Suspicious Ultrasound-Occult Non-Calcified Mammographic Masses, Asymmetries, and Architectural Distortions Are Moderate Probability for Malignancy

Suspicious non-calcified mammographic findings have not been evaluated with modern mammographic technique, and the purpose of this work is to compare the likelihood of malignancy for those findings. To do this, 5018 consecutive mammographically guided biopsies performed during 2016-2019 at a large metropolitan, community-based hospital system were retrospectively reviewed. In total, 4396 were excluded for targeting calcifications, insufficient follow-up, or missing data. Thirty-seven of 126 masses (29.4%) were malignant, 44 of 194 asymmetries (22.7%) were malignant, and 77 of 302 architectural distortions (AD, 25.5%) were malignant. The combined likelihood of malignancy was 25.4%. Older age was associated with a higher likelihood of malignancy for each imaging finding type (all p ≤ 0.006), and a possible ultrasound correlation was associated with a higher likelihood of malignancy when all findings were considered together (p = 0.012). Two-view asymmetries were more frequently malignant than one-view asymmetries (p = 0.03). There were two false-negative biopsies (98.7% sensitivity and 100% specificity). In conclusion, the 25.4% likelihood of malignancy confirms the recommendation for biopsy of suspicious, ultrasound-occult, mammographic findings. Mammographically guided biopsies were highly sensitive and specific in this study. Older patient age and a possible ultrasound correlation should raise concern given the increased likelihood of malignancy in those scenarios.

Management of Mammographic Architectural Distortion Based on Contrast-enhanced MRI and US Correlation

OBJECTIVE

The objective was to evaluate outcomes of mammographic architectural distortion (AD) with and without MRI and US correlates.

METHODS

A retrospective review of unexplained mammographic AD with subsequent MRI from January 1, 2007 to September 30, 2017 was performed using a reader-based study design. Mammographic, MRI, and US features and outcomes were documented. Truth was based on biopsy results or minimum two-year imaging follow-up. Measures of diagnostic accuracy were calculated.

RESULTS

Fifty-six cases of AD were included: 29 (51.8%) detected on 2D mammogram and 27 (48.2%) detected on digital breast tomosynthesis. Of 35.7% (20/56) with MRI correlate, 40.0% (8/20) were enhancing masses, 55.0% (11/20) were non-mass enhancement (NME), and 5.0% (1/20) were nonenhancing AD. Of eight enhancing masses, 75.0% (6/8) were invasive cancers, and 25.0% (2/8) were high-risk lesions. Of 11 NME, 18.2% (2/11) were ductal carcinoma in situ, 36.4% (4/11) were high-risk lesions, and 45.4% (5/11) were benign. Of 64.3% (36/56) without MRI correlate, 94.4% (34/36) were benign by pathology or follow-up, one (2.8%, 1/36) was a 4-mm focus of invasive cancer with US correlate, and one (1/36, 2.8%) was a high-risk lesion. Of cases without MRI and US correlates, one (3.0%, 1/33) was a high-risk lesion and 97.0% (32/33) were benign. The negative predictive value of mammographic AD without MRI correlate was 97.2% (35/36) and without both MRI and US correlates was 100.0% (33/33).

CONCLUSION

Mammographic AD without MRI or US correlate was not cancer in our small cohort and follow-up could be considered, reducing interventions.

Tomosynthesis-Detected Architectural Distortions: Correlations between Imaging Characteristics and Histopathologic Outcomes

OBJECTIVE

to determine the positive predictive value (PPV) of tomosynthesis (DBT)-detected architectural distortions (ADs) and evaluate correlations between AD's imaging characteristics and histopathologic outcomes.

METHODS

biopsies performed between 2019 and 2021 on ADs were included. Images were interpreted by dedicated breast imaging radiologists. Pathologic results after DBT-vacuum assisted biopsy (DBT-VAB) and core needle biopsy were compared with AD detected by DBT, synthetic2D (synt2D) and ultrasound (US).

RESULTS

US was performed to assess a correlation for ADs in all 123 cases and a US correlation was identified in 12/123 (9.7%) cases, which underwent US-guided core needle biopsy (CNB). The remaining 111/123 (90.2%) ADs were biopsied under DBT guidance. Among the 123 ADs included, 33/123 (26.8%) yielded malignant results. The overall PPV for malignancy was 30.1% (37/123). The imaging-specific PPV for malignancy was 19.2% (5/26) for DBT-only ADs, 28.2% (24/85) for ADs visible on DBT and synth2D mammography and 66.7% (8/12) for ADs with a US correlation with a statistically significant difference among the three groups (p = 0.01).

CONCLUSIONS

DBT-only ADs demonstrated a lower PPV of malignancy when compared with syntD mammography, and DBT detected ADs but not low enough to avoid biopsy. As the presence of a US correlate was found to be related with malignancy, it should increase the radiologist's level of suspicion, even when CNB returned a B3 result.

Pathologic Outcomes in Single Versus Multiple Areas of Architectural Distortion on Digital Breast Tomosynthesis

BACKGROUND. Digital breast tomosynthesis (DBT) has led to increased detection of architectural distortion (AD). Management of patients with multiple areas of AD is not established. OBJECTIVE. The purpose of this article is to compare pathologic outcomes between single and multiple areas of AD identified on DBT. METHODS. This retrospective study included 402 patients (mean age, 56 years) who underwent image-guided core needle biopsy of AD visualized on DBT between April 7, 2017, and April 16, 2019. Patients were classified as having a single or multiple areas of AD according to the presence of distinct areas of AD described in the clinical radiology reports. The pathologic diagnosis for each AD was on the basis of the most aggressive pathology identified on either biopsy or surgical excision, if performed. Patients with single and multiple areas of AD were compared. RESULTS. The sample included 372 patients with a single AD (145 benign, 121 high risk, 105 malignant, one other) and 30 patients with multiple visualized ADs, including 66 biopsied ADs (10 benign, 35 high risk, 21 malignant). At pathologic assessment on a per-lesion basis, multiple compared with single ADs showed higher frequency of high-risk pathology (53.0% vs 32.5%, p = .002) but no difference in frequency of malignancy (31.8% vs 28.2%, p = .56). In multivariable analysis of a range of patient-related characteristics, the presence of single versus multiple areas of AD was not independently associated with malignancy (p = .51). In patients with multiple areas of AD, the most aggressive pathology (benign, high risk, or malignant) across all ADs was not associated with the number of ADs (p = .73). In 8 of 24 patients with at least two ipsilateral biopsied ADs, the ipsilateral areas varied in terms of most aggressive pathology; in 5 of 10 patients with contralateral biopsied ADs, the contralateral areas varied in most aggressive pathology. CONCLUSION. The presence of multiple areas of AD, compared with a single AD, was significantly more likely to yield high-risk pathology but was not significantly different in yield of malignancy. In patients with multiple ADs, multiple ipsilateral or contralateral ADs commonly varied in pathologic classification (benign, high risk, or malignant). CLINICAL IMPACT. These findings may help guide management of AD visualized by DBT, including multiple ADs. For patients with multiple areas of AD, biopsy of all areas may be warranted given variation in pathologic diagnoses.

Diagnosis of architectural distortion on digital breast tomosynthesis using radiomics and deep learning

Purpose

To implement two Artificial Intelligence (AI) methods, radiomics and deep learning, to build diagnostic models for patients presenting with architectural distortion on Digital Breast Tomosynthesis (DBT) images.

Materials and Methods

A total of 298 patients were identified from a retrospective review, and all of them had confirmed pathological diagnoses, 175 malignant and 123 benign. The BI-RADS scores of DBT were obtained from the radiology reports, classified into 2, 3, 4A, 4B, 4C, and 5. The architectural distortion areas on craniocaudal (CC) and mediolateral oblique (MLO) views were manually outlined as the region of interest (ROI) for the radiomics analysis. Features were extracted using PyRadiomics, and then the support vector machine (SVM) was applied to select important features and build the classification model. Deep learning was performed using the ResNet50 algorithm, with the binary output of malignancy and benignity. The Gradient-weighted Class Activation Mapping (Grad-CAM) method was utilized to localize the suspicious areas. The predicted malignancy probability was used to construct the ROC curves, compared by the DeLong test. The binary diagnosis was made using the threshold of ≥ 0.5 as malignant.

Results

The majority of malignant lesions had BI-RADS scores of 4B, 4C, and 5 (148/175 = 84.6%). In the benign group, a substantial number of patients also had high BI-RADS ≥ 4B (56/123 = 45.5%), and the majority had BI-RADS ≥ 4A (102/123 = 82.9%). The radiomics model built using the combined CC+MLO features yielded an area under curve (AUC) of 0.82, the sensitivity of 0.78, specificity of 0.68, and accuracy of 0.74. If only features from CC were used, the AUC was 0.77, and if only features from MLO were used, the AUC was 0.72. The deep-learning model yielded an AUC of 0.61, significantly lower than all radiomics models (p<0.01), which was presumably due to the use of the entire image as input. The Grad-CAM could localize the architectural distortion areas.

Conclusion

The radiomics model can achieve a satisfactory diagnostic accuracy, and the high specificity in the benign group can be used to avoid unnecessary biopsies. Deep learning can be used to localize the architectural distortion areas, which may provide an automatic method for ROI delineation to facilitate the development of a fully-automatic computer-aided diagnosis system using combined AI strategies.

The Challenge of Digital Breast Tomosynthesis-Detected Architectural Distortion of the Breast: Inter-reader Variability and Imaging Characteristics That May Improve Positive Predictive Value

OBJECTIVE

To compare readers' performances when detecting architectural distortion (AD) on digital breast tomosynthesis (DBT). To determine the risk of malignancy of DBT with synthetic mammogram (SM)-detected AD and evaluate imaging features that are associated with malignancy risk.

METHODS

This IRB-approved retrospective review included all cases of DBT-detected AD that were recommended for biopsy from October 2013 to July 2019. Cases were reviewed by three breast radiologists and the overall agreement between radiologists was calculated. Medical records were reviewed for pathological outcomes and imaging findings. Statistical analyses used were Cohen's kappa and its 95% confidence interval, and one-way analysis of variance.

RESULTS

A total of 172 lesions were included. The overall agreement for the presence of AD in our study was fair (0.253). The majority (20/36, 55.5%) of the malignant ADs were associated with asymmetries (13/36, 36.1%), calcifications (4/36, 11.1%), or both (3/36, 8.3%), compared to nonmalignant ADs (40/136, 31.0%; P = 0.038). The positive predictive value (PPV) of DBT with SM-detected AD for malignancy was 21.8% (36/165), 18.8% (18/96) for DBT-detected AD, and 26.0% (18/69) for SM-detected AD, although the difference was not statistically significant (P = 0.258). A breast MRI correlate was identified for all malignant AD lesions (17/17, 100.0%; P = 0.004).

CONCLUSION

The detection of AD remains a challenging task for radiologists, with moderate-to-fair interobserver agreement. With a PPV for malignancy of 21.8%, percutaneous biopsy and subsequent pathology-imaging correlation are necessary for AD to exclude the possibility of malignancy.

Multilevel musculo-fascial defect magnetic resonance study of female pelvic floor: retrospective case control study in women with pelvic floor dysfunction after the first vaginal delivery

INTRODUCTION

Magnetic resonance imaging (MRI) provides a detailed display of the pelvic floor structures responsible for normal pelvic floor anatomy. The aim of the study is to assess the appearance of musculo-fascial defects in women with pelvic floor dysfunction following first vaginal delivery.

MATERIAL AND METHODS

Analysis of axial T3 (Tesla 3) MRI scans from a case control study of symptomatic (n = 149) and asymptomatic (n = 60) women after first vaginal delivery. Presence and severity of pelvic organ support and attachment system defects in three axial pelvic planes were assessed.

RESULTS

In the symptomatic group, major muscular defects were found in 67.1% (for pubovisceral muscle complex) and 87.9% (for iliococcygeal muscle). Only 6.7% of major pubovisceral and 35.0% of major iliococcygeal defects were identified in the controls (p = 0.000). Prolapse patients had an odds ratio (OR) of 22.1 (95% CI 8.94-54.67) to have major pubovisceral muscle complex defect and OR of 4.9 (95% CI 1.51-15.71) to have major iliococcygeal muscle defect. Fascial defects were found in 60.4% and 83.2% the symptomatic group, respectively. Those with prolapse had an OR of 29.1 (95% CI 9.77-86.31) to have facial defect at the level of pubovisceral muscle complex and an OR of 16.9 (95% CI 7.62-37.69) to have fascial defect at the level of iliococcygeal muscle. Uterosacral ligaments detachment was associated with prolapse with an OR of 10.1 (95% CI 4.01-25.29). For the model based on combination on all MRI markers, the area under the receiver operating characteristic curve is 0.921.

CONCLUSIONS

This study provides comprehensive data about first vaginal delivery-induced changes in the levator ani muscle and endopelvic fascial attachment system. These changes are seen also in asymptomatic controls, but they are significantly less expressed.

Evaluation of the Combination of Artificial Intelligence and Radiologist Assessments to Interpret Malignant Architectural Distortion on Mammography

Purpose

To compare the mammographic malignant architectural distortion (AD) detection performance of radiologists who read mammographic examinations unaided versus those who read these examinations with the support of artificial intelligence (AI) systems.

Material and Methods

This retrospective case-control study was based on a double-reading of clinical mammograms between January 2011 and December 2016 at a large tertiary academic medical center. The study included 177 malignant and 90 benign architectural distortion (AD) patients. The model was built based on the ResNeXt-50 network. Algorithms used deep learning convolutional neural networks, feature classifiers, image analysis algorithms to depict AD and output a score that translated to malignant. The accuracy for malignant AD detection was evaluated using area under the curve (AUC).

Results

The overall AUC was 0.733 (95% CI, 0.673-0.792) for Reader First-1, 0.652 (95% CI, 0.586-0.717) for Reader First-2, and 0.655 (95% CI, 0.590-0.719) for Reader First-3. and the overall AUCs for Reader Second-1, 2, 3 were 0.875 (95% CI, 0.830-0.919), 0.882 (95% CI, 0.839-0.926), 0.884 (95% CI, 0.841-0.927),respectively. The AUCs for all the reader-second radiologists were significantly higher than those for all the reader-first radiologists (Reader First-1 vs. Reader Second-1, P= 0.004). The overall AUC was 0.792 (95% CI, 0.660-0.925) for AI algorithms. The combination assessment of AI algorithms and Reader First-1 achieved an AUC of 0.880 (95% CI, 0.793-0.968), increased than the Reader First-1 alone and AI algorithms alone. AI algorithms alone achieved a specificity of 61.1% and a sensitivity of 80.6%. The specificity for Reader First-1 was 55.5%, and the sensitivity was 86.1%. The results of the combined assessment of AI and Reader First-1 showed a specificity of 72.7% and sensitivity of 91.7%. The performance showed significant improvements compared with AI alone (p<0.001) as well as the reader first-1 alone (p=0.006).

Conclusion

While the single AI algorithm did not outperform radiologists, an ensemble of AI algorithms combined with junior radiologist assessments were found to improve the overall accuracy. This study underscores the potential of using machine learning methods to enhance mammography interpretation, especially in remote areas and primary hospitals.

Architectural distortion detection based on superior-inferior directional context and anatomic prior knowledge in digital breast tomosynthesis

BACKGROUND

In 2020, breast cancer becomes the most leading diagnosed cancer all over the world. The burden is increasing in the prevention and treatment of breast cancer. Accurately detecting breast lesions in screening images is important for early detection of cancer. Architectural distortion (AD) is one of the breast lesions that need to be detected.

PURPOSE

To develop a deep-learning-based computer-aided detection (CADe) model for AD in digital breast tomosynthesis (DBT). This model uses the superior-inferior directional context of DBT and anatomic prior knowledge to reduce false positive (FP). It can identify some negative samples that cannot be distinguished by deep learning features.

METHODS

The proposed CADe model consists of three steps. In the first step, a deep learning detection network detects two-dimensional (2D) candidates of ADs in DBT slices with the inputs preprocessed by Gabor filters and convergence measure. In the second step, three-dimensional (3D) candidates are obtained by stacking 2D candidates along superior-inferior direction. In the last step, FP reduction for 3D candidates is implemented based on superior-inferior directional context and anatomic prior knowledge of breast. DBT data from 99 cases with AD were used as the training set to train the CADe model, and data from 208 cases were used as an independent test set (including 108 cases with AD and 100 cases without AD as the control group). The free-response receiver operating characteristic and mean true positive fraction (MTPF) in the range of 0.05-2.0 FPs per volume are used to evaluate the model.

RESULTS

Compared with the baseline model based on convergence measure, our proposed method demonstrates significant improvement (MTPF: 0.2826 ± 0.0321vs. 0.6640 ± 0.0399). Results of an ablation study show that our proposed context-based and anatomy-based FP reduction methods improve the detection performance. The number of FPs per DBT volume reduces from 2.47 to 1.66 at 80% sensitivity after employing these two schemes.

CONCLUSIONS

The deep learning model demonstrates practical value for AD detection. The results indicate that introducing superior-inferior directional context and anatomic prior knowledge into model can indeed reduce FPs and improve the performance of CADe model. This article is protected by copyright. All rights reserved.

Meta-analysis: Architectural distortion and breast MRI

BACKGROUND

The implementation of digital breast tomosynthesis has increased the detection of architectural distortion (AD). Managing this finding may be experienced as a clinical dilemma in daily practice. Breast Contrast-Enhanced MRI (CE-BMR) is a known modality in case of problem-solving tool for mammographic abnormalities. However, the data about AR and CE-BMR are scant.

OBJECTIVE

The purpose was to estimate the benefit of CE-BMR in the setting of architectural distortion detected mammographically through a systematic review and meta-analysis of the literature.

METHODS

A search of MEDLINE and EMBASE databases were conducted in 2020. Based on the PRISMA guidelines, an analysis was performed using the chi-square test of independence to determine if there was a significant association between the result of the test (positive or negative) and the participant condition (malignant or non-malignant).

RESULTS

Four studies were available. The negative predictive value (NPV) was 98.3% to 100%. The result of the chi-square indicated that there was significant association between the participant test result and the participant condition for the included publications (X(1,175)2= 84.051, p = 0.0001).

CONCLUSIONS

The high NPV could allow for deferral of a biopsy in favor of a short-interval imaging follow-up in the setting of a negative CE-BMR.

Architectural Distortion-Based Digital Mammograms Classification Using Depth Wise Convolutional Neural Network

Architectural distortion is the third most suspicious appearance on a mammogram representing abnormal regions. Architectural distortion (AD) detection from mammograms is challenging due to its subtle and varying asymmetry on breast mass and small size. Automatic detection of abnormal ADs regions in mammograms using computer algorithms at initial stages could help radiologists and doctors. The architectural distortion star shapes ROIs detection, noise removal, and object location, affecting the classification performance, reducing accuracy. The computer vision-based technique automatically removes the noise and detects the location of objects from varying patterns. The current study investigated the gap to detect architectural distortion ROIs (region of interest) from mammograms using computer vision techniques. Proposed an automated computer-aided diagnostic system based on architectural distortion using computer vision and deep learning to predict breast cancer from digital mammograms. The proposed mammogram classification framework pertains to four steps such as image preprocessing, augmentation and image pixel-wise segmentation. Architectural distortion ROI's detection, training deep learning, and machine learning networks to classify AD's ROIs into malignant and benign classes. The proposed method has been evaluated on three databases, the PINUM, the CBIS-DDSM, and the DDSM mammogram images, using computer vision and depth-wise 2D V-net 64 convolutional neural networks and achieved 0.95, 0.97, and 0.98 accuracies, respectively. Experimental results reveal that our proposed method outperforms as compared with the ShuffelNet, MobileNet, SVM, K-NN, RF, and previous studies.

Imaging Spectrum of Lobular Carcinoma In Situ and Correlation with Pathology Findings

Background  Lobular carcinoma in situ (LCIS) is a noninvasive neoplasm that is known to have an increased relative risk for developing subsequent invasive breast carcinoma. Pure LCIS is usually an incidental finding on histopathological examination (HPE) of tissue samples. However, in the recent years, there has been an increasing trend seen in the diagnosis of LCIS.

Purpose  This article aims to bring out the spectrum of appearances on breast imaging in confirmed cases of pure LCIS on HPE and immunohistochemical.

Materials and Methods  Cases that were confirmed as pure LCIS on HPE from core or excision biopsy were retrospectively analyzed for abnormalities on breast imaging. Digital breast tomosynthesis mammography was performed with high-resolution ultrasound with elastography for all cases. Magnetic resonance imaging (MRI) was performed in cases wherever indicated, with dynamic postcontrast imaging after injecting intravenous gadolinium.

Conclusion  LCIS is recognized as an intermediate risk factor for the development of breast cancer. Pure LCIS has varied histology and imaging patterns on mammography, high-resolution ultrasound, and MRI. It is important to recognize the imaging appearances of these lesions to enable the radiologist to detect LCIS early for proper management.

Tomosynthesis-Guided Vacuum-Assisted Breast Biopsy of Architectural Distortion Without a Sonographic Correlate: A Retrospective Review

BACKGROUND. Digital breast tomosynthesis-guided vacuum-assisted breast biopsy (DBT VAB) allows biopsy of findings seen better or exclusively on digital breast tomosynthesis (DBT), including architectural distortion. Although architectural distortion with an associated sonographic mass correlate has a high risk of malignancy, limited data describe the radiologic-pathologic correlation of tomosynthesis-detected architectural distortion without a sonographic correlate. OBJECTIVE. This study evaluates the malignancy rate of architectural distortions without a sonographic correlate that undergo DBT VAB and provides radiologic-pathologic correlation for benign, high-risk, and malignant entities that are associated with architectural distortion. METHODS. We retrospectively reviewed imaging, as well as pathology slides and/or reports, for DBT VABs performed for architectural distortion without a sonographic correlate at a single institution between June 1, 2017, and January 15, 2020. According to the correlative histopathology, cases were categorized as benign, high risk, or malignant, and specific histopathologic diagnoses were summarized. RESULTS. During the study period, 142 patients (mean age, 59 years) underwent DBT VAB for 151 unique architectural distortions without a sonographic correlate. DBT VAB revealed a malignant diagnosis in 27 (18%), a high-risk lesion in 50 (33%), and a benign diagnosis in 74 (49%). Two cases of atypical ductal hyperplasia were upgraded to malignancy, resulting in a final malignancy rate of 19% (n = 29/151). Most malignant lesions were invasive carcinomas (83%, n = 24/29); most invasive carcinomas were of lobular subtype (54%, n = 13/24). Most high-risk lesions were radial scars/complex sclerosing lesions (62%, n = 31/50). Most benign results represented fibrocystic change (66%, n = 49/74). A subset (11%, n = 8/74) of benign results were considered discordant and subsequently excised, with none representing malignancy. CONCLUSION. The final malignancy rate of 19% in architectural distortion without a sonographic correlate justifies a recommendation for biopsy using DBT VAB. CLINICAL IMPACT. Our results highlight the utility of DBT VAB in the era of DBT. The detailed radiologic-pathologic correlations will assist radiologists in assessing concordance when performing DBT VAB for architectural distortions and provide a reference for future patient management.

Architectural Distortion on Screening Digital Breast Tomosynthesis: Pathologic Outcomes and Indicators of Malignancy

OBJECTIVE

Digital breast tomosynthesis (DBT) has significantly improved cancer detection capabilities through its identification of subtle findings often imperceptible on 2D digital mammography, particularly architectural distortion (AD). The purpose of this study was to analyze of suspicious AD detected on screening DBT to evaluate the incidence of malignancy and to determine other patient or imaging characteristics in these cases as possible predictors of malignancy.

METHODS

This was an IRB approved retrospective analysis of subjects with AD detected on DBT screening mammography who were given a biopsy recommendation between January 1, 2016, and June 30, 2018. Univariate analysis of various imaging characteristics and patient high-risk factors was performed for statistical correlation with diagnosis of malignancy.

RESULTS

In the 218 DBT-detected AD findings with a final BI-RADS assessment of 4 or 5 on diagnostic workup, 94 (43.1%) yielded malignancy, 57 (26.2%) were classified as high-risk, and 67 (30.7%) were benign. There was a strong statistically significant association with malignancy in the cases with an US correlate (P < 0.0001). There was a statistically significant inverse correlation between malignancy and one-view findings (P = 0.0002). The presence of AD on 2D (P = 0.005) or synthetic 2D views (P = 0.002) showed statistically significant correlations with malignancy, whereas breast density or high-risk factors (P = 0.316) did not.

CONCLUSION

AD detected on DBT that persists on further workup and has no explainable cause should be considered suspicious for malignancy. Identification of the AD on both standard mammographic views and the presence of an US correlate significantly increase the probability of malignancy.

Assessing the Positive Predictive Value of Architectural Distortion Detected with Digital Breast Tomosynthesis in BI-RADS 4 Cases

OBJECTIVE

The purpose of this study was to evaluate the positive predictive value of biopsy (PPV3) of architectural distortion (AD) detected on digital breast tomosynthesis (DBT) in BI-RADS 4 cases, where suspicion for malignancy remains broad.

METHODS

This Institutional Review Board-approved, retrospective study included screening and diagnostic mammograms performed from August 2015 to December 2017 with DBT and digital mammography (DM) revealing suspicious AD with a BI-RADS 4 assessment. Medical records were reviewed for clinical data, imaging, and pathology results. Malignancy rate was assessed by lesion visibility on DM and DBT. Multivariate analysis was performed to assess the odds ratio (OR) of malignancy.

RESULTS

A total of 63/179 cases were malignant, yielding a PPV3 of 35%. No significant difference in PPV3 was found by race, personal or family history of breast cancer, presence of microcalcifications, or mammogram type. Architectural distortion was more likely to be malignant when an US correlate was present (PPV3 49% vs 19%; P < 0.0001). Multivariate analysis demonstrated a 3-fold increased OR for malignancy with an US correlate present (P = 0.005). Lesion visibility analysis revealed a higher PPV3 for AD visible on DM-DBT compared with DBT alone (44% vs 26%; P = 0.01) and when an US correlate was present (DM-DBT 54% vs 30%, P = 0.02; DBT-only 43% vs 11%, P < 0.001).

CONCLUSIONS

Tomosynthesis-detected BI-RADS 4 AD are malignant in 35% of cases and are more likely to be malignant if an US correlate is present and if visible on both DM and DBT.

Architectural Distortion on Digital Breast Tomosynthesis: Management Algorithm and Pathological Outcome

Architectural distortion on digital breast tomosynthesis (DBT) can occur due to benign and malignant causes. With DBT, there is an increase in the detection of architectural distortion compared with 2D digital mammography, and the positive predictive value is high enough to justify tissue sampling when imaging findings are confirmed. Workup involves supplemental DBT views and ultrasound, with subsequent image-guided percutaneous biopsy using the modality on which it is best visualized. If architectural distortion is subtle and/or questionable on diagnostic imaging, MRI may be performed for problem solving, with subsequent biopsy of suspicious findings using MRI or DBT guidance, respectively. If no suspicious findings are noted on MRI, a six-month follow-up DBT may be performed. On pathology, malignant cases are noted in 6.8%-50.7% of the cases, most commonly due to invasive ductal carcinoma, followed by invasive lobular carcinoma. Radial scars are the most common benign cause, with stromal fibrosis and sclerosing adenosis being much less common. As there is an increase in the number of benign pathological outcomes for architectural distortion on DBT compared with 2D digital mammography, concordance should be based on the level of suspicion of imaging findings. As discordant cases have upgrade rates of up to 25%, surgical consultation is recommended for discordant radiologic-pathologic findings.

Malignant Outcomes of Architectural Distortion on Tomosynthesis: A Systematic Review and Meta-Analysis

BACKGROUND. The literature has reported varying rates of malignancy for architectural distortion (AD) on digital breast tomosynthesis (DBT). OBJECTIVE. The purpose of this study was to evaluate the PPV for malignancy of AD on DBT without a known cause and to assess the presence of an ultrasound (US) correlate for malignant AD through systematic review and meta-analysis of the literature. EVIDENCE ACQUISITION. This meta-analysis included all studies published in Em-base, MEDLINE, and Evidence-Based Medicine Reviews databases through July 15, 2020, that assessed the rate of malignancy in patients with AD on DBT without a known cause that was deemed BI-RADS category 4 or 5. Rates of benign or high-risk lesions and the presence of a US correlate for malignant AD were assessed. Core needle biopsy or surgical pathology was used as the reference standard for lesion diagnosis. The pooled PPV and 95% CI were estimated using a random-effects model. EVIDENCE SYNTHESIS. Thirteen retrospective, observational studies were included, yielding 857 ADs seen on DBT. Of the 857 ADs, 339 were breast malignancies, yielding a pooled PPV for malignancy of 34.6% (95% CI, 24.5-46.3%). The pooled PPV for invasive malignancy was 34% (95% CI, 25-45%) and for ductal carcinoma in situ was 5% (95% CI, 4-7%). Of the 857 ADs, 235 (27.4%) were benign lesions, 282 (32.9%) were high-risk lesions, and 1 (0.1%) was a nonbreast metastatic lesion. From the studies that assessed for US correlates, 217 of 277 malignant ADs (78.3%) had a US correlate. CONCLUSION. The pooled PPV for malignancy of AD on DBT without a known cause is high at 34.6%, warranting tissue sampling. CLINICAL IMPACT. A needle biopsy should be performed for ADs on DBT without a known cause. Because most malignant distortions have a corresponding finding on US, a US examination should be performed to look for a correlate, but the absence of a correlate does not obviate a biopsy.

The diagnostic value of MRI for architectural distortion categorized as BI-RADS category 3-4 by mammography

BACKGROUND

Architectural distortion is a common mammographic sign that can be benign or malignant. This study investigated the diagnostic value of magnetic resonance imaging (MRI) for architectural distortions that were category 3-4 under the breast imaging reporting and data system (BI-RADS) by mammography.

METHODS

We retrospectively analyzed 219 pathologically confirmed lesions in 208 patients who had BI-RADS category 3-4 architectural distortion in mammography images. Two radiologists described and categorized the architectural distortion and assigned the BI-RADS categories to the corresponding lesions on MRI images. Using the postoperative pathological diagnosis as the gold standard, we performed receiver operating characteristic (ROC) analysis for the efficacy of mammography and MRI in differentiating patients with benign or malignant lesions.

RESULTS

Totally 151 benign lesions and 68 malignant lesions were confirmed. According to the full-field digital mammography (FFDM), 82 lesions were in BI-RADS category 3, 104 lesions in 4A, 29 lesions in 4B, and 4 lesions in 4C. The positive predictive values of FFDM for BI-RADS categories 3, 4A, 4B, and 4C were 13.4% (11/82), 27.9% (29/104), 82.8% (24/29), and 100.0% (4/4), respectively. According to MRI, 59 lesions were in BI-RADS categories 1-2, 87 lesions in 3, 39 lesions in 4, and 34 lesions in 5, with their positive predictive values being 0.0% (0/58), 2.3% (2/87), 89.7% (35/39), and 100.0% (34/34), respectively. The area under the ROC curve (AUC) of breast benign and malignant lesions differentiated by FFDM was 0.647, and the diagnostic sensitivity, specificity, and Youden index were 86.3%, 41.7%, and 0.280, respectively. The AUC of FFDM combined with dynamic contrast-enhanced MRI (DCE-MRI) in differentiating breast benign vs. malignant lesions was 0.851, and the diagnostic sensitivity, specificity, and Youden index were 89.2%, 80.7%, and 0.699, respectively. The AUC of FFDM combined with DCE-MRI and the apparent diffusion coefficient (ADC) in differentiating benign vs. malignant lesions was 0.983, and the diagnostic sensitivity, specificity, and Youden index were 98.1%, 97.5%, and 0.956, respectively.

CONCLUSIONS

MRI can improve the diagnostic efficiency of mammography in diagnosing BI-RADS category 3-4 architectural distortions and can help in the qualitative diagnosis of architectural distortion lesions.

Mammographic architectural distortion caused by cyst aspiration

Improvement in breast cancer screening technology has increased the detection of architectural distortion, which can often indicate underlying malignancy; however, there are also many benign causes of architectural distortion. We present a case of architectural distortion caused by cyst aspiration, representing a novel, benign cause.

Imaging Features of Nonmalignant and Malignant Architectural Distortion Detected by Tomosynthesis

OBJECTIVE

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSION

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

Diagnostic Accuracy of Digital Mammography in the Detection of Breast Cancer

Introduction Breast cancer has a high prevalence in the community and places very high demands on resources. Digital mammography provides a good quality image with reduced radiation dose and can detect breast carcinoma in its earlier stages, resulting in good prognosis and improved patient survival. Objective To calculate the diagnostic accuracy of digital mammography in the detection of breast cancer, using histopathology as a gold standard in women aged over 30 years, who are undergoing mammography for screening and diagnostic purposes. Materials and methods This was a cross-sectional analytical study, conducted in the department of radiology, for a total duration of 10 months. A total of 122 patients of age above 30 years, referred for digital mammography for the evaluation of different symptoms related to breast diseases, followed by biopsy/surgery and histopathology, were included in the study. Result Our data confirmed that digital mammography is a highly accurate tool for breast cancer detection having a sensitivity of 97%, a specificity of 64.5%, a positive predictive value of 89%, and a negative predictive value of 90.9%, with a diagnostic accuracy of 89.3%. Conclusion Considering our results, we recommend that digital mammography should replace screen-film mammography as a basic tool to detect breast cancer for both screening and diagnostic purposes.

Initial Experience of Tomosynthesis-Guided Vacuum-Assisted Biopsies of Tomosynthesis-Detected (2D Mammography and Ultrasound Occult) Architectural Distortions

OBJECTIVE

As experience and aptitude in digital breast tomosynthesis (DBT) have increased, radiologists are seeing more areas of architectural distortion (AD) on DBT images compared with standard 2D mammograms. The purpose of this study is to report our experience using tomosynthesis-guided vacuum-assisted biopsies (VABs) for ADs that were occult at 2D mammography and ultrasound and to analyze the positive predictive value for malignancy.

MATERIALS AND METHODS

We performed a retrospective review of 34 DBT-detected ADs that were occult at mammography and ultrasound.

RESULTS

We found a positive predictive value of 26% (nine malignancies in 34 lesions). Eight of the malignancies were invasive and one was ductal carcinoma in situ. The invasive cancers were grade 1 (4/8; 50%), grade 2 (2/8; 25%), or grade 3 (1/8; 13%); information about one invasive cancer was not available. The mean size of the invasive cancers at pathologic examination was 7.5 mm (range, 6-30 mm).

CONCLUSION

Tomosynthesis-guided VAB is a feasible method to sample ADs that are occult at 2D mammography and ultrasound. Tomosynthesis-guided VAB is a minimally invasive method that detected a significant number of carcinomas, most of which were grade 1 cancers. Further studies are needed.

Review and management of breast lesions detected with breast tomosynthesis but not visible on mammography and ultrasonography

Background Breast tomosynthesis is more sensitive than mammography and can detect lesions that are not always visible with conventional methods such as digital mammography (MG) and ultrasonography (US). No standardized approach is available for the management of lesions that are detectable with tomosynthesis but are not visible on MG or US. Purpose To review suspicious breast lesions detected with tomosynthesis but not visible on two-dimensional (2D) MG or US and to determine the management options for these lesions. Material and Methods Ethical committee approval was obtained. The radiological records, biopsy or surgery results, and follow-up findings of 107 patients who had a tomosynthesis-positive but MG- or US-negative breast lesion between 2011 and 2016 were retrospectively evaluated. Results Of 107 lesions visible only with tomosynthesis, 74% were architectural distortions and 26% were asymmetrical opacities. All patients underwent magnetic resonance imaging (MRI) for further evaluation. Among the 48 (45%) MRI-negative lesions, none had a suspicious alteration during the follow-up period. Among the MRI-positive lesions, 28% of the 50 architectural distortions and 11% of the nine asymmetrical opacities were malignant. Conclusion Given the inherent high false-positive rate of breast tomosynthesis, breast MRI prior to biopsy may reduce the number of unnecessary biopsies for suspicious breast lesions that are tomosynthesis-positive only.

Pathologic Outcomes of Architectural Distortion on Digital 2D Versus Tomosynthesis Mammography

OBJECTIVE

The purpose of this study is to compare the risk of malignancy associated with architectural distortion detected on 2D digital mammography (DM) versus digital breast tomosynthesis (DBT).

MATERIALS AND METHODS

We performed a retrospective review of architectural distortion cases recommended for biopsy from September 2007 to February 2011, the period before DBT integration (hereafter known as the DM group), and from January 2013 to June 2016, the period after DBT integration (hereafter known as the DBT group). Medical records were reviewed for imaging findings and pathology results.

RESULTS

Architectural distortion was more commonly detected in the DBT group than the DM group (0.14% [274/202,438 examinations] vs 0.07% [121/166,661 examinations]; p < 0.001). The positive predictive value of architectural distortion for malignancy was significantly lower in the DBT group than the DM group (50.7% [139/274 cases] vs 73.6% [89/121 cases]; p < 0.001). Radial scar was the most common nonmalignant finding in both groups, but it was more common in the DBT group (33.2% [91/274] vs 11.6% [14/121]; p < 0.001). In the DBT group, architectural distortion without correlative findings on ultrasound was less likely to represent malignancy than was architectural distortion with correlative findings on ultrasound (29.2% [31/106] vs 66.5% [105/158]; p < 0.001).

CONCLUSION

Architectural distortion is more commonly detected on DBT than DM and is less likely to represent malignancy on DBT. Architectural distortion on DBT is less likely to represent malignancy if there is no sonographic correlate; however, biopsy is warranted even in the absence of a sonographic correlate, given the nearly 30% risk of malignancy in this setting.

Architectural Distortion on Mammography: Correlation With Pathologic Outcomes and Predictors of Malignancy

OBJECTIVE

The objective of our study was to determine the risk of malignancy associated with architectural distortion and to evaluate the imaging and clinical features that may contribute to the prediction of malignancy in the setting of architectural distortion.

MATERIALS AND METHODS

We performed a retrospective review of architectural distortion cases from January 1, 2004, to December 31, 2013. Imaging findings and pathology outcomes were reviewed.

RESULTS

Over the 10-year study period, architectural distortion that was considered to be suspicious for or highly suggestive of malignancy was present in 435 of 231,051 (0.2%) mammographic examinations. Cases were excluded if the main finding described was a mass with an associated feature of architectural distortion (n = 62) or if no pathology results were available (n = 4). Two hundred seventy-five cases of invasive adenocarcinoma or ductal carcinoma in situ (DCIS) were identified; the positive predictive value (PPV) was therefore 74.5% (275/369). DCIS alone was identified in only 4.1% (15/369). The most common benign finding on pathology was a radial scar or complex sclerosing lesion (27/369, 7.3%). Architectural distortion was less likely to represent malignancy on screening mammography than on diagnostic mammography (67.0% vs 83.1%, respectively; p < 0.001). Architectural distortion without a sonographic correlate was less likely to represent malignancy than architectural distortion with a correlate (27.9% vs 82.9%, respectively; p < 0.001). There was no statistically significant difference in the malignancy rate between pure architectural distortion and architectural distortion with calcifications or asymmetries (73.0% vs 78.8%; p = 0.26).

CONCLUSION

The PPV of architectural distortion for malignancy is 74.5%. Architectural distortion is less likely to represent malignancy if detected on screening mammography than on diagnostic mammography or if there is no sonographic correlate.

Mammographically screen-detected asymmetric densities with architectural distortion and normal ultrasound at assessment: Value of MRI as a problem-solving tool

Four cases are presented in which asymptomatic clients from an Australian mammography screening programme (BreastScreen ACT) were recalled for assessment of an asymmetric density with possible architectural distortion. In all four women, mammographic work-up was equivocal and ultrasound showed no suspicious correlate for biopsy. It was then doubtful as to whether any significant lesion was present. In all four cases, MRI revealed the presence of malignancy. Breast MRI can be a useful problem-solving tool in the work-up of such cases.

Detection of mammographically occult architectural distortion on digital breast tomosynthesis screening: initial clinical experience

OBJECTIVE

Digital breast tomosynthesis (DBT) has been shown to improve the sensitivity of screening mammography. DBT may have the most potential impact in cases of subtle mammographic findings such as architectural distortion (AD). The objective of our study was to determine whether DBT provides better visualization of AD than digital mammography (DM) and whether sensitivity for cancer detection is increased by the addition of DBT as it relates to cases of mammographically occult AD.

MATERIALS AND METHODS

Retrospective review of BI-RADS category 0 reports from 9982 screening DM examinations with adjunct DBT were searched for the term "architectural distortion" and were reviewed in consensus by three radiologists. ADs were classified by whether they were seen better on DM or DBT, were seen equally well on both, or were occult on either modality. The electronic medical record was reviewed to identify additional imaging studies, biopsy results, and surgical excision pathology results.

RESULTS

Review identified 26 cases of AD, 19 (73%) of which were seen only on the DBT images. Of the remaining seven ADs, six were seen better on DBT than DM. On diagnostic workup, nine lesions were assigned to BI-RADS category 4 or 5. Surgical pathology revealed two invasive carcinomas, two ductal carcinoma in situ lesions, three radial scars, and two lesions showing atypia. The cancer detection rate of DBT in mammographically occult AD was 21% (4/19). The positive predictive value of biopsy was 44%.

CONCLUSION

DBT provides better visualization of AD than DM and identifies a subset of ADs that are occult on DM. Identification of additional ADs on DBT increases the cancer detection rate.