Breast tomosynthesis and digital mammography: a comparison of breast cancer visibility and BIRADS classification in a population of cancers with subtle mammographic findings

WHO-recommended levels of physical activity in relation to mammographic breast density, mammographic tumor appearance, and mode of detection of breast cancer

BACKGROUND

Despite known benefits of physical activity in reducing breast cancer risk, its impact on mammographic characteristics remain unclear and understudied. This study aimed to investigate associations between pre-diagnostic physical activity and mammographic features at breast cancer diagnosis, specifically mammographic breast density (MBD) and mammographic tumor appearance (MA), as well as mode of cancer detection (MoD).

METHODS

Physical activity levels from study baseline (1991-1996) and mammographic information from the time of invasive breast cancer diagnosis (1991-2014) of 1116 women enrolled in the Malmö Diet and Cancer Study cohort were used. Duration and intensity of physical activity were assessed according to metabolic equivalent of task hours (MET-h) per week, or World Health Organization (WHO) guideline recommendations. MBD was dichotomized into low-moderate or high, MA into spiculated or non-spiculated tumors, and MoD into clinical or screening detection. Associations were investigated through logistic regression analyses providing odds ratios (OR) with 95% confidence intervals (CI) in crude and multivariable-adjusted models.

RESULTS

In total, 32% of participants had high MBD at diagnosis, 37% had non-spiculated MA and 50% had clinical MoD. Overall, no association between physical activity and MBD was found with increasing MET-h/week or when comparing women who exceeded WHO guidelines to those subceeding recommendations (ORadj 1.24, 95% CI 0.78-1.98). Likewise, no differences in MA or MoD were observed across categories of physical activity.

CONCLUSIONS

No associations were observed between pre-diagnostic physical activity and MBD, MA, or MoD at breast cancer diagnosis. While physical activity is an established breast cancer prevention strategy, it does not appear to modify mammographic characteristics or screening detection.

Optimizing angular range in digital breast tomosynthesis: A phantom study investigating lesion detection across varied breast density and thickness

PURPOSE

To determine the optimal angular range (AR) for digital breast tomosynthesis (DBT) systems that provides highest lesion visibility across various breast densities and thicknesses.

METHOD

A modular DBT phantom, consisting of tissue-equivalent adipose and glandular modules, along with a module embedded with test objects (speckles, masses, fibers), was used to create combinations simulating different breast thicknesses, densities, and lesion locations. A prototype DBT system operated at four ARs (AR±7.5°, AR±12.5°, AR±19°, and AR±25°) to acquire 11 projection images for each combination, with separate fixed doses for thin and thick combinations. Three blinded radiologists independently assessed lesion visibility in reconstructed images; assessments were averaged and compared using linear mixed models.

RESULTS

Speckle visibility was highest with AR±7.5° or AR±12.5°, decreasing with wider ARs in all density and thickness combinations. The difference between AR±7.5° and AR±12.5° was not statistically significant, except for the tube-side speckles in thin-fatty combinations (5.83 [AR±7.5°] vs. 5.39 [AR±12.5°], P = 0.019). Mass visibility was not affected by AR in thick combinations, while AR±12.5° exhibited the highest mass visibility for both thin-fatty and thin-dense combinations (P = 0.032 and 0.007, respectively). Different ARs provided highest fiber visibility for different combinations; however, AR±12.5° consistently provided highest or comparable visibility. AR±12.5° showed highest overall lesion visibility for all density and thickness combinations.

CONCLUSIONS

AR±12.5° exhibited the highest overall lesion visibility across various phantom thicknesses and densities using a projection number of 11.

Screening the Implant-Augmented Breast with Digital Breast Tomosynthesis: Is Tomosynthesis Necessary for Non-implant-Displaced Views?

OBJECTIVE

To determine cancer visualization utility and radiation dose for non-implant-displaced (ID) views using standard protocol with digital breast tomosynthesis (DBT) vs alternative protocol with 2D only when screening women with implant augmentation.

METHODS

This retrospective cohort study identified women with implants who underwent screening DBT examinations that had abnormal findings from July 28, 2014, to December 31, 2021. Three fellowship-trained breast radiologists independently reviewed examinations retrospectively to determine if the initially identified abnormalities could be visualized on standard protocol (DBT with synthesized 2D (S2D) for ID and non-ID views) and alternate protocol (DBT with S2D for ID and only the S2D images for non-ID views). Estimated exam average glandular dose (AGD) and associations between cancer visualization with patient and implant characteristics for both protocols were evaluated.

RESULTS

The study included 195 patients (mean age 55 years ± 10) with 223 abnormal findings. Subsequent biopsy was performed for 86 abnormalities: 59 (69%) benign, 8 (9%) high risk, and 19 (22%) malignant. There was no significant difference in malignancy visualization rate between standard (19/223, 8.5%) and alternate (18/223, 8.1%) protocols (P = .92), but inclusion of the DBT for non-ID views found one additional malignancy. Total examination AGD using standard protocol (21.9 mGy ± 5.0) was significantly higher than it would be for estimated alternate protocol (12.6 mGy ± 5.0, P <.001). This remained true when stratified by breast thickness: 6.0-7.9 cm, 8.0-9.9 cm, >10.0 cm (all P <.001).

CONCLUSION

The inclusion of DBT for non-ID views did not significantly increase the cancer visualization rate but did significantly increase overall examination AGD.

The Tomosynthesis Broken Halo Sign: Diagnostic Utility for the Classification of Newly Diagnosed Breast Tumors

BACKGROUND

Compared to conventional 2D mammography, digital breast tomosynthesis (DBT) offers greater breast lesion detection rates. Ring-like hypodense artifacts surrounding dense lesions are a common byproduct of DBT. This study's purpose was to assess whether minuscule changes spanning this halo-termed the "broken halo sign"-could improve lesion classification.

METHODS

This retrospective study was approved by the local ethics review board. After screening 288 consecutive patients, DBT studies of 191 female participants referred for routine mammography with a subsequent histologically verified finding of the breast were assessed. Examined variables included patient age, histological diagnosis, architectural distortion, maximum size, maximum halo depth, conspicuous margins, irregular shape and broken halo sign.

RESULTS

While a higher halo strength was indicative of malignancy in general (p = 0.031), the broken halo sign was strongly associated with malignancy (p < 0.0001, odds ratio (OR) 6.33), alongside architectural distortion (p = 0.012, OR 3.49) and a diffuse margin (p = 0.006, OR 5.49). This was especially true for denser breasts (ACR C/D), where the broken halo sign was the only factor predicting malignancy (p = 0.03, 5.22 OR).

CONCLUSION

DBT-associated halo artifacts warrant thorough investigation in newly found breast lesions as they are associated with malignant tumors. The "broken halo sign"-the presence of small lines of variable diameter spanning the peritumoral areas of hypodensity-is a strong indicator of malignancy, especially in dense breasts, where architectural distortion may be obfuscated due to the surrounding tissue.

Deep learning denoising of digital breast tomosynthesis: Observer performance study of the effect on detection of microcalcifications in breast phantom images

BACKGROUND

The noise in digital breast tomosynthesis (DBT) includes x-ray quantum noise and detector readout noise. The total radiation dose of a DBT scan is kept at about the level of a digital mammogram but the detector noise is increased due to acquisition of multiple projections. The high noise can degrade the detectability of subtle lesions, specifically microcalcifications (MCs).

PURPOSE

We previously developed a deep-learning-based denoiser to improve the image quality of DBT. In the current study, we conducted an observer performance study with breast radiologists to investigate the feasibility of using deep-learning-based denoising to improve the detection of MCs in DBT.

METHODS

We have a modular breast phantom set containing seven 1-cm-thick heterogeneous 50% adipose/50% fibroglandular slabs custom-made by CIRS, Inc. (Norfolk, VA). We made six 5-cm-thick breast phantoms embedded with 144 simulated MC clusters of four nominal speck sizes (0.125-0.150, 0.150-0.180, 0.180-0.212, 0.212-0.250 mm) at random locations. The phantoms were imaged with a GE Pristina DBT system using the automatic standard (STD) mode. The phantoms were also imaged with the STD+ mode that increased the average glandular dose by 54% to be used as a reference condition for comparison of radiologists' reading. Our previously trained and validated denoiser was deployed to the STD images to obtain a denoised DBT set (dnSTD). Seven breast radiologists participated as readers to detect the MCs in the DBT volumes of the six phantoms under the three conditions (STD, STD+, dnSTD), totaling 18 DBT volumes. Each radiologist read all the 18 DBT volumes sequentially, which were arranged in a different order for each reader in a counter-balanced manner to minimize any potential reading order effects. They marked the location of each detected MC cluster and provided a conspicuity rating and their confidence level for the perceived cluster. The visual grading characteristics (VGC) analysis was used to compare the conspicuity ratings and the confidence levels of the radiologists for the detection of MCs.

RESULTS

The average sensitivities over all MC speck sizes were 65.3%, 73.2%, and 72.3%, respectively, for the radiologists reading the STD, dnSTD, and STD+ volumes. The sensitivity for dnSTD was significantly higher than that for STD (p < 0.005, two-tailed Wilcoxon signed rank test) and comparable to that for STD+. The average false positive rates were 3.9 ± 4.6, 2.8 ± 3.7, and 2.7 ± 3.9 marks per DBT volume, respectively, for reading the STD, dnSTD, and STD+ images but the difference between dnSTD and STD or STD+ did not reach statistical significance. The overall conspicuity ratings and confidence levels by VGC analysis for dnSTD were significantly higher than those for both STD and STD+ (p ≤ 0.001). The critical alpha value for significance was adjusted to be 0.025 with Bonferroni correction.

CONCLUSIONS

This observer study using breast phantom images showed that deep-learning-based denoising has the potential to improve the detection of MCs in noisy DBT images and increase radiologists' confidence in differentiating noise from MCs without increasing radiation dose. Further studies are needed to evaluate the generalizability of these results to the wide range of DBTs from human subjects and patient populations in clinical settings.

Radiation Dose Reduction in Digital Breast Tomosynthesis by MTANN with Multi-scale Kernels

Digital breast tomosynthesis (DBT) is an advanced three-dimensional screening modality for the early detection of breast cancer. DBT is able to reduce the problem of tissue overlap in standard two-dimensional mammograms, thus improving the sensitivity and specificity of cancer detection. Although DBT can improve diagnostic accuracy, it leads to higher radiation dose to patients compared to two-dimensional mammography. In this paper, we propose a novel radiation dose reduction technique that introduces multi-scale kernels to our original massive-training artificial neural network (MTANN) to reduce radiation dose substantially, while maintaining high image quality in DBT. After training our new MTANN with low-dose (LD) images and the corresponding "teaching" high-dose (HD) images, we can convert new LD images to "virtual" high-dose (VHD) images where noise and artifact in the LD images are significantly reduced. In VHD images, it is critical to preserve subtle structures and tiny patterns such as microcalcifications (MCs) which are essential for breast cancer diagnosis. We developed anatomical MTANN experts including an MC-specific expert with multi-scale kernels, which are combined by gating layers to generate whole VHD images. Our MTANN scheme was able to achieve a 79% dose reduction while preserving details of MCs. Experimental results demonstrated that our method achieved the highest performance among the best-known noise-reduction techniques and state-of-the-art deep-learning techniques.Clinical Relevance- Our method can decrease the dose radiation dose in DBT and maintain the image quality.

Investigating the prognostic value of mammographic breast density and mammographic tumor appearance in women with invasive breast cancer: The Malmö Diet and cancer study

BACKGROUND

High breast density is a risk factor for breast cancer. However, whether density is a prognostic factor is debatable. Also, tumor appearances are related to tumor characteristics. Here we investigate the relationship between breast cancer-specific survival and mammographic breast density and mammographic tumor appearances.

METHODS

Women in the Malmö Diet and Cancer study with invasive breast cancer 1991-2014 were included (n = 1116). Mammographic information, patient and tumor characteristics, vital status, and causes of death were collected through 2018. Breast cancer-specific survival was assessed with Kaplan-Meier estimates and Cox proportional hazard models. Analyses were adjusted for established prognostic factors and stratified by detection mode.

RESULTS

High breast density did not significantly impact breast cancer-specific survival. However, there may be increased risk in women with dense breasts and screening-detected tumors (HR 1.45, CI 0.87-2.43). Neither did tumor appearance impact breast cancer-specific survival at long-term follow-up.

CONCLUSIONS

Breast cancer prognosis in women with high breast density on mammography does not seem impaired compared to women with less dense breasts, once the cancer is established. Neither does mammographic tumor appearance seem to inflict on prognosis, findings that can be of value in the management of breast cancer.

The Impact of Adding Digital Breast Tomosynthesis to BI-RADS Categorization of Mammographically Equivocal Breast Lesions

Digital mammography (DM) is the cornerstone of breast cancer detection. Digital breast tomosynthesis (DBT) is an advanced imaging technique used for diagnosing and screening breast lesions, particularly in dense breasts. This study aimed to evaluate the impact of combining DBT with DM on the BI-RADS categorization of equivocal breast lesions. We prospectively evaluated 148 females with equivocal BI-RADS breast lesions (BI-RADS 0, 3, and 4) with DM. All patients underwent DBT. Two experienced radiologists analyzed the lesions. They then assigned a BI-RADS category for each lesion according to the BI-RADS 2013 lexicon, using DM, DBT, and integrated DM and DBT. We compared the results based on major radiological characteristics, BI-RADS classification, and diagnostic accuracy, using the histopathological examination of the lesions as a reference standard. The total number of lesions was 178 on DBT and 159 on DM. Nineteen lesions were discovered using DBT and were missed by DM. The final diagnoses of 178 lesions were malignant (41.6%) and benign (58.4%). Compared to DM, DBT produced 34.8% downgrading and 32% upgrading of breast lesions. Compared with DM, DBT decreased the number of BI-RADS 4 and 3. All the upgraded BI-RADS 4 lesions were confirmed to be malignant. The combination of DM and DBT improves the diagnostic accuracy of BI-RADS for evaluating and characterizing mammographic equivocal breast lesions and allows for proper BI-RADS categorization.

Comparison of Diagnostic Mammography-Guided Biopsy and Digital Breast Tomosynthesis-Guided Biopsy of Suspicious Breast Calcifications: Results in 1354 Biopsies

BACKGROUND. Studies have shown improved targeting and sampling of noncalcified lesions (asymmetries, masses, and architectural distortion) with digital breast tomosynthesis (DBT)-guided biopsy in comparison with digital mammography (DM)-guided stereotactic biopsy. Literature that compares the two techniques specifically for sampling calcifications has been scarce. OBJECTIVE. The purpose of this study was to compare the performance and outcomes of DM- and DBT-guided biopsy of suspicious calcifications. METHODS. This retrospective study included 1310 patients (mean age, 58 ± 12 [SD] years) who underwent a total of 1354 9-gauge vacuum-assisted core biopsies of suspicious calcifications performed at a single institution from May 22, 2017, to December 31, 2021. The decision to use a DM-guided or DBT-guided technique was made at the discretion of the radiologist performing the biopsy. Procedure time, the number of exposures during the procedure, and the histopathologic outcomes were recorded. The two techniques were compared using a two-sample t test for continuous variables and a chi-square test for categoric variables. Additional tests were performed using generalized estimating equations to control for the effect of the individual radiologist performing the biopsy. RESULTS. A total of 348 (26%) biopsies used DM guidance, and 1006 (74%) used DBT guidance. The mean procedure time was significantly lower for DBT-guided biopsy (14.9 ± 8.0 [SD] minutes) than for DM-guided biopsy (24.7 ± 14.3 minutes) (p < .001). The mean number of exposures was significantly lower for DBT-guided biopsy (4.1 ± 1.0 [SD] exposures) than for DM-guided biopsy (9.1 ± 3.3 exposures) (p < .001). The differences in procedure time and number of exposures remained significant (both p < .001) when controlling for the effect of the radiologist performing the biopsy. There were no significant differences (all p > .05) between DM-guided and DBT-guided biopsy in terms of the malignancy rate on initial biopsy (20% vs 19%), the rate of high-risk lesion upgrading (14% vs 22%), or the final malignancy rate (23% vs 22%). CONCLUSION. DBT-guided biopsy of suspicious calcifications can be performed with shorter procedure time and fewer exposures compared with DM-guided biopsy, without a significant difference in rates of malignancy or high-risk lesion upgrading. CLINICAL IMPACT. The use of a DBT-guided, rather than a DM-guided, biopsy technique for suspicious calcifications can potentially reduce patient discomfort and radiation exposure without affecting clinical outcomes.

Mammography-Guided Interventional Procedure

Mammography has been the standard screening method for breast cancer. In women with suspicious calcifications and architectural distortion identified on mammography or digital breast tomosynthesis only without detected on breast US, stereotactic biopsy and mammography-guided preoperative localization is one of the method for pathologic diagnosis. This review aims to describe the indication, contraindication, technique of stereotactic biopsy, clip placement after stereotactic biopsy, and digital breast tomosynthesis-guided stereotactic biopsy. In addition, this article reviews mammography-guided preoperative localization using a wire or non-wire device.

[Patterns in the Use and Perception of Digital Breast Tomosynthesis: A Survey of Korean Breast Radiologists]

Purpose

To evaluate the pattern of use and the perception of digital breast tomosynthesis (DBT) among Korean breast radiologists.

Materials and Methods

From March 22 to 29, 2021, an online survey comprising 27 questions was sent to members of the Korean Society of Breast Imaging. Questions related to practice characteristics, utilization and perception of DBT, and research interests. Results were analyzed based on factors using logistic regression.

Results

Overall, 120 of 257 members responded to the survey (response rate, 46.7%), 67 (55.8%) of whom reported using DBT. The overall satisfaction with DBT was 3.31 (1-5 scale). The most-cited DBT advantages were decreased recall rate (55.8%), increased lesion conspicuity (48.3%), and increased cancer detection (45.8%). The most-cited DBT disadvantages were extra cost for patients (46.7%), insufficient calcification characterization (43.3%), insufficient improvement in diagnostic performance (39.2%), and radiation dose (35.8%). Radiologists reported increased storage requirements and interpretation time for barriers to implementing DBT.

Conclusion

Further improvement of DBT techniques reflecting feedback from the user's perspective will help increase the acceptance of DBT in Korea.

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.

Automatic Classification of Simulated Breast Tomosynthesis Whole Images for the Presence of Microcalcification Clusters Using Deep CNNs

Microcalcification clusters (MCs) are among the most important biomarkers for breast cancer, especially in cases of nonpalpable lesions. The vast majority of deep learning studies on digital breast tomosynthesis (DBT) are focused on detecting and classifying lesions, especially soft-tissue lesions, in small regions of interest previously selected. Only about 25% of the studies are specific to MCs, and all of them are based on the classification of small preselected regions. Classifying the whole image according to the presence or absence of MCs is a difficult task due to the size of MCs and all the information present in an entire image. A completely automatic and direct classification, which receives the entire image, without prior identification of any regions, is crucial for the usefulness of these techniques in a real clinical and screening environment. The main purpose of this work is to implement and evaluate the performance of convolutional neural networks (CNNs) regarding an automatic classification of a complete DBT image for the presence or absence of MCs (without any prior identification of regions). In this work, four popular deep CNNs are trained and compared with a new architecture proposed by us. The main task of these trainings was the classification of DBT cases by absence or presence of MCs. A public database of realistic simulated data was used, and the whole DBT image was taken into account as input. DBT data were considered without and with preprocessing (to study the impact of noise reduction and contrast enhancement methods on the evaluation of MCs with CNNs). The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance. Very promising results were achieved with a maximum AUC of 94.19% for the GoogLeNet. The second-best AUC value was obtained with a new implemented network, CNN-a, with 91.17%. This CNN had the particularity of also being the fastest, thus becoming a very interesting model to be considered in other studies. With this work, encouraging outcomes were achieved in this regard, obtaining similar results to other studies for the detection of larger lesions such as masses. Moreover, given the difficulty of visualizing the MCs, which are often spread over several slices, this work may have an important impact on the clinical analysis of DBT images.

Risk-Associated Lesions of the Breast in Core Needle Biopsies: Current Approaches to Radiological-Pathological Correlation

Image-guided core needle biopsies (CNBs) of the breast frequently result in a diagnosis of a benign or atypical lesion associated with breast cancer risk. The subsequent clinical management of these patients is variable, reflecting a lack of consensus on criteria for selecting patients for clinical and radiological follow-up versus immediate surgical excision. In this review, the evidence from prospective studies of breast CNB with radiological-pathological correlation is evaluated and summarized. The data support an emerging consensus on the importance of radiologic-pathologic correlation in standardizing the selection of patients for active surveillance versus surgery.

Effect of Dose Level on Radiologists' Detection of Microcalcifications in Digital Breast Tomosynthesis: An Observer Study with Breast Phantoms

OBJECTIVES

To compare radiologists' sensitivity, confidence level, and reading efficiency of detecting microcalcifications in digital breast tomosynthesis (DBT) at two clinically relevant dose levels.

MATERIALS AND METHODS

Six 5-cm-thick heterogeneous breast phantoms embedded with a total of 144 simulated microcalcification clusters of four speck sizes were imaged at two dose modes by a clinical DBT system. The DBT volumes at the two dose levels were read independently by six MQSA radiologists and one fellow with 1-33 years (median 12 years) of experience in a fully-crossed counter-balanced manner. The radiologist located each potential cluster and rated its conspicuity and his/her confidence that the marked location contained a cluster. The differences in the results between the two dose modes were analyzed by two-tailed paired t-test.

RESULTS

Compared to the lower-dose mode, the average glandular dose in the higher-dose mode for the 5-cm phantoms increased from 1.34 to 2.07 mGy. The detection sensitivity increased for all speck sizes and significantly for the two smaller sizes (p <0.05). An average of 13.8% fewer false positive clusters was marked. The average conspicuity rating and the radiologists' confidence level were higher for all speck sizes and reached significance (p <0.05) for the three larger sizes. The average reading time per detected cluster reduced significantly (p <0.05) by an average of 13.2%.

CONCLUSION

For a 5-cm-thick breast, an increase in average glandular dose from 1.34 to 2.07 mGy for DBT imaging increased the conspicuity of microcalcifications, improved the detection sensitivity by radiologists, increased their confidence levels, reduced false positive detections, and increased the reading efficiency.

Pathological outcome of sonographically occult architectural distortions (AD) visible only on digital breast tomosynthesis, and comparison with AD visible also on 2D mammography

PURPOSE

To evaluate the rates of malignant and of high-risk lesions among sonographically occult architectural distortions (AD) visible only on digital breast tomosynthesis (DBT) and compare them with AD visible on 2D mammography (2D) and DBT.

METHOD

The records of 1104 DBT-vacuum assisted biopsies (DBT-VAB) were retrospectively reviewed and 218 cases of AD were identified. Complete radiologic examinations and pathologic results were available for 113 sonographically occult AD (1 clinically-detected, 112 clinically-occult). 2D and DBT images were reviewed and AD were divided into a "DBT-detected" group (visible on only DBT) and a "2D-detected" group (visible both in 2D and DBT). The rates of malignant and of high-risk lesions in the "DBT-detected" AD group were calculated and compared to those of the "2D-detected" AD group.

RESULTS

Thirty-five (31%) of 113 AD were assessed as "DBT-detected", while 78 (69%) as "2D-detected". DBT-VAB results were benign lesions in 63 (56%) AD, high-risk lesions in 32 (28%) AD and malignant lesions in 18 (16%) AD. Four (12.5%) high-risk lesions were upgraded to malignancy at surgery. Based on final pathology, the malignancy rate was significantly higher in the "DBT-detected" group than the "2D-detected" group (34% [12/35 cases] vs 13% [10/78]; p < 0.05). The high-risk lesion rates were 32% (11/35 cases) in the "DBT-detected" group and 22% (17/78 cases) in the "2D-detected" group (p > 0.05).

CONCLUSIONS

AD visible on only DBT proved to be malignant in about one third of cases, which exceeded the malignancy rate of AD visible on also 2D. A similar proportion of DBT-only AD was represented by high-risk lesions.

Three-dimensional tomosynthesis versus two-dimensional mammography in detection and characterization of different breast lesions

Background

Breast cancer is considered the most serious lesion among different breast lesions. Mammography is the corner stone for screening for detection of breast cancer. It has been modified to digital mammography (DM) and then to digital breast tomosynthesis (DBT). Tomosynthesis is an emerging technique for diagnosis and screening of breast lesions.

The aim of this study is to interrogate whether the addition of DBT to DM helps in better detection and characterization of different breast lesions.

Methods

This is a prospective study carried on 38 female patients according to our inclusion criteria. All patients were evaluated by using DM alone and thereafter with the addition of DBT to DM. Recall rate was calculated, and the imaging findings of each case were correlated with the final diagnosis and follow-up.

Results

DM identified 32 lesions while DBT with DM identified 37 lesions. On DM alone, 17 lesions were characterized as masses, 5 as focal asymmetry, 2 as architectural distortion, 7 as microcalcification and 1 as macrocalcification. With the addition of DBT, 27 lesions were characterized as masses, 1 as focal asymmetry, 1 as architectural distortion, 7 as microcalcification and 1 as macrocalcification. So, there were better detection and characterization of lesions with the addition of DBT than DM alone. The sensitivity, specificity, AUC, positive and negative predictive values were significantly higher with the addition of DBT to DM (100%, 90.5%, 0.952, 90% and 100%, respectively) than with DM (77.8%, 80.9%, 0.794, 77.8% and 80.9%, respectively) for all breast lesions.

Conclusions

The addition of DBT to DM helps in better detection and characterization of different breast lesions. This leads to early detection of breast cancer, improvement of the performance of radiologists and saving time by reduction of recall rate.

Do automated breast ultrasound and tomosynthesis have an effective role in dense breast evaluation?

Background

Mammography plays a great role in reducing breast cancer mortality as it is the standard method of breast imaging and screening. But the accuracy of mammography performance reduces in cancer detection in women with dense breast due to the summation of images and overlapping of breast tissue. ABUS and tomosynthesis both recently help to detect breast cancer in dense breasted women. This prospective study was done in the female imaging unit and approved by its research and ethical committee; all the patients did an informed consent during the period from October 2018 to March 2019. The study was conducted on 38 patients with 38 lesions subjected to digital mammography, tomosynthesis and automated breast ultrasound (ABUS), who all had dense breast in mammography.

Results

Automated breast ultrasound (ABUS) showed 100% in all sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV) as well as accuracy, while the digital mammography tomosynthesis showed 100% in specificity, 87.5% in sensitivity, 100% in PPV, 82.4% in NPV and 92.1% accuracy.

Conclusion

Automated breast ultrasound (ABUS) together with tomosynthesis makes a revolution in breast screening and detecting cancer in women with dense breasts.

SCREENING MAMMOGRAPHY: DIAGNOSTIC EFFICACY-ISSUES AND CONSIDERATIONS FOR THE 2020S

Diagnostic efficacy in medical imaging is ultimately a reflection of radiologist performance. This can be influenced by numerous factors, some of which are patient related, such as the physical size and density of the breast, and machine related, where some lesions are difficult to visualise on traditional imaging techniques. Other factors are human reader errors that occur during the diagnostic process, which relate to reader experience and their perceptual and cognitive oversights. Given the large-scale nature of breast cancer screening, even small increases in diagnostic performance equate to large numbers of women saved. It is important to identify the causes of diagnostic errors and how detection efficacy can be improved. This narrative review will therefore explore the various factors that influence mammographic performance and the potential solutions used in an attempt to ameliorate the errors made.

The development of breast radiology: the Acta Radiologica perspective

The encouraging results of modern breast cancer care builds on tremendous improvements in diagnostics and therapy during the 20th century. Scandinavian countries have made important footprints in the development of breast diagnostics regarding technical development of imaging, cell and tissue sampling methods and, not least, population screening with mammography. The multimodality approach in combination with multidisciplinary clinical work in breast cancer serve as a role model for the management of many cancer types worldwide. The development of breast radiology is well represented in the research published in this journal and this historical review will describe the most important steps.

Architectural distortion outcome: digital breast tomosynthesis-detected versus digital mammography-detected

OBJECTIVES

To compare the outcome for DBT-detected and DM-detected suspicious AD, to evaluate the risk of malignancy and if is affected by the US or MRI imaging correlation.

METHODS

All cases with suspicious AD (ultimately assigned BI-RADS 4 or 5 categories) were retrospectively included. Two radiologists independently reviewed DM and DBT images in two sessions for detection (DM vs. DBT). US and MRI imaging correlation findings were recorded. Pathologic results were compared between DBT-detected and DM-detected AD.

RESULTS

Among 137 detected ADs, 103 (75.2%) were DM-detected, and 34 (24.8%) were only DBT-detected (p = 0.01). The malignancy rate was lower for DBT-detected than DM-detected AD (14.7% vs. 45.6%) (p = 0.01). Malignancy rate was higher with US-positive than US-negative correlation at DM-detected AD (49.4% vs. 27.8%) (p = 0.01). Malignancy rate was not different for DBT-detected AD with (16.7%) or without (12.5%) sonographic correlation. NPV based on radiologists' level of suspicion was high (86.2%-97.2%) but not sufficient enough to forgo biopsy. Of 34 sonographically occult ADs, a positive-MRI correlation was identified in 19 (55.9%) ADs (7 were malignant, 12 were benign). A negative-MRI correlation was identified in 15 (44.1%) ADs; all had a benign outcome (p = 0.01).

CONCLUSIONS

DBT-detected AD is less likely to represent malignancy than does DM-detected; however, the risk of malignancy is not low enough to forgo biopsy. MRI-negative correlation in sonographically occult AD was significantly associated with benign outcomes and can avoid unnecessary interventions.

Comparing the diagnostic efficacy of full field digital mammography with digital breast tomosynthesis using BIRADS score in a tertiary cancer care hospital

Introduction

Breast cancer is one of the leading cancers in females worldwide, and its incidence has been rising at an exponential pace in the last 10 years even in India. Mammography has been the mainstay for detection of breast cancer over decades and has gradually advanced from screen film to full-field digital mammography. Recently, tomosynthesis has evolved as an advanced imaging investigation for early diagnosis of breast lesions in both diagnostic and screening settings.

Aim of Study

To compare and evaluate the impact of digital breast tomosynthesis (DBT) compared to full-field digital mammography (FFDM) in the interpretation of BIRADS score in both diagnostic and screening settings.

Settings and Design

A 1-year prospective longitudinal study was conducted in the Department of Radio-diagnosis in our institute using Hologic Selenia Dimensions for mammography as well as tomosynthesis.

Materials and Methods

One hundred women known or suspected (opportunistic screening) for breast cancer were evaluated either with FFDM alone or both FFDM and DBT. Sensitivity, specificity, positive predictive value, negative predictive value, and P value were used to assess the various diagnostic criteria in our study.

Results

Addition of DBT to FFDM results in a statistically significant increase in the sensitivity, specificity, and positive predictive value, and a statistically significant decrease in the false positive rates. Similar results were noted in both diagnostic and screening cases. It was observed that, in most cases, i.e. a total of 47, DBT did not change the BIRADS scoring; however, its addition increased the diagnostic confidence. BIRADS was upgraded and downgraded in 14 and 31 cases, respectively, with the addition of DBT to FFDM. New lesions were seen with addition of DBT to FFDM in 8 cases.

Conclusion

Addition of DBT to FFDM results in increase in sensitivity, specificity, positive predictive value, and a statistically significant decrease in false positive rates in both diagnostic and screening cases. As addition of tomosynthesis results in a significant decrease in recall rate, it should be added, at least, in all screening mammography programs.

Detection of Microcalcifications in Spiral Breast Computed Tomography with Photon-Counting Detector Is Feasible: A Specimen Study

The primary objective of the study was to compare a spiral breast computed tomography system (SBCT) to digital breast tomosynthesis (DBT) for the detection of microcalcifications (MCs) in breast specimens. The secondary objective was to compare various reconstruction modes in SBCT. In total, 54 breast biopsy specimens were examined with mammography as a standard reference, with DBT, and with a dedicated SBCT containing a photon-counting detector. Three different reconstruction modes were applied for SBCT datasets (Recon1 = voxel size (0.15 mm)³, smooth kernel; Recon2 = voxel size (0.05 mm)³, smooth kernel; Recon3 = voxel size (0.05 mm)³, sharp kernel). Sensitivity and specificity of DBT and SBCT for the detection of suspicious MCs were analyzed, and the McNemar test was used for comparisons. Diagnostic confidence of the two readers (Likert Scale 1 = not confident; 5 = completely confident) was analyzed with ANOVA. Regarding detection of MCs, reader 1 had a higher sensitivity for DBT (94.3%) and Recon2 (94.9%) compared to Recon1 (88.5%; p < 0.05), while sensitivity for Recon3 was 92.4%. Respectively, reader 2 had a higher sensitivity for DBT (93.0%), Recon2 (92.4%), and Recon3 (93.0%) compared to Recon1 (86.0%; p < 0.05). Specificities ranged from 84.7–94.9% for both readers (p > 0.05). The diagnostic confidence of reader 1 was better with SBCT than with DBT (DBT 4.48 ± 0.88, Recon1 4.77 ± 0.66, Recon2 4.89 ± 0.44, and Recon3 4.75 ± 0.72; DBT vs. Recon1/2/3: p < 0.05), while reader 2 found no differences. Sensitivity and specificity for the detection of MCs in breast specimens is equal for DBT and SBCT when a small voxel size of (0.05 mm)³ is used with an equal or better diagnostic confidence for SBCT compared to DBT.

Foveated Model Observers for Visual Search in 3D Medical Images

Model observers have a long history of success in predicting human observer performance in clinically-relevant detection tasks. New 3D image modalities provide more signal information but vastly increase the search space to be scrutinized. Here, we compared standard linear model observers (ideal observers, non-pre-whitening matched filter with eye filter, and various versions of Channelized Hotelling models) to human performance searching in 3D 1/f2.8 filtered noise images and assessed its relationship to the more traditional location known exactly detection tasks and 2D search. We investigated two different signal types that vary in their detectability away from the point of fixation (visual periphery). We show that the influence of 3D search on human performance interacts with the signal's detectability in the visual periphery. Detection performance for signals difficult to detect in the visual periphery deteriorates greatly in 3D search but not in 3D location known exactly and 2D search. Standard model observers do not predict the interaction between 3D search and signal type. A proposed extension of the Channelized Hotelling model (foveated search model) that processes the image with reduced spatial detail away from the point of fixation, explores the image through eye movements, and scrolls across slices can successfully predict the interaction observed in humans and also the types of errors in 3D search. Together, the findings highlight the need for foveated model observers for image quality evaluation with 3D search.

A Model-Based Optimization Framework for Iterative Digital Breast Tomosynthesis Image Reconstruction

Digital Breast Tomosynthesis is an X-ray imaging technique that allows a volumetric reconstruction of the breast, from a small number of low-dose two-dimensional projections. Although it is already used in the clinical setting, enhancing the quality of the recovered images is still a subject of research. The aim of this paper was to propose and compare, in a general optimization framework, three slightly different models and corresponding accurate iterative algorithms for Digital Breast Tomosynthesis image reconstruction, characterized by a convergent behavior. The suggested model-based implementations are specifically aligned to Digital Breast Tomosynthesis clinical requirements and take advantage of a Total Variation regularizer. We also tune a fully-automatic strategy to set a proper regularization parameter. We assess our proposals on real data, acquired from a breast accreditation phantom and a clinical case. The results confirm the effectiveness of the presented framework in reconstructing breast volumes, with particular focus on the masses and microcalcifications, in few iterations and in enhancing the image quality in a prolonged execution.

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

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

Mammographic tumour appearance is related to clinicopathological factors and surrogate molecular breast cancer subtype

Mammographic tumour appearance may provide prognostic useful information. For example, spiculation indicates invasiveness, but also better survival compared to tumours with other appearances. We aimed to study the relationship between mammographic tumour appearance and established clinicopathological factors, including surrogate molecular breast cancer subtypes, in the large Malmö Diet and Cancer Study. A total of 1116 women with invasive breast cancer, diagnosed between 1991 and 2014, were included. Mammographic tumour appearance in relation to status for oestrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2, histological grade, Ki67 and molecular subtype was analysed using various regression models. All models were adjusted for relevant confounders, including breast density, which can affect mammographic appearance. The results consistently showed that spiculated tumours are indicative of favourable characteristics, as they are more likely to be ER and PR positive, and more often exhibit lower histological grade and lower Ki67 expression. Furthermore, spiculated tumours tend to be of luminal A-like subtype, which is associated with a good prognosis. The establishment of associations between mammographic tumour appearance and clinico­pathological factors may aid in characterizing breast cancer at an earlier stage. This could contribute to more individualized breast cancer treatment in the future.

Digital Breast Tomosynthesis Versus Additional Diagnostic Mammographic Views for the Evaluation of Asymmetric Mammographic Densities

Introduction Many young females present with an advanced stage of breast cancer, which has a negative effect on the prognosis. Digital breast tomosynthesis is a new emerging imaging technique that aids in improving the specificity of mammography with subsequent early detection of breast cancer, especially in women with radiographically dense breasts. Tomosynthesis is subjectively preferred to conventional mammography and may offer superior diagnostic accuracy for the evaluation of breast lesions. Method Two breast radiologists retrospectively reviewed asymmetric densities using protocols that were institutional review board-approved in 185 patients aged 18 - 70 years (mean: 48 years) who underwent diagnostic mammography and tomosynthesis. Each asymmetric density was interpreted once with tomosynthesis and once with supplemental mammographic views; both modes included the mediolateral oblique and craniocaudal views in a fully crossed and balanced design by using a five-category Breast Imaging Reporting and Data System (BI-RADS) assessment and a probability-of-malignancy score. If the abnormality persisted and appeared benign or completely disappeared on both modalities, the agreement between additional views and tomosynthesis was determined by calculating Kappa value. If there was a discrepancy between additional views and tomosynthesis, the abnormality was subjected to ultrasound. In our study, 89 asymmetric densities were subjected to ultrasound. Results In a total of 182 cases, 84 (46.15%) were categorized as BIRADS-0; 97 (53.30 %) as BIRADS-I, and one (0.55 %) as BIRADS-II on an additional view. Among the asymmetric densities categorized as BIRADS-0 on additional mammography views, digital breast tomosynthesis categorized 72, six, five, and one patient as BIRADS-0, BIRADS-I, BIRADS-II, and BIRADS-IV, respectively. For densities categorized as BIRADS-I (97) on additional view, digital breast tomosynthesis categorized 10 and 87 densities as BIRADS-0 and BIRADS-I, respectively. No change in the BIRADS category was observed among BIRADS-II and BIRADS-IV. A significant difference was observed with the chi-square test among BIRADS categories assigned by an additional view and digital breast tomosynthesis with a p-value of < 0.001. There was, however, a substantial agreement among additional views and tomosynthesis with a kappa value of 0.767. Conclusion Our study results suggest that tomosynthesis may be equivalent to, if not more equivalent to, additional imaging in the assessment of mammographically-detected asymmetric densities, thus improving BI-RADS classification and patient management.

The added value of digital breast tomosynthesis in improving diagnostic performance of BI-RADS categorization of mammographically indeterminate breast lesions

Background

Mammographic findings are seen more clearly in tomographic images with consequent improvement of Breast Imaging Reporting and Data System (BI-RADS) in categorization of indeterminate breast lesions. This study aimed to evaluate the added value of digital breast tomosynthesis (DBT) to BI-RADS classification in categorization of indeterminate breast lesions after digital mammography (DM) as an initial approach.

Methods and results

We prospectively evaluated 296 women with BI-RADS indeterminate breast lesions (BI-RADS 0, 3, and 4) by DM between January 2018 and October 2019. All patients underwent DBT. Two radiologists evaluated lesions and assigned a BI-RADS category to each lesion according to BI-RADS lexicon 2013 classification using DM, DBT, and combined DM and DBT. The results were compared in terms of main radiological features, diagnostic performance, and BI-RADS classification using histopathology as the reference standard. A total of 355 lesions were detected on DBT and 318 lesions on DM. Thirty-seven lesions were detected by DBT and not seen by DM. The final diagnoses of 355 lesions were 58.3% benign and 41.7% malignant. In comparison to DM, DBT produced 31.5% upgrading and 35.2% downgrading of BI-RADS scoring of breast lesions. DBT reduced number of BI-RADS 3 and 4, compared to DM. All upgraded BI-RADS 4 were malignant. The combination of DBT and DM significantly increased the performance of BI-RADS in the diagnosis of indeterminate breast lesions versus DM or DBT alone (p < 0.001).

Conclusion

Adding DBT to BI-RADS improves its diagnostic performance in detection and characterization of mammography indeterminate breast lesions.

Digital Mammography Stereotactic Biopsy versus Digital Breast Tomosynthesis-guided Biopsy: Differences in Biopsy Targets, Pathologic Results, and Discordance Rates

Background Digital breast tomosynthesis (DBT)-guided biopsy is increasingly used in practice. It is important to know expected changes in biopsy targets, pathologic results, and discordance rates. Purpose To compare biopsy target types, pathologic results, and discordance rates for 2 years preceding and 2 years following implementation of DBT-guided biopsy. Materials and Methods All 9-gauge vacuum-assisted core biopsies from a single tertiary breast center that used digital mammography (DM) stereotactic guidance from 2013 to 2015 and DBT-guided biopsy from 2015 to 2017 were retrospectively reviewed. All mammographic examinations were performed with DBT. Patient demographics, biopsy target type, pathologic reports, surgical excision specimens when available, breast density, and imaging follow-up results were recorded. Biopsy targets and discordance rates between radiologic and pathologic examinations were compared between the two biopsy groups. Generalized mixed modeling was used to examine results before and after DBT-guided biopsy. Results A total of 1313 women underwent 1405 breast biopsies: 643 by using DM (August 2013 to July 2015) (median age, 56 years; interquartile range, 49-66 years) and 762 by using DBT (August 2015 to July 2017) (median age, 58 years; interquartile range, 50-67 years), (P = .58). Calcifications were the most common biopsy target for both groups, constituting 89.9% (578 of 643) of DM-guided biopsies and 71.1% (542 of 762) of DBT-guided biopsies (P = .03). The rate of architectural distortion biopsies was 2.0% (13 of 643) with DM-guided biopsy and 17.7% (135 of 762) with DBT-guided biopsy (P = .01). Although overall malignancy rate was similar for DM-guided biopsy (27.8% [179 of 643]) and DBT-guided biopsy (24.8% [191 of 762], P = .54), DBT-guided biopsy helped identify a similar percentage of invasive malignancies (37.4% [72 of 191] vs 29.0% [52 of 179] at DM P = .35), but more radial sclerosing lesions (8.3% [95% confidence interval {CI}: 6.0, 10.0] vs 1.7% [95% CI: 1.0, 3.1]) (P = .01). The discordance rate was 1.4% (95% CI: 1.0, 2.7) with DM-guided biopsy and 4.5% (95% CI: 3.2, 6.3) with DBT-guided biopsy (P = .01). Of the 34 discordant DBT-guided biopsies, 30 were architectural distortions. Conclusion With the transition to digital breast tomosynthesis-guided biopsy, more architectural distortions were biopsied, more radial sclerosing lesions were identified, and more discordance existed in radiologic and pathologic examinations, with a similar percentage of carcinomas diagnosed. © RSNA, 2020 Online supplemental material is available for this article.

GPU acceleration of a model-based iterative method for Digital Breast Tomosynthesis

Digital Breast Tomosynthesis (DBT) is a modern 3D Computed Tomography X-ray technique for the early detection of breast tumors, which is receiving growing interest in the medical and scientific community. Since DBT performs incomplete sampling of data, the image reconstruction approaches based on iterative methods are preferable to the classical analytic techniques, such as the Filtered Back Projection algorithm, providing fewer artifacts. In this work, we consider a Model-Based Iterative Reconstruction (MBIR) method well suited to describe the DBT data acquisition process and to include prior information on the reconstructed image. We propose a gradient-based solver named Scaled Gradient Projection (SGP) for the solution of the constrained optimization problem arising in the considered MBIR method. Even if the SGP algorithm exhibits fast convergence, the time required on a serial computer for the reconstruction of a real DBT data set is too long for the clinical needs. In this paper we propose a parallel SGP version designed to perform the most expensive computations of each iteration on Graphics Processing Unit (GPU). We apply the proposed parallel approach on three different GPU boards, with computational performance comparable with that of the boards usually installed in commercial DBT systems. The numerical results show that the proposed GPU-based MBIR method provides accurate reconstructions in a time suitable for clinical trials.

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.

What do we know about volumetric medical image interpretation?: a review of the basic science and medical image perception literatures

Interpretation of volumetric medical images represents a rapidly growing proportion of the workload in radiology. However, relatively little is known about the strategies that best guide search behavior when looking for abnormalities in volumetric images. Although there is extensive literature on two-dimensional medical image perception, it is an open question whether the conclusions drawn from these images can be generalized to volumetric images. Importantly, volumetric images have distinct characteristics (e.g., scrolling through depth, smooth-pursuit eye-movements, motion onset cues, etc.) that should be considered in future research. In this manuscript, we will review the literature on medical image perception and discuss relevant findings from basic science that can be used to generate predictions about expertise in volumetric image interpretation. By better understanding search through volumetric images, we may be able to identify common sources of error, characterize the optimal strategies for searching through depth, or develop new training and assessment techniques for radiology residents.

Digital Breast Tomosynthesis: Concepts and Clinical Practice

Digital breast tomosynthesis (DBT) is emerging as the standard of care for breast imaging based on improvements in both screening and diagnostic imaging outcomes. The additional information obtained from the tomosynthesis acquisition decreases the confounding effect of overlapping tissue, allowing for improved lesion detection, characterization, and localization. In addition, the quasi three-dimensional information obtained from the reconstructed DBT data set allows a more efficient imaging work-up than imaging with two-dimensional full-field digital mammography alone. Herein, the authors review the benefits of DBT imaging in screening and diagnostic breast imaging.

Can Digital Breast Tomosynthesis Replace Full-Field Digital Mammography? A Multireader, Multicase Study of Wide-Angle Tomosynthesis

OBJECTIVE. The purpose of this study was to test the hypothesis whether two-view wide-angle digital breast tomosynthesis (DBT) can replace full-field digital mammography (FFDM) for breast cancer detection. SUBJECTS AND METHODS. In a multireader multicase study, bilateral two-view FFDM and bilateral two-view wide-angle DBT images were independently viewed for breast cancer detection in two reading sessions separated by more than 1 month. From a pool of 764 patients undergoing screening and diagnostic mammography, 330 patient-cases were selected. The endpoints were the mean ROC AUC for the reader per breast (breast level), ROC AUC per patient (subject level), noncancer recall rates, sensitivity, and specificity. RESULTS. Twenty-nine of 31 readers performed better with DBT than FFDM regardless of breast density. There was a statistically significant improvement in readers' mean diagnostic accuracy with DBT. The subject-level AUC increased from 0.765 (standard error [SE], 0.027) for FFDM to 0.835 (SE, 0.027) for DBT (p = 0.002). Breast-level AUC increased from 0.818 (SE, 0.019) for FFDM to 0.861 (SE, 0.019) for DBT (p = 0.011). The noncancer recall rate per patient was reduced by 19% with DBT (p < 0.001). Masses and architectural distortions were detected more with DBT (p < 0.001); calcifications trended lower (p = 0.136). Accuracy for detection of invasive cancers was significantly greater with DBT (p < 0.001). CONCLUSION. Reader performance in breast cancer detection is significantly higher with wide-angle two-view DBT independent of FFDM, verifying the robustness of DBT as a sole view. However, results of perception studies in the vision sciences support the inclusion of an overview image.

Transfer Learning From Convolutional Neural Networks for Computer-Aided Diagnosis: A Comparison of Digital Breast Tomosynthesis and Full-Field Digital Mammography

RATIONALE AND OBJECTIVES

With the growing adoption of digital breast tomosynthesis (DBT) in breast cancer screening, we compare the performance of deep learning computer-aided diagnosis on DBT images to that of conventional full-field digital mammography (FFDM).

MATERIALS AND METHODS

In this study, we retrospectively collected FFDM and DBT images of 78 biopsy-proven lesions from 76 patients. A region of interest was selected for each lesion on FFDM, synthesized 2D, and DBT key slice images. Features were extracted from each lesion using a pretrained convolutional neural network (CNN) and served as input to a support vector machine classifier trained in the task of predicting likelihood of malignancy.

RESULTS

From receiver operating characteristic (ROC) analysis of all 78 lesions, the synthesized 2D image performed best in both the cradiocaudal view (area under the ROC curve [AUC] = 0.81, SE = 0.05) and mediolateral oblique view (AUC = 0.88, SE = 0.04) in the task of lesion characterization. When cradiocaudal and mediolateral oblique data of each lesion were merged through soft voting, DBT key slice image performed best (AUC = 0.89, SE = 0.04). When only masses and architectural distortions (ARDs) were considered, DBT performed significantly better than FFDM (p = 0.024).

CONCLUSION

DBT performed significantly better than FFDM in the merged view classification of mass and ARD lesions. The increased performance suggests that the information extracted by the CNN from DBT images may be more relevant to lesion malignancy status than the information extracted from FFDM images. Therefore, this study provides supporting evidence for the efficacy of computer-aided diagnosis on DBT in the evaluation of mass and ARD lesions.

Breast Cancer Conspicuity on Simultaneously Acquired Digital Mammographic Images versus Digital Breast Tomosynthesis Images

Background Digital breast tomosynthesis (DBT) has been shown to improve screening outcomes compared with digital mammography (DM) alone. However, little is known about differences in breast cancer conspicuity between DM and DBT or by mammographic view. Purpose To compare conspicuity of breast cancers at DM versus DBT and by mammographic view, craniocaudal (CC) versus mediolateral oblique (MLO). Materials and Methods Lesion conspicuity was graded by three readers by using a 0-5 numerical scale on both DM and DBT images from combined DM and DBT studies for 197 consecutive screening-detected cancers in women (mean age, 60.4 years ± 11.1 [standard deviation]) from October 1, 2011, through December 31, 2014. Intermodality (ie, DM vs DBT) and intramodality (ie, CC vs MLO) analyses were performed. For intramodality analyses, conspicuity was analyzed by view, CC versus MLO, within the same modality. Conspicuity grades were dichotomized into low (scores 0-3) and high (scores 4 and 5) conspicuity. This binary result was assessed by using a generalized linear mixed-effects model with logit link function, random-effect intercept for reader, and compound symmetry covariance structure for lesion. Results Cancers were more likely to be high conspicuity at DBT than at DM (odds ratio [OR], 2.4; 95% confidence interval [CI]: 1.9, 3.0; P < .01). At both DM and DBT, cancers were more likely to be high conspicuity at the CC than the MLO view (DM vs DBT OR, 1.6 [95% CI: 1.3, 1.9] vs 1.7 [95% CI: 1.3, 2.1], respectively; P < .01 for both). Cancers seen at one view only were more often detected at CC than MLO for both DM and DBT (DM vs DBT OR, 1.6 [95% CI: 1.2, 2.0] vs 3.6 [95% CI: 1.9, 7.0], respectively; P < .01.). Conclusion Cancers were more conspicuous at digital breast tomosynthesis than at digital mammography. Cancers may only be detected at one of two views, and they are more likely to be seen at the craniocaudal view. © RSNA, 2019.

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.

Breast tomosynthesis: state of the art

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

Multi-domain features for reducing false positives in automated detection of clustered microcalcifications in digital breast tomosynthesis

PURPOSE

In digital breast tomosynthesis (DBT) imaging, a microcalcification (MC) cluster may span across different slices and blurring exists in the out-of-focus slices. We developed a radiomics approach to extract features from focus slice and combine multiple spatial domains to reduce false positives (FPs) in an automated pipeline of detecting MC clusters.

METHODS

We performed a retrospective study on a cohort of 290 Chinese women patients with a total of 580 DBT volumes. We developed an automated MC detection pipeline that consists of two stages: an initial detection to identify a set of MC candidates that may include many FPs, followed by a radiomics-based classification model to identify and reduce the FPs. We extract both two-dimensional (2D) and three-dimensional (3D) radiomics features from multiple spatial domains, including a focus slice, projection image, and tomographic volume. A linear discriminant classifier was used coupled with a sequential forward feature selection procedure. The free-response operating characteristics (FROC) curve and partial area under the FROC curve (pAUC) in the FP rate range of 0 to 2 per DBT volume were used to evaluate the model's performance.

RESULTS

At a sensitivity of 90%, the FP rate was reduced from 1.3 to 0.2 per DBT volume after applying the multi-domain-based classification on the initial detections. The multi-domain yielded a significantly higher pAUC compared to the initial detection (increase of pAUC = 0.2278, P < 0.0001), focus slice (increase of pAUC = 0.0345, P = 0.0152), project image (increase of pAUC = 0.1043, P < 0.0001), and tomographic volume (increase of pAUC = 0.0791, P = 0.0032).

CONCLUSION

The radiomic features extracted from the three domains may provide complementary information and their integration can significantly reduce FPs in automated detection of MCs in DBT volumes on a large Chinese women population.

Synthesizing mammogram from digital breast tomosynthesis

The purpose of this study is to develop a new method for generating synthesized mammogram (SM) from digital breast tomosynthesis (DBT) and to assess its potential as an adjunct to DBT. We first applied multiscale bilateral filtering to the reconstructed DBT slices to enhance the high-frequency features and reduce noise. A maximum intensity projection (MIP) image was then obtained from the high-frequency components of the DBT slices. A multiscale image fusion method was designed to combine the MIP image and the central DBT projection view into an SM and further enhance the high-frequency features. We conducted a pilot reader study to visually assess the image quality of SM in comparison to full field digital mammograms (FFDM). For each DBT craniocaudal or mediolateral view, a clinical FFDM of the corresponding view was retrospectively collected. Three MQSA radiologists, blinded to the pathological and other clinical information, independently interpreted the SM and the corresponding FFDM side by side marked with the lesion locations. The differences in the BI-RADS assessments of both MCs and masses between SM and FFDM did not achieve statistical significance for all three readers. The conspicuity of MCs on SM was superior to that on FFDM and the BI-RADS assessments of MCs were comparable while the conspicuity of masses on SM was degraded and interpretation on SM was less accurate than that on FFDM. The SM may be useful for efficient prescreening of MCs in DBT but the DBT should be used for detection and characterization of masses.

Comparison of Digital Breast Tomosynthesis and Digital Mammography for Detection of Breast Cancer in Kuwaiti Women

OBJECTIVE

To investigate the sensitivity and specificity of digital mammography (DM) and digital breast tomosynthesis (DBT) for the detection of breast cancer in comparison to histopathology findings.

SUBJECTS AND METHODS

We included 65 breast lesions in 58 women, each detected by two diagnostic mammography techniques - DM and DBT using Senographe Essential (GE Healthcare, Buc, France) - and subsequently confirmed by histopathology. The Breast Imaging Reporting and Data System was used for characterizing the lesions.

RESULTS

The average age of women was 48.3 years (range 26-81 years). There were 34 malignant and 31 benign breast lesions. The sensitivity of DM and DBT was 73.5 and 100%, respectively, while the specificity was 67.7 and 94%, respectively. Receiver operating characteristic curve analysis showed an overall diagnostic advantage of DBT over DM, with a significant difference between DBT and DM (p < 0.001). By performing Cohen's kappa test, we found that there was a strong level of agreement according to Altman guidelines between DBT and histopathology findings (0.97), but a weak agreement between DM and histopathology findings (0.47).

CONCLUSION

DBT improves the clinical accuracy of mammography by increasing both sensitivity and specificity. We believe that this improvement is due to improved image visibility and quality. These results could be of interest to health care institutions as they may impact their decision on whether to upgrade to DBT not only for diagnosis, but also for screening.

Factors Affecting Breast Cancer Detectability on Digital Breast Tomosynthesis and Two-Dimensional Digital Mammography in Patients with Dense Breasts

Objective

To compare digital breast tomosynthesis (DBT) and conventional full-field digital mammography (FFDM) in the detectability of breast cancers in patients with dense breast tissue, and to determine the influencing factors in the detection of breast cancers using the two techniques.

Materials and Methods

Three blinded radiologists independently graded cancer detectability of 300 breast cancers (288 women with dense breasts) on DBT and conventional FFDM images, retrospectively. Hormone status, histologic grade, T stage, and breast cancer subtype were recorded to identify factors affecting cancer detectability. The Wilcoxon signed-rank test was used to compare cancer detectability by DBT and conventional FFDM. Fisher's exact tests were used to determine differences in cancer characteristics between detectability groups. Kruskal-Wallis tests were used to determine whether the detectability score differed according to cancer characteristics.

Results

Forty breast cancers (13.3%) were detectable only with DBT; 191 (63.7%) breast cancers were detected with both FFDM and DBT, and 69 (23%) were not detected with either. Cancer detectability scores were significantly higher for DBT than for conventional FFDM (median score, 6; range, 0–6; p < 0.001). The DBT-only cancer group had more invasive lobular-type breast cancers (22.5%) than the other two groups (i.e., cancer detected on both types of image [both-detected group], 5.2%; cancer not detected on either type of image [both-non-detected group], 7.3%), and less detectability of ductal carcinoma in situ (5% vs. 16.8% [both-detected group] vs. 27.5% [both-non-detected group]). Low-grade cancers were more often detected in the DBT-only group than in the both-detected group (22.5% vs. 10%, p = 0.026). Human epidermal growth factor receptor-2 (HER-2)-negative cancers were more often detected in the DBT-only group than in the both-detected group (92.3% vs. 70.5%, p = 0.004). Cancers surrounded by mostly glandular tissue were detected less often in the DBT only group than in the both-non-detected group (10% vs. 31.9%, p = 0.016). DBT cancer detectability scores were significantly associated with cancer type (p = 0.012), histologic grade (p = 0.013), T and N stage (p = 0.001, p = 0.024), proportion of glandular tissue surrounding lesions (p = 0.013), and lesion type (p < 0.001).

Conclusion

Invasive lobular, low-grade, or HER-2-negative cancer is more detectable with DBT than with conventional FFDM in patients with dense breasts, but cancers surrounded by mostly glandular tissue might be missed with both techniques.