculated. RESULTS: Screening MRI, CEM, US, DBT, and FFDM costs were $249, $120, $83, $28, and $30. Personnel was the major contributor to cost (60.0%-87.0%) for all screening exams except MRI where equipment was the major contributor (62.2%). Diagnostic MRI, CEM, US, and FFDM costs were $241, $123, $70, and $43. Personnel was the major contributor to cost (60.5%-88.6%) for all diagnostic exams except MRI where equipment was the major contributor (61.8%). Costs of MRI-guided, stereotactic and US-guided biopsy were $1611, $826, and $356. Supplies contributed 40.5%-49.8% and personnel contributed 30.7%-55.6% to the total cost of biopsies. CONCLUSION: TDABC provides assessment of actual costs of performing breast imaging. Costs and contributors varied across screening, diagnostic and biopsy exams and modalities. Practices may consider this methodology in understanding costs and making changes directed at cost savings.

Quality control for digital tomosynthesis in the ECOG-ACRIN EA1151 TMIST trial.

BACKGROUND: The Tomosynthesis Mammography Imaging Screening Trial (TMIST), EA1151 conducted by the Eastern Cooperative Oncology Group (ECOG)/American College of Radiology Imaging Network (ACRIN) is a randomized clinical trial designed to assess the effectiveness for breast cancer screening of digital breast tomosynthesis (TM) compared to digital mammography (DM). Equipment from multiple vendors is being used in the study. PURPOSE: For the findings of the study to be valid and capture the true capacities of the two technology types, it is important that all equipment is operated within appropriate parameters with regard to image quality and dose. A harmonized QC program was established by a core physics team. Since there are over 120 trial sites, a centralized, automated QC program was chosen as the most practical design. This report presents results of the weekly QC testing program. A companion paper will review quality monitoring based on data from the headers of the patient images. METHODS: Study images are collected centrally after de-identification using the "TRIAD" application developed by ACR. The core physics team devised and implemented a minimal set of quality control (QC) tests to evaluate the tomosynthesis and 2D mammography systems. Weekly, monthly and annual testing is performed by the site mammography technologists with images submitted directly to the physics core. The weekly physics QC tests are described: SDNR of a low-contrast mass object, artifact spread, spatial resolution, tracking of technical factors, and in-slice noise power spectra. RESULTS: As of December 31, 2022 (5 years), 145 sites with 411 machines had submitted QC data. A total of 136 742 TMIST participant screening imaging studies had been performed. The 5th and 95th percentile mean glandular doses for a single tomosynthesis exposure to a 4.0 cm thick PMMA phantom ("standard breast phantom") were 1.24 and 1.68 mGy respectively. The largest sources of QC non-conformance were: operator error, not following the QC protocol exactly, unreported software updates and preventive maintenance activities that affected QC setpoints. Noise power spectra were measured, however, standardization of performance targets across machine types and software revisions was difficult. Nevertheless, for each machine type, test measurement results were very consistent when the protocol was followed. Deviations in test results were mostly related to software and hardware changes. CONCLUSION: Most systems performed very consistently. Although this is a harmonized program using identical phantoms and testing protocols, it is not appropriate to apply universal threshold or target metrics across the machine types because the systems have different non-linear reconstruction algorithms and image display filters. It was found to be more useful to assess pass/fail criteria in terms of relative deviations from baseline values established when a system is first characterized and after equipment is changed. Generally, systems which needed repair failed suddenly, but in retrospect, for a few cases, drops in SDNR and increases in mAs were observed prior to tube failure. TMIST is registered as NCT03233191 by Clinicaltrials.gov.

Annual screening strategies in BRCA1 and BRCA2 gene mutation carriers: a comparative effectiveness analysis.

BACKGROUND: Although breast cancer screening with mammography and magnetic resonance imaging (MRI) is recommended for breast cancer-susceptibility gene (BRCA) mutation carriers, there is no current consensus on the optimal screening regimen. METHODS: The authors used a computer simulation model to compare 6 annual screening strategies (film mammography [FM], digital mammography [DM], FM and magnetic resonance imaging [MRI] or DM and MRI contemporaneously, and alternating FM/MRI or DM/MRI at 6-month intervals) beginning at ages 25 years, 30 years, 35 years, and 40 years, and 2 strategies of annual MRI with delayed alternating DM/FM versus clinical surveillance alone. Strategies were evaluated without and with mammography-induced breast cancer risk using 2 models of excess relative risk. Input parameters were obtained from the medical literature, publicly available databases, and calibration. RESULTS: Without radiation risk effects, alternating DM/MRI starting at age 25 years provided the highest life expectancy (BRCA1, 72.52 years, BRCA2, 77.63 years). When radiation risk was included, a small proportion of diagnosed cancers was attributable to radiation exposure (BRCA1, <2%; BRCA2, <4%). With radiation risk, alternating DM/MRI at age 25 years or annual MRI at age 25 years/delayed alternating DM at age 30 years was the most effective, depending on the radiation risk model used. Alternating DM/MRI starting at age 25 years also produced the highest number of false-positive screens per woman (BRCA1, 4.5 BRCA2, 8.1). CONCLUSIONS: Annual MRI at age 25 years/delayed alternating DM at age 30 years is probably the most effective screening strategy in BRCA mutation carriers. Screening benefits, associated risks, and personal acceptance of false-positive results should be considered in choosing the optimal screening strategy for individual women.

Locally advanced breast cancer: MR imaging for prediction of response to neoadjuvant chemotherapy--results from ACRIN 6657/I-SPY TRIAL.

PURPOSE: To compare magnetic resonance (MR) imaging findings and clinical assessment for prediction of pathologic response to neoadjuvant chemotherapy (NACT) in patients with stage II or III breast cancer. MATERIALS AND METHODS: The HIPAA-compliant protocol and the informed consent process were approved by the American College of Radiology Institutional Review Board and local-site institutional review boards. Women with invasive breast cancer of 3 cm or greater undergoing NACT with an anthracycline-based regimen, with or without a taxane, were enrolled between May 2002 and March 2006. MR imaging was performed before NACT (first examination), after one cycle of anthracyline-based treatment (second examination), between the anthracycline-based regimen and taxane (third examination), and after all chemotherapy and prior to surgery (fourth examination). MR imaging assessment included measurements of tumor longest diameter and volume and peak signal enhancement ratio. Clinical size was also recorded at each time point. Change in clinical and MR imaging predictor variables were compared for the ability to predict pathologic complete response (pCR) and residual cancer burden (RCB). Univariate and multivariate random-effects logistic regression models were used to characterize the ability of tumor response measurements to predict pathologic outcome, with area under the receiver operating characteristic curve (AUC) used as a summary statistic. RESULTS: Data in 216 women (age range, 26-68 years) with two or more imaging time points were analyzed. For prediction of both pCR and RCB, MR imaging size measurements were superior to clinical examination at all time points, with tumor volume change showing the greatest relative benefit at the second MR imaging examination. AUC differences between MR imaging volume and clinical size predictors at the early, mid-, and posttreatment time points, respectively, were 0.14, 0.09, and 0.02 for prediction of pCR and 0.09, 0.07, and 0.05 for prediction of RCB. In multivariate analysis, the AUC for predicting pCR at the second imaging examination increased from 0.70 for volume alone to 0.73 when all four predictor variables were used. Additional predictive value was gained with adjustments for age and race. CONCLUSION: MR imaging findings are a stronger predictor of pathologic response to NACT than clinical assessment, with the greatest advantage observed with the use of volumetric measurement of tumor response early in treatment.

Comparative effectiveness of positron emission mammography and MRI in the contralateral breast of women with newly diagnosed breast cancer.

OBJECTIVE: The objective of our study was to compare the performance of positron emission mammography (PEM) with that of MRI in the evaluation of the contralateral breast of women with newly diagnosed cancer. SUBJECTS AND METHODS: Four hundred seventy-two women with newly diagnosed breast cancer offered breast-conserving surgery from September 2006 through November 2008 consented to participate in a multicenter protocol. Participants underwent contrast-enhanced breast MRI and 18F-FDG PEM in randomized order, and the examinations were interpreted independently. The performance characteristics of the imaging modalities were compared using the McNemar test and generalized estimating equations. A retrospective blinded review of PEM images was performed by four experienced observers to understand the reasons for false-negatives. RESULTS: Three hundred sixty-seven women (median age, 58 years; age range, 26-93 years) eligible for analysis completed the appropriate follow-up for study inclusion. Fifteen women (4.1%) were found to have contralateral cancer (11 invasive [mean tumor size, 12 mm; median, 10 mm; range, 1-22 mm] and four ductal carcinoma in situ). Of the 15 cases, both PEM and MRI showed three (20%), only MRI showed 11 (73%), and one (6.7%) was found at prophylactic mastectomy. MRI sensitivity at 14 of 15 (93%; 95% CI, 66-94) was higher than PEM at three of 15 (20%; 95% CI, 5.3-46) (p<0.001). On PEM, three additional cancers were seen prospectively but were considered probably benign and two other cancers were visible in retrospect at the site. Of 352 contralateral breasts without cancer, findings were negative or benign on PEM for 335 (95.2%; 95% CI, 92.2-97.0), which is more than MRI at 315 (89.5%; 95% CI, 85.7-92.4; p=0.002). The positive predictive value (PPV) of PEM-prompted biopsies (3/14 [21%]) was not significantly different from the PPV of MRI (15/54 [28%], p=0.58). On blinded retrospective PEM review of the 15 contralateral cancers, PEM findings for 11 (73%) were considered suspicious. CONCLUSION: Contralateral cancer was found in 15 of 367 women (4.1%), with MRI showing 14 (93%). Eleven contralateral cancers (73%) were visible on PEM, but only three (20%) were recognized prospectively as suspicious. Lesions that are visible on PEM should be viewed as suspicious unless known to be benign by prior breast imaging or biopsy.

Detection of breast cancer with addition of annual screening ultrasound or a single screening MRI to mammography in women with elevated breast cancer risk.

CONTEXT: Annual ultrasound screening may detect small, node-negative breast cancers that are not seen on mammography. Magnetic resonance imaging (MRI) may reveal additional breast cancers missed by both mammography and ultrasound screening. OBJECTIVE: To determine supplemental cancer detection yield of ultrasound and MRI in women at elevated risk for breast cancer. DESIGN, SETTING, AND PARTICIPANTS: From April 2004-February 2006, 2809 women at 21 sites with elevated cancer risk and dense breasts consented to 3 annual independent screens with mammography and ultrasound in randomized order. After 3 rounds of both screenings, 612 of 703 women who chose to undergo an MRI had complete data. The reference standard was defined as a combination of pathology (biopsy results that showed in situ or infiltrating ductal carcinoma or infiltrating lobular carcinoma in the breast or axillary lymph nodes) and 12-month follow-up. MAIN OUTCOME MEASURES: Cancer detection rate (yield), sensitivity, specificity, positive predictive value (PPV3) of biopsies performed and interval cancer rate. RESULTS: A total of 2662 women underwent 7473 mammogram and ultrasound screenings, 110 of whom had 111 breast cancer events: 33 detected by mammography only, 32 by ultrasound only, 26 by both, and 9 by MRI after mammography plus ultrasound; 11 were not detected by any imaging screen. Among 4814 incidence screens in the second and third years combined, 75 women were diagnosed with cancer. Supplemental incidence-screening ultrasound identified 3.7 cancers per 1000 screens (95% CI, 2.1-5.8; P < .001). Sensitivity for mammography plus ultrasound was 0.76 (95% CI, 0.65-0.85); specificity, 0.84 (95% CI, 0.83-0.85); and PPV3, 0.16 (95% CI, 0.12-0.21). For mammography alone, sensitivity was 0.52 (95% CI, 0.40-0.64); specificity, 0.91 (95% CI, 0.90-0.92); and PPV3, 0.38 (95% CI, 0.28-0.49; P < .001 all comparisons). Of the MRI participants, 16 women (2.6%) had breast cancer diagnosed. The supplemental yield of MRI was 14.7 per 1000 (95% CI, 3.5-25.9; P = .004). Sensitivity for MRI and mammography plus ultrasound was 1.00 (95% CI, 0.79-1.00); specificity, 0.65 (95% CI, 0.61-0.69); and PPV3, 0.19 (95% CI, 0.11-0.29). For mammography and ultrasound, sensitivity was 0.44 (95% CI, 0.20-0.70, P = .004); specificity 0.84 (95% CI, 0.81-0.87; P < .001); and PPV3, 0.18 (95% CI, 0.08 to 0.34; P = .98). The number of screens needed to detect 1 cancer was 127 (95% CI, 99-167) for mammography; 234 (95% CI, 173-345) for supplemental ultrasound; and 68 (95% CI, 39-286) for MRI after negative mammography and ultrasound results. CONCLUSION: The addition of screening ultrasound or MRI to mammography in women at increased risk of breast cancer resulted in not only a higher cancer detection yield but also an increase in false-positive findings. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT00072501.

Use of BI-RADS 3-probably benign category in the American College of Radiology Imaging Network Digital Mammographic Imaging Screening Trial.

PURPOSE: To determine (a) how often the Breast Imaging Reporting and Data System (BI-RADS) category 3 was used in the American College of Radiology Imaging Network (ACRIN) Digital Mammographic Imaging Screening Trial (DMIST), either at the time of screening mammography or after work-up, (b) how often subjects actually returned for the recommended follow-up examination, and (c) the rate and stages of any malignancies subsequently found in subjects for whom short-term interval follow-up was recommended. MATERIALS AND METHODS: This study was approved by the Institutional Review Board at all institutions where subjects were enrolled. All subjects participating in DMIST gave informed consent and the study was HIPAA-compliant. A total of 47,599 DMIST-eligible and evaluable subjects, all of whom consented to undergo both digital and screen-film mammography, were included in this analysis. Cases referred for short-term interval follow-up based on digital, screen-film, or both imaging examinations were determined. Compliance with the recommendations and the final outcome (malignancy diagnosis at biopsy or no malignancy confirmed through follow-up) of each evaluable case were determined. RESULTS: A total of 1114 of the 47,599 (2.34%) subjects had tumors assigned a BI-RADS 3 category and were recommended to undergo short-interval follow-up. In this study, 791 of 1114 (71%) of the subjects were compliant with the recommendation and returned for short-interval follow-up. Of the women who did not return for short-interval follow-up, 70% (226 of 323) did return for their next annual mammography. Among all subjects whose tumors were assigned a BI-RADS 3 category either at screening mammography or after additional work-up, nine of 1114 (0.81%) were found to have cancer. Of the nine biopsy-proved cancers, six were invasive cancers and three were ductal carcinoma in situ stage Tis-T1c. The invasive cancers were all less than 2 cm in size. CONCLUSION: In DMIST, radiologists used the BI-RADS 3 classification infrequently (2.3% of patients). Tumors assigned a BI-RADS 3 category had a low rate of malignancy. The relatively high rate of noncompliance with short-interval follow-up recommendations (323 of 1114, or 29%) supports prior recommendations that radiologists thoroughly evaluate lesions before placing them in this category.

Breast cancer: comparative effectiveness of positron emission mammography and MR imaging in presurgical planning for the ipsilateral breast.

PURPOSE: To determine the performance of positron emission mammography (PEM), as compared with magnetic resonance (MR) imaging, including the effect on surgical management, in ipsilateral breasts with cancer. MATERIALS AND METHODS: Four hundred seventy-two women with newly diagnosed breast cancer who were offered breast-conserving surgery consented from September 2006 to November 2008 to participate in a multicenter institutional review board-approved, HIPAA-compliant protocol. Participants underwent contrast material-enhanced MR imaging and fluorine 18 fluorodeoxyglucose PEM in randomized order; resultant images were interpreted independently. Added biopsies and changes in surgical procedure for the ipsilateral breast were correlated with histopathologic findings. Performance characteristics were compared by using the McNemar test and generalized estimating equations. RESULTS: Three hundred eighty-eight women (median age, 58 years; age range, 26-93 years; median estimated tumor size, 1.5 cm) completed the study. Additional cancers were found in 82 (21%) women (82 ipsilateral breasts; median tumor size, 0.7 cm). Twenty-eight (34%) of the 82 breasts were identified with both PEM and MR imaging; 21 (26%) breasts, with MR imaging only; 14 (17%) breasts, with PEM only; and seven (8.5%) breasts, with mammography and ultrasonography. Twelve (15%) cases of additional cancer were missed at all imaging examinations. Integration of PEM and MR imaging increased cancer detection-to 61 (74%) of 82 breasts versus 49 (60%) of 82 breasts identified with MR imaging alone (P < .001). Of 306 breasts without additional cancer, 279 (91.2%) were correctly assessed with PEM compared with 264 (86.3%) that were correctly assessed with MR imaging (P = .03). The positive predictive value of biopsy prompted by PEM findings (47 [66%] of 71 cases) was higher than that of biopsy prompted by MR findings (61 [53%] of 116 cases) (P = .016). Of 116 additional cancers, 61 (53%) were depicted by MR imaging and 47 (41%) were depicted by PEM (P = .043). Fifty-six (14%) of the 388 women required mastectomy: 40 (71%) of these women were identified with MR imaging, and 20 (36%) were identified with PEM (P < .001). Eleven (2.8%) women underwent unnecessary mastectomy, which was prompted by only MR findings in five women, by only PEM findings in one, and by PEM and MR findings in five. Thirty-three (8.5%) women required wider excision: 24 (73%) of these women were identified with MR imaging, and 22 (67%) were identified with PEM. CONCLUSION: PEM and MR imaging had comparable breast-level sensitivity, although MR imaging had greater lesion-level sensitivity and more accurately depicted the need for mastectomy. PEM had greater specificity at the breast and lesion levels. Eighty-nine (23%) participants required more extensive surgery: 61 (69%) of these women were identified with MR imaging, and 41 (46%) were identified with PEM (P = .003). Fourteen (3.6%) women had tumors seen only at PEM.