How does c-view image quality compare with conventional 2D FFDM?

Generalisable deep learning method for mammographic density prediction across imaging techniques and self-reported race

BACKGROUND

Breast density is an important risk factor for breast cancer complemented by a higher risk of cancers being missed during screening of dense breasts due to reduced sensitivity of mammography. Automated, deep learning-based prediction of breast density could provide subject-specific risk assessment and flag difficult cases during screening. However, there is a lack of evidence for generalisability across imaging techniques and, importantly, across race.

METHODS

This study used a large, racially diverse dataset with 69,697 mammographic studies comprising 451,642 individual images from 23,057 female participants. A deep learning model was developed for four-class BI-RADS density prediction. A comprehensive performance evaluation assessed the generalisability across two imaging techniques, full-field digital mammography (FFDM) and two-dimensional synthetic (2DS) mammography. A detailed subgroup performance and bias analysis assessed the generalisability across participants' race.

RESULTS

Here we show that a model trained on FFDM-only achieves a 4-class BI-RADS classification accuracy of 80.5% (79.7-81.4) on FFDM and 79.4% (78.5-80.2) on unseen 2DS data. When trained on both FFDM and 2DS images, the performance increases to 82.3% (81.4-83.0) and 82.3% (81.3-83.1). Racial subgroup analysis shows unbiased performance across Black, White, and Asian participants, despite a separate analysis confirming that race can be predicted from the images with a high accuracy of 86.7% (86.0-87.4).

CONCLUSIONS

Deep learning-based breast density prediction generalises across imaging techniques and race. No substantial disparities are found for any subgroup, including races that were never seen during model development, suggesting that density predictions are unbiased.

Audit of data from examination image headers collected for quality assurance in the ECOG-ACRIN EA1151 tomosynthesis mammographic imaging screening trial (TMIST)

PURPOSE

A comprehensive, centrally-monitored physics quality control (QC) program was developed for the Tomosynthesis Imaging Screening Trial (TMIST), a randomized controlled trial of digital breast tomosynthesis (TM) versus digital mammography (DM) for cancer screening. As part of the program, in addition to a set of phantom-based tests, de-identified data on image acquisition and processing parameters were captured from the DICOM headers of all individual patient images in the trial. These data were analyzed to assess the potential usefulness of header data from digital mammograms and tomosynthesis images of patients for quality assurance in breast imaging.

METHODS

Data were automatically extracted from the headers of all de-identified patient mammograms and tomosynthesis images in the TMIST study. Image acquisition parameters and estimated radiation doses were tracked for individual sites, systems and across system types. These parameters included (among others) kV, target/filter use, number of acquired views per examination, AEC mode, compression thickness and force and detector temperature. Consistency of manually entered study data parameters (subject ID, screening time-point) from TMIST was evaluated. Preliminary observations from the program are presented.

RESULTS

We report on data from 812 651 images from 135 525 examinations acquired between October, 2017 and December, 2022. Data came from 6 system models from 3 manufacturers. There was greater variability both in the number of views used and in the estimated (proxy) doses received in DM exams compared to TM. Mean proxy doses per examination varied among manufacturers from 2.76-4.54 mGy for DM and 3-4.84 mGy for the tomosynthesis component in the TM arm with maximum examination proxy doses of 20 and 26 mGy for DM and TM respectively. Mean proxy doses per examination for the combination examination in TM (tomosynthesis plus digital mammography) varied from 6.6 to 7.6 mGy among manufacturers with a maximum of 44.5 mGy.

CONCLUSIONS

Overall, modern digital mammography and tomosynthesis systems used in TMIST have operated very reliably. Doses vary considerably due to variation in the number of views per examination, thickness and fibro-glandularity of the breast, and choices in the use of synthesized versus actual 2D mammography in the TM examination. These data may also be useful in predicting equipment problems. Header information is valuable not only for automated QC, but also for cross-checking accuracy and consistency of data in a clinical study.

A 2D Synthesized Image Improves the 3D Search for Foveated Visual Systems

Current medical imaging increasingly relies on 3D volumetric data making it difficult for radiologists to thoroughly search all regions of the volume. In some applications (e.g., Digital Breast Tomosynthesis), the volumetric data is typically paired with a synthesized 2D image (2D-S) generated from the corresponding 3D volume. We investigate how this image pairing affects the search for spatially large and small signals. Observers searched for these signals in 3D volumes, 2D-S images, and while viewing both. We hypothesize that lower spatial acuity in the observers' visual periphery hinders the search for the small signals in the 3D images. However, the inclusion of the 2D-S guides eye movements to suspicious locations, improving the observer's ability to find the signals in 3D. Behavioral results show that the 2D-S, used as an adjunct to the volumetric data, improves the localization and detection of the small (but not large) signal compared to 3D alone. There is a concomitant reduction in search errors as well. To understand this process at a computational level, we implement a Foveated Search Model (FSM) that executes human eye movements and then processes points in the image with varying spatial detail based on their eccentricity from fixations. The FSM predicts human performance for both signals and captures the reduction in search errors when the 2D-S supplements the 3D search. Our experimental and modeling results delineate the utility of 2D-S in 3D search-reduce the detrimental impact of low-resolution peripheral processing by guiding attention to regions of interest, effectively reducing errors.

Radiologists' performance in reading digital breast tomosynthesis with and without synthesized views for cancer detection

OBJECTIVE

The study aims to evaluate the diagnostic efficacy of radiologists and radiology trainees in digital breast tomosynthesis (DBT) alone vs DBT plus synthesized view (SV) for an understanding of the adequacy of DBT images to identify cancer lesions.

METHODS

Fifty-five observers (30 radiologists and 25 radiology trainees) participated in reading a set of 35 cases (15 cancer) with 28 readers reading DBT and 27 readers reading DBT plus SV. Two groups of readers had similar experience in interpreting mammograms. The performances of participants in each reading mode were compared with the ground truth and calculated in term of specificity, sensitivity, and ROC AUC. The cancer detection rate in various levels of breast density, lesion types and lesion sizes between 'DBT' and 'DBT + SV' were also analyzed. The difference in diagnostic accuracy of readers between two reading modes was assessed using Man-Whitney U test. p < 0.05 indicated a significant result.

RESULTS

There was no significant difference in specificity (0.67-vs-0.65; p = 0.69), sensitivity (0.77-vs-0.71; p = 0.09), ROC AUC (0.77-vs-0.73; p = 0.19) of radiologists reading DBT plus SV compared with radiologists reading DBT. Similar result was found in radiology trainees with no significant difference in specificity (0.70-vs-0.63; p = 0.29), sensitivity (0.44-vs-0.55; p = 0.19), ROC AUC (0.59-vs-0.62; p = 0.60) between two reading modes. Radiologists and trainees obtained similar results in two reading modes for cancer detection rate with different levels of breast density, cancer types and sizes of lesions (p > 0.05).

CONCLUSION

Findings show that the diagnostic performances of radiologists and radiology trainees in DBT alone and DBT plus SV were equivalent in identifying cancer and normal cases.

ADVANCES IN KNOWLEDGE

DBT alone had equivalent diagnostic accuracy as DBT plus SV which could imply the consideration of using DBT as a sole modality without SV.

Automated image quality assessment of mammography phantoms: a systematic review

BACKGROUND

Computerized image analysis is a viable technique for evaluating image quality as a complement to human observers.

PURPOSE

To systematically review the image analysis software used in the assessment of 2D image quality using mammography phantoms.

MATERIAL AND METHODS

A systematic search of multiple databases was performed from inception to July 2020 for articles that incorporated computerized analysis of 2D images of physical mammography phantoms to determine image quality.

RESULTS

A total of 26 studies were included, 12 were carried out using direct digital imaging and 14 using screen film mammography. The ACR phantom (model-156) was the most frequently evaluated phantom, possibly due to the lack of accepted standard software. In comparison to the inter-observer variations, the computerized image analysis was more consistent in scoring test objects. The template matching method was found to be one of the most reliable algorithms, especially for high-contrast test objects, while several algorithms found low-contrast test objects to be harder to distinguish due to the smaller contrast variations between test objects and their backgrounds. This was particularly true for small object sizes.

CONCLUSION

Image analysis software was in agreement with human observers but demonstrated higher consistency and reproducibility of quality evaluation. Additionally, using computerized analysis, several quantitative metrics such as contrast-to-noise ratio (CNR) and the signal-to-noise ratio (SNR) could be used to complement the conventional scoring method. Implementing a computerized approach for monitoring image quality over time would be crucial to detect any deteriorating mammography system before clinical images are impacted.

A new breast phantom suitable for digital mammography, contrast-enhanced digital mammography and digital breast tomosynthesis

Our objective is to report a new breast phantom that provides the objective assessment for three types of clinical mammography, i.e. digital mammography (DM), contrast-enhanced digital mammography (CEDM), and digital breast tomosynthesis (DBT). The tissue-equivalent materials are used to represent the corresponding tissue, and the layer-by-layer structure with separate regions is designed for image quality assessment of different mammography modes. For DM imaging, substitutes for microcalcifications and fibroglandular tissue of different sizes are used to simulate the conventional breast. For CEDM imaging, the tumor module that can be injected with imaging contrast agents is adopted to distinguish normal tissue and diseased tissue in the dense breast. For DBT imaging, the overlapping breast mass module with multiple layers is designed to perform the layer-by-layer imaging of overlapping tissue. In addition, the quantitative assessment module of image quality is designed based on contrast-to-noise ratio, modulation transfer function and artifact spread function. This phantom allows image quality to be evaluated objectively for three different types of the clinical mammography, while it provides an effective tool for optimizing the dose-image quality relationship of patients.

Digital Breast Tomosynthesis: A Decade of Practice in Review

Digital breast tomosynthesis (DBT), introduced in 2011, was thought to be a further evolution of full-field digital mammography (DM). Assessing DBT presents unique challenges. The widely variable settings in which DBT has been applied affect outcomes. In initial studies comparing DM-DBT with DM, outcomes for cancer detection rates (CDRs) and recall rates have been mixed. CDR improves most in biennial screening settings, with little or no improvement in annual screening. Recall rates improve most where rates are highest; no improvement is seen in European prospective trials. Adoption of synthesized mammography (SM), derived from the tomosynthesis acquisition and intended to avoid the DM exposure, has been slow because of inferior image quality. Despite this, SM-DBT has shown equivalent outcomes measures to DM-DBT. An important exception is the To-Be randomized controlled trial, which showed that SM-DBT was equivalent to DM in CDR, not better. To date, interval cancer rate, a surrogate for mortality reduction, has not been shown to be improved by DBT. We may have reached the limit of morphological assessment in x-ray technique. Its use may evolve with advancements in technology as use of contrast agents expands, algorithms for SM progress, and tomosynthesis-guided biopsy proliferates. Our expectations of the contributions of DBT will evolve as well.

Multi-scale cascaded networks for synthesis of mammogram to decrease intensity distortion and increase model-based perceptual similarity

PURPOSE

Synthetic digital mammogram (SDM) is a 2D image generated from digital breast tomosynthesis (DBT) and used as a substitute for a full-field digital mammogram (FFDM) to reduce the radiation dose for breast cancer screening. The previous deep learning-based method used FFDM images as the ground truth, and trained a single neural network to directly generate SDM images with similar appearances (e.g., intensity distribution, textures) to the FFDM images. However, the FFDM image has a different texture pattern from DBT. The difference in texture pattern might make the training of the neural network unstable and result in high-intensity distortion, which makes it hard to decrease intensity distortion and increase perceptual similarity (e.g., generate similar textures) at the same time. Clinically, radiologists want to have a 2D synthesized image that feels like an FFDM image in vision and preserves local structures such as both mass and microcalcifications (MCs) in DBT because radiologists have been trained on reading FFDM images for a long time, while local structures are important for diagnosis. In this study, we proposed to use a deep convolutional neural network to learn the transformation to generate SDM from DBT.

METHOD

To decrease intensity distortion and increase perceptual similarity, a multi-scale cascaded network (MSCN) is proposed to generate low-frequency structures (e.g., intensity distribution) and high-frequency structures (e.g., textures) separately. The MSCN consist of two cascaded sub-networks: the first sub-network is used to predict the low-frequency part of the FFDM image; the second sub-network is used to generate a full SDM image with textures similar to the FFDM image based on the prediction of the first sub-network. The mean-squared error (MSE) objective function is used to train the first sub-network, termed low-frequency network, to generate a low-frequency SDM image. The gradient-guided generative adversarial network's objective function is to train the second sub-network, termed high-frequency network, to generate a full SDM image with textures similar to the FFDM image.

RESULTS

1646 cases with FFDM and DBT were retrospectively collected from the Hologic Selenia system for training and validation dataset, and 145 cases with masses or MC clusters were independently collected from the Hologic Selenia system for testing dataset. For comparison, the baseline network has the same architecture as the high-frequency network and directly generates a full SDM image. Compared to the baseline method, the proposed MSCN improves the peak-to-noise ratio from 25.3 to 27.9 dB and improves the structural similarity from 0.703 to 0.724, and significantly increases the perceptual similarity.

CONCLUSIONS

The proposed method can stabilize the training and generate SDM images with lower intensity distortion and higher perceptual similarity.

Our experience using synthesized mammography vs full field digital mammography in population-based screening

Background

Synthesized Mammogram (SM) from Digital Breast Tomosynthesis (DBT) images is introduced to replace the routine Full Field Digital Mammography (FFDM) to reduce radiation dose.

Purpose

to compare the conspicuity of cancer related findings between SM and FFDM and combination of these methods with DBT.

Methods

The study was conducted in a tertiary breast imaging center, where 200 women referred for screening were enrolled in the study sequentially. Patients underwent FFDM and DBT simultaneously and a two-year follow-up was done. Data was evaluated for Breast Imaging Reporting and Data System (BI-RADS) score, breast density, mass lesions, calcification, and focal asymmetry by two expert breast radiologists. Comparison between different methods was made by Cohen Kappa test.

Results

22 patients with likely malignant findings went under biopsy. Taking histopathologic findings and two-year follow up as reference, the overall sensitivity and specificity for FFDM+DBT (86.1 and 88.9 respectively) and SM+DBT (86.1 and 88.2) didn't show a meaningful difference. Comparing SM and FFDM, calcification in 20 subjects were overlooked on SM, but later detected when combined with DBT. Considering breast composition and BI-RADS categorization, an excellent agreement existed between the readers.

Conclusion

Screening with SM+DBT shows comparable results with FFDM+DBT considering BI-RADS categorization of the patients. Although SM showed slightly inferior sensitivity compared to FFDM, after combining DBT with SM no malignant appearing calcification or mass lesion was missed.

Comparisons between artificial intelligence computer-aided detection synthesized mammograms and digital mammograms when used alone and in combination with tomosynthesis images in a virtual screening setting

PURPOSE

To compare the reader performance of artificial intelligence computer-aided detection synthesized mammograms (AI CAD SM) with that of digital mammograms (DM) when used alone or in combination with digital breast tomosynthesis (DBT) images.

MATERIALS AND METHODS

This retrospective multireader (n = 4) study compared the reader performances in 388 cases (84 cancer, 83 benign, and 221 normal or benign cases). The overall accuracy of the breast-based assessment was determined by four radiologists using two sequential reading modes: DM followed by DM + DBT; and AI CAD SM followed by AI CAD SM + DBT. Each breast was rated by each reader using five-category ratings, where 3 or higher was considered positive. The area under the receiver-operating characteristic curve (AUC) and reading time were evaluated.

RESULTS

The mean AUC values for DM, AI CAD SM, DM + DBT, and AI CAD SM + DBT were 0.863, 0.895, 0.886, and 0.902, respectively. The mean AUC of AI CAD SM was significantly higher (P < 0.0001) than that of DM. The mean AUC of AI CAD SM + DBT was higher than that of DM + DBT (P = 0.094). A significant reduction in the reading time was observed after using AI CAD SM + DBT when compared with that after using DM + DBT (P < 0.001).

CONCLUSION

AI CAD SM + DBT might prove more effective than DM + DBT in a screening setting because of its lower radiation dose, noninferiority, and shorter reading time compared to DM + DBT.

Performance evaluation of digital breast tomosynthesis systems: physical methods and experimental data

Digital breast tomosynthesis (DBT) has become a well-established breast imaging technique, whose performance has been investigated in many clinical studies, including a number of prospective clinical trials. Results from these studies generally point to non-inferiority in terms of microcalcification detection and superior mass-lesion detection for DBT imaging compared to digital mammography (DM). This modality has become an essential tool in the clinic for assessment and ad-hoc screening but is not yet implemented in most breast screening programmes at a state or national level. While evidence on the clinical utility of DBT has been accumulating, there has also been progress in the development of methods for technical performance assessment and quality control of these imaging systems. DBT is a relatively complicated ‘pseudo-3D’ modality whose technical assessment poses a number of difficulties. This paper reviews methods for the technical performance assessment of DBT devices, starting at the component level in part one and leading up to discussion of system evaluation with physical test objects in part two. We provide some historical and basic theoretical perspective, often starting from methods developed for DM imaging. Data from a multi-vendor comparison are also included, acquired under the medical physics quality control protocol developed by EUREF and currently being consolidated by a European Federation of Organisations for Medical Physics working group. These data and associated methods can serve as a reference for the development of reference data and provide some context for clinical studies.

Image Quality Comparison between Digital Breast Tomosynthesis Images and 2D Mammographic Images Using the CDMAM Test Object

To evaluate the image quality (IQ) of synthesized two-dimensional (s2D) and tomographic layer (TL) mammographic images in comparison to the 2D digital mammographic images produced with a new digital breast tomosynthesis (DBT) system. Methods: The CDMAM test object was used for IQ evaluation of actual 2D images, s2D and TL images, acquired using all available acquisition modes. Evaluation was performed automatically using the commercial software that accompanied CDMAM. Results: The IQ scores of the TLs with the in-focus CDMAM were comparable, although usually inferior to those of 2D images acquired with the same acquisition mode, and better than the respective s2D images. The IQ results of TLs satisfied the EUREF limits applicable to 2D images, whereas for s2D images this was not the case. The use of high-dose mode (H-mode), instead of normal-dose mode (N-mode), increased the image quality of both TL and s2D images, especially when the standard mode (ST) was used. Although the high-resolution (HR) mode produced TL images of similar or better image quality compared to ST mode, HR s2D images were clearly inferior to ST s2D images. Conclusions: s2D images present inferior image quality compared to 2D and TL images. The HR mode produces TL images and s2D images with half the pixel size and requires a 25% increase in average glandular dose (AGD). Despite that, IQ evaluation results with CDMAM are in favor of HR resolution mode only for TL images and mainly for smaller-sized details.

Prospective Comparison of Synthesized Mammography with DBT and Full-Field Digital Mammography with DBT Uncovers Recall Disagreements That may Impact Cancer Detection

RATIONALE AND OBJECTIVES

Synthesized mammography with digital breast tomosynthesis (SM+DBT) and full-field digital mammography with DBT were prospectively evaluated for recall rate (RR), cancer detection rate (CDR), positive predictive value 1 (PPV1), lesion recall differences, and disagreements in recall for additional imaging.

MATERIALS AND METHODS

From December 15, 2015 to January 15, 2017, after informed consent was obtained for this Health Insurance Portability and Accountability Act compliant study, each enrolled patient's SM+DBT and FFDM+DBT were interpreted sequentially by one of eight radiologists. RR, CDR, PPV1, and imaging findings (asymmetry, focal asymmetry, mass, architectural distortion, and calcifications) recalled were reviewed.

RESULTS

For SM+DBT and FFDM+DBT in 1022 patients, RR was 7.3% and 7.9% (SM+DBT vs. FFDM+DBT: diff= -0.6%; 90% CI= -1.4%, 0.1%); CDR was 6.8 and 7.8 per 1000 (SM+DBT vs. FFDM+DBT: diff= -1.0, 95% CI= -5.5, 2.8, p = 0.317); PPV1 was 9.3% and 9.9% (relative positive predictive value for SM+DBT vs. FFDM+DBT: 0.95, 95% CI: 0.73-1.22, p = 0.669). FFDM+DBT detected eight cancers; SM+DBT detected seven (missed 1 cancer with calcifications). SM+DBT and FFDM+DBT disagreed on patient recall for additional imaging in 19 patients, with majority (68%, 13/19 patients) in the recall of patients for calcifications. For calcifications, SM+DBT recalled six patients that FFDM+DBT did not recall, and FFDM+DBT recalled seven patients that SM+DBT did not recall, even though the total number of calcifications finding recalled was similar overall for both SM+DBT and FFDM+DBT.

CONCLUSION

Disagreement in recall of patients for calcifications may impact cancer detection by SM+DBT, warranting further investigation.

Assessment of screen-recalled abnormalities for digital breast tomosynthesis versus digital mammography screening in the BreastScreen Maroondah trial

INTRODUCTION

Australia's first population-based pilot trial comparing digital breast tomosynthesis (DBT) and digital mammography (DM) screening reported detection measures in 2019. This study describes the trial's secondary outcomes pertaining to the assessment process in women screened with DBT or DM, including the type of recalled abnormalities and the procedures performed.

METHODS

Women with suspected abnormalities at screening were recalled for further investigation. Outcome measures were number of lesions assessed, types of imaging findings recalled to assessment, and data on testing and assessment outcomes; these were reported using descriptive analyses of lesion-specific data.

RESULTS

A total of 274 lesions and 203 lesions were reported in the DBT-screened and DM-screened groups, respectively. There were a higher proportion of lesions depicted as calcifications (32.4% vs 21.3%), and a lower proportion of lesions depicted as asymmetrical densities (3.2% vs 15.7%) for DBT recalls than DM recalls. A lower proportion of DBT-recalled lesions was assessed with additional mammography than DM-recalled lesions (49.3% vs 93.1%). Higher proportions of DBT-recalled lesions than DM-recalled lesions were investigated with clinical breast examination (50.4% vs 39.9%), core needle biopsy (45.6% vs 28.6%) and open biopsy (4.0% vs 1.0%). Similar proportions of DBT- and DM-recalled lesions were assessed using ultrasound (76.3% vs 71.4%).

CONCLUSION

Assessment of screen-recalled lesions showed that, compared with DM, DBT found more benign and more malignant lesions, and generally required more procedures except for less additional mammography workup. These findings show that a transition to DBT screening changes the assessment workload.

Could Breast Tomosynthesis With Synthetic View Mammography Aid Standard Two-Dimensional Mammography in Evaluation at Symptomatic Triple Assessment Breast Clinics?

Background

This study aimed to determine whether breast tomosynthesis and synthetic view mammography (SM) can aid standard two-dimensional mammography (S2DM) in the evaluation of symptomatic women at triple assessment clinics (TACs).

Methodology

Digital breast tomosynthesis (DBT), SM, and S2DM were performed on 400 patients at symptomatic breast TACs between September 2020 and November 2020. Diagnostic findings on mammography and ultrasound were retrospectively recorded and analyzed by a breast-trained radiologist with 13 years of clinical experience. Pathology results for all biopsies were recorded and correlated with the mammographic and ultrasound findings.

Results

The combination of DBT and SM was superior to S2DM in the following settings: calcifications were more conspicuous on SM than S2DM in 44% of patients with calcifications. Mass margins were better defined on DBT than S2DM in 71% of patients with masses. Distortion was more easily detectable in 11% of patients with distortion on SM and in 44% of patients with distortion on DBT compared with S2DM. All malignant lesions were identified on all modalities.

Conclusions

Combined DBT and SM demonstrated several advantages over S2DM alone. SM can provide equal and sometimes superior diagnostic performance with the added benefit of requiring no additional radiation exposure when synthesized from DBT data. We conclude that adding DBT and SM to S2DM aids in the assessment of symptomatic women, and omitting S2DM results in no loss of clinically relevant information for women presenting to symptomatic breast clinics.

Comparison of diagnostic performances in the evaluation of breast microcalcifications: synthetic mammography versus full-field digital mammography

BACKGROUND

Although several studies proved that SM could substitute for FFDM, the efficacy of SM in microcalcification evaluation remains controversial.

AIMS

To investigate the diagnostic performance of synthetic mammography (SM) in the evaluation of microcalcifications in comparison with full-field digital mammography (FFDM).

METHODS

In this retrospective study, 76 mammograms of 76 patients who underwent FFDM and digital breast tomosynthesis (DBT) acquisitions concomitantly between 2018 and 2019 and whose final mammography interpretation revealed microcalcifications (28 malignant microcalcifications and 48 benign microcalcifications) were included. All mammograms were reviewed independently by three radiologists with different levels of breast imaging experience. Readers were blinded to patient outcomes and interpreted each case in two separate reading sessions (first FFDM, second SM + DBT), according to the BI-RADS lexicon. The area under the receiver operating characteristic (ROC) curve (AUC) was calculated using ROC analysis in all cases for FFDM and SM + DBT sessions. The readers also assigned conspicuity scores to mammograms. The interobserver agreement was calculated using intraclass correlation coefficients (ICC).

RESULTS

The overall AUCs for malignant microcalcifications were 0.80 (95% CI: 0.75-0.85) in FFDM and 0.85 (95% CI: 0.80-0.89) in SM, and no significant difference was found between the groups (p = 0.0603). The sensitivity of the readers increased slightly with experience. The ICC values of BI-RADS categorization between readers were 0.93 (95% CI: 0.90-0.95) and 0.94 (95% CI: 0.91-0.96) for FFDM and SM, respectively.

CONCLUSIONS

SM had similar diagnostic performance in the evaluation of breast microcalcifications in comparison with FFDM, regardless of reader experience levels.

The impact on lesion detection via a multi-vendor study: A phantom-based comparison of digital mammography, digital breast tomosynthesis, and synthetic mammography

PURPOSE

The aim of this study is to perform a test object-based comparison of the imaging performance of digital mammography (DM), digital breast tomosynthesis (DBT), and synthetic mammography (SM).

METHODS

Two test objects were used, the CDMAM and the L1-structured phantom. Small-detail detectability was assessed using CDMAM and the microcalcification simulating specks in the L1-structured background. Detection of spiculated and non-spiculated mass-like objects was assessed using the L1 phantom. Six different systems were included: Amulet Innovality (Fujifilm), Senographe Pristina (GEHC), 3Dimensions (Hologic), Giotto Class (IMS), Clarity 2D/3D (Planmed), and Mammomat Revelation (Siemens). Images were acquired under automatic exposure control (AEC) and at adjusted levels of AEC/2 and 2 × AEC level. Threshold gold thickness (T_tr ) was established for the 0.13-mm-diameter CDMAM discs. Threshold diameters for the calcifications (d_{tr_c} ), the spiculated masses (d_{tr_sm} ), and for the non-spiculated masses (d_{tr_nsm} ) were established. The threshold condition was defined as the thickness or diameter for a 62.5% correct score.

RESULTS

T_tr for DM was generally superior to DBT, which in turn was superior to SM, but for most systems, these differences between modes were not significant. For L1, no significant differences in d_{tr_c} were found between DM and DBT. The increase in d_{tr_c} from DM to SM at AEC dose was 1%, 19%, 11%, 14%, 46%, and 27% for the Fujifilm, GEHC, Hologic, IMS, Planmed, and Siemens, respectively, indicating significantly poorer performance for all vendors except for Fujifilm, Hologic, and IMS. For both mass types, DBT performed better than SM, while SM showed no significant difference with DM (except for Fujifilm spiculated masses). The dose had an impact on small-detail detectability for both phantoms but did not influence the detection of either mass type.

CONCLUSIONS

Both phantoms indicated potentially reduced small-detail detectability for SM versus DM and DBT and should therefore not be used in stand-alone mode. The L1 phantom demonstrated no significant difference in microcalcification detection between DM and DBT and also demonstrated the superiority of DBT, compared to DM for mass detection, for all six systems.

Synthesis of Mammogram From Digital Breast Tomosynthesis Using Deep Convolutional Neural Network With Gradient Guided cGANs

Synthetic digital mammography (SDM), a 2D image generated from digital breast tomosynthesis (DBT), is used as a potential substitute for full-field digital mammography (FFDM) in clinic to reduce the radiation dose for breast cancer screening. Previous studies exploited projection geometry and fused projection data and DBT volume, with different post-processing techniques applied on re-projection data which may generate different image appearance compared to FFDM. To alleviate this issue, one possible solution to generate an SDM image is using a learning-based method to model the transformation from the DBT volume to the FFDM image using current DBT/FFDM combo images. In this study, we proposed to use a deep convolutional neural network (DCNN) to learn the transformation to generate SDM using current DBT/FFDM combo images. Gradient guided conditional generative adversarial networks (GGGAN) objective function was designed to preserve subtle MCs and the perceptual loss was exploited to improve the performance of the proposed DCNN on perceptual quality. We used various image quality criteria for evaluation, including preserving masses and MCs which are important in mammogram. Experiment results demonstrated progressive performance improvement of network using different objective functions in terms of those image quality criteria. The methodology we exploited in the SDM generation task to analyze and progressively improve image quality by designing objective functions may be helpful to other image generation tasks.

[Assessment of imaging performance of digital breast tomosynthesis based on systematic simulation]

OBJECTIVE

To assess the imaging performance of digital breast tomography (DBT) based on systematic simulation.

OBJECTIVE

The raw measurements of physical phantoms at a variety of radiation dose levels and clinical patients at the normal radiation dose were acquired from a clinical DBT system for low-dose simulation and reconstruction using 3 reconstruction algorithms, namely Feldkamp-Davis-Kress (FDK), simultaneous algebraic reconstruction technique (SART) and adaptive steepest-descent projection onto convex sets with total-variation constraint (ASDPOCS-TV) algorithms. The image quality was compared across different radiation dose levels and reconstruction algorithms in terms of signal-to-noise ratio (SNR), peak signal-to-noise ratio (PSNR), noise-power spectrum (NPS), artifact spread function (ASF) and full width at half maximum (FWHM) of ASF indexes.

OBJECTIVE

The reliability of low-dose DBT simulation strategy was verified by the experiment. Within a suitable range of dose levels, increasing the doses resulted in reduced high-frequency noise component and significantly increased SNR (P < 0.05). But when the value of exposure was below 40 mAs, the images acquired at different dose levels had similar representation. The performance of the 3 reconstruction algorithms varied for different anatomical structures, and the image quality of ASDPOCS-TV algorithm was generally superior to SART and FDK algorithms with less through-plane artifacts and noise.

OBJECTIVE

The quality of DBT images is significantly affected by both radiation dose and reconstruction algorithms. A tradeoff of the parameters, the overall image quality and the clinical needs for diagnostic purposes should be considered to achieve the optimal imaging performance on a given clinical task.

Digital Breast Tomosynthesis: an Overview

Breast cancer is emerging as the most common malignancy in Indian women. Mammography is one of the few screening modalities available to the modern world that has proved itself of much use by aiding early detection and treatment of non-palpable, node-negative breast cancers. However, due to its two-dimensional nature, many cases of malignancies are still missed, to be detected at a later date or by an alternate modality. In 2011, FDA approved the supplemental use of digital breast tomosynthesis (DBT) in screening and diagnostic set ups. The acquisition of multiple low-dose projection images of the compressed parenchyma provided a 'third' dimension to the mammogram whereby the breast tissue could be seen layer by layer on the workstation. It improves cancer detection rate, and reduces recall rate and false-positive findings by improving lesion characterization. The current review discusses the principle of DBT with a comprehensive study of the literature.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13193-021-01310-y.

Evaluation of microcalcification contrast in clinical images for digital mammography and synthetic mammography

PURPOSE

The aim of this work was to compare, in a clinical study, digital mammography and synthetic mammography imaging by evaluating the contrast in microcalcifications of different sizes.

METHODS

A retrospective review of microcalcifications from 46 patients was undertaken. A Hologic 3-Dimensions mammography system and a HD Combo protocol was used for simultaneous acquisition of the digital and synthetic images. Microcalcifications were classified in accordance with their size, and patient breast images were classified in accordance with their density as adipose, moderately dense and dense. The contrast of the microcalcifications was measured and the contrast ratio between synthetic and digital images was compared. An additional qualitative assessment of the images was presented to correlate the conspicuity of the microcalcifications with the suppression of the structure noise.

RESULTS

Microcalcifications in adipose background always exhibit a comparable or better contrast on synthetic images, regardless their size. For moderately dense background, synthetic images show a better contrast in 91.2 % of cases for small microcalcifications and in 90.9 % of cases for large microcalcifications. For a dense background, better contrast is seen in 89.5 % of cases for small microcalcifications, and in 85.7 % of cases for large microcalcifications. The contrast ratio increases with increasing breast glandularity. The suppression of structure noise also contributes to the enhancement of microcalcifications in the synthetic images.

CONCLUSIONS

Synthetic mammography imaging is superior to digital mammography imaging in terms of microcalcification contrast, regardless their size and breast density.

Digital Mammography Has Persistently Increased High-Grade and Overall DCIS Detection Without Altering Upgrade Rate

OBJECTIVE. The purpose of this article is to evaluate whether digital mammography (DM) is associated with persistent increased detection of ductal carcinoma in situ (DCIS) or has altered the upgrade rate of DCIS to invasive cancer. MATERIALS AND METHODS. An institutional review board-approved retrospective search identified DCIS diagnosed in women with mammographic calcifications between 2001 and 2014. Ipsilateral cancer within 2 years, masses, papillary DCIS, and patients with outside imaging were excluded, yielding 484 cases. Medical records were reviewed for mammographic calcifications, technique, and pathologic diagnosis. Mammograms were interpreted by radiologists certified by the Mammography Quality Standards Act. The institution transitioned from film-screen mammography (FSM) to exclusive DM by 2010. Statistical analyses were performed using chi-square test. RESULTS. Of 484 DCIS cases, 158 (33%) were detected by FSM and 326 (67%) were detected by DM. The detection rate was higher with DM than FSM (1.4 and 0.7 per 1000, respectively; p < .001). The detection rate of high-grade DCIS doubled with DM compared with FSM (0.8 and 0.4 per 1000, respectively; p < .001). The prevalent peak of DM-detected DCIS was 2.7 per 1000 in 2008. Incident DM detection remained double FSM (1.4 vs 0.7 per 1000). Similar proportions of high-grade versus low- to intermediate-grade DCIS were detected with both modalities. There was no significant difference in the upgrade rate of DCIS to invasive cancer between DM (10%; 34/326) and FSM (10%; 15/158) (p = .74). High-grade DCIS led to 71% (35/49) of the upgrades to invasive cancer. CONCLUSION. DM was associated with a significant doubling in DCIS and high-grade DCIS detection, which persisted after prevalent peak. The majority of upgrades to invasive cancer arose from high-grade DCIS. DM was not associated with decreased upgrade to invasive cancer.

Digital Breast Tomosynthesis: Update on Technology, Evidence, and Clinical Practice

Digital breast tomosynthesis (DBT) has been widely adopted in breast imaging in both screening and diagnostic settings. The benefits of DBT are well established. Compared with two-dimensional digital mammography (DM), DBT preferentially increases detection of invasive cancers without increased detection of in-situ cancers, maximizing identification of biologically significant disease, while mitigating overdiagnosis. The higher sensitivity of DBT for architectural distortion allows increased diagnosis of invasive cancers overall and particularly improves the visibility of invasive lobular cancers. Implementation of DBT has decreased the number of recalls for false-positive findings at screening, contributing to improved specificity at diagnostic evaluation. Integration of DBT in diagnostic examinations has also resulted in an increased percentage of biopsies with positive results, improving diagnostic confidence. Although individual DBT examinations have a longer interpretation time compared with that for DM, DBT has streamlined the diagnostic workflow and minimized the need for short-term follow-up examinations, redistributing much-needed time resources to screening. Yet DBT has limitations. Although improvements in cancer detection and recall rates are seen for patients in a large spectrum of age groups and breast density categories, these benefits are minimal in women with extremely dense breast tissue, and the extent of these benefits may vary by practice environment and by geographic location. Although DBT allows detection of more invasive cancers than does DM, its incremental yield is lower than that of US and MRI. Current understanding of the biologic profile of DBT-detected cancers is limited. Whether DBT improves breast cancer-specific mortality remains a key question that requires further investigation. ^©RSNA, 2021.

Comparison of two-dimensional synthesized mammograms versus original digital mammograms: a quantitative assessment

This study objectively evaluates the similarity between standard full-field digital mammograms and two-dimensional synthesized digital mammograms (2DSM) in a cohort of women undergoing mammography. Under an institutional review board-approved data collection protocol, we retrospectively analyzed 407 women with digital breast tomosynthesis (DBT) and full-field digital mammography (FFDM) examinations performed from September 1, 2014, through February 29, 2016. Both FFDM and 2DSM images were used for the analysis, and 3216 available craniocaudal (CC) and mediolateral oblique (MLO) view mammograms altogether were included in the dataset. We analyzed the mammograms using a fully automated algorithm that computes 152 structural similarity, texture, and mammographic density-based features. We trained and developed two different global mammographic image feature analysis-based breast cancer detection schemes for 2DSM and FFDM images, respectively. The highest structural similarity features were obtained on the coarse Weber Local Descriptor differential excitation texture feature component computed on the CC view images (0.8770) and MLO view images (0.8889). Although the coarse structures are similar, the global mammographic image feature-based cancer detection scheme trained on 2DSM images outperformed the corresponding scheme trained on FFDM images, with area under a receiver operating characteristic curve (AUC) = 0.878 ± 0.034 and 0.756 ± 0.052, respectively. Consequently, further investigation is required to examine whether DBT can replace FFDM as a standalone technique, especially for the development of automated objective-based methods.

Technical evaluation of image quality in synthetic mammograms obtained from 15° and 40° digital breast tomosynthesis in a commercial system: a quantitative comparison

Digital breast tomosynthesis (DBT) has recently gained interest both for breast cancer screening and diagnosis. Its employment has increased also in conjunction with digital mammography (DM), to improve cancer detection and reduce false positive recall rate. Synthetic mammograms (SMs) reconstructed from DBT data have been introduced to replace DM in the DBT + DM approach, for preserving the benefits of the dual-acquisition modality whilst reducing radiation dose and compression time. Therefore, different DBT models have been commercialized and the effective potential of each system has been investigated. In particular, wide-angle DBT was shown to provide better depth resolution than narrow-angle DBT, while narrow-angle DBT allows better identification of microcalcifications compared to wide-angle DBT. Given the increasing employment of SMs as supplement to DBT, a comparison of image quality between SMs obtained in narrow-angle and wide-angle DBT is of practical interest. Therefore, the aim of this phantom study was to evaluate and compare the image quality of SMs reconstructed from 15° (SM₁₅) and 40° (SM₄₀) DBT in a commercial system. Spatial resolution, noise and contrast properties were evaluated through the modulation transfer function (MTF), noise power spectrum, maps of signal-to-noise ratio (SNR), image contrast, contrast-to-noise ratio (CNR) and contrast-detail (CD) thresholds. SM₄₀ expressed higher MTF than SM₁₅, but also lower SNR and CNR levels. SM₁₅ and SM₄₀ were characterized by slight different texture, and a different behavior in terms of contrast was found. SM₁₅ provided better CD performances than SM₄₀. These results suggest that the employment of wide/narrow-angle DBT + SM images should be optimized based on the specific image task.

Digital Breast Tomosynthesis: Technique and Common Artifacts

Image optimization at digital breast tomosynthesis (DBT) involves a series of trade-offs between multiple variables. Wider sweep angles provide better separation of overlapping tissues, but they result in decreased in-plane resolution as well as increased scan times that may be prone to patient motion. Techniques to reduce scan time, such as continuous tube motion and pixel binning during detector readout, reduce the chances of patient motion but may degrade the in-plane resolution. Image artifacts are inherent to DBT because of the limited angular range of the acquisition. Iterative reconstruction algorithms have been shown to reduce various DBT artifacts.

Comparison of Mass Size Measurements: Synthesized Mammography Versus Full-Field Digital Mammography

OBJECTIVES

To compare mass size measurements between synthesized mammography (SM) and full-field digital mammography (FFDM), and to assess interobserver agreement for those measurements.

MATERIALS AND METHODS

One hundred and forty-three patients who underwent FFDM and digital breast tomosynthesis acquisitions during the same compression session were included in the study. Two observers with four-and 1-year experience with digital breast tomosynthesis and SM images, respectively, measured mass sizes independently in two different sessions that were 2 weeks apart, and were blinded to each other. The first session included only FFDM images, and the second session included only SM images. Largest dimension of masses was measured in millimeters. Paired t test was used to compare differences in size measurements between FFDM and SM images. Intraclass correlation coefficient test was used to analyze interobserver agreement. Bland-Altman analyses were performed to evaluate agreements between the imaging techniques and between the observers.

RESULTS

The mean mass sizes on FFDM and SM images were 20.27 ± 14.10 and 18.50 ± 13.05 mm, respectively, for the first observer and 21.56 ± 14.84 and 19.89 ± 13.68 mm, respectively, for the second observer. The mass size measurements were significantly different between FFDM and SM for both observers (p < 0.001). Range of measurement errors, defined as 95% limits of agreements between two imaging techniques for observers 1 and 2 were ±1.96*1.36 mm, and ±1.96*1.53 mm, respectively. Range of measurement errors, defined as 95% limits of agreements between two observers for SM and FFDM were ±1.96*3.68 mm, and ±1.96*3.35 mm, respectively.

CONCLUSION

The measured mass sizes were significantly smaller on SM than FFDM images, and the interobserver differences for both of the imaging techniques were greater than the differences measured between FFDM and SM images.

Performance of 2D Synthetic Mammography Versus Digital Mammography in the Detection of Microcalcifications at Screening

OBJECTIVE. The purpose of this study is to compare the performance of 2D synthetic mammography (SM) to that of full-field digital mammography (FFDM) in the detection of microcalcifications and to evaluate radiologists' preference between the two imaging modalities for assessing calcifications. MATERIALS AND METHODS. A fully crossed, mode-balanced, paired-case (n = 160), retrospective, multireader (n = 3) performance study was implemented to compare screening mammograms acquired with digital breast tomosynthesis and both FFDM and SM between 2015 and 2017. The study cohort included 70 patients with mammograms recalled for microcalcifications (35 with malignant findings and 35 with benign findings) and was supplemented with 90 patients with mammograms with negative findings. In separate sessions, readers interpreted SM or FFDM images by recording a BI-RADS assessment and the probability of malignancy. In a final session that included 70 mammograms with microcalcifications, readers recorded their subjective assessment of microcalcification conspicuity and diagnostic confidence. RESULTS. There was no difference in diagnostic accuracy as assessed by comparing the likelihood of malignancy based on the AUC of plotted ROCs, with AUCs of 91% (95% CI, 83-97%) and 88% (95% CI, 79-95%) observed for SM and FFDM, respectively (p = 0.392), and with noninferiority of SM compared with FFDM (p = 0.011). No significant difference was observed between SM and FFDM in terms of sensitivity (77% vs 73%, respectively; p = 0.366) or negative predictive value (84% vs 82%, respectively; p = 0.598). The specificity and positive predictive value of SM were lower than those of FFDM (91% vs 98%, respectively [p = 0.034], and 87% vs 96%, respectively [p = 0.034]). All readers found calcifications to be more conspicuous on SM (p < 0.0001); however, no significant difference in subjective diagnostic confidence was seen. CONCLUSION. SM is noninferior to FFDM in the detection of microcalcifications. Despite the increased conspicuity of microcalcifications on SM, the subjective diagnostic confidence in the two modalities is comparable.

Comparative analysis between synthetic mammography reconstructed from digital breast tomosynthesis and full-field digital mammography for breast cancer detection and visibility

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2D synthetic mammography images from the DBT dataset do not require additional radiation exposure.

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We compare observer performance between 2DSM and FFDM for breast cancer detection and visibility.

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Diagnostic performances of 2DSM and FFDM images were comparable for detecting breast cancers.

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2DSM may eliminate the need for additional FFDM during DBT-based imaging.

Purpose

To compare observer performance between synthetic mammography (2DSM) and full-field digital mammography (FFDM) for breast cancer detection and visibility.

Method

A retrospective analysis was conducted on 136 histopathologically proven cases of breast cancer in patients who underwent FFDM and digital breast tomosynthesis (DBT). 2DSM images were reconstructed from DBT data, and 2DSM and FFDM images were reviewed and evaluated for mammographic features, probability of malignancy (BI-RADS classification), and lesion conspicuity. DBT images were not reviewed. Statistical differences in cancer detection rates between 2DSM and FFDM images were analyzed using the McNemar test, agreement on BI-RADS assessment between 2DSM and FFDM was assessed using Cohen’s kappa test, and the Wilcoxon’s signed rank test was used to compare visibility scores.

Results

Mean cancer detection rates with 2DSM and FFDM images were 84.6 % and 87.8 %, respectively. In subgroup analyses, differences in breast density, tumor size, and presence of calcifications were not statistically significant. Agreement between 2DSM and FFDM images for BI-RADS classification was graded as good with Cohen’s k-coefficient of 0.78 ± 0.05. Visibility scores in both modalities of images were similar for all lesions combined; however, 2DSM had significantly better visibility scores for calcified cancers (p < 0.01), and in dense breast tissue (p < 0.01).

Conclusions

Diagnostic performances of 2DSM and FFDM images were comparable for detecting breast cancers, and it is possible that 2DSM may eliminate the need for additional FFDM during DBT-based imaging due to advances in image reconstruction methods.

Survey Results Regarding Uptake and Impact of Synthetic Digital Mammography With Tomosynthesis in the Screening Setting

Synthesized digital mammography (SM) was developed to replace digital mammography (DM) in digital breast tomosynthesis (DBT) imaging to reduce radiation dose. This survey assessed utilization and attitudes regarding SM in DBT screening. The study was institutional review board exempt. An online survey was sent to members of the Society of Breast Imaging in June 2018. Questions included practice information, utilization of DBT and SM, perception of change in recall rates (RRs) and cancer detection rates (CDRs) with SM-DBT versus DM-DBT, and attitudes regarding SM versus DM in DBT screening. χ2 Tests were used to compare response frequencies across groups. In all, 312 of 2,600 Society of Breast Imaging members responded to the survey (12%). Of respondents, 96% reported DBT capability, and 83% reported SM capability. Of those without SM, the most cited reasons were cost or administration and image quality concerns (both 32%). In addition, 40% reported combined SM and DM use in DBT screens, and 52% reported SM use without DM in the majority of DBT screens. The overall satisfaction with SM was 3.4 of 5 (1-5 scale). Most cited SM advantages were decreased dose (85%) and increased lesion conspicuity (27%). The most cited SM disadvantages were calcification characterization (61%) and decreased image quality (31%). Most respondents were unsure if CDRs changed (44%) and RR changed (30%) with few reporting adverse outcomes (6% RR increase, 1% CDR decrease). Most radiologists screening with DBT have SM, but only one-half have replaced DM with SM. Despite few reported adverse screening outcomes with SM-DBT, radiologists have concerns about image quality, specifically calcification characterization.

Comprehensive assessment of image quality in synthetic and digital mammography: a quantitative comparison

Recent advances in digital breast tomosynthesis (DBT) technology were focused on the reconstruction of 2D "Synthesized Mammograms" (SMs) from DBT dataset. The introduction of SMs could avoid an additional digital mammography (DM) which is often required in complement to DBT examinations. Therefore, breast absorbed dose and compression time can be significantly reduced in DBT+SM procedures with respect to DBT+DM modality. However, to date, a limited number of studies have objectively characterised the image quality of SMs with respect to DM images. Therefore, the aim of this phantom study was to comprehensively compare SMs and DM images in terms of several image quality parameters. A Selenia Dimensions system (Hologic, Bedford, Mass, USA) was employed in this work. Five different phantoms were adopted to study noise, contrast and spatial resolution properties of the images. Specifically, noise power spectrum (NPS), maps of signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), modulation transfer function (MTF) and contrast-detail (CD) thresholds were evaluated both for SM and DM modalities. SMs were characterised by different texture, noise and SNR spatial distribution properties with respect to DM images. Additionally, while in some conditions SM provides higher CNR than DM, lower overall performances in terms spatial resolution and CD curves were found in comparison to DM images. Therefore, given the great benefits of SMs in terms of dose and compression time saving, further clinical investigations on SMs image quality properties could be of practical interest to integrate our findings.

Synthetic 2-Dimensional Mammography Can Replace Digital Mammography as an Adjunct to Wide-Angle Digital Breast Tomosynthesis

OBJECTIVES

The aim of this study was to evaluate the detection rate and diagnostic performance of 2-dimensional synthetic mammography (SM) as an adjunct to wide-angle digital breast tomosynthesis (WA-DBT) compared with digital mammography (DM) alone or to DM in combination with WA-DBT.

MATERIALS AND METHODS

There were 205 women with 179 lesions included in this retrospective reader study. Patients underwent bilateral, 2-view (2v) DM and WA-DBT between March and June 2015. The standard of reference was histology and/or 1-year stability at follow-up. Four blinded readers randomly evaluated images according to the BI-RADS lexicon from 3 different protocols: 2v DM alone, 2v DM with 2v WA-DBT, and 2v SM with 2v WA-DBT. Detection rate, sensitivity, specificity, and accuracy were calculated and compared using multivariate analysis. Readers' confidence and image quality were evaluated.

RESULTS

The detection rate ranged from 68.7% to 79.9% for DM, 76.5% to 84.4% for DM with WA-DBT, and 73.2% to 84.9% for SM with WA-DBT. Sensitivity and accuracy were significantly higher when DBT was available (P < 0.001). Specificity did not differ significantly between DM only, DM with WA-DBT, or SM with WA-DBT (P ≥ 0.846). Wide-angle DBT combined readings did not differ between SM and DM in terms of sensitivity, specificity, and accuracy (P ≥ 0.341). Readers' confidence and image quality was rated good to excellent.

CONCLUSIONS

Wide-angle DBT combined with DM or SM increases sensitivity and accuracy without reducing specificity compared with DM alone. Wide-angle DBT combined readings did not differ between SM and DM; therefore, SM should replace DM for combined readings with WA-DBT.

Comparison of the diagnostic performance of synthesized two-dimensional mammography and full-field digital mammography alone or in combination with digital breast tomosynthesis

PURPOSE

To investigate whether digital breast tomosynthesis (DBT) and subsequently generated synthesized mammography (SM) images show a better performance than full-field digital mammography (FFDM) images for diagnosing malignant breast lesions. In addition, the radiation doses for SM using different procedures were compared.

MATERIALS AND METHODS

This prospective study enrolled 212 women (age ≥ 25 years) with clinically suspicious breast lesions. All participants underwent FFDM and DBT with the same breast compression. Finally, 222 lesions were confirmed by pathological analysis. The mammogram results were evaluated according to the BI-RADS criteria and compared with the pathological results. The diagnostic performances, morphological features and average glandular doses (AGDs) were compared.

RESULTS

In total, 141 malignant lesions and 81 benign lesions were confirmed by pathological analysis. The overall AGD showed no significant difference between FFDM and DBT. Compared with 2D imaging, the AUC values of FFDM plus DBT and SM plus DBT were both significantly different overall (P = 0.0002) and remained significantly different in dense breasts (P < 0.0001). In terms of morphologic characteristics, lesions showed similar morphology between FFDM and SM, while the lesion characteristics were discordant from 2D imaging to DBT in 33 lesions in dense breasts.

CONCLUSIONS

Compared to FFDM, 2D SM images generated from DBT had significantly improved diagnostic efficacy for detecting malignant breast lesions without increasing radiation doses. This new procedure is useful for characterizing breast lesions, particularly in dense breasts.

Breast tomosynthesis: state of the art

Breast tomosynthesis is a continually improving tool for diagnostic radiologists. This update about tomosynthesis reviews the advantages of the technique both in patients with suspected or known disease and in screening, as well as its limitations, of which the dose of radiation is the most important. The more recent advent of synthesized mammography, computer-assisted detection, and tomosynthesis-guided biopsy have helped to reduce the dose of radiation used and have improved the diagnostic performance of tomosynthesis, so they are also discussed in this review.

Calcifications at Digital Breast Tomosynthesis: Imaging Features and Biopsy Techniques

Full-field digital mammography (FFDM), the standard of care for breast cancer screening, has some limitations. With the advent of digital breast tomosynthesis (DBT), improvements including decreased recall rates and increased cancer detection rates have been observed. The quasi-three-dimensional capability of DBT reduces breast tissue overlap, a significant limitation of FFDM. However, early studies demonstrate that a few cancers detected at FFDM may not be diagnosed at DBT-only screening, and lesions with calcifications as the dominant feature may look less suspicious at DBT or not be visible at all. These findings support the use of combined FFDM and DBT protocols to optimize screening performance. However, this combination would approximately double the patient's radiation exposure. The development of computer algorithms that generate two-dimensional synthesized mammography (SM) views from DBT has improved calcification conspicuity and sensitivity. Therefore, SM may substitute for FFDM in screening protocols, reducing radiation exposure. DBT plus SM demonstrates significantly better performance than that of FFDM alone, although there are reports of missed malignant calcifications. Thus, some centers continue to perform FFDM with DBT. Use of DBT in breast imaging has also necessitated the development of DBT-guided biopsy. DBT-guided biopsy may have a higher success rate than that of stereotactic biopsy, with a shorter procedure time. While DBT brings substantial improvements to breast cancer imaging, it is important to be aware of its strengths and limitations regarding detection of calcifications. This article reviews the imaging appearance of breast calcifications at DBT, discusses calcification biopsy techniques, and provides an overview of the current literature. Online supplemental material is available for this article. ^©RSNA, 2019 An earlier incorrect version of this article appeared online. This article was corrected on February 13, 2019.

Microcalcifications Detected at Screening Mammography: Synthetic Mammography and Digital Breast Tomosynthesis versus Digital Mammography

Purpose To compare the performance of two-dimensional synthetic mammography (SM) plus digital breast tomosynthesis (DBT) versus conventional full-field digital mammography (FFDM) in the detection of microcalcifications on screening mammograms. Materials and Methods In this retrospective multireader observer study, 72 consecutive screening mammograms recalled for microcalcifications from June 2015 through August 2016 were evaluated with both FFDM and DBT. The data set included 54 mammograms with benign microcalcifications and 18 mammograms with malignant microcalcifications, and 20 additional screening mammograms without microcalcifications used as controls. FFDM alone was compared to synthetic mammography plus DBT. Four readers independently reviewed each data set and microcalcification recalls were tabulated. Sensitivity and specificity for microcalcification detection were calculated for SM plus DBT and for FFDM alone. Interreader agreement was calculated with Fleiss kappa values. Results Reader agreement was kappa value of 0.66 (P < .001) for FFDM and 0.63 (P < .001) for SM plus DBT. For FFDM, the combined reader sensitivity for all microcalcifications was 80% (229 of 288; 95% confidence interval [CI]: 74%, 84%) and for malignant microcalcifications was 92% (66 of 72; 95% CI: 83%, 97%). For SM plus DBT, the combined reader sensitivity for all microcalcifications was 75% (215 of 288; 95% CI: 69%, 80%) and for malignant microcalcifications was 94% (68 of 72; 95% CI: 86%, 98%). For FFDM, the combined reader specificity for all microcalcifications was 98% (78 of 80; 95% CI: 91%, 100%) and for malignant microcalcifications was 98% (78 of 80; 95% CI: 91%, 100%). For SM plus DBT, combined reader specificity for all microcalcifications was 95% (76 of 80; 95% CI: 88%, 99%) and for malignant microcalcifications was 95% (76 of 80; 95% CI: 88%, 99%). Mixed-effects model concluded no differences between modalities (‒0.03; 95% CI: ‒0.08, 0.01; P = .13). Conclusion Relative to full-field digital mammography, synthetic mammography plus digital breast tomosynthesis had similar sensitivity and specificity for the detection of microcalcifications previously identified for recall at screening mammography. © RSNA, 2018 See also the editorial by Bae and Moon in this issue.

A comparative study of physical image quality in digital and synthetic mammography from commercially available mammography systems

We present a comparison between full field digital mammography and synthetic mammography, performed on several mammography systems from four different manufacturers. The analysis is carried out on both the digital and synthetic images of two commercially available mammography phantoms, and focuses on a set of objective metrics that encode the geometrical appearance of imaging features of diagnostic interest. In particular, we measured sizes and contrasts of several clusters of microcalcification specks, shapes and contrasts of circular masses, and the power spectrum of background regions mimicking the heterogeneous texture of the breast parenchyma. Despite the potential issues of tomosynthesis in terms of image blurring, the synthetic images do not highlight any globally significant differences in the rendering of the details of interest, when compared to the original digital mammograms: relative contrasts are generally preserved, as well as the geometry of broad structures. We conclude that, as far as the considered objective metrics are concerned, the image quality of synthetic mammography does not exhibit significant differences with respect to the one of full field digital mammography, for all the considered systems.

Evaluation of a computer-aided detection (CAD)-enhanced 2D synthetic mammogram: comparison with standard synthetic 2D mammograms and conventional 2D digital mammography

AIM

To evaluate the diagnostic performance of computer-aided detection (CAD)-enhanced synthetic mammograms in comparison with standard synthetic mammograms and full-field digital mammography (FFDM).

MATERIALS AND METHODS

A CAD-enhanced synthetic mammogram, a standard synthetic mammogram, and FFDM were available in 68 breast-screening cases recalled for soft-tissue abnormalities (masses, parenchymal deformities, and asymmetric densities). Two radiologists, blinded to image type and final assessment outcome, retrospectively read oblique and craniocaudal projections for each type of mammogram. The resulting 204 pairs of 2D images were presented in random order and scored on a five-point scale (1, normal to 5, malignant) without access to the Digital breast tomosynthesis (DBT) slices. Receiver operating characteristic (ROC) curve analysis was performed.

RESULTS

There were 34 biopsy-proven malignancies and 34 normal/benign cases. Diagnostic accuracy was significantly improved for the CAD-enhanced synthetic mammogram compared to the standard synthetic mammogram (area under the ROC curve [AUC]=0.846 and AUC=0.683 respectively, p=0.004) and compared to the conventional 2D FFDM (AUC=0.724, p=0.027). The CAD-enhanced synthetic mammogram had the highest diagnostic accuracy for all soft-tissue abnormalities, and for malignant lesions sensitivity was not affected by tumour size. For all 68 cases, there was an average of 3.2 areas enhanced per image. For the 34 cancer cases, 97.4% of lesions were correctly enhanced, with 2.1 false areas enhanced per image.

CONCLUSIONS

CAD enhancement significantly improves performance of synthetic 2D mammograms and also exhibits improved diagnostic accuracy compared to conventional 2D FFDM.

Screening for breast cancer in 2018-what should we be doing today?

Although screening mammography has delivered many benefits since its introduction in Canada in 1988, questions about perceived harms warrant an up-to-date review. To help oncologists and physicians provide optimal patient recommendations, the literature was reviewed to find the latest guidelines for screening mammography, including benefits and perceived harms of overdiagnosis, false positives, false negatives, and technologic advances. For women 40-74 years of age who actually participate in screening every 1-2 years, breast cancer mortality is reduced by 40%. With appropriate corrections, overdiagnosis accounts for 10% or fewer breast cancers. False positives occur in about 10% of screened women, 80% of which are resolved with additional imaging, and 10%, with breast biopsy. An important limitation of screening is the false negatives (15%-20%). The technologic advances of digital breast tomosynthesis, breast ultrasonography, and magnetic resonance imaging counter the false negatives of screening mammography, particularly in women with dense breast tissue.

Comparison of Breast Density Between Synthesized Versus Standard Digital Mammography

PURPOSE

To evaluate perceptual difference in breast density classification using synthesized mammography (SM) compared with standard or full-field digital mammography (FFDM) for screening.

MATERIALS AND METHODS

This institutional review board-approved, retrospective, multireader study evaluated breast density on 200 patients who underwent baseline screening mammogram during which both SM and FFDM were obtained contemporaneously from June 1, 2016, through November 30, 2016. Qualitative breast density was independently assigned by seven readers initially evaluating FFDM alone. Then, in a separate session, these same readers assigned breast density using synthetic views alone on the same 200 patients. The readers were again blinded to each other's assignment. Qualitative density assessment was based on BI-RADS fifth edition. Interreader agreement was evaluated with κ statistic using 95% confidence intervals. Testing for homogeneity in paired proportions was performed using McNemar's test with a level of significance of .05.

RESULTS

For patients across the SM and standard 2-D data set, diagnostic testing with McNemar's test with P = 0.32 demonstrates that the minimal density transitions across FFDM and SM are not statistically significant density shifts. Taking clinical significance into account, only 8 of 200 (4%) patients had clinically significant transition (dense versus not dense). There was substantial interreader agreement with overall κ in FFDM of 0.71 (minimum 0.53, maximum 0.81) and overall SM κ average of 0.63 (minimum 0.56, maximum 0.87).

CONCLUSION

Overall subjective breast density assignment by radiologists on SM is similar to density assignment on standard 2-D mammogram.

Synthesized Mammography: Clinical Evidence, Appearance, and Implementation

Digital breast tomosynthesis (DBT) has improved conventional mammography by increasing cancer detection while reducing recall rates. However, these benefits come at the cost of increased radiation dose. Synthesized mammography (s2D) has been developed to provide the advantages of DBT with nearly half the radiation dose. Since its F.D.A. approval, multiple studies have evaluated the clinical performance of s2D. In clinical practice, s2D images are not identical to conventional 2D images and are designed for interpretation with DBT as a complement. This article reviews the present literature to assess whether s2D is a practical alternative to conventional 2D, addresses the differences in mammographic appearance of findings, and provides suggestions for implementation into clinical practice.

Can the synthetic C view images be used in isolation for diagnosing breast malignancy without reviewing the entire digital breast tomosynthesis data set?

AIMS AND OBJECTIVES

The aim of this study was to determine if the synthetic C view acquired at digital breast tomosynthesis (DBT) would give adequate information to confirm a malignancy and could obviate the need to review all the tomosynthesis image data set.

METHODS

All patients with biopsy-proven breast cancer recalled from screening mammograms between May and September 2016 were included for review. For each patient, the screening 2D mammogram, the synthetic C view, and the DBT images were reviewed by three breast radiologists and each assigned a BIRADS code. Any discrepancies were reviewed and resolved by consensus.

RESULTS

A total of 92 patients were diagnosed with breast cancer in this time period. Fourteen were excluded because they did not have DBT performed. Five women were recalled for evaluation of two lesions. In total, 83 lesions were assessed. In 27 cases, the BIRADS code remained unchanged in the three modalities. In 16 cases, the lesions appeared more concerning on C view and DBT that on the original mammogram but were not definitive for malignancy (BIRADS 4). In 29 cases, a BIRADS 5 code was assigned on C view and tomosynthesis but not on 2D. For 11 lesions, a BIRADS 5 code was assigned only on DBT. Four women had BIRADS 5 lesions seen on both the C view and DBT that were not seen on the screening 2D mammogram. One was multifocal.

CONCLUSION

While the synthetic C view gives additional information when compared to a screening 2D mammogram, the full DBT tomosynthesis data set needs to be reviewed to diagnose a breast malignancy.