Helga S. Marques

Combined Screening With Ultrasound and Mammography vs Mammography Alone in Women at Elevated Risk of Breast Cancer

CONTEXT Screening ultrasound may depict small, node-negative breast cancers not seen on mammography. OBJECTIVE To compare the diagnostic yield, defined as the proportion of women with positive screen test results and positive reference standard, and performance of screening with ultrasound plus mammography vs mammography alone in women at elevated risk of breast cancer. DESIGN, SETTING, AND PARTICIPANTS From April 2004 to February 2006, 2809 women, with at least heterogeneously dense breast tissue in at least 1 quadrant, were recruited from 21 sites to undergo mammographic and physician-performed ultrasonographic examinations in randomized order by a radiologist masked to the other examination results. Reference standard was defined as a combination of pathology and 12-month follow-up and was available for 2637 (96.8%) of the 2725 eligible participants. MAIN OUTCOME MEASURES Diagnostic yield, sensitivity, specificity, and diagnostic accuracy (assessed by the area under the receiver operating characteristic curve) of combined mammography plus ultrasound vs mammography alone and the positive predictive value of biopsy recommendations for mammography plus ultrasound vs mammography alone. RESULTS Forty participants (41 breasts) were diagnosed with cancer: 8 suspicious on both ultrasound and mammography, 12 on ultrasound alone, 12 on mammography alone, and 8 participants (9 breasts) on neither. The diagnostic yield for mammography was 7.6 per 1000 women screened (20 of 2637) and increased to 11.8 per 1000 (31 of 2637) for combined mammography plus ultrasound; the supplemental yield was 4.2 per 1000 women screened (95% confidence interval [CI], 1.1-7.2 per 1000; P = .003 that supplemental yield is 0). The diagnostic accuracy for mammography was 0.78 (95% CI, 0.67-0.87) and increased to 0.91 (95% CI, 0.84-0.96) for mammography plus ultrasound (P = .003 that difference is 0). Of 12 supplemental cancers detected by ultrasound alone, 11 (92%) were invasive with a median size of 10 mm (range, 5-40 mm; mean [SE], 12.6 [3.0] mm) and 8 of the 9 lesions (89%) reported had negative nodes. The positive predictive value of biopsy recommendation after full diagnostic workup was 19 of 84 for mammography (22.6%; 95% CI, 14.2%-33%), 21 of 235 for ultrasound (8.9%, 95% CI, 5.6%-13.3%), and 31 of 276 for combined mammography plus ultrasound (11.2%; 95% CI. 7.8%-15.6%). CONCLUSIONS Adding a single screening ultrasound to mammography will yield an additional 1.1 to 7.2 cancers per 1000 high-risk women, but it will also substantially increase the number of false positives. TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT00072501.

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.

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.

Cystic Breast Masses and the ACRIN 6666 Experience

Masses due to cystic lesions of the breast are extremely common findings on mammography, ultrasonography, and magnetic resonance imaging. Although many of these lesions can be dismissed as benign simple cysts, requiring intervention only for symptomatic relief, complex cystic and solid masses require biopsy. Perhaps, the most challenging are complicated cysts, that is, cysts with internal debris. When the debris is mobile or a fluid-debris level is seen, complicated cysts can be dismissed as benign findings. As an isolated finding, homogeneous complicated cysts can be classified as probably benign, with intervention only considered with interval development or enlargement, abscess is suspected, or if suspicious features develop. When multiple and bilateral complicated and simple cysts are present (ie, at least three, with at least one in each breast), a benign, BI-RADS 2, assessment is usually appropriate. Clustered microcysts are common benign findings in pre- and perimenopausal women, though short-interval surveillance may be appropriate for many such lesions in post-menopausal women, particularly if the lesion is new or rather small or deep (ie, diagnostic uncertainty).

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.

Accuracy of Soft-Copy Digital Mammography versus That of Screen-Film Mammography according to Digital Manufacturer: ACRIN DMIST Retrospective Multireader Study

PURPOSE To retrospectively compare the accuracy for cancer diagnosis of digital mammography with soft-copy interpretation with that of screen-film mammography for each digital equipment manufacturer, by using results of biopsy and follow-up as the reference standard. MATERIALS AND METHODS The primary HIPAA-compliant Digital Mammographic Imaging Screening Trial (DMIST) was approved by the institutional review board of each study site, and informed consent was obtained. The approvals and consent included use of data for future HIPAA-compliant retrospective research. The American College of Radiology Imaging Network DMIST collected screening mammography studies performed by using both digital and screen-film mammography in 49 528 women (mean age, 54.6 years; range, 19-92 years). Digital mammography systems from four manufacturers (Fischer, Fuji, GE, and Hologic) were used. For each digital manufacturer, a cancer-enriched reader set of women screened with both digital and screen-film mammography in DMIST was constructed. Each reader set contained all cancer-containing studies known for each digital manufacturer at the time of reader set selection, together with a subset of negative and benign studies. For each reader set, six or 12 experienced radiologists attended two randomly ordered reading sessions 6 weeks apart. Each radiologist identified suspicious findings and rated suspicion of breast cancer in identified lesions by using a seven-point scale. Results were analyzed according to digital manufacturer by using areas under the receiver operating characteristic curve (AUCs), sensitivity, and specificity for soft-copy digital and screen-film mammography. Results for Hologic digital are not presented owing to the fact that few cancer cases were available. The implemented design provided 80% power to detect average AUC differences of 0.09, 0.08, and 0.06 for Fischer, Fuji, and GE, respectively. RESULTS No significant difference in AUC, sensitivity, or specificity was found between Fischer, Fuji, and GE soft-copy digital and screen-film mammography. Large reader variations occurred with each modality. CONCLUSION No statistically significant differences were found between soft-copy digital and screen-film mammography for Fischer, Fuji, and GE digital mammography equipment.

Cancer Cases from ACRIN Digital Mammographic Imaging Screening Trial: Radiologist Analysis with Use of a Logistic Regression Model

PURPOSE To determine which factors contributed to the Digital Mammographic Imaging Screening Trial (DMIST) cancer detection results. MATERIALS AND METHODS This project was HIPAA compliant and institutional review board approved. Seven radiologist readers reviewed the film hard-copy (screen-film) and digital mammograms in DMIST cancer cases and assessed the factors that contributed to lesion visibility on both types of images. Two multinomial logistic regression models were used to analyze the combined and condensed visibility ratings assigned by the readers to the paired digital and screen-film images. RESULTS Readers most frequently attributed differences in DMIST cancer visibility to variations in image contrast--not differences in positioning or compression--between digital and screen-film mammography. The odds of a cancer being more visible on a digital mammogram--rather than being equally visible on digital and screen-film mammograms--were significantly greater for women with dense breasts than for women with nondense breasts, even with the data adjusted for patient age, lesion type, and mammography system (odds ratio, 2.28; P < .0001). The odds of a cancer being more visible at digital mammography--rather than being equally visible at digital and screen-film mammography--were significantly greater for lesions imaged with the General Electric digital mammography system than for lesions imaged with the Fischer (P = .0070) and Fuji (P = .0070) devices. CONCLUSION The significantly better diagnostic accuracy of digital mammography, as compared with screen-film mammography, in women with dense breasts demonstrated in the DMIST was most likely attributable to differences in image contrast, which were most likely due to the inherent system performance improvements that are available with digital mammography. The authors conclude that the DMIST results were attributable primarily to differences in the display and acquisition characteristics of the mammography devices rather than to reader variability.

Diffusion MRI quality control and functional diffusion map results in ACRIN 6677/RTOG 0625: A multicenter, randomized, phase II trial of bevacizumab and chemotherapy in recurrent glioblastoma

Functional diffusion mapping (fDM) is a cancer imaging technique that quantifies voxelwise changes in apparent diffusion coefficient (ADC). Previous studies have shown value of fDMs in bevacizumab therapy for recurrent glioblastoma multiforme (GBM). The aim of the present study was to implement explicit criteria for diffusion MRI quality control and independently evaluate fDM performance in a multicenter clinical trial (RTOG 0625/ACRIN 6677). A total of 123 patients were enrolled in the current multicenter trial and signed institutional review board-approved informed consent at their respective institutions. MRI was acquired prior to and 8 weeks following therapy. A 5-point QC scoring system was used to evaluate DWI quality. fDM performance was evaluated according to the correlation of these metrics with PFS and OS at the first follow-up time-point. Results showed ADC variability of 7.3% in NAWM and 10.5% in CSF. A total of 68% of patients had usable DWI data and 47% of patients had high quality DWI data when also excluding patients that progressed before the first follow-up. fDM performance was improved by using only the highest quality DWI. High pre-treatment contrast enhancing tumor volume was associated with shorter PFS and OS. A high volume fraction of increasing ADC after therapy was associated with shorter PFS, while a high volume fraction of decreasing ADC was associated with shorter OS. In summary, DWI in multicenter trials are currently of limited value due to image quality. Improvements in consistency of image quality in multicenter trials are necessary for further advancement of DWI biomarkers.

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.

Assessing the Stand-Alone Sensitivity of Computer-Aided Detection With Cancer Cases From the Digital Mammographic Imaging Screening Trial

OBJECTIVE The purpose of this study was to assess the sensitivities and false-detection rates of two computer-aided detection (CADe) systems when applied to digital or film-screen mammograms in detecting the known breast cancer cases from the Digital Mammographic Imaging Screening Trial (DMIST) breast cancer screening population. MATERIALS AND METHODS Available film-screen and digital mammograms of 161 breast cancer cases from DMIST were analyzed by two CADe systems, iCAD Second-Look and R2 ImageChecker. Three experienced breast-imaging radiologists reviewed the CADe marks generated for each available cancer case, recording the number and locations of CADe marks and whether each CADe mark location corresponded with the known location of the cancer. RESULTS For the 161 cancer cases included in this study, the sensitivities of the DMIST reader without CAD were 0.43 (69/161, 95% CI 0.35-0.51) for digital and 0.41 (66/161, 0.33-0.49) for film-screen mammography. The sensitivities of iCAD were 0.74 (119/161, 0.66-0.81) for digital and 0.69 (111/161, 0.61-0.76) for film-screen mammography, both significantly higher than the DMIST study sensitivities (p < 0.0001 for both). The average number of false CADe marks per case of iCAD was 2.57 (SD, 1.92) for digital and 3.06(1.72) for film-screen mammography. The sensitivity of R2 was 0.74 (119/161, 0.66-0.81) for digital, and 0.60 (97/161, 0.52-0.68) for film-screen mammography, both significantly higher than the DMIST study sensitivities (p < 0.0001 for both). The average number of false CADe marks per case of R2 was 2.07 (1.57) for digital and 1.52 (1.45) for film-screen mammography. CONCLUSION Our results suggest the use of CADe in interpretation of digital and film-screen mammograms could lead to improvements in cancer detection.