A multiple x-ray-source array (MXA) system with a planar two-dimensional source distribution for digital breast tomosynthesis

BACKGROUND

Digital breast tomosynthesis (DBT) has outpaced digital mammography in clinical adoption in the United States; however, substantial technological limitations remain to image quality in DBT, including undersampling from a one-dimensional (1D) scan geometry, x-ray source motion during acquisition, and patient motion artifacts from long exam times.

PURPOSE

A thermionic cathode x-ray system employing two-dimensional (2D, planar) multiple x-ray-source arrays (MXA) is proposed to improve DBT image quality.

METHODS

A 1D MXA, consisting of a linear array of thermionic cathodes was used to simulate a 2D MXA. The 1D MXA included 11 focal spots separated by a distance ofΔ d ${{\Delta}}d$  = 23 mm. The 11 cathodes were paired with 11 molybdenum 50 mm diameter anode disks, mounted on a rotating shaft within a single vacuum enclosure. Image quality was investigated as a function of MXA configuration by integrating the 1D MXA with a 200 × 250 mm2 flat panel detector at a source-to-detector distance of 630 mm, resulting in a 20° tomographic arc. To simulate a 2D MXA, the detector (with phantom) was translated orthogonally to the linear array by a distance ( δ $\delta $ ) ranging from δ $\delta $  = 0 mm (conventional 1D) to δ $\delta $  = 57 mm. All sources operated at 30 kV with 80 mA and 4.5 mAs/pulse, yielding ∼100 mAs per DBT dataset. DBT reconstructions involved 22 projections and used filtered backprojection with a ramp and Hann apodization filter. Volumetric reconstructions for each source were weighted by sampling differences between sources, and averaged. Image quality was assessed in terms of contrast-to-noise ratio (CNR), background clutter noise and power spectrum, and slice sensitivity profile (SSP) using a set of physical phantoms, including: (i) contrast-detail signals coupled to spherical clutter (PMMA in air); (ii) an SSP phantom; (iii) a commercial "breast" phantom (CIRS BR3D, Sun Nuclear, Norfolk, VA); and (iv) bovine muscle.

RESULTS

Background clutter noise amplitude reduced monotonically from the 1D MXA (σclutter = 5.9 A.U., δ $\delta $  = 0 mm) and 2D MXA arrays with increasing δ $\delta $ , with statistical significance between the 1D MXA and 2D MXA with δ $\delta $  = 57 mm (σclutter = 5.0 A.U., p < 0.001). The contrast-detail/clutter phantom demonstrated CNR from the 2D MXA (δ  = 57 mm) outperforming the 1D MXA in all combinations of contrast and detail. 2D power spectrum analysis of clutter demonstrated a pronounced Fourier domain null cone for the 1D MXA in the anterior field-of-view (away from the 1D MXA position), whereas the 2D MXA geometry (δ = 57 mm) did not exhibit the null cone. The SSP was 15%-50% narrower (FWHM) for the 2D versus the 1D geometry, across all reconstruction setups.

CONCLUSIONS

The advantages of a 2D source geometry for DBT imaging were demonstrated quantitatively compared to a conventional 1D line of x-ray sources. The improvement in the 2D geometry was attributed both to improved Fourier domain sampling and reduced SSP. We conclude that 2D MXA sources have the potential to substantially improve DBT imaging in comparison to existing commercial DBT systems.

An Efficient Deep Neural Network to Classify Large 3D Images With Small Objects

3D imaging enables accurate diagnosis by providing spatial information about organ anatomy. However, using 3D images to train AI models is computationally challenging because they consist of 10x or 100x more pixels than their 2D counterparts. To be trained with high-resolution 3D images, convolutional neural networks resort to downsampling them or projecting them to 2D. We propose an effective alternative, a neural network that enables efficient classification of full-resolution 3D medical images. Compared to off-the-shelf convolutional neural networks, our network, 3D Globally-Aware Multiple Instance Classifier (3D-GMIC), uses 77.98%-90.05% less GPU memory and 91.23%-96.02% less computation. While it is trained only with image-level labels, without segmentation labels, it explains its predictions by providing pixel-level saliency maps. On a dataset collected at NYU Langone Health, including 85,526 patients with full-field 2D mammography (FFDM), synthetic 2D mammography, and 3D mammography, 3D-GMIC achieves an AUC of 0.831 (95% CI: 0.769-0.887) in classifying breasts with malignant findings using 3D mammography. This is comparable to the performance of GMIC on FFDM (0.816, 95% CI: 0.737-0.878) and synthetic 2D (0.826, 95% CI: 0.754-0.884), which demonstrates that 3D-GMIC successfully classified large 3D images despite focusing computation on a smaller percentage of its input compared to GMIC. Therefore, 3D-GMIC identifies and utilizes extremely small regions of interest from 3D images consisting of hundreds of millions of pixels, dramatically reducing associated computational challenges. 3D-GMIC generalizes well to BCS-DBT, an external dataset from Duke University Hospital, achieving an AUC of 0.848 (95% CI: 0.798-0.896).

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.

Diagnostic Performance of Digital Breast Tomosynthesis with the Two-Dimensional Synthesized Mammogram for Suspicious Breast Microcalcifications Compared to Full-Field Digital Mammography in Stereotactic Breast Biopsy

Purpose

To evaluate the diagnostic performance of digital breast tomosynthesis (DBT) with the two-dimensional synthesized mammogram (2DSM), compared to full-field digital mammography (FFDM), for suspicious microcalcifications in the breast ahead of stereotactic biopsy and to assess the diagnostic image visibility of the images.

Materials and Methods

This retrospective study involved 189 patients with microcalcifications, which were histopathologically verified by stereotactic breast biopsy, who underwent DBT with 2DSM and FFDM between January 8, 2015, and January 20, 2020. Two radiologists assessed all cases of microcalcifications based on Breast Imaging Reporting and Data System (BI-RADS) independently. They were blinded to the histopathologic outcome and additionally evaluated lesion visibility using a five-point scoring scale.

Results

Overall, the inter-observer agreement was excellent (0.9559). Under the setting of category 4A as negative due to the low possibility of malignancy and to avoid the dilution of malignancy criteria in our study, McNemar tests confirmed no significant difference between the performances of the two modalities in detecting microcalcifications with a high potential for malignancy (4B, 4C, or 5; p = 0.1573); however, the tests showed a significant difference between their performances in detecting microcalcifications with a high potential for benignancy (4A; p = 0.0009). DBT with 2DSM demonstrated superior visibility and diagnostic performance than FFDM in dense breasts.

Conclusion

DBT with 2DSM is superior to FFDM in terms of total diagnostic accuracy and lesion visibility for benign microcalcifications in dense breasts. This study suggests a promising role for DBT with 2DSM as an accommodating tool for stereotactic biopsy in female with dense breasts and suspicious breast microcalcifications.

Intratumoral and Peritumoral Analysis of Mammography, Tomosynthesis, and Multiparametric MRI for Predicting Ki-67 Level in Breast Cancer: a Radiomics-Based Study

PURPOSE

To noninvasively evaluate the use of intratumoral and peritumoral regions from full-field digital mammography (DM), digital breast tomosynthesis (DBT), dynamic contrast-enhanced (DCE), and diffusion-weighted (DW) magnetic resonance imaging (MRI) images separately and combined to predict the Ki-67 level based on radiomics.

PROCEDURES

A total of 209 patients with pathologically confirmed breast cancer were consecutively enrolled from September 2017 to March 2021, who underwent DM, DBT, DCE-MRI, and DW MRI scans. Radiomics features were calculated from intratumoral and peritumoral regions in each modality and selected with the least absolute shrinkage and selection operator (LASSO) regression. Radiomics signatures (RSs) were built based on intratumoral, peritumoral, and combined intra- and peritumoral regions. The prediction performance of the RSs was evaluated using the area under the receiver operating characteristic curve (AUC), specificity, and sensitivity as comparison metrics. A nomogram was constructed by integrating the multi-model RS and important clinical predictors and assessed by calibration and decision curve analysis.

RESULTS

The combined intra- and peritumoral RSs improved the AUC compared with intra- or peritumoral RSs in each modality. The DCE plus DW MRI yielded higher AUC and specificity but lower sensitivity compared with the DM plus DBT. The nomogram incorporating the multi-model RS, age, and lymph node metastasis status achieved the best prediction performance in the training (AUC, nomogram vs. fusion RS vs. clinical model, 0.922 vs. 0.917 vs. 0.672) and validation (AUCs, nomogram vs. fusion RS vs. clinical model, 0.866 vs. 0.838 vs. 0.661) cohorts. DCA analysis confirmed the potential clinical utility of the nomogram.

CONCLUSIONS

Peritumoral regions can provide complementary information to intratumoral regions in mammography and MRI for the prediction of Ki-67 levels. The MRI performed better than mammography in terms of AUC and specificity but weaker in sensitivity. The nomogram has a predictive advantage over each modality and could be a potential tool for predicting Ki-67 levels in breast cancer.

Intratumoral analysis of digital breast tomosynthesis for predicting the Ki-67 level in breast cancer: A multi-center radiomics study

PURPOSE

To non-invasively evaluate the Ki-67 level in digital breast tomosynthesis (DBT) images of breast cancer (BC) patients based on subregional radiomics.

METHODS

A total of 266 patients who underwent DBT scans were consecutively enrolled at two centers, between September 2017 and September 2021. The whole tumor region was partitioned into various intratumoral subregions, based on individual- and population-level clustering. Handcrafted radiomics and deep learning-based features were extracted from the subregions and from the whole tumor region, and were selected by least absolute shrinkage and selection operator (LASSO) regression, yielding radiomics signatures (RSs). The area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity were calculated to assess the developed RSs.

RESULTS

Each breast tumor region was partitioned into an inner subregion (S1) and a marginal subregion (S2). The RSs derived from S1 always generated higher AUCs compared with those from S2 or from the whole tumor region (W), for the external validation cohort (AUCs, S1 vs. W, handcrafted RSs: 0.583 [95% CI, 0.429-0.727] vs. 0.559 [95% CI, 0.405-0.705], p-value: 0.920; deep RSs: 0.670 [95% CI, 0.516-0.802] vs. 0.551 [95% CI, 0.397-0.698], p-value: 0.776). The fusion RSs, combining handcrafted and deep learning-based features derived from S1, yielded the highest AUCs of 0.820 (95% CI, 0.714-0.900) and 0.792 (95% CI, 0.647-0.897) for the internal and external validation cohorts, respectively.

CONCLUSIONS

The subregional radiomics approach can accurately predict the Ki-67 level based on DBT data; thus, it may be used as a potential non-invasive tool for preoperative treatment planning in BC.

Does automated breast ultrasound (ABUS) add to breast tomosynthesis (DBT) in assessment of lesions in dense breasts?

Background

As mammography has its known limitations in dense breast, additional imaging is usually needed. We aimed to evaluate the role of automated breast ultrasound in addition to tomosynthesis in detection and diagnosis of breast lesions in dense breasts. Seventy patients with dense breasts subjected to full-field digital mammography (FFDM) including digital breast tomosynthesis (DBT) and automated breast ultrasound (ABUS). Both studies were evaluated by two experienced radiologists to assess breast composition, mass characterization, asymmetry, calcification, axillary lymphadenopathy, extent of disease (EOD), skin thickening, retraction, architectural distortion, and BIRADS classification. All breast masses were interpreted as above described and then correlated with final pathological diagnosis.

Results

Study included 70 females presenting with different types of breast lesions. Eighty-two masses were detected: 53 benign (n = 53/82), 29 malignant (n = 29/82). Histopathology of the masses was reached by core biopsy (n = 30), FNAC (n = 14), and excisional biopsy (n = 11). The rest of the masses (n = 27/82) were confirmed by their characteristic sonographic appearances; 20 cases of multiple bilateral anechoic simple cysts, 7 typical fibroadenomas showed stationary course on follow-up. As regards the final BIRADS score given for both modalities, tomosynthesis showed accuracy of 93.1% in characterization of malignant masses with accuracy of 94.3% in benign masses, on the other hand automated ultrasound showed 100% accuracy in characterization of malignant masses with 98.1% accuracy in benign masses.

Conclusion

Adding ABUS to tomosynthesis has proven a valuable imaging tool for characterization of breast lesions in dense breasts both as screening and diagnostic tool. They proved to be more sensitive and specific than digital mammography alone in showing tissue overlap, tumor characterization, lesion margins, extent, and multiplicity of malignant lesions.

Breast cancer screening in average and high-risk women

Breast cancer is the most common cancer among females worldwide with rising incidence. In the United States, screening mammography and advances in therapy have lowered mortality by 41% since 1990. Screening mammography is supported by randomized control trials (RCT), observational studies, and computer model data. Digital breast tomosynthesis is a new technology that addresses limitations in mammography resulting from overlapping breast tissue, improving its sensitivity and specificity. Patients at high risk for breast cancer include those with a ≥20% lifetime risk, high-risk germline mutation, or history of thoracic radiation treatment between 10-30 years of age. Such patients are recommended to undergo annual screening mammography and adjunctive annual screening breast MRI. Patients unable to undergo MRI may undergo whole breast ultrasound or contrast-enhanced mammography. Pregnant and lactating patients at average risk for breast cancer are recommended to undergo age-appropriate screening mammography.

Radiomic Evaluations of the Diagnostic Performance of DM, DBT, DCE MRI, DWI, and Their Combination for the Diagnosisof Breast Cancer

Objectives

This study aims to evaluate digital mammography (DM), digital breast tomosynthesis (DBT), dynamic contrast-enhanced (DCE), and diffusion-weighted (DW) MRI, individually and combined, for the values in the diagnosis of breast cancer, and propose a visualized clinical-radiomics nomogram for potential clinical uses.

Methods

A total of 120 patients were enrolled between September 2017 and July 2018, all underwent preoperative DM, DBT, DCE, and DWI scans. Radiomics features were extracted and selected using the least absolute shrinkage and selection operator (LASSO) regression. A radiomics nomogram was constructed integrating the radiomics signature and important clinical predictors, and assessed with the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA).

Results

The radiomics signature derived from DBT plus DM generated a lower area under the ROC curve (AUC) and sensitivity, but a higher specificity compared with that from DCE plus DWI. The nomogram integrating the combined radiomics signature, age, and menstruation status achieved the best diagnostic performance in the training (AUCs, nomogram vs. combined radiomics signature vs. clinical model, 0.975 vs. 0.964 vs. 0.782) and validation (AUCs, nomogram vs. combined radiomics signature vs. clinical model, 0.983 vs. 0.978 vs. 0.680) cohorts. DCA confirmed the potential clinical usefulness of the nomogram.

Conclusions

The DBT plus DM provided a lower AUC and sensitivity, but a higher specificity than DCE plus DWI for detecting breast cancer. The proposed clinical-radiomics nomogram has diagnostic advantages over each modality, and can be considered as an efficient tool for breast cancer screening.

Using Facebook Live to Advocate Breast Cancer Screening

With current conflicting and confusing screening mammography guidelines between major medical organizations, radiologists have an opportunity to educate and advocate for patients using the power of social media. The authors provide a brief overview on the impact of social media in radiology, in particular Facebook, as well as challenges encountered by radiologists as they establish an online presence, and how to effectively use Facebook Live to advocate for screening mammography.

A history of DMIST and its implications - Limited resources should be better spent

Randomized, Controlled Trials (RCT), the most rigorous tests of efficacy, had proven that mammography screening reduces deaths by early detection. This had been validated in studies that showed that screening in the community also resulted in fewer deaths. Film mammography (FM) had been replaced by Xeroradiography (XM) which had been replaced by Screen/Film Mammography (SFM) which was being replaced by Full Field Digital Mammography (FFDM). The FDA required FFDM to undergo a Premarket Approval (PMA) instead of the usual 510 K required for conversion for other x-ray studies to digital imaging. In addition, the FDA was going to require that even after a PMA, the FFDM systems were going to have to undergo a post approval RCT comparison to SFM. Experience and science were able to convince the FDA that a post-approval trial was not needed, and the requirement was dropped. Congress, however, had earmarked $25 million to support the trial that was no longer required. It appears that the Digital Mammographic Imaging Screening Trial (DMIST) was undertaken to take advantage of the earmarked money and was used to compare SFM to FFDM for cancer detection. The historical issues involved with DMIST provide an important background for the Tomosynthesis Mammographic Imaging Screening Trial (TMIST). Just as the monies for DMIST could have been better spent on an RCT of MRI for screening, the monies for TMIST could be better spent to improve our ability to detect more breast cancers at a time in their growth when cure may be possible.

Robust breast cancer detection in mammography and digital breast tomosynthesis using an annotation-efficient deep learning approach

Breast cancer remains a global challenge, causing over 600,000 deaths in 2018 (ref. ¹). To achieve earlier cancer detection, health organizations worldwide recommend screening mammography, which is estimated to decrease breast cancer mortality by 20-40% (refs. ^2,3). Despite the clear value of screening mammography, significant false positive and false negative rates along with non-uniformities in expert reader availability leave opportunities for improving quality and access^4,5. To address these limitations, there has been much recent interest in applying deep learning to mammography^6-18, and these efforts have highlighted two key difficulties: obtaining large amounts of annotated training data and ensuring generalization across populations, acquisition equipment and modalities. Here we present an annotation-efficient deep learning approach that (1) achieves state-of-the-art performance in mammogram classification, (2) successfully extends to digital breast tomosynthesis (DBT; '3D mammography'), (3) detects cancers in clinically negative prior mammograms of patients with cancer, (4) generalizes well to a population with low screening rates and (5) outperforms five out of five full-time breast-imaging specialists with an average increase in sensitivity of 14%. By creating new 'maximum suspicion projection' (MSP) images from DBT data, our progressively trained, multiple-instance learning approach effectively trains on DBT exams using only breast-level labels while maintaining localization-based interpretability. Altogether, our results demonstrate promise towards software that can improve the accuracy of and access to screening mammography worldwide.

A prototype Multi-X-ray-source array (MXA) for digital breast tomosynthesis

The design and testing of a prototype Multi-X-ray-source Array (MXA) for digital breast tomosynthesis is reported. The MXA is comprised of an array of tungsten filament cathodes with focus cup grid-controlled modulation and a common rotating anode housed in a single vacuum envelope. Prototypes consisting of arrays of three-source elements and eleven-source-elements were fabricated and evaluated. The prototype sources demonstrated focal spot sizes of 0.3 mm at 45 kV with 50 mA. Measured x-ray spectra were consistent with the molybdenum anode employed, and the tube output (air kerma) was between 0.6 mGy/100 mAs at 20 kV and 17 mGy/100 mAs at 45 kV with a distance of 100 cm. HVL measurements ranged from 0.5 mm Al at 30 kV to 0.8 mm Al at 45 kV, and x-ray pulse widths were varied from 20 ms to 110 ms at operating frequencies ultimately to be limited by source turn-on/off times of ∼1 ms. Initial results of reconstructed tomographic data are presented.

Advanced and futuristic approaches for breast cancer diagnosis

Background

Breast cancer is the most frequent cancer and one of the most common causes of death in women, impacting almost 2 million women each year. Tenacity or perseverance of breast cancer in women is very high these days with an extensive increasing rate of 3 to 5% every year. Along with hurdles faced during treatment of breast tumor, one of the crucial causes of delay in treatment is invasive and poor diagnostic techniques for breast cancer hence the early diagnosis of breast tumors will help us to improve its management and treatment in the initial stage.

Main body

Present review aims to explore diagnostic techniques for breast cancer that are currently being used, recent advancements that aids in prior detection and evaluation and are extensively focused on techniques that are going to be future of breast cancer detection with better efficiency and lesser pain to patients so that it helps to a physician to prevent delay in treatment of cancer. Here, we have discussed mammography and its advanced forms that are the need of current era, techniques involving radiation such as radionuclide methods, the potential of nanotechnology by using nanoparticle in breast cancer, and how the new inventions such as breath biopsy, and X-ray diffraction of hair can simply use as a prominent method in breast cancer early and easy detection tool.

Conclusion

It is observed significantly that advancement in detection techniques is helping in early diagnosis of breast cancer; however, we have to also focus on techniques that will improve the future of cancer diagnosis in like optical imaging and HER2 testing.

Diagnostic accuracy of digital breast tomosynthesis in combination with 2D mammography for the characterisation of mammographic abnormalities

This study aims to assess the diagnostic accuracy of digital breast tomosynthesis in combination with full field digital mammography (DBT + FFDM) in the charaterisation of Breast Imaging-reporting and Data System (BI-RADS) category 3, 4 and 5 lesions. Retrospective cross-sectional study of 390 patients with BI-RADS 3, 4 and 5 mammography with available histopathology examination results were recruited from in a single center of a multi-ethnic Asian population. 2 readers independently reported the FFDM and DBT images and classified lesions detected (mass, calcifications, asymmetric density and architectural distortion) based on American College of Radiology-BI-RADS lexicon. Of the 390 patients recruited, 182 malignancies were reported. Positive predictive value (PPV) of cancer was 46.7%. The PPV in BI-RADS 4a, 4b, 4c and 5 were 6.0%, 38.3%, 68.9%, and 93.1%, respectively. Among all the cancers, 76% presented as masses, 4% as calcifications and 20% as asymmetry. An additional of 4% of cancers were detected on ultrasound. The sensitivity, specificity, PPV and NPV of mass lesions detected on DBT + FFDM were 93.8%, 85.1%, 88.8% and 91.5%, respectively. The PPV for calcification is 61.6% and asymmetry is 60.7%. 81.6% of cancer detected were invasive and 13.3% were in-situ type. Our study showed that DBT is proven to be an effective tool in the diagnosis and characterization of breast lesions and supports the current body of literature that states that integrating DBT to FFDM allows good characterization of breast lesions and accurate diagnosis of cancer.

Computational Radiology in Breast Cancer Screening and Diagnosis Using Artificial Intelligence

Breast cancer screening has been shown to significantly reduce mortality in women. The increased utilization of screening examinations has led to growing demands for rapid and accurate diagnostic reporting. In modern breast imaging centers, full-field digital mammography (FFDM) has replaced traditional analog mammography, and this has opened new opportunities for developing computational frameworks to automate detection and diagnosis. Artificial intelligence (AI), and its subdomain of deep learning, is showing promising results and improvements on diagnostic accuracy, compared to previous computer-based methods, known as computer-aided detection and diagnosis.

In this commentary, we review the current status of computational radiology, with a focus on deep neural networks used in breast cancer screening and diagnosis. Recent studies are developing a new generation of computer-aided detection and diagnosis systems, as well as leveraging AI-driven tools to efficiently interpret digital mammograms, and breast tomosynthesis imaging. The use of AI in computational radiology necessitates transparency and rigorous testing. However, the overall impact of AI to radiology workflows will potentially yield more efficient and standardized processes as well as improve the level of care to patients with high diagnostic accuracy.

Characterization of the imaging settings in screening mammography using a tracking and reporting system: A multi-center and multi-vendor analysis

A tracking and reporting system was developed to monitor radiation dose in X-ray breast imaging. We used our tracking system to characterize and compare the mammographic practices of five breast imaging centers located in the United States and Brazil. Clinical data were acquired using eight mammography systems comprising three modalities: computed radiography (CR), full-field digital mammography (FFDM), and digital breast tomosynthesis (DBT). Our database consists of metadata extracted from 334,234 images. We analyzed distributions and correlations of compressed breast thickness (CBT), compression force, target-filter combinations, X-ray tube voltage, and average glandular dose (AGD). AGD reference curves were calculated based on AGD distributions as a function of CBT. These curves represent an AGD reference for a particular population and system. Differences in AGD and imaging settings were attributed to a combination of factors, such as improvements in technology, imaging protocol, and patient demographics. The tracking system allows the comparison of various imaging settings used in screening mammography, as well as the tracking of patient- and population-specific breast data collected from different populations.

Characteristics of Invasive Breast Cancer Detected by Digital Breast Tomosynthesis on Screening and Diagnostic Mammograms

OBJECTIVE

To determine whether there is added benefit for 3D mammography in the context of screening and diagnostic imaging, particularly relating to known prognostic characteristics, including histopathology, receptor status, and axillary lymph node involvement.

METHODS

An institutional review board-approved retrospective review was performed of our mammography and pathology databases from October 2012 to May 2015 to identify biopsy-proven invasive breast carcinoma detected on screening and diagnostic mammograms by 2D plus 3D (2D + 3D) imaging. Percentages of cancer detection by 2D and 3D were compared. Correlation with histopathology and lymph node status was analyzed.

RESULTS

Of 53 cancers diagnosed on 12 543 screening mammograms, 36 (67.9%) were better visualized on 3D (not visualized, equivocal, or only seen in retrospect on 2D). Of the 62 cancers diagnosed on 4090 diagnostic mammograms, 24 (38.7%) cancers were better detected on 3D. A statistically significant greater number of cancers were better detected on 3D in the screening compared to the diagnostic mammograms (67.9% vs 38.7%, P < .05). A significantly higher frequency of less aggressive tumors (grade I and grade II, positive estrogen/progesterone receptor, Her2 negative) was detected by 3D, with higher significance in the screening population. Additionally, there was a higher frequency of positive axillary lymph nodes in cancers detected by 3D in the screening group.

CONCLUSION

Three-dimension increases invasive breast cancer detection, particularly pathologically less aggressive tumors, in both screening and diagnostic mammograms with more benefit for the screening population. Three-dimensional mammography detected more breast cancer associated with metastatic axillary lymph nodes in the screening population.

Breast lesion size assessment in mastectomy specimens: Correlation of cone-beam breast-CT, digital breast tomosynthesis and full-field digital mammography with histopathology

To compare the accuracy of breast lesion size measurement of cone-beam breast-CT (CBBCT), digital breast tomosynthesis (DBT) and full-field digital mammography (FFDM).Patients scheduled for mastectomy due to at least 1 malignant breast lesion were included. Mastectomy specimens were examined by CBBCT, DBT, FFDM, and histopathology.A total of 94 lesions (40 patients) were included. Histopathological analyses revealed 47 malignant, 6 high-risk, and 41 benign lesions. Mean histopathological lesion size was 20.8 mm (range 2-100). Mean absolute size deviation from histopathology was largest for FFDM (5.3 ± 6.7 mm) and smallest for CBBCT 50 mA, high-resolution mode (4.3 ± 6.7 mm). Differences between imaging modalities did not reach statistical significance (P = .85).All imaging methods tend to overestimate breast lesion size compared to histopathological gold standard. No significant differences were found regarding size measurements, although in tendency CBBCT showed better lesion detection and cT classification over FFDM.

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.

Antecedents: A Half-Century of Imaging the Breast

The field of Breast Imaging evolved because a fairly small number of dedicated individuals realized the lifesaving potential of detecting breast cancer earlier. They persevered despite persistent efforts to curtail screening. From the first attempts to produce X-ray images of the breast to magnetic resonance and digital breast tomosynthesis, investigators have worked continuously to develop better ways to detect breast cancer at a time when cure is possible, while working continuously to preserve access for women to screening. Consequently, the death rate from breast cancer has declined by more than 40%. Therapy has improved, but therapy saves lives when breast cancers are treated early.

Emergence of "Big Data" and Its Potential and Current Limitations in Medical Imaging

Although electronic imaging was performed in the early 1950s in nuclear medicine, it was the introduction of computed tomography in 1972 that caused a revolution in medical imaging in that it marked the beginning of the inevitable transformation to digital imaging. This transformation is now more or less complete. While initially these CT images were relatively small, comprised of only about 6400 pixels per slice, the steady move toward higher spatial resolution, multislice imaging, digital radiography, and fluoroscopy rapidly increased the size of images and the amount of data required to be stored, processed, displayed, and moved about in a medical imaging department. The more recent introduction of digital pathology with submicron-sized pixels and the need for color further increases these demands. Rising work volumes in hospital, a push for cost containment, and a move toward greater precision in diagnosis and treatment of disease all work together to motivate the development of automated image analysis algorithms and techniques to improve efficiencies in in vivo imaging and pathology. This may require bringing together information from different imaging and nonimaging sources within the institution. While technological development has provided practical means for storage of the burgeoning data load and the use of multiple processors and high-speed networks has enabled more sophisticated analysis locally or in the cloud, challenges remain in terms of the ability to integrate data from different systems, the development of appropriately annotated image bases for training and testing of algorithms, and issues around privacy and ownership in obtaining access to patient-related data.

Authorship and Impact of Gender-Specific Research in Major Radiology Journals

PURPOSE

The purpose of this study is to quantify the relationship between author gender and publication topic, as well as the impact of gender-related research.

METHODS

We reviewed all original research publications in Radiology, American Journal of Roentgenology, and Academic Radiology from 2011 through 2015. For each article, we recorded the gender of all authors and the last author H-index, years in practice, and academic rank. The total citations and citation rate (citations per year) were calculated for each article. Articles were categorized as gender-neutral, women's health, or men's health.

RESULTS

There were 1,934 publications involving 11,657 authors. Women represented 30% of first, 25% of last, and 28% of all authors. There were 1,596 (83%) gender-neutral, 276 (14%) women's health, and 61 (3%) men's health articles. Women's health articles were associated with a female first (odds ratio [OR] = 5.0, P < .001) and last author (OR = 6.4, P < .001), as well as more female authors (male = 1.4, female = 3.6, P < .001). Men's health articles were associated with a male first (OR = 2.6, P = .004) and last author (OR = 2.2, P = .03). There were significantly more citations for men's (43.5 ± 54.9, P < .001) and women's health (27.6 ± 37.5, P < .008) articles than gender-neutral articles (21.9 ± 28.9). Similarly, the article citation rate was higher for men's (10.6 ± 11.3, P < .001) and women's health (6.8 ± 8.5, P = .004) articles than gender-neutral publications (5.3 ± 7.0).

CONCLUSION

Radiology researchers publish more often on topics related to their own gender. Furthermore, men's and women's health research generates more citations than gender-neutral research.

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.

Breast tomosynthesis for the clarification of mammographic BI-RADS 3 lesions can decrease follow-up examinations and enables immediate cancer diagnosis

Background The limited sensitivity of mammography in case of a high breast density often produces unclear or false-positive findings, so-called BI-RADS 3 lesions, which have to be followed up to prove benignity. Digital breast tomosynthesis (DBT) was developed to reduce such summation effects. Purpose To evaluate the influence of an additional DBT on the management of mammographic BI-RADS 3 findings and whether DBT can decrease the time to definitive diagnosis or not. Material and Methods We analyzed 87 patients with a mammographic non-calcified BI-RADS 3 lesion who underwent an additional DBT of the affected breast. A follow-up two-dimensional (2D) examination or a histological result of the lesion had to be available. The images were analyzed especially for the BI-RADS category and incremental diagnostic accuracy. Moreover, the inter-reader reliability and the radiation dose were evaluated. Results The BI-RADS category has been changed by the addition of DBT: 57.1% were assessed as BI-RADS 1 or 2, 4.6% as BI-RADS 4, and only 38.3% remained as BI-RADS 3. The intraclass correlation coefficient for the three readers showed a good agreement for inter-reader reliability. No false-negative examination was found in the follow-ups. Nine lesions were biopsied (seven benign, two malignant). Both malignant lesions were suspicious in the DBT (BI-RADS 4). A significant higher glandular dose was necessary for the DBT. Conclusion DBT has the potential to reduce the recall-rate of BI-RADS 3 lesions and to find and diagnose malignant lesions earlier than 2D mammography alone.

Imaging Features of Nonmalignant and Malignant Architectural Distortion Detected by Tomosynthesis

OBJECTIVE

The objective of our study was to determine the ability of tomosynthesis (3D) to detect nonmalignant and malignant architectural distortion (AD) on 3D screening mammograms compared with digital mammography (2D) only and to correlate the 3D imaging features of nonmalignant and malignant AD with pathology findings.

MATERIALS AND METHODS

For this single-institution retrospective study, screening mammography reports from October 1, 2012, to December 1, 2016, that included AD as a finding were reviewed. Associated additional imaging studies and pathology results were also reviewed.

RESULTS

Three-dimensional mammography showed statistically significant increased detection of both nonmalignant and malignant AD compared with 2D only (0.10% [24/24,902 examinations] vs 0.01% [1/9470 examinations], p < 0.05; and 0.21% [52/24,902 examinations] vs 0.07% [7/9470 examinations], p < 0.05, respectively). Higher percentages of nonmalignant AD (16%) were occult on ultrasound compared with malignant AD (3%). The pathologic diagnoses of nonmalignant AD included radial scar (42%), sclerosing adenosis (16%), stromal or dense fibrosis (16%), and other miscellaneous benign causes (25%). Morphologically, nonmalignant AD was more likely to show symmetric or spoke-wheel spiculation appearance (58% vs 2%, p < 0.05) and central lucency (25% vs 0%, p < 0.05) than malignant AD, whereas malignant AD was more likely to show asymmetric spiculation (98% vs 42%, p < 0.05) and central mass 60% vs 0%, p < 0.05) than nonmalignant AD.

CONCLUSION

Malignant AD and nonmalignant AD are more readily detected by 3D mammography than 2D mammography. Three-dimensional imaging features of AD can help to distinguish nonmalignant types in which symmetric or spoke-wheel spiculation with central lucency are more often seen and are more often occult on ultrasound.

Monochromatic mammography using scanning multilayer X-ray mirrors

A prototype system for breast imaging using monochromatic X-rays has been developed using a scanning multilayer X-ray mirror in combination with a conventional mammography tube and an imaging detector. The X-ray mirror produces a monochromatic fan beam tuned near 19 keV, with an energy bandpass of approximately 1.5 keV. Rotating the mirror about the tube's focal spot in synchronization with the X-ray generator and detector enables the acquisition of monochromatic X-ray images over large areas. The X-ray mirror also can be rotated completely out of the beam so that conventional polychromatic images can be acquired using a K-edge filter, facilitating direct comparison between the two modes of operation. The system was used to image synthetic, tissue-equivalent breast phantoms in order to experimentally quantify the improvements in image quality and dose that can be realized using monochromatic radiation. Nine custom phantoms spanning a range of thicknesses and glandular/adipose ratios, each containing both glandular- and calcification-equivalent features, were used to measure contrast and signal-difference-to-noise ratio (SDNR). Mean glandular dose (MGD) was computed from measured entrance exposure, and a figure-of-merit (FOM) was computed as FOM = SDNR²/MGD in each case. Monochromatic MGD ranges from 0.606 to 0.134 of polychromatic MGD for images having comparable glandular SDNR, depending on breast thickness and glandularity; relative monochromatic dose decreases with increasing glandularity for all thicknesses. Monochromatic FOM values are higher than the corresponding polychromatic FOM values in all but one case. Additionally, the monochromatic contrast for glandular features is higher than the polychromatic contrast in all but one case as well. These results represent important steps toward the realization of clinically practical monochromatic X-ray breast imaging systems having lower dose and better image quality, including those for digital mammography, digital breast tomosynthesis, contrast-enhanced spectral mammography and other modalities, for safer, more accurate breast cancer detection, diagnosis and staging.

Quantitative analysis of enhanced malignant and benign lesions on contrast-enhanced spectral mammography

OBJECTIVE

To retrospectively analyze the quantitative measurement and kinetic enhancement among pathologically proven benign and malignant lesions using contrast-enhanced spectral mammography (CESM).

METHODS

We investigated the differences in enhancement between 44 benign and 108 malignant breast lesions in CESM, quantifying the extent of enhancements and the relative enhancements between early (between 2-3 min after contrast medium injection) and late (3-6 min) phases.

RESULTS

The enhancement was statistically stronger in malignancies compared to benign lesions, with good performance by the receiver operating characteristic curve [0.877, 95% confidence interval (0.813-0.941)]. Using optimal cut-off value at 220.94 according to Youden index, the sensitivity was 75.9%, specificity 88.6%, positive likelihood ratio 6.681, negative likelihood ratio 0.272 and accuracy 82.3%. The relative enhancement patterns of benign and malignant lesions, showing 29.92 vs 73.08% in the elevated pattern, 7.14 vs 92.86% in the steady pattern, 5.71 vs 94.29% in the depressed pattern, and 80.00 vs 20.00% in non-enhanced lesions (p < 0.0001), respectively.

CONCLUSION

Despite variations in the degree of tumour angiogenesis, quantitative analysis of the breast lesions on CESM documented the malignancies had distinctive stronger enhancement and depressed relative enhancement patterns than benign lesions. Advances in knowledge: To our knowledge, this is the first study evaluating the feasibility of quantifying lesion enhancement on CESM. The quantities of enhancement were informative for assessing breast lesions in which the malignancies had stronger enhancement and more relative depressed enhancement than the benign lesions.

Preliminary Results of a New Auxiliary Mechatronic Near-Field Radar System to 3D Mammography for Early Detection of Breast Cancer

Accurate and early detection of breast cancer is of high importance, as it is directly associated with the patients’ overall well-being during treatment and their chances of survival. Uncertainties in current breast imaging methods can potentially cause two main problems: (1) missing newly formed or small tumors; and (2) false alarms, which could be a source of stress for patients. A recent study at the Massachusetts General Hospital (MGH) indicates that using Digital Breast Tomosynthesis (DBT) can reduce the number of false alarms, when compared to conventional mammography. Despite the image quality enhancement DBT provides, the accurate detection of cancerous masses is still limited by low radiological contrast (about 1%) between the fibro-glandular tissue and affected tissue at X-ray frequencies. In a lower frequency region, at microwave frequencies, the contrast is comparatively higher (about 10%) between the aforementioned tissues; yet, microwave imaging suffers from low spatial resolution. This work reviews conventional X-ray breast imaging and describes the preliminary results of a novel near-field radar imaging mechatronic system (NRIMS) that can be fused with the DBT, in a co-registered fashion, to combine the advantages of both modalities. The NRIMS consists of two antipodal Vivaldi antennas, an XY positioner, and an ethanol container, all of which are particularly designed based on the DBT physical specifications. In this paper, the independent performance of the NRIMS is assessed by (1) imaging a bearing ball immersed in sunflower oil and (2) computing the heat Specific Absorption Rate (SAR) due to the electromagnetic power transmitted into the breast. The preliminary results demonstrate that the system is capable of generating images of the ball. Furthermore, the SAR results show that the system complies with the standards set for human trials. As a result, a configuration based on this design might be suitable for use in realistic clinical applications.

Added Value of Digital Breast Tomosynthesis Combined with Digital Mammography According to Reader Agreement: Changes in BI-RADS Rate and Follow-Up Management

BACKGROUND

The aim of this study was to evaluate the added value of digital breast tomosynthesis (DBT) when combined with digital mammography (DM) in BI-RADS assessment and follow-up management.

METHODS

From February 2014 to January 2015, 214 patients underwent DM and DBT, acquired with a Siemens Mammomat Inspiration unit. 2 expert readers independently reviewed the studies in 2 steps: DM and DM+DBT, according to BI-RADS rate. Patients with BI-RADS 0, 3, 4, and 5 were recalled for work-up. Inter-reader agreement for BI-RADS rate and work-up rate were evaluated using Cohen's kappa.

RESULTS

Inter-reader agreement (κ value) for BI-RADS classification was 0.58 for DM and 0.8 for DM+DBT. DM+DBT increased the number of BI-RADS 1, 2, 4, 5 and reduced the number of BI-RADS 0 and 3 for both readers compared to DM alone. Regarding work-up rate agreement, κ was poor for DM and substantial (0.7) for DM+DBT. DM+DBT also reduced the work-up rate for both Reader 1 and Reader 2.

CONCLUSION

DM+DBT increased the number of negative and benign cases (BI-RADS 1 and 2) and suspicious and malignant cases (BI-RADS 4 and 5), while it reduced the number of BI-RADS 0 and 3. DM+DBT also improved inter-reader agreement and reduced the overall recall for additional imaging or short-interval follow-up.

Digital Breast Tomosynthesis Practice Patterns Following 2011 FDA Approval: A Survey of Breast Imaging Radiologists

RATIONALE AND OBJECTIVES

To evaluate uptake, patterns of use, and perception of digital breast tomosynthesis (DBT) among practicing breast radiologists.

MATERIALS AND METHODS

Institutional Review Board exemption was obtained for this Health Insurance Portability and Accountability Act-compliant electronic survey, sent to 7023 breast radiologists identified via the Radiological Society of North America database. Respondents were asked of their geographic location and practice type. DBT users reported length of use, selection criteria, interpretive sequences, recall rate, and reading time. Radiologist satisfaction with DBT as a diagnostic tool was assessed (1-5 scale).

RESULTS

There were 1156 (16.5%) responders, 65.8% from the United States and 34.2% from abroad. Of these, 749 (68.6%) use DBT; 22.6% in academia, 56.5% private, and 21% other. Participants are equally likely to report use of DBT if they worked in academics versus in private practice (78.2% [169 of 216] vs 71% [423 of 596]) (odds ratio, 1.10; 95% confidence interval: 0.87-1.40; P = 1.000). Of nonusers, 43% (147 of 343) plan to adopt DBT. No US regional differences in uptake were observed (P = 1.000). Although 59.3% (416 of 702) of DBT users include synthetic 2D (s2D) for interpretation, only 24.2% (170 of 702) use s2D alone. Majority (66%; 441 of 672) do not perform DBT-guided procedures. Radiologist (76.6%) (544 of 710) satisfaction with DBT as a diagnostic tool is high (score ≥ 4/5).

CONCLUSIONS

DBT is being adopted worldwide across all practice types, yet variations in examination indication, patient selection, utilization of s2D images, and access to DBT-guided procedures persist, highlighting the need for consensus and standardization.

Interpretation of digital breast tomosynthesis: preliminary study on comparison with picture archiving and communication system (PACS) and dedicated workstation

OBJECTIVE

To compare the diagnostic accuracy and efficiency in the interpretation of digital breast tomosynthesis (DBT) images using a picture archiving and communication system (PACS) and a dedicated workstation.

METHODS

97 DBT images obtained for screening or diagnostic purposes were stored in both a workstation and a PACS and evaluated in combination with digital mammography by three independent radiologists retrospectively. Breast Imaging-Reporting and Data System final assessments and likelihood of malignancy (%) were assigned and the interpretation time when using the workstation and PACS was recorded. Receiver operating characteristic curve analysis, sensitivities and specificities were compared with histopathological examination and follow-up data as a reference standard.

RESULTS

Area under the receiver operating characteristic curve values for cancer detection (0.839 vs 0.815, p = 0.6375) and sensitivity (81.8% vs 75.8%, p = 0.2188) showed no statistically significant differences between the workstation and PACS. However, specificity was significantly higher when analysing on the workstation than when using PACS (83.7% vs 76.9%, p = 0.009). When evaluating DBT images using PACS, only one case was deemed necessary to be reanalysed using the workstation. The mean time to interpret DBT images on PACS (1.68 min/case) was significantly longer than that to interpret on the workstation (1.35 min/case) (p < 0.0001).

CONCLUSION

Interpretation of DBT images using PACS showed comparable diagnostic performance to a dedicated workstation, even though it required a longer reading time. Advances in knowledge: Interpretation of DBT images using PACS is an alternative to evaluate the images when a dedicated workstation is not available.

The role of cone-beam breast-CT for breast cancer detection relative to breast density

OBJECTIVES

To evaluate the impact of breast density on the diagnostic accuracy of non-contrast cone-beam breast computed tomography (CBBCT) in comparison to mammography for the detection of breast masses.

METHODS

A retrospective study was conducted from August 2015 to July 2016. Fifty-nine patients (65 breasts, 112 lesions) with BI-RADS, 5th edition 4 or 5 assessment in mammography and/or ultrasound of the breast received an additional non-contrast CBBCT. Independent double blind reading by two radiologists was performed for mammography and CBBCT imaging. Sensitivity, specificity and AUC were compared between the modalities.

RESULTS

Breast lesions were histologically examined in 85 of 112 lesions (76%). The overall sensitivity for CBBCT (reader 1: 91%, reader 2: 88%) was higher than in mammography (both: 68%, p<0.001), and also for the high-density group (p<0.05). The specificity and AUC was higher for mammography in comparison to CBBCT (p<0.05 and p<0.001). The interobserver agreement (ICC) between the readers was 90% (95% CI: 86-93%) for mammography and 87% (95% CI: 82-91%) for CBBCT.

CONCLUSIONS

Compared with two-view mammography, non-contrast CBBCT has higher sensitivity, lower specificity, and lower AUC for breast mass detection in both high and low density breasts.

KEY POINTS

• Overall sensitivity for non-contrast CBBCT ranged between 88%-91%. • Sensitivity was higher for CBBCT than mammography in both density types (p<0.001). • Specificity was higher for mammography than CBBCT in both density types (p<0.05). • AUC was larger for mammography than CBBCT in both density types (p<0.001).

How Does the Display Luminance Level Affect Detectability of Breast Microcalcifications and Spiculated Lesions in Digital Breast Tomosynthesis (DBT) Images?

RATIONALE AND OBJECTIVES

This study evaluates the influence of the calibrated luminance level of medical displays in the detectability of microcalcifications and spiculated lesions in digital breast tomosynthesis images.

MATERIALS AND METHODS

Four models of medical displays with calibrated maximum and minimum luminance, respectively, ranging from 500 to 1000 cd/m² and from 0.5 to 1.0 cd/m², were investigated. Forty-eight studies were selected by a senior radiologist: 16 with microcalcifications, 16 with spiculated lesions, and 16 without lesions. All images were anonymized and blindly evaluated by one senior and two junior radiologists. For each study, lesion presence or absence and localization statements, interpretative difficulty level, and overall quality were reported. Cohen's kappa statistic was computed between monitors and within or between radiologists to estimate the reproducibility in correctly identifying lesions; for multireader-multicase analysis, the weighted jackknife alternative free-response receiver operating characteristic statistical tool was applied.

RESULTS

Intraradiologist reproducibility ranged from 0.75 to 1.00. Interreader as well as reader-truth agreement values were >0.80 and higher with the two 1000 cd/m² luminance displays than with the lower luminance displays for each radiologist. Performances in the detectability of breast lesions were significantly greater with the 1000 cd/m² luminance displays when compared to the display with the lowest luminance value (P value <0.001).

CONCLUSIONS

Our findings highlight the role of display luminance level on the accuracy of detecting breast lesions.

New diagnostic tools for breast cancer

Imaging plays a major role in the diagnosis, treatment, and follow-up of breast cancer. Findings that require further assessment will be detected both at screening and curative mammography. Most findings that are further worked up tend to yield benign diagnoses. Consequently, there is an ongoing search for new tools to reduce recalls and unnecessary biopsies while maintaining or improving cancer detection rates. The clinically most promising methods in this respect are described and discussed in this review.

Visualization of Breast Microcalcifications on Digital Breast Tomosynthesis and 2-Dimensional Digital Mammography Using Specimens

Purpose:

The purpose of this study is to compare the visibility of microcalcifications of digital breast tomosynthesis (DBT) and full-field digital mammography (FFDM) using breast specimens.

Materials And Methods:

Thirty-one specimens’ DBT and FFDM were retrospectively reviewed by four readers.

Results:

The image quality of microcalcifications of DBT was rated as superior or equivalent in 71.0% by reader 1, 67.8% by reader 2, 64.5% by reader 3, and 80.6% by reader 4. The Fleiss kappa statistic for agreement among readers was 0.31.

Conclusions:

We suggest that image quality of DBT appears to be comparable with or better than FFDM in terms of revealing microcalcifications.

Multimodal breast cancer imaging using coregistered dynamic diffuse optical tomography and digital breast tomosynthesis

Diffuse optical tomography (DOT) is emerging as a noninvasive functional imaging method for breast cancer diagnosis and neoadjuvant chemotherapy monitoring. In particular, the multimodal approach of combining DOT with x-ray digital breast tomosynthesis (DBT) is especially synergistic as DBT prior information can be used to enhance the DOT reconstruction. DOT, in turn, provides a functional information overlay onto the mammographic images, increasing sensitivity and specificity to cancer pathology. We describe a dynamic DOT apparatus designed for tight integration with commercial DBT scanners and providing a fast (up to 1 Hz) image acquisition rate to enable tracking hemodynamic changes induced by the mammographic breast compression. The system integrates 96 continuous-wave and 24 frequency-domain source locations as well as 32 continuous wave and 20 frequency-domain detection locations into low-profile plastic plates that can easily mate to the DBT compression paddle and x-ray detector cover, respectively. We demonstrate system performance using static and dynamic tissue-like phantoms as well as in vivo images acquired from the pool of patients recalled for breast biopsies at the Massachusetts General Hospital Breast Imaging Division.

Digital Breast Tomosynthesis: Cost-Effectiveness of Using Private and Medicare Insurance in Community-Based Health Care Facilities

OBJECTIVE

The purpose of this study was to determine whether digital breast tomosynthesis (DBT) is a cost-effective alternative to full-field digital mammography (FFDM) for both Medicare and privately insured patients undergoing screening mammography.

MATERIALS AND METHODS

A retrospective data analysis was performed between July 15, 2013, and July 14, 2014, with data on women presenting for screening mammography that included any additional radiologic workup (n = 6319). Patients chose to undergo DBT or FFDM on the basis of personal preference, physician suggestion, and cost difference. The summation of findings over the 1-year period were used to calculate recall rates, cancer detection rates, and billing costs for a regional private insurer and Medicare.

RESULTS

Data from the 6319 patients who participated were divided: 3655 patients underwent DBT, and 2664 underwent FFDM during the year of screening. Private insurance billing cost $2.9 million, and Medicare cost $1.2 million for screening, follow-up imaging, and radiologic procedures. Per-person costs were approximately $40 higher for the DBT group using both forms of insurance. However, cost per cancer detected was lower in the DBT group for both private and governmental insurance, leading to potentially $3.7 million and $899,000 saved per 100 cancers found. After standardization of the difference in cancer detection rates between the two groups, DBT was a cost-equivalent alternative to FFDM for private insurance billing but was a cost-inefficient alternative with respect to Medicare costs.

CONCLUSION

In a community-based setting, DBT is a cost-equivalent or potentially cost-effective alternative to FFDM and has the capacity for improving cancer detection and recall rates.

Impact of prior mammograms on combined reading of digital mammography and digital breast tomosynthesis

Background Although digital breast tomosynthesis (DBT) is an emerging technique yielding higher sensitivity and specificity compared to digital mammography (DM) alone, relative contribution of prior mammograms on the interpretation of DBT combined with DM has not been investigated. Purpose To retrospectively compare the diagnostic performances of DM, DM + DBT, and DM + DBT with prior mammograms. Material and Methods Three breast radiologists independently reviewed images of 116 patients with 24 cancers in the sequential order of DM, DM + DBT, and DM + DBT with prior mammograms using Breast Imaging Reporting and Data System (BI-RADS) assessment categories. Results The average areas under the receiver operating characteristic curve (AUC) of DM, DM + DBT, and DM + DBT with prior mammograms were 0.712, 0.777, and 0.816, respectively. Adding prior mammograms did not significantly affect the AUC of DM + DBT ( P = 0.108), whereas adding DBT significantly increased the AUC of DM ( P = 0.009). Sensitivity for DM, DM + DBT, and DM + DBT with prior mammograms was 58.3%, 69.4%, and 69.4%, and specificities were 84.1%, 85.9%, and 93.8%, respectively. Addition of DBT significantly increased the sensitivity ( P = 0.0090) of DM. Prior mammograms significantly improved the specificity of DM + DBT ( P = 0.0004), whereas adding prior mammogram did not affect sensitivity of DM + DBT ( P = 1.000). Conclusion DBT significantly increases the overall sensitivity and diagnostic performance of DM. Prior mammograms significantly increase the specificity of DM + DBT but have no significant effect on sensitivity and overall diagnostic performance.