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).

Comparison of Contrast-Enhanced Mammography With Conventional Digital Mammography in Breast Cancer Screening: A Pilot Study.

PURPOSE: To perform a pilot evaluation of contrast-enhanced mammography (CEM) for screening to determine whether it can improve accuracy and reader confidence in diagnosis. METHODS AND MATERIALS: This institutional review board-approved reader study was comprised of 64 de-identified CEM cases acquired from December 1, 2014, to June 7, 2016, including 48 negative, 5 biopsy-proven benign, and 11 biopsy-proven malignancies. Negative cases were followed for at least 2 years without evidence of cancer. Ten breast imagers of varying experience first rated the low-energy (LE) mammogram and then the CEM examination using BI-RADS categories and a 5-point Likert scale for confidence in diagnosis. RESULTS: There were 635 out a total possible 640 complete reader interpretations included in this analysis. The remaining five incomplete interpretations were excluded. Median sensitivity and specificity improved with the addition of CEM (sensitivity: 0.86 [95% confidence interval {CI}: 0.74-0.95] versus 1 [95% CI: 0.83-1.00], specificity: 0.85 [95% CI: 0.64-0.94] versus 0.88 [95% CI: 0.80-0.92]). Individual receiver operating characteristic curves showed significant improvement with CEM (mean area under the curve increase = 0.056 [95% CI: 0.015-0.097], P = .002). The addition of CEM significantly improved average confidence in 5 of 10 readers when compared with LE (P < .0001) and improved pooled confidence across all tissue density categories, except the almost entirely fatty category. There was a trend toward improved confidence with increasing tissue density with CEM. Degree of background parenchymal enhancement did not affect readers' level of improvement in confidence when interpreting CEM. SUMMARY: CEM improved reader performance and confidence compared with viewing only LE, suggesting a role for CEM in breast cancer screening for which larger trials are warranted.

Impact of prevalence and case distribution in lab-based diagnostic imaging studies.

We investigated effects of prevalence and case distribution on radiologist diagnostic performance as measured by area under the receiver operating characteristic curve (AUC) and sensitivity-specificity in lab-based reader studies evaluating imaging devices. Our retrospective reader studies compared full-field digital mammography (FFDM) to screen-film mammography (SFM) for women with dense breasts. Mammograms were acquired from the prospective Digital Mammographic Imaging Screening Trial. We performed five reader studies that differed in terms of cancer prevalence and the distribution of noncancers. Twenty radiologists participated in each reader study. Using split-plot study designs, we collected recall decisions and multilevel scores from the radiologists for calculating sensitivity, specificity, and AUC. Differences in reader-averaged AUCs slightly favored SFM over FFDM (biggest AUC difference: 0.047, SE = 0.023 , p = 0.047 ), where standard error accounts for reader and case variability. The differences were not significant at a level of 0.01 (0.05/5 reader studies). The differences in sensitivities and specificities were also indeterminate. Prevalence had little effect on AUC (largest difference: 0.02), whereas sensitivity increased and specificity decreased as prevalence increased. We found that AUC is robust to changes in prevalence, while radiologists were more aggressive with recall decisions as prevalence increased.

Impact of Different Study Populations on Reader Behavior and Performance Metrics: Initial Results.

The FDA recently completed a study on design methodologies surrounding the Validation of Imaging Premarket Evaluation and Regulation called VIPER. VIPER consisted of five large reader sub-studies to compare the impact of different study populations on reader behavior as seen by sensitivity, specificity, and AUC, the area under the ROC curve (receiver operating characteristic curve). The study investigated different prevalence levels and two kinds of sampling of non-cancer patients: a screening population and a challenge population. The VIPER study compared full-field digital mammography (FFDM) to screen-film mammography (SFM) for women with heterogeneously dense or extremely dense breasts. All cases and corresponding images were sampled from Digital Mammographic Imaging Screening Trial (DMIST) archives. There were 20 readers (American Board Certified radiologists) for each sub-study, and instead of every reader reading every case (fully-crossed study), readers and cases were split into groups to reduce reader workload and the total number of observations (split-plot study). For data collection, readers first decided whether or not they would recall a patient. Following that decision, they provided an ROC score for how close or far that patient was from the recall decision threshold. Performance results for FFDM show that as prevalence increases to 50%, there is a moderate increase in sensitivity and decrease in specificity, whereas AUC is mainly flat. Regarding precision, the statistical efficiency (ratio of variances) of sensitivity and specificity relative to AUC are 0.66 at best and decrease with prevalence. Analyses comparing modalities and the study populations (screening vs. challenge) are still ongoing.

Mammographic Density Change With Estrogen and Progestin Therapy and Breast Cancer Risk.

Background: Estrogen plus progestin therapy increases both mammographic density and breast cancer incidence. Whether mammographic density change associated with estrogen plus progestin initiation predicts breast cancer risk is unknown. Methods: We conducted an ancillary nested case-control study within the Women's Health Initiative trial that randomly assigned postmenopausal women to daily conjugated equine estrogen 0.625 mg plus medroxyprogesterone acetate 2.5 mg or placebo. Mammographic density was assessed from mammograms taken prior to and one year after random assignment for 174 women who later developed breast cancer (cases) and 733 healthy women (controls). Logistic regression analyses included adjustment for confounders and baseline mammographic density when appropriate. Results: Among women in the estrogen plus progestin arm (97 cases/378 controls), each 1% positive change in percent mammographic density increased breast cancer risk 3% (odds ratio [OR] = 1.03, 95% confidence interval [CI] = 1.01 to 1.06). For women in the highest quintile of mammographic density change (>19.3% increase), breast cancer risk increased 3.6-fold (95% CI = 1.52 to 8.56). The effect of estrogen plus progestin use on breast cancer risk (OR = 1.28, 95% CI = 0.90 to 1.82) was eliminated in this study, after adjusting for change in mammographic density (OR = 1.00, 95% CI = 0.66 to 1.51). Conclusions: We found the one-year change in mammographic density after estrogen plus progestin initiation predicted subsequent increase in breast cancer risk. All of the increased risk from estrogen plus progestin use was mediated through mammographic density change. Doctors should evaluate changes in mammographic density with women who initiate estrogen plus progestin therapy and discuss the breast cancer risk implications.

Dedicated Three-dimensional Breast Computed Tomography: Lesion Characteristic Perception by Radiologists.

OBJECTIVES: To assess radiologist confidence in the characterization of suspicious breast lesions with a dedicated three-dimensional breast computed tomography (DBCT) system in comparison to diagnostic two-dimensional digital mammography (dxDM). MATERIALS AND METHODS: Twenty women were recruited who were to undergo a breast biopsy for a Breast Imaging-Reporting and Data System (BI-RADS) 4 or 5 lesion evaluated with dxDM in this Institutional Review Board-approved study. The enrolled subjects underwent imaging of the breast(s) of concern using DBCT. Seven radiologists reviewed the cases. Each reader compared DBCT to the dxDM and was asked to specify the lesion type and BI-RADS score for each lesion and modality. They also compared lesion characteristics: Shape for masses or morphology for calcifications; and margins for masses or distribution for calcifications between the modalities using confidence scores (0-100). RESULTS: Twenty-four biopsied lesions were included in this study: 17 (70.8%) masses and 7 (29.2%) calcifications. Eight (33.3%) lesions were malignant, and 16 (66.7%) were benign. Across all lesions, there was no significant difference in the margin/distribution (Δ = -0.99, P = 0.84) and shape/morphology (Δ = -0.10, P = 0.98) visualization confidence scores of DBCT in relation to dxDM. However, analysis by lesion type showed a statistically significant increase in reader shape (Δ =11.34, P = 0.013) and margin (Δ =9.93, P = 0.023) visualization confidence with DBCT versus dxDM for masses and significant decrease in reader morphology (Δ = -29.95, P = 0.001) and distribution (Δ = -28.62, P = 0.002) visualization confidence for calcifications. CONCLUSION: Reader confidence in the characterization of suspicious masses is significantly improved with DBCT, but reduced for calcifications. Further study is needed to determine whether this technology can be used for breast cancer screening.

Tomosynthesis for breast cancer screening.

Breast tomosynthesis, a three-dimensional x-ray based breast imaging technology, has been available for clinical use in the United States since 2011. In this paper we review the literature on breast cancer screening with this new technology including where gaps in knowledge remain.

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.

Automated delineation of calcified vessels in mammography by tracking with uncertainty and graphical linking techniques.

As a potential biomarker for women's cardiovascular and chronic kidney diseases, breast arterial calcification (BAC) in mammography has become an emerging research topic in recent years. To provide more objective measurement for vascular structures with calcium depositions in mammography, a new computerized method is introduced in this paper to delineate the calcified vessels. Specifically, we leverage two underlying cues, namely calcification and vesselness, into a multiple seeded tracking with uncertainty scheme. This new vessel-tracking scheme generates plenty of sampling paths to describe the complicated topology of the vascular structures with calcium depositions. A compiling and linking process is further carried out to organize the sampling paths together to be the vessel segments that likely belong to the same vessel tract. The proposed method has been evaluated on 63 mammograms, by comparison with manual delineations from two experts using various assessment metrics. The experiment results confirm the efficacy and stability of the proposed method, and also indicate that the proposed method can be potentially used as a convenient BAC measurement tool in replacement of the trivial and tedious manual delineation tasks.

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.

Comparison of radiologist performance with photon-counting full-field digital mammography to conventional full-field digital mammography.

RATIONALE AND OBJECTIVES: The purpose of this study was to assess the performance of a MicroDose photon-counting full-field digital mammography (PCM) system in comparison to full-field digital mammography (FFDM) for area under the receiver-operating characteristic (ROC) curve (AUC), sensitivity, specificity, and feature analysis of standard-view mammography for women presenting for screening mammography, diagnostic mammography, or breast biopsy. MATERIALS AND METHODS: A total of 133 women were enrolled in this study at two European medical centers, with 67 women who had a pre-existing 10-36 months FFDM enrolled prospectively into the study and 66 women who underwent breast biopsy and had screening PCM and diagnostic FFDM, including standard craniocaudal and mediolateral oblique views of the breast with the lesion, enrolled retrospectively. The case mix consisted of 49 cancers, 17 biopsy-benign cases, and 67 normal cases. Sixteen radiologists participated in the reader study and interpreted all 133 cases in both conditions, separated by washout period of ≥4 weeks. ROC curve and free-response ROC curve analyses were performed for noninferiority of PCM compared to FFDM using a noninferiority margin Δ value of 0.10. Feature analysis of the 66 cases with lesions was conducted with all 16 readers at the conclusion of the blinded reads. Mean glandular dose was recorded for all cases. RESULTS: The AUC for PCM was 0.947 (95% confidence interval [CI], 0.920-0.974) and for FFDM was 0.931 (95% CI, 0.898-0.964). Sensitivity per case for PCM was 0.936 (95% CI, 0.897-0.976) and for FFDM was 0.908 (95% CI, 0.856-0.960). Specificity per case for PCM was 0.764 (95% CI, 0.688-0.841) and for FFDM was 0.749 (95% CI, 0.668-0.830). Free-response ROC curve figures of merit were 0.920 (95% CI, 0.881-0.959) and 0.903 (95% CI, 0.858-0.948) for PCM and FFDM, respectively. Sensitivity per lesion was 0.903 (95% CI, 0.846-0.960) and 0.883 (95% CI, 0.823-0.944) for PCM and FFDM, respectively. The average false-positive marks per image of noncancer cases were 0.265 (95% CI, 0.171-0.359) and 0.281 (95% CI, 0.188-0.374) for PCM and FFDM, respectively. Noninferiority P values for AUC, sensitivity (per case and per lesion), specificity, and average false-positive marks per image were all statistically significant (P < .001). The noninferiority P value for free-response ROC was <.025, from the 95% CI for the difference. Feature analysis resulted in PCM being preferred to FFDM by the readers for ≥70% of the cases. The average mean glandular dose for PCM was 0.74 mGy (95% CI, 0.722-0.759 mGy) and for FFDM was 1.23 mGy (95% CI, 1.199-1.262 mGy). CONCLUSIONS: In this study, radiologist performance with PCM was not inferior to that with conventional FFDM at an average 40% lower mean glandular dose.

Diffraction enhanced imaging of a rat model of gastric acid aspiration pneumonitis.

RATIONALE AND OBJECTIVES: Diffraction-enhanced imaging (DEI) is a type of phase contrast x-ray imaging that has improved image contrast at a lower dose than conventional radiography for many imaging applications, but no studies have been done to determine if DEI might be useful for diagnosing lung injury. The goals of this study were to determine if DEI could differentiate between healthy and injured lungs for a rat model of gastric aspiration and to compare diffraction-enhanced images with chest radiographs. MATERIALS AND METHODS: Radiographs and diffraction-enhanced chest images of adult Sprague Dawley rats were obtained before and 4 hours after the aspiration of 0.4 mL/kg of 0.1 mol/L hydrochloric acid. Lung damage was confirmed with histopathology. RESULTS: The radiographs and diffraction-enhanced peak images revealed regions of atelectasis in the injured rat lung. The diffraction-enhanced peak images revealed the full extent of the lung with improved clarity relative to the chest radiographs, especially in the portion of the lower lobe that extended behind the diaphragm on the anteroposterior projection. CONCLUSIONS: For a rat model of gastric acid aspiration, DEI is capable of distinguishing between a healthy and an injured lung and more clearly than radiography reveals the full extent of the lung and the lung damage.

Comparison of image acquisition and radiologist interpretation times in a diagnostic mammography center.

RATIONALE AND OBJECTIVES: The purpose of this study was to determine the acquisition and interpretation times of screen-film mammography and soft-copy digital mammography in a diagnostic mammography center. MATERIALS AND METHODS: The study was conducted in three phases for patients presenting for clinical diagnostic workup to a mammography clinic. In the first phase, technologist acquisition and processing times and radiologist interpretation time were measured for patients imaged with a screen-film mammographic system. During the second phase of the study, times were measured for patients imaged with a direct radiographic digital mammographic system, with interpretation performed on a soft-copy display system. During the third phase, 3 months after installation of the soft-copy display system, times were measured again for patients imaged on the same direct radiographic digital mammographic system, with interpretation with the same soft-copy system. The same four experienced breast imaging radiologists and seven technologists participated in all phases of the study. All data were entered into a database, and statistical analysis was conducted using weighted linear models and logarithmic transformation. RESULTS: Times were obtained for 295 patients. There were 100 patients each for phases 1 and 2 and 95 patients for phase 3. Diagnostic mammographic acquisition times with processing were 13.02 min/case for screen film (phase 1), 8.16 min/case for digital (phase 2), and 10.66 min/case for digital (phase 3) (P < .001 and P < .0001, respectively). In addition, the radiologist interpretation time for digital mammography in both phases was not significantly different from that for film mammography (P = .2853 and P = .2893, respectively). There was no significant difference between phases 2 and 3 (P = 1.0000). The mean interpretation times were 3.75 min/case for screen film, 2.14 min/case for digital (phase 2), and 2.26 min/case for digital (phase 3). CONCLUSIONS: Digital mammography significantly shortened the acquisition time for diagnostic mammography. There was no significant difference in interpretation time compared to screen-film mammography in a diagnostic mammography setting.

Effect of breast compression on lesion characteristic visibility with diffraction-enhanced imaging.

RATIONALE AND OBJECTIVES: Conventional mammography can not distinguish between transmitted, scattered, or refracted x-rays, thus requiring breast compression to decrease tissue depth and separate overlapping structures. Diffraction-enhanced imaging (DEI) uses monochromatic x-rays and perfect crystal diffraction to generate images with contrast based on absorption, refraction, or scatter. Because DEI possesses inherently superior contrast mechanisms, the current study assesses the effect of breast compression on lesion characteristic visibility with DEI imaging of breast specimens. MATERIALS AND METHODS: Eleven breast tissue specimens, containing a total of 21 regions of interest, were imaged by DEI uncompressed, half-compressed, or fully compressed. A fully compressed DEI image was displayed on a soft-copy mammography review workstation, next to a DEI image acquired with reduced compression, maintaining all other imaging parameters. Five breast imaging radiologists scored image quality metrics considering known lesion pathology, ranking their findings on a 7-point Likert scale. RESULTS: When fully compressed DEI images were compared to those acquired with approximately a 25% difference in tissue thickness, there was no difference in scoring of lesion feature visibility. For fully compressed DEI images compared to those acquired with approximately a 50% difference in tissue thickness, across the five readers, there was a difference in scoring of lesion feature visibility. The scores for this difference in tissue thickness were significantly different at one rocking curve position and for benign lesion characterizations. These results should be verified in a larger study because when evaluating the radiologist scores overall, we detected a significant difference between the scores reported by the five radiologists. CONCLUSIONS: Reducing the need for breast compression might increase patient comfort during mammography. Our results suggest that DEI may allow a reduction in compression without substantially compromising clinical image quality.

Detection of arterial calcification in mammograms by random walks.

A fully automatic algorithm is developed for breast arterial calcification extraction in mammograms. This algorithm is implemented in two major steps: a random-walk based tracking step and a compiling and linking step. With given seeds from detected calcification points, the tracking algorithm traverses the vesselness map by exploring the uncertainties of three tracking factors, i.e., traversing direction, jumping distance, and vesselness value, to generate all possible sampling paths. The compiling and linking algorithm further organizes and groups all sampling paths into calcified vessel tracts. The experimental results show that the performance of the proposed automatic calcification extraction algorithm is statistically close to that obtained by manual delineations.

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.

Radiologist evaluation of an X-ray tube-based diffraction-enhanced imaging prototype using full-thickness breast specimens.

RATIONALE AND OBJECTIVES: Conventional mammographic image contrast is derived from x-ray absorption, resulting in breast structure visualization due to density gradients that attenuate radiation without distinction between transmitted, scattered, or refracted x-rays. Diffraction-enhanced imaging (DEI) allows for increased contrast with decreased radiation dose compared to conventional mammographic imaging because of monochromatic x-rays, its unique refraction-based contrast mechanism, and excellent scatter rejection. However, a lingering drawback to the clinical translation of DEI has been the requirement for synchrotron radiation. MATERIALS AND METHODS: The authors' laboratory developed a DEI prototype (DEI-PR) using a readily available tungsten x-ray tube source and traditional DEI crystal optics, providing soft tissue images at 60 keV. Images of full-thickness human breast tissue specimens were acquired on synchrotron-based DEI (DEI-SR), DEI-PR, and digital mammographic systems. A panel of expert radiologists evaluated lesion feature visibility and correlation with pathology after receiving training on the interpretation of refraction contrast mammographic images. RESULTS: For mammographic features (mass, calcification), no significant differences were detected between the DEI-SR and DEI-PR systems. Benign lesions were perceived as better seen by radiologists using the DEI-SR system than the DEI-PR system at the [111] reflectivity, with generalizations limited by small sample size. No significant differences between DEI-SR and DEI-PR were detected for any other lesion type (atypical, cancer) at either crystal reflectivity. CONCLUSIONS: Thus, except for benign lesion characterizations, the DEI-PR system's performance was roughly equivalent to that of the traditional DEI system, demonstrating a significant step toward clinical translation of this modality for breast cancer applications.

Comparison of soft-copy and hard-copy reading for full-field digital mammography.

PURPOSE: To compare radiologists' performance in detecting breast cancer when reading full-field digital mammographic (FFDM) images either displayed on monitors or printed on film. MATERIALS AND METHODS: This study received investigational review board approval and was HIPAA compliant, with waiver of informed consent. A reader study was conducted in which 26 radiologists read screening FFDM images displayed on high-resolution monitors (soft-copy digital) and printed on film (hard-copy digital). Three hundred thirty-three cases were selected from the Digital Mammography Image Screening Trial screening study (n = 49,528). Of these, 117 were from patients who received a diagnosis of breast cancer within 15 months of undergoing screening mammography. The digital mammograms were displayed on mammographic workstations and printed on film according to the manufacturer's specifications. Readers read both hard-copy and soft-copy images 6 weeks apart. Each radiologist read a subset of the total images. Twenty-two readers were assigned to evaluate images from one of three FFDM systems, and four readers were assigned to evaluate images from two mammographic systems. Each radiologist assigned a malignancy score on the basis of overall impression by using a seven-point scale, where 1 = definitely not malignant and 7 = definitely malignant. RESULTS: There were no significant differences in the areas under the receiver operating characteristic curves (AUCs) for the primary comparison. The AUCs for soft-copy and hard-copy were 0.75 and 0.76, respectively (95% confidence interval: -0.04, 0.01; P = .36). Secondary analyses showed no significant differences in AUCs on the basis of manufacturer type, lesion type, or breast density. CONCLUSION: Soft-copy reading does not provide an advantage in the interpretation of digital mammograms. However, the display formats were not optimized and display software remains an evolving process, particularly for soft-copy reading.

Mammographic findings of partial breast irradiation.

RATIONALE AND OBJECTIVES: The aim of this study was to determine if patients who underwent partial-breast irradiation followed by segmental mastectomies had fewer mammographic changes on the first post-treatment mammogram than those who underwent segmental mastectomies followed by whole-breast irradiation. MATERIALS AND METHODS: Subjects enrolled in a study of partial-breast irradiation therapy after segmental mastectomy (intraoperative radiation therapy) plus a random sample of patients who underwent segmental mastectomies followed by conventional whole-breast radiation therapy were identified through the institution's breast cancer database from March 2003 through February 2006. A radiologist specializing in breast imaging reviewed and recorded each patient's pretreatment mammogram for breast density and tumor location and the first post-treatment mammogram, obtained within the first year of treatment, for three common types of mammographic change seen after breast surgery and radiation treatment (breast edema, skin thickening, and surgical scarring), which when severe make it difficult to use mammography for continuing follow-up of the conserved breast. The extent of mammographic change was noted by the radiologist as minimal, moderate, or marked. The data were entered into a database, and statistical analysis was conducted using logistic regression models and chi(2) tests. The effect of breast density on mammographic change was also assessed. RESULTS: The severity of edema was lower with decreasing breast density (P < .006). There was no apparent effect of breast density on the severity of skin thickening. The extent of surgical scarring decreased as breast density increased (P < .026). Analysis of the data from the cumulative logistic regression models demonstrated that even after controlling for breast density, patients who underwent whole-breast radiation therapy had significantly more edema (P = .003), skin thickening (P = .003), and surgical scarring than those who underwent intraoperative radiation therapy (P < .001). CONCLUSION: Patients have a higher probability of having fewer post-treatment mammographic changes after partial-breast irradiation followed by segmental mastectomy than after breast conservation surgery followed by whole-breast irradiation.