Performance comparison of single-view digital breast tomosynthesis plus single-view digital mammography with two-view digital mammography

Benefit of digital breast tomosynthesis in symptomatic young women (≤30 years) diagnosed with BI-RADS category 4 or 5 on ultrasound

AIM

To evaluate the addition of digital breast tomosynthesis (DBT) in the diagnosis of breast lesions in symptomatic young Chinese women (≤30 years) diagnosed with Breast Imaging Reporting and Data System (BI-RADS) category 4 or 5 on ultrasound, and demonstrate the potential use of combining DBT with ultrasound.

MATERIALS AND METHODS

This retrospective analysis included 5 years of digital mammography (DM) and DBT data (January 2015 to July 2020). In total, 768 DBT and DM examinations were performed in 713 young women. The results were determined by pathological assessment. Diagnostic performance was measured based on the sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV), and receiver operating characteristic area under the curve (AUC).

RESULTS

Compared with DM alone, DBT + DM increased the sensitivity from 82.5% to 93.2%, specificity from 70.8% to 84%, accuracy from 74% to 86.5%, NPV from 93.6% to 97.4% (all p<0.01). The AUC of DBT + DM (0.946, 95% confidence interval [CI]: 0.927-0.960) was greater than that of DM (0.884, 95% CI: 0.859-0.905; p<0.001). The differences in the BI-RADS category distributions of malignant and benign lesions were both statistically significant (p<0.001). DM alone led to 36 false-negative diagnoses, whereas the inclusion of DBT identified breast cancer in 22 of those cases. There were 4.9% (10/206) false-negative diagnoses in ultrasound. After adding DBT, four breast cancers were detected. An additional six breast cancers were diagnosed by biopsy based on an assessment of BI-RADS 4A by DBT/DM.

CONCLUSION

DBT + DM significantly improves the diagnostic performance in this young population, especially in young people with higher breast density. Moreover, DBT is an effective supplementary examination to ultrasound.

Stand-Alone Artificial Intelligence for Breast Cancer Detection in Mammography: Comparison With 101 Radiologists

BACKGROUND

Artificial intelligence (AI) systems performing at radiologist-like levels in the evaluation of digital mammography (DM) would improve breast cancer screening accuracy and efficiency. We aimed to compare the stand-alone performance of an AI system to that of radiologists in detecting breast cancer in DM.

METHODS

Nine multi-reader, multi-case study datasets previously used for different research purposes in seven countries were collected. Each dataset consisted of DM exams acquired with systems from four different vendors, multiple radiologists' assessments per exam, and ground truth verified by histopathological analysis or follow-up, yielding a total of 2652 exams (653 malignant) and interpretations by 101 radiologists (28 296 independent interpretations). An AI system analyzed these exams yielding a level of suspicion of cancer present between 1 and 10. The detection performance between the radiologists and the AI system was compared using a noninferiority null hypothesis at a margin of 0.05.

RESULTS

The performance of the AI system was statistically noninferior to that of the average of the 101 radiologists. The AI system had a 0.840 (95% confidence interval [CI] = 0.820 to 0.860) area under the ROC curve and the average of the radiologists was 0.814 (95% CI = 0.787 to 0.841) (difference 95% CI = -0.003 to 0.055). The AI system had an AUC higher than 61.4% of the radiologists.

CONCLUSIONS

The evaluated AI system achieved a cancer detection accuracy comparable to an average breast radiologist in this retrospective setting. Although promising, the performance and impact of such a system in a screening setting needs further investigation.

Digital breast tomosynthesis for breast cancer detection: a diagnostic test accuracy systematic review and meta-analysis

OBJECTIVES

No consensus exists on digital breast tomosynthesis (DBT) utilization for breast cancer detection. We performed a diagnostic test accuracy systematic review and meta-analysis comparing DBT, combined DBT and digital mammography (DM), and DM alone for breast cancer detection in average-risk women.

METHODS

MEDLINE and EMBASE were searched until September 2018. Comparative design studies reporting on the diagnostic accuracy of DBT and/or DM for breast cancer detection were included. Demographic, methodologic, and diagnostic accuracy data were extracted. Risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS)-2 tool. Accuracy metrics were pooled using bivariate random-effects meta-analysis. The impact of multiple covariates was assessed using meta-regression.

PROSPERO ID

CRD 42018111287.

RESULTS

Thirty-eight studies reporting on 488,099 patients (13,923 with breast cancer) were included. Eleven studies were at low risk of bias. DBT alone, combined DBT and DM, and DM alone demonstrated sensitivities of 88% (95% confidence interval [CI] 83-92), 88% (CI 83-92), and 79% (CI 75-82), as well as specificities of 84% (CI 76-89), 81% (CI 73-88), and 79% (CI 71-85), respectively. The greater sensitivities of DBT alone and combined DBT and DM compared to DM alone were preserved in the combined meta-regression models accounting for other covariates (p = 0.003-0.006). No significant difference in diagnostic accuracy between DBT alone and combined DBT and DM was identified (p = 0.175-0.581).

CONCLUSIONS

DBT is more sensitive than DM, while the addition of DM to DBT provides no additional diagnostic benefit. Consideration of these findings in breast cancer imaging guidelines is recommended.

KEY POINTS

• Digital breast tomosynthesis with or without additional digital mammography is more sensitive in detecting breast cancer than digital mammography alone in women at average risk for breast cancer. • The addition of digital mammography to digital breast tomosynthesis provides no additional diagnostic benefit in detecting breast cancer compared to digital breast tomosynthesis alone. • The specificity of digital breast tomosynthesis with or without additional digital mammography is no different than digital mammography alone in the detection of breast cancer.

Can we reduce the workload of mammographic screening by automatic identification of normal exams with artificial intelligence? A feasibility study

Purpose

To study the feasibility of automatically identifying normal digital mammography (DM) exams with artificial intelligence (AI) to reduce the breast cancer screening reading workload.

Methods and materials

A total of 2652 DM exams (653 cancer) and interpretations by 101 radiologists were gathered from nine previously performed multi-reader multi-case receiver operating characteristic (MRMC ROC) studies. An AI system was used to obtain a score between 1 and 10 for each exam, representing the likelihood of cancer present. Using all AI scores between 1 and 9 as possible thresholds, the exams were divided into groups of low- and high likelihood of cancer present. It was assumed that, under the pre-selection scenario, only the high-likelihood group would be read by radiologists, while all low-likelihood exams would be reported as normal. The area under the reader-averaged ROC curve (AUC) was calculated for the original evaluations and for the pre-selection scenarios and compared using a non-inferiority hypothesis.

Results

Setting the low/high-likelihood threshold at an AI score of 5 (high likelihood > 5) results in a trade-off of approximately halving (− 47%) the workload to be read by radiologists while excluding 7% of true-positive exams. Using an AI score of 2 as threshold yields a workload reduction of 17% while only excluding 1% of true-positive exams. Pre-selection did not change the average AUC of radiologists (inferior 95% CI > − 0.05) for any threshold except at the extreme AI score of 9.

Conclusion

It is possible to automatically pre-select exams using AI to significantly reduce the breast cancer screening reading workload.

Key Points

• There is potential to use artificial intelligence to automatically reduce the breast cancer screening reading workload by excluding exams with a low likelihood of cancer.

• The exclusion of exams with the lowest likelihood of cancer in screening might not change radiologists’ breast cancer detection performance.

• When excluding exams with the lowest likelihood of cancer, the decrease in true-positive recalls would be balanced by a simultaneous reduction in false-positive recalls.

A new breast tomosynthesis imaging method: Continuous Sync-and-Shoot - technical feasibility and initial experience

Background

Digital breast tomosynthesis (DBT) is gaining popularity in breast imaging. There are several different technical approaches for conducting DBT imaging.

Purpose

To determine optimal imaging parameters, test patient friendliness, evaluate the initial diagnostic performance, and describe diagnostic advances possible with the new Continuous Sync-and-Shoot method.

Material and Methods

Thirty-six surgical breast specimens were imaged with digital mammography (DM) and a prototype of a DBT system (Planmed Oy, Helsinki, Finland). We tested the patient friendliness of the sync-and-shoot movement without radiation exposure in eight volunteers. Different imaging parameters were tested with 20 specimens to identify the optimal combination: angular range 30°, 40°, and 60°; pixel binning; Rhodium (Rh) and Silver (Ag) filtrations; and different kV and mAs values. Two breast radiologists evaluated 16 DM and DBT image pairs and rated six different image properties. Imaging modalities were compared with paired t-test.

Results

The Continuous Sync-and-Shoot method produced diagnostically valid images. Five out of eight volunteers felt no/minimal discomfort, three experienced mild discomfort from the tilting movement of the detector, with the motion being barely recognized. The combination of 30°, Ag filtering, and 2 × 2 pixel binning produced the best image quality at an acceptable dose level. DBT was significantly better in all six evaluated properties (P < 0.05). Mean Dose_DBT/Dose_DM ratio was 1.22 (SD = 0.42).

Conclusion

The evaluated imaging method is feasible for imaging and analysing surgical breast specimens and DBT is significantly better than DM in image evaluation.

Diagnostic Efficacy of Synthesized 2D Digital Breast Tomosynthesis in Multi-ethnic Malaysian Population

Synthesized 2D images can be reconstructed from tomosynthesis images in breast imaging. This study aims to investigate the diagnostic efficacy of synthesized 2D images (C-View) in comparison to full field digital mammography (FFDM) when used with digital breast tomosynthesis (DBT) in multi-ethnic Malaysian population. FFDM and C-View images (n = 380) were independently evaluated by three readers through Breast Imaging Reporting and Data System (BI-RADS) categorisation, breast density and lesion characterisation. Statistical analysis was done comparing sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of C-View + DBT with FFDM + DBT as standard of reference. Very good interreader agreement in BI-RADS category and density assessment between C-View + DBT and FFDM + DBT, with high sensitivity, specificity, PPV and NPV of C-View + DBT when compared with FFDM + DBT. There was comparable PPV between C-View + DBT and FFDM + DBT, with histopathology as gold standard. High level of interreader agreement in BI-RADS category and density assessment for FFDM + DBT and C-View + DBT. There was good agreement between FFDM + DBT and C-View + DBT in mass characterization, and almost perfect agreement in calcification and asymmetric density. 52.2% lower radiation dose incurred when using C-View + DBT. Hence, synthesized 2D images are comparable to FFDM with reduction in radiation dose within the limits of Malaysian multi-ethnic population.

Detection of Breast Cancer with Mammography: Effect of an Artificial Intelligence Support System

Purpose To compare breast cancer detection performance of radiologists reading mammographic examinations unaided versus supported by an artificial intelligence (AI) system. Materials and Methods An enriched retrospective, fully crossed, multireader, multicase, HIPAA-compliant study was performed. Screening digital mammographic examinations from 240 women (median age, 62 years; range, 39-89 years) performed between 2013 and 2017 were included. The 240 examinations (100 showing cancers, 40 leading to false-positive recalls, 100 normal) were interpreted by 14 Mammography Quality Standards Act-qualified radiologists, once with and once without AI support. The readers provided a Breast Imaging Reporting and Data System score and probability of malignancy. AI support provided radiologists with interactive decision support (clicking on a breast region yields a local cancer likelihood score), traditional lesion markers for computer-detected abnormalities, and an examination-based cancer likelihood score. The area under the receiver operating characteristic curve (AUC), specificity and sensitivity, and reading time were compared between conditions by using mixed-models analysis dof variance and generalized linear models for multiple repeated measurements. Results On average, the AUC was higher with AI support than with unaided reading (0.89 vs 0.87, respectively; P = .002). Sensitivity increased with AI support (86% [86 of 100] vs 83% [83 of 100]; P = .046), whereas specificity trended toward improvement (79% [111 of 140]) vs 77% [108 of 140]; P = .06). Reading time per case was similar (unaided, 146 seconds; supported by AI, 149 seconds; P = .15). The AUC with the AI system alone was similar to the average AUC of the radiologists (0.89 vs 0.87). Conclusion Radiologists improved their cancer detection at mammography when using an artificial intelligence system for support, without requiring additional reading time. Published under a CC BY 4.0 license. See also the editorial by Bahl in this issue.

New reconstruction algorithm for digital breast tomosynthesis: better image quality for humans and computers

Background

The image quality of digital breast tomosynthesis (DBT) volumes depends greatly on the reconstruction algorithm.

Purpose

To compare two DBT reconstruction algorithms used by the Siemens Mammomat Inspiration system, filtered back projection (FBP), and FBP with iterative optimizations (EMPIRE), using qualitative analysis by human readers and detection performance of machine learning algorithms.

Material and Methods

Visual grading analysis was performed by four readers specialized in breast imaging who scored 100 cases reconstructed with both algorithms (70 lesions). Scoring (5-point scale: 1 = poor to 5 = excellent quality) was performed on presence of noise and artifacts, visualization of skin-line and Cooper’s ligaments, contrast, and image quality, and, when present, lesion visibility. In parallel, a three-dimensional deep-learning convolutional neural network (3D-CNN) was trained (n = 259 patients, 51 positives with BI-RADS 3, 4, or 5 calcifications) and tested (n = 46 patients, nine positives), separately with FBP and EMPIRE volumes, to discriminate between samples with and without calcifications. The partial area under the receiver operating characteristic curve (pAUC) of each 3D-CNN was used for comparison.

Results

EMPIRE reconstructions showed better contrast (3.23 vs. 3.10, P = 0.010), image quality (3.22 vs. 3.03, P < 0.001), visibility of calcifications (3.53 vs. 3.37, P = 0.053, significant for one reader), and fewer artifacts (3.26 vs. 2.97, P < 0.001). The 3D-CNN-EMPIRE had better performance than 3D-CNN-FBP (pAUC-EMPIRE = 0.880 vs. pAUC-FBP = 0.857; P < 0.001).

Conclusion

The new algorithm provides DBT volumes with better contrast and image quality, fewer artifacts, and improved visibility of calcifications for human observers, as well as improved detection performance with deep-learning algorithms.

The role of digital breast tomosynthesis in the breast assessment clinic: a review

Mammography has long been considered as the primary technique in breast cancer detection and assessment. Despite low specificity, mammography has been preferred over other contemporary techniques such as magnetic resonance imaging (MRI), computed tomography (CT) and ultrasonography (US) due to superior sensitivity and significant health economic benefits. The development of a new technique, a limited angle cone beam pseudo-three-dimensional tomosynthesis, digital breast tomosynthesis (DBT), has gained momentum. Several preliminary studies and ongoing trials are showing evidence of the benefits of DBT in improving lesion visibility, accuracy of cancer detection and observer performance. This raises the possibility of adoption of DBT in the breast cancer assessment clinic, wherein confirming or dismissing the presence of malignancy (at the potential site identified during screening) is of utmost importance. Identification of suspected malignancy in terms of lesion characteristics and location is also essential in assessment. In this literature review, we evaluate the role of DBT for use in breast cancer assessment and its future in biopsy.

Imaging features and conspicuity of invasive lobular carcinomas on digital breast tomosynthesis

OBJECTIVE

To review the imaging features of invasive lobular carcinoma (ILC) seen on digital breast tomosynthesis (DBT) in comparison with invasive ductal carcinoma (IDC), and to evaluate whether DBT could improve conspicuity and tumour size assessment of ILC in comparison with digital mammography (DM).

METHODS

Institutional review board with waiver of informed consent was obtained for this retrospective study. Patients with ILC or IDC who underwent DBT and DM at the time of diagnosis were included. DM and DBT images were reviewed in consensus by two breast radiologists in order to assess imaging features, conspicuity and maximum tumour diameter of ILC and IDC. Pathology on the surgical specimen was considered the standard of reference for assessment of tumour size.

RESULTS

43 patients (20 patients with ILC and 23 patients with IDC) were included. On DBT, compared with IDC, ILC presented less frequently as masses (40% vs 78%) (p = 0.01) and more frequently as isolated distortion (20% vs 0%) (p = 0.03). ILC presented more often as asymmetries (60%) than masses (20%) on DM (p = 0.02) but not on DBT (35% vs 40%; p = 1.00). Conspicuity of ILC was significantly higher on DBT than on DM (p = 0.002), while the difference between the two techniques was not significant for IDC (p = 0.2). Regarding ILC, concordance in tumour size measurement between DBT and pathology was fair (intraclass correlation coefficient = 0.24).

CONCLUSION

ILC rarely presented as dense masses but frequently demonstrated architectural distortion on DBT. DBT increased lesion conspicuity but failed to accurately assess tumour size of ILC. Advances in knowledge: (1) This study describes specific features of ILC on DBT. (2) It shows that DBT can improve conspicuity of ILC.

Comparison of two-dimensional synthesized mammogram (2DSM) and conventional full-field digital mammogram (FFDM) for evaluation of breast cancer

PURPOSE

To compare the diagnostic efficacy of 2DSM and FFDM for evaluation of breast cancer.

MATERIALS AND METHODS

A retrospective observer performance study was done by 3 breast radiologists. The diagnostic accuracy, image quality, and detailed lesion characterization of each 2DSM and FFDM were evaluated blindly to determine superior modality.

RESULTS

The diagnostic accuracy was not significantly different between two modalities. The image quality was superior in 2DSM (p-value 0.0362).

CONCLUSIONS

2DSM showed equivalent diagnostic accuracy and superior image quality to FFDM. Overall characterization of the lesion was better in 2DSM, and 2DSM showed superiority in evaluation of spiculated margins.

Replacing single-view mediolateral oblique (MLO) digital mammography (DM) with synthesized mammography (SM) with digital breast tomosynthesis (DBT) images: Comparison of the diagnostic performance and radiation dose with two-view DM with or without MLO-DBT

OBJECTIVES

To evaluate the diagnostic performance and radiation dose of single view cranio-caudal (CC) digital mammography (DM) plus mediolateral oblique (MLO) digital breast tomosynthesis (DBT) combined with synthesized mammography (SM) in comparison with two-view DM with or without DBT.

MATERIAL AND METHODS

This study was approved by our institutional review board, and informed consent was obtained from 130 women. Paired two-view DM and single MLO-DBT with SM images were acquired, and four independent retrospective reading sessions of different combinations of DM, SM and DBT were performed for the presence of malignant tumors using jackknife alternative free-response receiver operator curve (JAFROC) methods. The diagnostic performances and average glandular dose (AGD) were compared between different combinations of DM, SM and DBT.

RESULTS

Of 159 lesions in 130 patients, 27 were malignant. When using MLO-DBT with SM instead of MLO-DM, a significantly higher sensitivity (P=0.016) and specificity (P=0.012) were noted than with two-view DM, and comparable figure of merit (FOM), sensitivity, and specificity to two-view DM with DBT were noted. The mean AGD of CC-DM plus MLO-DBT with SM was 5.78mGy±1.06 per patient, which was significantly lower than that with two-view DM with MLO-DBT (8.45mGy±1.32; P <0.001) and slightly higher than that with two-view DM (5.30mGy±0.63).

CONCLUSIONS

The combined use of CC-DM plus MLO-DBT with SM showed higher sensitivity and specificity to two-view DM with a smaller AGD increment and comparable diagnostic performance to that of two-view DM with MLO-DBT with a significantly lower mean AGD.

Detectability comparison of modes in dual-mode digital breast tomosynthesis

BACKGROUND

The objectives of this study were: (1) to evaluate the detectability of full-field digital mammography (FFDM) plus dual-mode digital breast tomosynthesis (DBT) and compare it with that of FFDM alone and (2) to compare the detectability of high-resolution-mode (HR mode used with 40°-angle imaging, 100-µm pixel size, and higher dose) DBT with that of standard-mode (ST mode used with 15°-angle imaging, 150-µm pixel size, and lower dose) DBT for diagnostic evaluation.

MATERIALS

The local Institutional Review Board approved this retrospective study of two different sets of cases. All participants gave written informed consent. FFDM and DBT images of 471 women who were recalled were acquired between August 2013 and October 2014. HR mode and ST mode were applied to 155 breasts and 157 breasts, respectively. The cases of both modes were selected randomly. Eight radiologists interpreted the images. The detectability for recall cases and for follow cases, and area under the receiver operating characteristic curve (AUC) were calculated.

RESULTS

Adding DBT to FFDM significantly increased the detectability for recall cases and AUC relative to those of FFDM alone (HR mode 8.9 %; 95 % confidence interval (CI) 5.7, 15.0 %; P = 0.013 and 4.9 %; 95 % CI 2.1, 7.7 %; P = 0.001; ST mode 8.3 %; 95 % CI 4.1, 12.1 %; P = 0.007 and 2.9 %; 95 % CI 0.5, 5.3 %; P = 0.02), whereas the detectability for follow cases did not significantly differ. The AUC increase was significantly higher in HR mode than in ST mode (1.5 %; 95 % CI 0.5, 3.7 %; P = 0.023).

CONCLUSION

Adding HR-mode or ST-mode DBT to FFDM significantly improved the detectability for diagnostic evaluation case.

Tomosynthesis in the Diagnostic Setting: Changing Rates of BI-RADS Final Assessment over Time

Purpose To evaluate the effect of tomosynthesis in diagnostic mammography on the Breast Imaging Reporting and Data System (BI-RADS) final assessment categories over time. Materials and Methods This retrospective study was approved by the institutional review board. The authors reviewed all diagnostic mammograms obtained during a 12-month interval before (two-dimensional [2D] mammography [June 2, 2010, to June 1, 2011]) and for 3 consecutive years after (tomosynthesis year 1 [2012], tomosynthesis year 2 [2013], and tomosynthesis year 3 [2014]) the implementation of tomosynthesis. The requirement to obtain informed consent was waived. The rates of BI-RADS final assessment categories 1-5 were compared between the 2D and tomosynthesis groups. The positive predictive values after biopsy (PPV3) for BI-RADS category 4 and 5 cases were compared. The mammographic features (masses, architectural distortions, calcifications, focal asymmetries) of lesions categorized as probably benign (BI-RADS category 3) and those for which biopsy was recommended (BI-RADS category 4 or 5) were reviewed. The χ(2) test was used to compare the rates of BI-RADS final assessment categories 1-5 between the two groups, and multivariate logistic regression analysis was performed to compare all diagnostic studies categorized as BI-RADS 3-5. Results There was an increase in the percentage of cases reported as negative or benign (BI-RADS category 1 or 2) with tomosynthesis (58.7% with 2D mammography vs 75.8% with tomosynthesis at year 3, P < .0001). A reduction in the percentage of probably benign (BI-RADS category 3) final assessments also occurred (33.3% with 2D mammography vs 16.4% with tomosynthesis at year 3, P < .0001). Although the rates of BI-RADS 4 or 5 assessments did not change significantly with tomosynthesis (8.0% with 2D mammography vs 7.8% with tomosynthesis at year 3, P = .2), there was a significant increase in the PPV3 (29.6% vs 50%, respectively; P < .0001). These trends increased during the 3 years of tomosynthesis use. Conclusion Tomosynthesis in the diagnostic setting resulted in progressive shifts in the BI-RADS final assessment categories over time, with a significant increase in the proportion of studies classified as normal, a continued decrease in the rate of studies categorized as probably benign, and improved diagnostic confidence in biopsy recommendations. (©) RSNA, 2016.

Digital Breast Tomosynthesis: State of the Art

This topical review on digital breast tomosynthesis (DBT) is provided with the intent of describing the state of the art in terms of technology, results from recent clinical studies, advanced applications, and ongoing efforts to develop multimodality imaging systems that include DBT. Particular emphasis is placed on clinical studies. The observations of increase in cancer detection rates, particularly for invasive cancers, and the reduction in false-positive rates with DBT in prospective trials indicate its benefit for breast cancer screening. Retrospective multireader multicase studies show either noninferiority or superiority of DBT compared with mammography. Methods to curtail radiation dose are of importance. (©) RSNA, 2015.

"Off Label" Use of FDA-Approved Devices and Digital Breast Tomosynthesis

OBJECTIVE

The purpose of this article is to clarify for radiologists the meaning of U.S. Food and Drug Administration (FDA) approval with respect to Digital Breast Tomosynthesis (DBT).

CONCLUSION

DBT is a major improvement over 2D mammography in the detection of cancers (sensitivity) and the reduction in recalls resulting from screening (specificity). Most imaging systems that have been approved by the FDA are used "off label" for breast imaging. Although the FDA determines which claims a manufacturer can make for a device, physicians may use approved devices, such as DBT, off label to provide better patient care.

Digital breast tomosynthesis in one or two views as a replacement or adjunct technique to full-field digital mammography

Clinical studies using different imaging protocols to perform digital breast tomosynthesis (DBT) were reviewed (2008-14) to assess interpretive accuracy. Descriptive pooled statistics were used to estimate and summarise accuracy measures for each type of imaging protocol in relation to that of two-view full-field digital mammography (FFDM). In studies comparing multiple DBT imaging protocols, a trend of increased performance was often seen when including both the mediolateral oblique and craniocaudal views for DBT alone and even more so for DBT adjunct to FFDM. Overall, the average ΔAUC (%; sd) across studies for stand-alone DBT (relative to FFDM), in one and in two views, were 2.2 (± 3.7) and 5.9 (± 4.6), and when used together with FFDM, 3.9 (± 2.0) and 6.7 (± 0.9). With respect to individual studies, improvements in accuracy using DBT were present for different types of imaging protocols although the magnitude of the impact varied between studies, and some studies did not show significant improvements in comparison with FFDM. The most consistent effect of improvement in breast cancer detection was seen across studies for two-view DBT with FFDM. These summary findings may depend on the sampling constraints present in tomosynthesis imaging and on other factors discussed in this paper. In order to investigate these effects more thoroughly and how they might impact outcomes, comparative or randomized-controlled trials are warranted.

Review of radiation dose estimates in digital breast tomosynthesis relative to those in two-view full-field digital mammography

We examined how radiation dose levels in digital breast tomosynthesis (DBT) differ from those used in 2-view full-field digital mammography (FFDM). Acquisition parameter settings and information on the average absorbed dose to the glandular tissues within the breasts were reviewed based on clinical studies that evaluated DBT and FFDM. Dose ratios (DDBT/DFFDM) were derived from imaging protocols, which included tomosynthesis in 1- or 2-views alone, and as an adjunct technique to FFDM. Stand-alone DBT was associated with a much lower to a slightly higher radiation dose compared to that of comparable FFDM units, as summarized in dose ratio ranges of 0.34-1.0 for 1-view DBT, and 0.68-1.17 for 2-view DBT. One of the lowest reported dose estimates was obtained using a photon-counting DBT unit (avg. 0.70 mGy/scan; range: 0.28-1.26 mGy). Breast doses for DBT combined with FFDM are summarized in dose ratio ranges of 1.03-1.5 for 1-view DBT plus FFDM, and 2.0-2.23 for 2-view DBT plus FFDM. In the latter of these settings, the dose was reduced by ∼45% when 2D-views, reconstructed from the DBT images ("synthetic 2D images"), were used as a substitute for FFDM. Stand-alone DBT operated at lower to slightly higher radiation doses in comparison to FFDM. For DBT combined with FFDM, radiation doses were elevated, at maximum by a factor ∼2 1/4 of that of FFDM alone. In this setting, a replacement of FFDM with synthetic 2D-views reduced the breast dose approximately by half, which has substantial implications for population screening programs.

X-ray scatter correction in breast tomosynthesis with a precomputed scatter map library

PURPOSE

To develop and evaluate the impact on lesion conspicuity of a software-based x-ray scatter correction algorithm for digital breast tomosynthesis (DBT) imaging into which a precomputed library of x-ray scatter maps is incorporated.

METHODS

A previously developed model of compressed breast shapes undergoing mammography based on principal component analysis (PCA) was used to assemble 540 simulated breast volumes, of different shapes and sizes, undergoing DBT. A Monte Carlo (MC) simulation was used to generate the cranio-caudal (CC) view DBT x-ray scatter maps of these volumes, which were then assembled into a library. This library was incorporated into a previously developed software-based x-ray scatter correction, and the performance of this improved algorithm was evaluated with an observer study of 40 patient cases previously classified as BI-RADS® 4 or 5, evenly divided between mass and microcalcification cases. Observers were presented with both the original images and the scatter corrected (SC) images side by side and asked to indicate their preference, on a scale from -5 to +5, in terms of lesion conspicuity and quality of diagnostic features. Scores were normalized such that a negative score indicates a preference for the original images, and a positive score indicates a preference for the SC images.

RESULTS

The scatter map library removes the time-intensive MC simulation from the application of the scatter correction algorithm. While only one in four observers preferred the SC DBT images as a whole (combined mean score = 0.169 ± 0.37, p > 0.39), all observers exhibited a preference for the SC images when the lesion examined was a mass (1.06 ± 0.45, p < 0.0001). When the lesion examined consisted of microcalcification clusters, the observers exhibited a preference for the uncorrected images (-0.725 ± 0.51, p < 0.009).

CONCLUSIONS

The incorporation of the x-ray scatter map library into the scatter correction algorithm improves the efficiency of the algorithm. The observer study presented here is also the first test of the scatter correction algorithm with patient images and human observers, and demonstrates its potential to improve the clinical performance of DBT.

Computer-aided detection of clustered microcalcifications in multiscale bilateral filtering regularized reconstructed digital breast tomosynthesis volume

PURPOSE

Develop a computer-aided detection (CADe) system for clustered microcalcifications in digital breast tomosynthesis (DBT) volume enhanced with multiscale bilateral filtering (MSBF) regularization.

METHODS

With Institutional Review Board approval and written informed consent, two-view DBT of 154 breasts, of which 116 had biopsy-proven microcalcification (MC) clusters and 38 were free of MCs, was imaged with a General Electric GEN2 prototype DBT system. The DBT volumes were reconstructed with MSBF-regularized simultaneous algebraic reconstruction technique (SART) that was designed to enhance MCs and reduce background noise while preserving the quality of other tissue structures. The contrast-to-noise ratio (CNR) of MCs was further improved with enhancement-modulated calcification response (EMCR) preprocessing, which combined multiscale Hessian response to enhance MCs by shape and bandpass filtering to remove the low-frequency structured background. MC candidates were then located in the EMCR volume using iterative thresholding and segmented by adaptive region growing. Two sets of potential MC objects, cluster centroid objects and MC seed objects, were generated and the CNR of each object was calculated. The number of candidates in each set was controlled based on the breast volume. Dynamic clustering around the centroid objects grouped the MC candidates to form clusters. Adaptive criteria were designed to reduce false positive (FP) clusters based on the size, CNR values and the number of MCs in the cluster, cluster shape, and cluster based maximum intensity projection. Free-response receiver operating characteristic (FROC) and jackknife alternative FROC (JAFROC) analyses were used to assess the performance and compare with that of a previous study.

RESULTS

Unpaired two-tailed t-test showed a significant increase (p < 0.0001) in the ratio of CNRs for MCs with and without MSBF regularization compared to similar ratios for FPs. For view-based detection, a sensitivity of 85% was achieved at an FP rate of 2.16 per DBT volume. For case-based detection, a sensitivity of 85% was achieved at an FP rate of 0.85 per DBT volume. JAFROC analysis showed a significant improvement in the performance of the current CADe system compared to that of our previous system (p = 0.003).

CONCLUSIONS

MBSF regularized SART reconstruction enhances MCs. The enhancement in the signals, in combination with properly designed adaptive threshold criteria, effective MC feature analysis, and false positive reduction techniques, leads to a significant improvement in the detection of clustered MCs in DBT.

Digital breast tomosynthesis versus mammography and breast ultrasound: a multireader performance study

OBJECTIVES

To compare the diagnostic performance of single-view breast tomosynthesis (BT) with that of dual-view mammography (MX); to assess the benefit of adding the craniocaudal (CC) mammographic view to BT, and of adding BT to MX plus breast ultrasound, considered to be the reference work-up.

METHODS

One hundred and fifty-five consenting patients with unresolved mammographic and/or ultrasound findings or breast symptoms underwent conventional work-up plus mediolateral oblique-view BT of the affected breast. The final study set in 130 patients resulted in 55 malignant and 76 benign and normal cases. Seven breast radiologists rated the cases through five sequential techniques using a BIRADS-based scale: MX, MX + ultrasound, MX + ultrasound + BT, BT, BT + MX(CC). Multireader, multicase receiver operating characteristic (ROC) analysis was performed and performance of the techniques was assessed from the areas under ROC curves. The performance of BT and of BT + MX(CC) was tested versus MX; the performance of MX + ultrasound + BT tested versus MX + ultrasound.

RESULTS

Tomosynthesis was found to be non-inferior to mammography. BT + MX(CC) did not appear to be superior to MX, and MX + ultrasound + BT not superior to MX + ultrasound.

CONCLUSIONS

Overall, none of the five techniques tested outperformed the others. Further clinical studies are needed to clarify the role of BT as a substitute for traditional work-up in the diagnostic environment.

KEY POINTS

• Digital breast tomosynthesis is a new adjunct to mammography and breast ultrasound. • We compared the diagnostic performance of these investigations in an experimental observer study. • Single-view breast tomosynthesis was confirmed as non-inferior to dual-view mammography. • None of the investigations (or combinations) tested outperformed the others. • Further prospective studies are needed to clarify precise role of tomosynthesis for diagnostic application.

Prospective trial comparing full-field digital mammography (FFDM) versus combined FFDM and tomosynthesis in a population-based screening programme using independent double reading with arbitration

OBJECTIVES

To compare double readings when interpreting full field digital mammography (2D) and tomosynthesis (3D) during mammographic screening.

METHODS

A prospective, Ethical Committee approved screening study is underway. During the first year 12,621 consenting women underwent both 2D and 3D imaging. Each examination was independently interpreted by four radiologists under four reading modes: Arm A-2D; Arm B-2D + CAD; Arm C-2D + 3D; Arm D-synthesised 2D + 3D. Examinations with a positive score by at least one reader were discussed at an arbitration meeting before a final management decision. Paired double reading of 2D (Arm A + B) and 2D + 3D (Arm C + D) were analysed. Performance measures were compared using generalised linear mixed models, accounting for inter-reader performance heterogeneity (P < 0.05).

RESULTS

Pre-arbitration false-positive scores were 10.3 % (1,286/12,501) and 8.5 % (1,057/12,501) for 2D and 2D + 3D, respectively (P < 0.001). Recall rates were 2.9 % (365/12,621) and 3.7 % (463/12,621), respectively (P = 0.005). Cancer detection was 7.1 (90/12,621) and 9.4 (119/12,621) per 1,000 examinations, respectively (30 % increase, P < 0.001); positive predictive values (detected cancer patients per 100 recalls) were 24.7 % and 25.5 %, respectively (P = 0.97). Using 2D + 3D, double-reading radiologists detected 27 additional invasive cancers (P < 0.001).

CONCLUSION

Double reading of 2D + 3D significantly improves the cancer detection rate in mammography screening.

KEY POINTS

• Tomosynthesis-based screening was successfully implemented in a large prospective screening trial. • Double reading of tomosynthesis-based examinations significantly reduced false-positive interpretations. • Double reading of tomosynthesis significantly increased the detection of invasive cancers.

Epidemiology of Breast Cancer - Current Figures and Trends

The epidemiology of breast cancer has clearly changed in the past few years. On the basis of current data from population-based cancer registries characteristic numbers for incidence, prevalence, mortality and survival after breast cancer are presented. The number of incident cases has increased to around 72 000 in 2009 (+ 23 % since 2003). It is estimated that at present 250 000 women with a prevalent breast cancer (5-year prevalence) are living in Germany. The most frequent localisation is the outer upper quadrant of the breast. Poorly differentiated or undifferentiated tumour tissue is found in every third patient. Since 2003 the age-standardised mortality has declined slightly (- 9 %) whereas the relative survival has improved from 79 to 86 %. Changes in the epidemiology of breast cancer can most probably be attributed to the introduction of early detection programmes such as mammography screening as well as to improved treatment options. To what extent mammography screening will lead to a further reduction of mortality remains to be seen.