Breast Cancer Mortality among Women with a BRCA1 or BRCA2 Mutation in a Magnetic Resonance Imaging Plus Mammography Screening Program.

Annual breast magnetic resonance imaging (MRI) plus mammography is the standard of care for screening women with inherited BRCA1/2 mutations. However, long-term breast cancer-related mortality with screening is unknown. Between 1997 and June 2011, 489 previously unaffected BRCA1/2 mutation carriers aged 25 to 65 years were screened with annual MRI plus mammography on our study. Thereafter, participants were eligible to continue MRI screening through the high-risk Ontario Breast Screening Program. In 2019, our data were linked to the Ontario Cancer Registry of Cancer Care Ontario to identify all incident cancers, vital status and causes of death. Observed breast cancer mortality was compared to expected mortality for age-matched women in the general population. There were 91 women diagnosed with breast cancer (72 invasive and 19 ductal carcinoma in situ (DCIS)) with median follow-up 7.4 (range: 0.1 to 19.2) years. Four deaths from breast cancer were observed, compared to 2.0 deaths expected (standardized mortality ratio (SMR) 2.0, p = 0.14). For the 489 women in the study, the probability of not dying of breast cancer at 20 years from the date of the first MRI was 98.2%. Annual screening with MRI plus mammography is a reasonable option for women who decline or defer risk-reducing mastectomy.

Breast Cancer Screening: Beyond Mortality.

Traditionally, the effectiveness of breast cancer screening has been measured in terms of reducing the number of deaths attributable to breast cancer. Other metrics such as the number of life-years or quality-adjusted life-years gained through screening may be more relevant and certainly may better reflect the important burden of the disease on younger women, their families, and society. The effects of earlier detection of breast cancer in reducing morbidities associated with treatment have often also been neglected. In addition, the harms and limitations associated with cancer screening have been poorly quantified and are seldom put into perspective vis-à-vis the benefits. Here, these alternative measures will be discussed and quantified.

Quantifying masking in clinical mammograms via local detectability of simulated lesions.

PURPOSE: High mammographic density is known to be associated with decreased sensitivity of mammography. Recent changes in the BI-RADS density assessment address the effect of masking by densities, but the BI-RADS assessment remains qualitative and achieves only moderate agreement between radiologists. An automated, quantitative algorithm that estimates the likelihood of masking of simulated masses in a mammogram by dense tissue has been developed. The algorithm considers both the effects of loss of contrast due to density and the distracting texture or appearance of dense tissue. METHODS: A local detectability (dL) map is created by tessellating the mammograms into overlapping regions of interest (ROIs), for which the detectability by a non-prewhitening observer is computed using local estimates of the noise power spectrum and volumetric breast density (VBD). The dL calculation was validated in a 4-alternative forced-choice observer study on the ROIs of 150 craniocaudal digital mammograms. The dL metric was compared against the inverse threshold contrast, (ΔµT)(-1) from the observer study, the anatomic noise parameter ß, the radiologist's BI-RADS density category, and a validated measure of VBD (Cumulus). RESULTS: The mean dL had a high correlation of r = 0.915 and r = 0.699 with (ΔµT)(-1) in the computerized and human observer study, respectively. In comparison, the local VBD estimate had a low correlation of 0.538 with (ΔµT)(-1). The mean dL had a correlation of 0.663, 0.835, and 0.696 with BI-RADS density, ß, and Cumulus VBD, respectively. CONCLUSIONS: The proposed dL metric may be useful in characterizing the potential for lesion masking by dense tissue. Because it uses information about the anatomic noise or tissue appearance, it is more closely linked to lesion detectability than VBD metrics.

Ultrasound as the Primary Screening Test for Breast Cancer: Analysis From ACRIN 6666.

BACKGROUND: Mammography is not widely available in all countries, and breast cancer incidence is increasing. We considered performance characteristics using ultrasound (US) instead of mammography to screen for breast cancer. METHODS: Two thousand eight hundred nine participants were enrolled at 20 sites in the United States, Canada, and Argentina in American College of Radiology Imaging 6666. Two thousand six hundred sixty-two participants completed three annual screens (7473 examinations) with US and film-screen (n = 4351) or digital (n = 3122) mammography and had biopsy or 12-month follow-up. Cancer detection, recall, and positive predictive values were determined. All statistical tests were two-sided. RESULTS: One hundred ten women had 111 breast cancer events: 89 (80.2%) invasive cancers, median size 12 mm. The number of US screens to detect one cancer was 129 (95% bootstrap confidence interval [CI] = 110 to 156), and for mammography 127 (95% CI = 109 to 152). Cancer detection was comparable for each of US and mammography at 58 of 111 (52.3%) vs 59 of 111 (53.2%, P = .90), with US-detected cancers more likely invasive (53/58, 91.4%, median size 12 mm, range = 2-40 mm), vs mammography at 41 of 59 (69.5%, median size 13 mm, range = 1-55 mm, P < .001). Invasive cancers detected by US were more frequently node-negative, 34 of 53 (64.2%) vs 18 of 41 (43.9%) by mammography (P = .003). For 4814 incidence screens (years 2 and 3), US had higher recall and biopsy rates and lower PPV of biopsy (PPV3) than mammography: The recall rate was 10.7% (n = 515) vs 9.4% (n = 453, P = .03), the biopsy rate was 5.5% (n = 266) vs 2.0% (n = 97, P < .001), and PPV3 was 11.7% (31/266) vs 38.1% (37/97, P < .001). CONCLUSIONS: Cancer detection rate with US is comparable with mammography, with a greater proportion of invasive and node-negative cancers among US detections. False positives are more common with US screening.

A phase I/II trial of epirubicin and docetaxel in locally advanced breast cancer (LABC) on 2-weekly or 3-weekly schedules: NCIC CTG MA.22.

This phase I/II neoadjuvant trial (ClinicalTrials.gov identifier NCT00066443) determined maximally-tolerated doses (MTD), dose-limiting toxicities, response-to-therapy, and explored the role of novel response biomarkers. MA.22 accrued T3N0, any N2 or N3, and T4 breast cancer patients. Treatment was 6 cycles of 3-weekly (Schedule A; N = 47) or 8 cycles of 2-weekly (Schedule B; N = 46) epirubicin/docetaxel chemotherapy in sequential phase I/II studies, with growth factor support. In phase I of each schedule, MTDs were based on DLT. In phase II, clinical responses (CR/PR) and pathologic complete responses (pCR) were assessed. Tumor biopsy cores were obtained pre-, mid-, and post-treatment: 3 for pathologic assessment; 3 for microarray studies. DLT for Schedule A was febrile neutropenia at 105 mg/m(2) epirubicin and 75 mg/m(2) docetaxel; for schedule B, it was fatigue at 75 mg/m(2) for both agents. Phase II doses were 90 mg/m(2) epirubicin/75 mg/m(2) docetaxel for Schedule A and 60 mg/m(2) (both agents) for Schedule B. Schedule A CR/PR and pCR rates were 90 and 10 %, with large reductions in tumor RNA content and integrity following treatment; Schedule B results were 93 and 0 %, with smaller reductions in RNA quality. Pre-treatment expression of several genes was associated with clinical response, including those within a likely amplicon at 17q12 (ERBB2, TCAP, GSDMB, and PNMT). The combination regimens had acceptable toxicity, good clinical response, induction of changes in tumor RNA content and integrity. Pre-treatment expression of particular genes was associated with clinical responses, including several near 17q12, which with ERBB2, may better identify chemoresponsiveness.

Anatomical noise in contrast-enhanced digital mammography. Part II. Dual-energy imaging.

PURPOSE: Dual-energy (DE) contrast-enhanced digital mammography (CEDM) uses an iodinated contrast agent in combination with digital mammography (DM) to evaluate lesions on the basis of tumor angiogenesis. In DE imaging, low-energy (LE) and high-energy (HE) images are acquired after contrast administration and their logarithms are subtracted to cancel the appearance of normal breast tissue. Often there is incomplete signal cancellation in the subtracted images, creating a background "clutter" that can impair lesion detection. This is the second component of a two-part report on anatomical noise in CEDM. In Part I the authors characterized the anatomical noise for single-energy (SE) temporal subtraction CEDM by a power law, with model parameters α and ß. In this work the authors quantify the anatomical noise in DE CEDM clinical images and compare this with the noise in SE CEDM. The influence on the anatomical noise of the presence of iodine in the breast, the timing of imaging postcontrast administration, and the x-ray energy used for acquisition are each evaluated. METHODS: The power law parameters, α and ß, were measured from unprocessed LE and HE images and from DE subtracted images to quantify the anatomical noise. A total of 98 DE CEDM cases acquired in a previous clinical pilot study were assessed. Conventional DM images from 75 of the women were evaluated for comparison with DE CEDM. The influence of the imaging technique on anatomical noise was determined from an analysis of differences between the power law parameters as measured in DM, LE, HE, and DE subtracted images for each subject. RESULTS: In DE CEDM, weighted image subtraction lowers ß to about 1.1 from 3.2 and 3.1 in LE and HE unprocessed images, respectively. The presence of iodine has a small but significant effect in LE images, reducing ß by about 0.07 compared to DM, with α unchanged. Increasing the x-ray energy, from that typical in DM to a HE beam, significantly decreases α by about 2×10(-5) mm2, and lowers ß by about 0.14 compared to LE images. A comparison of SE and DE CEDM at 4 min postcontrast shows equivalent power law parameters in unprocessed images, and lower α and ß by about 3×10(-5) mm2 and 0.50, respectively, in DE versus SE subtracted images. CONCLUSIONS: Image subtraction in both SE and DE CEDM reduces ß by over a factor of 2, while maintaining α below that in DM. Given the equivalent α between SE and DE unprocessed CEDM images, and the smaller anatomical noise in the DE subtracted images, the DE approach may have an advantage over SE CEDM. It will be necessary to test this potential advantage in future lesion detectability experiments, which account for realistic lesion signals. The authors' results suggest that LE images could be used in place of DM images in CEDM exam interpretation.

Anatomical noise in contrast-enhanced digital mammography. Part I. Single-energy imaging.

PURPOSE: The use of an intravenously injected iodinated contrast agent could help increase the sensitivity of digital mammography by adding information on tumor angiogenesis. Two approaches have been made for clinical implementation of contrast-enhanced digital mammography (CEDM), namely, single-energy (SE) and dual-energy (DE) imaging. In each technique, pairs of mammograms are acquired, which are then subtracted with the intent to cancel the appearance of healthy breast tissue to permit sensitive detection and specific characterization of lesions. Patterns of contrast agent uptake in the healthy parenchyma, and uncanceled signal from background tissue create a "clutter" that can mask or mimic an enhancing lesion. This type of "anatomical noise" is often the limiting factor in lesion detection tasks, and thus, noise quantification may be useful for cascaded systems analysis of CEDM and for phantom development. In this work, the authors characterize the anatomical noise in CEDM clinical images and the authors evaluate the influence of the x-ray energy used for acquisition, the presence of iodine in the breast, and the timing of imaging postcontrast administration on anatomical noise. The results are presented in a two-part report, with SE CEDM described here, and DE CEDM in Part II. METHODS: A power law is used to model anatomical noise in CEDM images. The exponent, ß, which describes the anatomical structure, and the constant α, which represents the magnitude of the noise, are determined from Wiener spectra (WS) measurements on images. A total of 42 SE CEDM cases from two previous clinical pilot studies are assessed. The parameters α and ß are measured both from unprocessed images and from subtracted images. RESULTS: Consistent results were found between the two SE CEDM pilot studies, where a significant decrease in ß from a value of approximately 3.1 in the unprocessed images to between about 1.1 and 1.8 in the subtracted images was observed. Increasing the x-ray energy from that used in conventional DM to those of typical SE CEDM spectra with mean energies above 33 keV significantly decreased α by about a factor of 19, in agreement with theory. Compared to precontrast images, in the unprocessed postcontrast images at 30 s postinjection, α was larger by about 7.4 × 10(-7) mm(2) and ß was decreased by 0.2. While α did not vary significantly with the time after contrast administration, ß from the unprocessed image WS increased linearly, and ß from subtracted image WS increased with an initial quadratic relationship that plateaued by about 5 min postinjection. CONCLUSIONS: The presence of an iodinated contrast agent in the breast produced small, but significant changes in the power law parameters of unprocessed CEDM images compared to the precontrast images. Image subtraction in SE CEDM significantly reduced anatomical noise compared to conventional DM, with a reduction in both α and ß by about a factor of 2. The data presented here, and in Part II of this work, will be useful for modeling of CEDM backgrounds, for systems characterization and for lesion detectability experiments using models that account for anatomical noise.

Dual-energy contrast-enhanced digital mammography: initial clinical results of a multireader, multicase study.

INTRODUCTION: The purpose of this study was to compare the diagnostic accuracy of dual-energy contrast-enhanced digital mammography (CEDM) as an adjunct to mammography (MX) ± ultrasonography (US) with the diagnostic accuracy of MX ± US alone. METHODS: One hundred ten consenting women with 148 breast lesions (84 malignant, 64 benign) underwent two-view dual-energy CEDM in addition to MX and US using a specially modified digital mammography system (Senographe DS, GE Healthcare). Reference standard was histology for 138 lesions and follow-up for 12 lesions. Six radiologists from 4 institutions interpreted the images using high-resolution softcopy workstations. Confidence of presence (5-point scale), probability of cancer (7-point scale), and BI-RADS scores were evaluated for each finding. Sensitivity, specificity and ROC curve areas were estimated for each reader and overall. Visibility of findings on MX ± CEDM and MX ± US was evaluated with a Likert scale. RESULTS: The average per-lesion sensitivity across all readers was significantly higher for MX ± US ± CEDM than for MX ± US (0.78 vs. 0.71 using BIRADS, p = 0.006). All readers improved their clinical performance and the average area under the ROC curve was significantly superior for MX ± US ± CEDM than for MX ± US ((0.87 vs 0.83, p = 0.045). Finding visibility was similar or better on MX ± CEDM than MX ± US in 80% of cases. CONCLUSIONS: Dual-energy contrast-enhanced digital mammography as an adjunct to MX ± US improves diagnostic accuracy compared to MX ± US alone. Addition of iodinated contrast agent to MX facilitates the visualization of breast lesions.

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.

Is ductal carcinoma in situ with "possible invasion" more predictive of invasive carcinoma than pure ductal carcinoma in situ?

OBJECTIVES: To compare the underestimation of ductal carcinoma in situ (DCIS) vs DCIS with "possible invasion" at breast biopsy and to determine if any factors related to clinical indication, imaging abnormality, biopsy, or DCIS-grade affected the likelihood of underestimation. METHODS: Of 3836 consecutive lesions that were biopsied by using a 14-gauge needle, 117 lesions revealed DCIS. Surgical pathology results of invasive carcinoma were compared with needle biopsy results of DCIS or DCIS with possible invasion. Clinical indication, imaging abnormality, biopsy guidance modality, sample number, and histologic grade were recorded. Yates corrected χ(2) and Fisher exact tests were used to determine differences between groups. RESULTS: A total of 101 lesions were DCIS and 16 were DCIS with possible invasion at biopsy. Thirty-six of 117 lesions (31%) revealed invasive carcinoma at resection pathology. Invasive carcinoma was present more often when DCIS with possible invasion was diagnosed compared with pure DCIS (7/16 [44%] vs 29/101 [29%], P = .36). No factor, including clinical indication, imaging abnormality, biopsy guidance method, sample number, or grade, was found to significantly affect the likelihood of underestimation for lesions diagnosed as DCIS vs DCIS with "possible invasion." The likelihood of pure DCIS underestimation significantly increased when lesions were high grade compared with either intermediate or low grade (18/44 [41%] vs 9/44 [21%] vs 2/10 [20%], P = .03). CONCLUSION: For lesions biopsied by using a 14-gauge needle, there is a trend towards underestimation of the presence of invasive carcinoma when pathology reveals DCIS with possible invasion compared with pure DCIS. High-grade DCIS was significantly more likely to be underestimated.

Improvement in DCIS detection rates by MRI over time in a high-risk breast screening study.

Although magnetic resonance imaging (MRI) is much more sensitive than mammography for detecting early invasive breast cancer, in many high-risk screening studies MRI was less sensitive than mammography for detecting ductal carcinoma in situ (DCIS). We reviewed our experience detecting DCIS in our single center study of annual MRI, mammography, ultrasound and clinical breast examination (CBE) for screening very high-risk women. All cases of DCIS±microinvasion and invasive cancer were compared in two time frames: before (period A) and after (period B) July 2001-when we acquired expertise in the detection of DCIS with MRI-with respect to patient demographics, method of detection, and rates of detection of invasive cancer and DCIS. In period A there were 15 cases (3.1% of 486 screens) in 223 women, of which 2 (13%) were DCIS-one with microinvasion-neither detected by MRI. In period B there were 29 cases (3.3% of 877 screens) in 391 women, of which 10 (34%) were DCIS±microinvasion (p=0.04), all 10 detected by MRI but only one by mammography. No DCIS cases were detected by ultrasound or CBE. Specificity was lower in period B than in period A but acceptable. The ability to detect DCIS with screening MRI improves significantly with experience. MRI-guided biopsy capability is essential for a high-risk screening program. In experienced centers the increased sensitivity of MRI relative to mammography is at least as high for DCIS as it is for invasive breast cancer.

Reasons women at elevated risk of breast cancer refuse breast MR imaging screening: ACRIN 6666.

PURPOSE: To determine reasons for nonparticipation in a trial of supplemental screening with magnetic resonance (MR) imaging after mammography and ultrasonography (US). MATERIALS AND METHODS: Women(n = 2809) at elevated risk of breast cancer were enrolled in the American College of Radiology Imaging Network 6666 US Screening Protocol at 21 institutions. Fourteen institutions met technical and experience requirements for this institutional review board-approved, HIPAA-compliant substudy of supplemental screening with MR imaging. Those women who had completed 0-, 12-, and 24-month screenings with mammography combined with US were considered for a single contrast material-enhanced MR examination within 8 weeks after completing the 24-month mammography-US screening. A total of 1593 women had complete MR substudy registration data: 378 of them were ineligible for the study, and 1215 had analyzable data. Reasons for nonparticipation were determined. Demographic data were compared between study participants and nonparticipants. RESULTS: Of 1215 women with analyzable data, 703 (57.9%), with a mean age of 54.8 years, were enrolled in the MR substudy and 512 (42.1%) declined participation. Women with a 25% or greater lifetime risk of breast cancer were more likely to participate (odds ratio, 1.53; 95% confidence interval: 1.10, 2.12). Of 512 nonparticipants, 130 (25.4%) refused owing to claustrophobia; 93 (18.2%), owing to time constraints; 62 (12.1%), owing to financial concerns; 47 (9.2%), because their physician would not provide a referral and/or did not believe MR imaging was indicated; 40 (7.8%), because they were not interested; 39 (7.6%), because they were medically intolerant to MR imaging; 29 (5.7%), because they did not want to undergo intravenous injection; 27 (5.3%), owing to additional biopsy or other procedures that might be required subsequently; 21 (4.1%), owing to MR imaging scheduling constraints; 11 (2.2%), because of the travel required; seven (1.4%), owing to gadolinium-related risks or allergies; and six (1.2%), for unknown reasons. CONCLUSION: Of 1215 women with elevated breast cancer risk who could, according to protocol guidelines, undergo breast MR imaging, only 57.9% agreed to participate.

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.

Accurate estimation of compressed breast thickness in mammography.

The determination of volumetric breast density (VBD) from mammograms requires an accurate knowledge of the thickness of the compressed breast. Previously, the authors described a technique for measuring local thicknesses using optical stereoscopic photogrammetry [A. H. Tyson, G. E. Mawdsley, and M. J. Yaffe, "Measurement of compressed breast thickness by optical stereoscopic photogrammetry," Med. Phys. 36(2), 569-576 (2009)]. Here, the authors describe the use of this tool to guide the development of a simpler, more practical field technique for the estimation of breast thickness and test its accuracy. Phantoms were constructed having similar shapes and compression characteristics to breasts of different sizes. These phantoms were compressed at different forces on several types of mammography units and their thickness under compression was measured using optical stereoscopic photogrammetry at many points of contact with the compression plate. A prediction equation was developed that uses the readout of compressed thickness and compression force provided by the mammography system to estimate local breast thickness. Using this approach, systems can be calibrated to an accuracy of better than 5 mm in thickness using a simple test object compared to an error of up to 15 mm associated with using only the thickness readout of the mammography machine. On the systems tested, the estimated value of VBD obtained using this method is significantly reduced from that determined using the constant thickness reported by the mammography machine.

Technical developments in mammography.

The art, science, and technology of mammography have developed steadily over the past 35 y. Mammography is a central tool for diagnosis of symptoms of breast cancer. In addition, periodic screening of asymptomatic women in certain age groups has been clearly demonstrated to contribute to reduction of mortality from breast cancer. Technical improvements have allowed the examination to be carried out at substantially lower radiation dose than was necessary to obtain a good image in the 1970's, while at the same time providing greatly improved contrast, spatial resolution, dynamic range and tissue coverage. Digital mammography overcomes many of the technical limitations inherent in screen-film mammography and has been shown to offer increased accuracy for women under 50 and those with dense breasts. The radiation risk associated with mammography cannot be ignored, however, modern analysis suggests that it is very low, especially compared to the benefits from the exam. Nevertheless, imaging should be conducted with careful attention to efficient use of the radiation. New techniques, currently under development and evaluation, promise to add further to the value of mammography.

Preliminary in vivo validation of a dedicated breast MRI and sonographic coregistration imaging system.

OBJECTIVE: Sonographic correlation of breast MRI findings is often challenging. We present a preliminary in vivo feasibility study evaluating the degree of error of a new MRI-sonography coregistration system for showing MRI and sonographically visible breast lesions. CONCLUSION: In 10 patients with 13 lesions, the system was found to be an accurate means for targeting sonography to MRI of the same breast lesions.

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.

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.

Diagnostic accuracy of digital versus film mammography: exploratory analysis of selected population subgroups in DMIST.

PURPOSE: To retrospectively compare the accuracy of digital versus film mammography in population subgroups of the Digital Mammographic Imaging Screening Trial (DMIST) defined by combinations of age, menopausal status, and breast density, by using either biopsy results or follow-up information as the reference standard. MATERIALS AND METHODS: DMIST included women who underwent both digital and film screening mammography. Institutional review board approval at all participating sites and informed consent from all participating women in compliance with HIPAA was obtained for DMIST and this retrospective analysis. Areas under the receiver operating characteristic curve (AUCs) for each modality were compared within each subgroup evaluated (age < 50 vs 50-64 vs >or= 65 years, dense vs nondense breasts at mammography, and pre- or perimenopausal vs postmenopausal status for the two younger age cohorts [10 new subgroups in toto]) while controlling for multiple comparisons (P < .002 indicated a significant difference). All DMIST cancers were evaluated with respect to mammographic detection method (digital vs film vs both vs neither), mammographic lesion type (mass, calcifications, or other), digital machine type, mammographic and pathologic size and diagnosis, existence of prior mammographic study at time of interpretation, months since prior mammographic study, and compressed breast thickness. RESULTS: Thirty-three centers enrolled 49 528 women. Breast cancer status was determined for 42,760 women, the group included in this study. Pre- or perimenopausal women younger than 50 years who had dense breasts at film mammography comprised the only subgroup for which digital mammography was significantly better than film (AUCs, 0.79 vs 0.54; P = .0015). Breast Imaging Reporting and Data System-based sensitivity in this subgroup was 0.59 for digital and 0.27 for film mammography. AUCs were not significantly different in any of the other subgroups. For women aged 65 years or older with fatty breasts, the AUC showed a nonsignificant tendency toward film being better than digital mammography (AUCs, 0.88 vs 0.70; P = .0025). CONCLUSION: Digital mammography performed significantly better than film for pre- and perimenopausal women younger than 50 years with dense breasts, but film tended nonsignificantly to perform better for women aged 65 years or older with fatty breasts.