Independent predictors of breast malignancy in screen-detected microcalcifications: biopsy results in 2545 cases

Improving the Quantitative Analysis of Breast Microcalcifications: A Multiscale Approach

Accurate characterization of microcalcifications (MCs) in 2D digital mammography is a necessary step toward reducing the diagnostic uncertainty associated with the callback of indeterminate MCs. Quantitative analysis of MCs can better identify MCs with a higher likelihood of ductal carcinoma in situ or invasive cancer. However, automated identification and segmentation of MCs remain challenging with high false positive rates. We present a two-stage multiscale approach to MC segmentation in 2D full-field digital mammograms (FFDMs) and diagnostic magnification views. Candidate objects are first delineated using blob detection and Hessian analysis. A regression convolutional network, trained to output a function with a higher response near MCs, chooses the objects which constitute actual MCs. The method was trained and validated on 435 screening and diagnostic FFDMs from two separate datasets. We then used our approach to segment MCs on magnification views of 248 cases with amorphous MCs. We modeled the extracted features using gradient tree boosting to classify each case as benign or malignant. Compared to state-of-the-art comparison methods, our approach achieved superior mean intersection over the union (0.670 ± 0.121 per image versus 0.524 ± 0.034 per image), intersection over the union per MC object (0.607 ± 0.250 versus 0.363 ± 0.278) and true positive rate of 0.744 versus 0.581 at 0.4 false positive detections per square centimeter. Features generated using our approach outperformed the comparison method (0.763 versus 0.710 AUC) in distinguishing amorphous calcifications as benign or malignant.

Utility of detection of breast calcifications with integrated real-time radiography system (IRRS) during digital breast tomosynthesis (DBT)-guided vacuum assisted biopsy (VAB): initial single-center experience

PURPOSE

To determine whether the presence of calcifications in specimens collected during stereotactic-guided vacuum-assisted breast biopsies (VABB) is sufficient to ascertain their adequacy for final diagnosis at pathology.

MATERIALS AND METHODS

Digital breast tomosynthesis (DBT)-guided VABBs were performed on 74 patients with calcifications as target. Each biopsy consisted of the collection of 12 samplings with a 9-gauge needle. This technique was integrated with a real-time radiography system (IRRS) which allowed the operator to determine whether calcifications were included in the specimens at the end of each of the 12 tissue collections through the acquisition of a radiograph of every sampling. Calcified and non-calcified specimens were separately sent to pathology and evaluated.

RESULTS

A total of 888 specimens were retrieved, 471 containing calcifications and 417 without. In 105 (22.2%) samples out of 471 with calcifications cancer was detected, while the remaining 366 (77.7%) were non-cancerous. Out of 417 specimens without calcifications 56 (13.4%) were cancerous, whereas 361 (86.5%) were non-cancerous. Seven hundred and twenty-seven specimens out of all 888 were cancer-free (81.8%, 95%CI 79-84%).

CONCLUSION

Although there is a statistical significative difference between calcified and non-calcified samples and the detection of cancer (p < 0.001), our study shows that the sole presence of calcifications in the specimens is not sufficient to determine their adequacy for final diagnosis at pathology because non-calcified samples can be cancerous and vice-versa. Ending biopsies when calcifications are first detected through IRRS could lead to false negative results.

Biomineralogical signatures of breast microcalcifications

Microcalcifications, primarily biogenic apatite, occur in cancerous and benign breast pathologies and are key mammographic indicators. Outside the clinic, numerous microcalcification compositional metrics (e.g., carbonate and metal content) are linked to malignancy, yet microcalcification formation is dependent on microenvironmental conditions, which are notoriously heterogeneous in breast cancer. We interrogate multiscale heterogeneity in 93 calcifications from 21 breast cancer patients using an omics-inspired approach: For each microcalcification, we define a "biomineralogical signature" combining metrics derived from Raman microscopy and energy-dispersive spectroscopy. We observe that (i) calcifications cluster into physiologically relevant groups reflecting tissue type and local malignancy; (ii) carbonate content exhibits substantial intratumor heterogeneity; (iii) trace metals including zinc, iron, and aluminum are enhanced in malignant-localized calcifications; and (iv) the lipid-to-protein ratio within calcifications is lower in patients with poor composite outcome, suggesting that there is potential clinical value in expanding research on calcification diagnostic metrics to include "mineral-entrapped" organic matrix.

Multi-modality radiomics nomogram based on DCE-MRI and ultrasound images for benign and malignant breast lesion classification

OBJECTIVE

To develop a multi-modality radiomics nomogram based on DCE-MRI, B-mode ultrasound (BMUS) and strain elastography (SE) images for classifying benign and malignant breast lesions.

MATERIAL AND METHODS

In this retrospective study, 345 breast lesions from 305 patients who underwent DCE-MRI, BMUS and SE examinations were randomly divided into training (n = 241) and testing (n = 104) datasets. Radiomics features were extracted from manually contoured images. The inter-class correlation coefficient (ICC), Mann-Whitney U test and the least absolute shrinkage and selection operator (LASSO) regression were applied for feature selection and radiomics signature building. Multivariable logistic regression was used to develop a radiomics nomogram incorporating radiomics signature and clinical factors. The performance of the radiomics nomogram was evaluated by its discrimination, calibration, and clinical usefulness and was compared with BI-RADS classification evaluated by a senior breast radiologist.

RESULTS

The All-Combination radiomics signature derived from the combination of DCE-MRI, BMUS and SE images showed better diagnostic performance than signatures derived from single modality alone, with area under the curves (AUCs) of 0.953 and 0.941 in training and testing datasets, respectively. The multi-modality radiomics nomogram incorporating the All-Combination radiomics signature and age showed excellent discrimination with the highest AUCs of 0.964 and 0.951 in two datasets, respectively, which outperformed all single modality radiomics signatures and BI-RADS classification. Furthermore, the specificity of radiomics nomogram was significantly higher than BI-RADS classification (both p < 0.04) with the same sensitivity in both datasets.

CONCLUSION

The proposed multi-modality radiomics nomogram based on DCE-MRI and ultrasound images has the potential to serve as a non-invasive tool for classifying benign and malignant breast lesions and reduce unnecessary biopsy.

Reducing Unnecessary Biopsies Using Digital Breast Tomosynthesis and Ultrasound in Dense and Nondense Breasts

Aim: To compare digital breast tomosynthesis (DBT) and ultrasound in women recalled for assessment after a positive screening mammogram and assess the potential for each of these tools to reduce unnecessary biopsies. Methods: This data linkage study included 538 women recalled for assessment from January 2017 to December 2019. The association between the recalled mammographic abnormalities and breast density was analysed using the chi-square independence test. Relative risks and the number of recalled cases requiring DBT and ultrasound assessment to prevent one unnecessary biopsy were compared using the McNemar test. Results: Breast density significantly influenced recall decisions (p < 0.001). Ultrasound showed greater potential to decrease unnecessary biopsies than DBT: in entirely fatty (21% vs. 5%; p = 0.04); scattered fibroglandular (23% vs. 10%; p = 0.003); heterogeneously dense (34% vs. 7%; p < 0.001) and extremely dense (39% vs. 9%; p < 0.001) breasts. The number of benign cases needing assessment to prevent one unnecessary biopsy was significantly lower with ultrasound than DBT in heterogeneously dense (1.8 vs. 7; p < 0.001) and extremely dense (1.9 vs. 5.1; p = 0.03) breasts. Conclusion: Women with dense breasts are more likely to be recalled for assessment and have a false-positive biopsy. Women with dense breasts benefit more from ultrasound assessment than from DBT.

A Mammography-Based Nomogram for Prediction of Malignancy in Breast Suspicious Calcification

AIM

To establish a predictive nomogram for malignancy risk stratification of micro-calcifications (MCCs) detected on mammography.

MATERIALS AND METHODS

Consecutive mammograms from January 2017 to March 2021 were retrospectively reviewed. Traditional clinical features were recorded and mammographic features were estimated according to the 5th BI-RADS. A nomogram was developed to graphically predict the malignancy risk based on multivariate logistic regression analysis. The discrimination and calibration performance of the prediction model was assessed.

RESULTS

There were 123 cases of suspicious MCCs with final pathological results identified with a malignancy rate of 55.2%. The malignancy rates of subgroups divided according to the morphology and distribution of MCCs, age, menopausal status and the maximum diameter of MCCs were significantly different. Multivariate logistic analysis showed that a menopause status of postmenopausal, maximum diameters of MCCs ≥2 cm, the morphology of MCCs as fine pleomorphic or fine linear or branching, and the distribution of MCCs as linear or segmental were predictive of a higher probability of malignancy. A prediction nomogram was developed based on four risk factors, including menopausal status as well as the maximum diameters, distribution and morphology of the MCCs. The AUC of that nomogram was 0.839 (95%CI:0.771-0.903).

CONCLUSION

In mammography, the morphology, distribution and maximum diameter of MCCs, and the menopausal status are independent predictors of malignant suspicious MCCs and are readily available in the clinical setting. The nomogram developed in this study for individualized malignancy risk stratification of suspicious MCCs shows a reliable discrimination performance.

Deep learning in breast imaging

Millions of breast imaging exams are performed each year in an effort to reduce the morbidity and mortality of breast cancer. Breast imaging exams are performed for cancer screening, diagnostic work-up of suspicious findings, evaluating extent of disease in recently diagnosed breast cancer patients, and determining treatment response. Yet, the interpretation of breast imaging can be subjective, tedious, time-consuming, and prone to human error. Retrospective and small reader studies suggest that deep learning (DL) has great potential to perform medical imaging tasks at or above human-level performance, and may be used to automate aspects of the breast cancer screening process, improve cancer detection rates, decrease unnecessary callbacks and biopsies, optimize patient risk assessment, and open up new possibilities for disease prognostication. Prospective trials are urgently needed to validate these proposed tools, paving the way for real-world clinical use. New regulatory frameworks must also be developed to address the unique ethical, medicolegal, and quality control issues that DL algorithms present. In this article, we review the basics of DL, describe recent DL breast imaging applications including cancer detection and risk prediction, and discuss the challenges and future directions of artificial intelligence-based systems in the field of breast cancer.

Comprehensive quantitative malignant risk prediction of pure grouped amorphous calcifications: clinico-mammographic nomogram

BACKGROUND

Pure grouped amorphous calcifications are classified as Breast Imaging Reporting and Data System (BI-RADS) category 4B suspicious calcifications and recommended for biopsy. However, the biopsies often reveal benign findings, especially in screening mammograms (92.4-97.2%).

METHODS

Mammograms of 699 pure grouped amorphous calcifications with final pathological results were analyzed in this retrospective study. The maximum span (MS) of the group of calcifications and the MS of the parallel/vertical direction of the mammary duct (MPS/MVS) were measured, and the MPS to MVS ratio was calculated. Based on the MS and ratio, 2 prediction nomograms with other clinic-mammographic features were developed. The discrimination performance of the models was assessed and compared by the area under the receiver operating characteristic curve (AUC). Scatterplots were created to determine the cutoff values with fewer misdiagnoses of malignant calcifications and fewer false positives.

RESULTS

Ultimately, 2 prediction models were successfully developed based on the 4 risk factors of age, purpose of the mammogram, whether multiple or single calcifications, and the MS [odds ratio (OR) =1.06, P=0.02]/ratio (OR =6.05, P<0.001). Both models had good discrimination. The ratio model performed better than the MS model in the training cohort (AUC of 0.875 and 0.834, respectively, P=0.003) and validation cohort (AUC 0.908 and 0.867, respectively, P=0.047). For the group with probably benign calcifications (as detected by the ratio nomogram), the malignancy rates were 2.7% [95% confidence interval (CI): 1.00% to 6.53%] and 1.19% (95% CI: 0.06% to 7.37%) in the training and validation cohorts, respectively, and 44.12% and 47.70% of benign biopsies were detected in the training and validation cohorts, respectively.

CONCLUSIONS

The clinico-mammographic quantitative malignancy risk prediction nomogram showed favorable discrimination and calibration performance. The ratio model showed better diagnostic efficiency than the MS model, and identified >40% of benign biopsies.

Breast cancer incidence by age at discovery of mammographic abnormality in women participating in French organized screening campaigns

OBJECTIVE

Statistical modeling was already predicted the occurrence/prognosis of breast cancer from previous radiological findings. This study predicts the breast cancer risk by the age at discovery of mammographic abnormality in the French breast cancer screening program.

STUDY DESIGN

This was a cohort study.

METHODS

The study included 261,083 women who meet the inclusion criteria: aged 50-74 years, living in French departments (Ain, Doubs, Haute-Saône, Jura, Territoire-de-Belfort, and Yonne), with at least two mammograms between January 1999 and December 2017, of which the first was 'normal/benign'. The incidence of each abnormality (microcalcifications, spiculated mass, obscured mass, architectural distortion, and asymmetric density) was first estimated, then the breast cancer risk was predicted secondly according to the age at discovery of each mammographic abnormality, using an actuarial life table and a Cox model.

RESULTS

Overall breast cancer (6326 cases) incidence was 3.3 (3.0; 3.1)/1000 person-years. The breast cancer incidence increased proportionally with the discovery age of the speculated mass and microcalcifications. The incidence was twice as high when the spiculated mass age of discovery was ≥70 (12.2 [10.4; 14.4]) compared with age 50-54 years (5.8 [5.1; 6.7]). Depending on the spiculated mass discovery age, the breast cancer risk increased by at least 40% between the age groups 55-59 years (1.4 [1.0; 1.8]) and ≥70 years (2.4 [1.9; 3.3]). Whatever the abnormality, the incidence of breast cancer was higher when it was present in only one breast.

CONCLUSION

The study highlights a stable incidence of breast cancer between successive mammograms, an increased risk of breast cancer with the finding age of spiculated mass and microcalcifications. The reduced delay between the abnormality discovery date and the breast cancer diagnosis date would justify a specific follow-up protocol after the finding of these two abnormalities.

Mammographic features are associated with cardiometabolic disease risk and mortality

AIMS

In recent years, microcalcifications identified in routine mammograms were found to be associated with cardiometabolic disease in women. Here, we aimed to systematically evaluate the association of microcalcifications and other mammographic features with cardiometabolic disease risk and mortality in a large screening cohort and to understand a potential genetic contribution.

METHODS AND RESULTS

This study included 57 867 women from a prospective mammographic screening cohort in Sweden (KARMA) and 49 583 sisters. Cardiometabolic disease diagnoses and mortality and medication were extracted by linkage to Swedish population registries with virtually no missing data. In the cardiometabolic phenome-wide association study, we found that a higher number of microcalcifications were associated with increased risk for multiple cardiometabolic diseases, particularly in women with pre-existing cardiometabolic diseases. In contrast, dense breasts were associated with a lower incidence of cardiometabolic diseases. Importantly, we observed similar associations in sisters of KARMA women, indicating a potential genetic overlap between mammographic features and cardiometabolic traits. Finally, we observed that the presence of microcalcifications was associated with increased cardiometabolic mortality in women with pre-existing cardiometabolic diseases (hazard ratio and 95% confidence interval: 1.79 [1.24-2.58], P = 0.002) while we did not find such effects in women without cardiometabolic diseases.

CONCLUSIONS

We found that mammographic features are associated with cardiometabolic risk and mortality. Our results strengthen the notion that a combination of mammographic features and other breast cancer risk factors could be a novel and affordable tool to assess cardiometabolic health in women attending mammographic screening.

Management of breast lesions seen on US images: dual-model radiomics including shear-wave elastography may match performance of expert radiologists

PURPOSE

To develop a nomogram incorporating B-mode ultrasound (BMUS) and shear-wave elastography (SWE) radiomics to predict malignant status of breast lesions seen on US non-invasively.

METHODS

Data on 278 consecutive patients from Hospital #1 (training cohort) and 123 cases from Hospital #2 (external validation cohort) referred for breast US with subsequent histopathologic analysis between May 2017 and October 2019 were retrospectively collected. Using their BMUS and SWE images, we built a radiomics nomogram to improve radiology workflow for management of breast lesions. The performance of the algorithm was compared with a consensus of three ACR BI-RADS committee experts and four individual radiologists, all of whom interpreted breast US images in clinical practice.

RESULTS

Twelve features from BMUS and three from SWE were selected finally to construct the respective radiomic signature. The nomogram based on the dual-modal US radiomics achieved good diagnostic performance in the training (AUC 0.96; 95% confidence intervals [CI], 0.94-0.98) and the validation set (AUC 0.92; 95% CI, 0.87-0.97). For the 123 test lesions, the algorithm achieved 105 of 123 (85%) accuracy, comparable to the expert consensus (104 of 123 [85%], P =  0.86) and four individual radiologists (93, 99, 95 and 97 of 123, with P value of 0.05, 0.31, 0.10 and 0.18 respectively). Furthermore, the model also performed well in the BI-RADS 4 and 5 categories.

CONCLUSIONS

Performance of a dual-model US radiomics nomogram based on SWE for breast lesion classification may comparable to that of expert radiologists who used ACR BI-RADS guideline.

Multiple Pathways for Pathological Calcification in the Human Body

Biomineralization of skeletal components (e.g., bone and teeth) is generally accepted to occur under strict cellular regulation, leading to mineral-organic composites with hierarchical structures and properties optimized for their designated function. Such cellular regulation includes promoting mineralization at desired sites as well as inhibiting mineralization in soft tissues and other undesirable locations. In contrast, pathological mineralization, with potentially harmful health effects, can occur as a result of tissue or metabolic abnormalities, disease, or implantation of certain biomaterials. This progress report defines mineralization pathway components and identifies the commonalities (and differences) between physiological (e.g., bone remodeling) and pathological calcification formation pathways, based, in part, upon the extent of cellular control within the system. These concepts are discussed in representative examples of calcium phosphate-based pathological mineralization in cancer (breast, thyroid, ovarian, and meningioma) and in cardiovascular disease. In-depth mechanistic understanding of pathological mineralization requires utilizing state-of-the-art materials science imaging and characterization techniques, focusing not only on the final deposits, but also on the earlier stages of crystal nucleation, growth, and aggregation. Such mechanistic understanding will further enable the use of pathological calcifications in diagnosis and prognosis, as well as possibly provide insights into preventative treatments for detrimental mineralization in disease.

Malignancy Risk Stratification Prediction of Amorphous Calcifications Based on Clinical and Mammographic Features

Purpose

To explore the potential factors influencing the malignancy risk of amorphous calcifications and establish a predictive nomogram for malignancy risk stratification.

Patients and Methods

Consecutive mammograms from January 2013 to December 2018 were retrospectively reviewed. Traditional clinical features were recorded, and mammographic features were estimated according to the 5th BI-RADS. Included calcifications were randomly divided into the training and validation cohorts. A nomogram was developed to graphically predict the risk of malignancy (risk) based on stepwise multivariate logistic regression analysis. The discrimination and calibration performance of the model were assessed in both the training and validation cohorts.

Results

Finally, 1018 amorphous calcifications with final pathological results in 907 women were identified with a malignancy rate of 28.4% (95% CI: 25.7%, 31.3%). The malignancy rates of subgroups divided by the distribution of calcifications, quantity of calcifications, age, menopausal status and family history of cancer were significantly different. There were 712 cases and 306 cases in the training and validation cohorts. The prediction nomogram was finally developed based on four risk factors, including age and distribution, maximum diameter and quantity of calcifications. The AUC of the nomogram was 0.799 (95% CI: 0.761, 0.836) in the training cohort and 0.795 (95% CI: 0.738, 0.852) in the validation cohort.

Conclusion

On mammography, the distribution, maximum diameter and quantity of calcifications are independent predictors of malignant amorphous calcifications and can be easily obtained in the clinic. The nomogram developed in this study for individualized malignancy risk stratification of amorphous calcifications shows good discrimination performance.

Value of multimodality imaging in the diagnosis of breast lesions with calcification: A retrospective study

PURPOSE

To assess the value of conventional ultrasound (US), contrast-enhanced ultrasound (CEUS) and mammography in the diagnosis of breast lesions with calcifications.

METHODS

A total of 87 breast lesions with calcification were subjected to US, CEUS and mammography and divided into 3 groups: Group A (all cases), Group A1 (31 cases who underwent US and CEUS first followed by mammography), and Group A2 (56 cases who underwent mammography first followed by US and CEUS). A receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic efficacy of different methods in different groups.

RESULTS

In Group A, the area under the ROC curve (AUROC) of CEUS were 0.937, which were significantly higher than that of mammography (p < 0.05). In Group A1, the AUROC of CEUS were 0.842, which were not significantly different from that of US and mammography (p > 0.05). In Group A2, the AUROC of CEUS were 0.987, which were significantly higher than that of mammography and US (p < 0.05).

CONCLUSION

Based on the mammography results, the combination of US and CEUS might improve the diagnostic efficacy in breast lesions with calcification.

Quantitative chemical imaging of breast calcifications in association with neoplastic processes

Calcifications play an essential role in early breast cancer detection and diagnosis. However, information regarding the chemical composition of calcifications identified on mammography and histology is limited. Detailed spectroscopy reveals an association between the chemical composition of calcifications and breast cancer, warranting the development of novel analytical tools to better define calcification types. Previous investigations average calcification composition across broad tissue sections with no spatially resolved information or provide qualitative visualization, which prevents a robust linking of specific spatially resolved changes in calcification chemistry with the pathologic process.

Method: To visualize breast calcification chemical composition at high spatial resolution, we apply hyperspectral stimulated Raman scattering (SRS) microscopy to study breast calcifications associated with a spectrum of breast changes ranging from benign to neoplastic processes, including atypical ductal hyperplasia, ductal carcinoma in situ, and invasive ductal carcinoma. The carbonate content of individual breast calcifications is quantified using a simple ratiometric analysis.

Results: Our findings reveal that intra-sample calcification carbonate content is closely associated with local pathological processes. Single calcification analysis supports previous studies demonstrating decreasing average carbonate level with increasing malignant potential. Sensitivity and specificity reach >85% when carbonate content level is used as the single differentiator in separating benign from neoplastic processes. However, the average carbonate content is limiting when trying to separate specific diagnostic categories, such as fibroadenoma and invasive ductal carcinoma. Second harmonic generation (SHG) data can provide critical information to bridge this gap.

Conclusion: SRS, combined with SHG, can be a valuable tool in better understanding calcifications in carcinogenesis, diagnosis, and possible prognosis. This study not only reveals previously unknown large variations of breast microcalcifications in association with local malignancy but also corroborates the clinical value of linking microcalcification chemistry to breast malignancy. More importantly, it represents an important step in the development of a label-free imaging strategy for breast cancer diagnosis with tremendous potential to address major challenges in diagnostic discordance in pathology.

Diagnostic upgrade of atypical ductal hyperplasia of the breast based on evaluation of histopathological features and calcification on core needle biopsy

AIMS

Atypical ductal hyperplasia (ADH) of breast is increasingly diagnosed in core needle biopsy (CNB). As higher-grade lesions were found in the excision in a substantial proportion of ADH on CNB, factors predicting risk of subsequent upgrade are clinically significant. This study aims to investigate relevant histopathological factors in CNB that could predict diagnostic upgrade at excision.

METHODS AND RESULTS

One hundred and forty-three cases of CNB with paired subsequent excision were evaluated for multiple clinicopathological parameters related to CNB sampling, ADH morphology, calcification and other co-existing histological features, and which of these parameters were associated with diagnostic upgrade at subsequent excisions were determined. Forty-eight cases (34.3%) were upgraded to malignancy, including 15 invasive cancers and 33 ductal carcinomas in situ (DCIS). An increased tissue area occupied by ADH (P = 0.026), a higher number of ADH foci (P = 0.004), the presence of solid pattern (P = 0.037) and older age (P = 0.012) were positively associated with upgrade, while negative associations were found with the presence of micropapillary pattern (P = 0.025), co-existing columnar cell lesions (CCL) (P = 0.001) and the presence of calcifications (P = 0.009). Multivariate logistic regression analysis showed that the number of ADH foci (HR = 2.810, P = 0.013) was an independent positive predictor, while co-existing CCL (HR = 0.391, P = 0.013) was an independent negative predictor for upgrade.

CONCLUSIONS

Patients with ADH in CNB showing the presence of co-existing CCL and a lower number of ADH foci have a lower risk of disease upgrade at excision, and are potential candidates for observation-only management.

Does establishing a preoperative nomogram including ultrasonographic findings help predict the likelihood of malignancy in patients with microcalcifications?

BACKGROUND

Mammography (MG) is highly sensitive for detecting microcalcifications, but has low specificity. This study investigates whether establishing a preoperative nomogram including ultrasonographic findings can help predict the likelihood of malignancy in patients with mammographic microcalcification.

METHODS

Between May 2012 and January 2017, 475 patients with suspicious microcalcifications detected on MG underwent ultrasonography (US). The χ² test was used to screen risk factors among the variables. Then, a multivariate logistic regression analysis was performed to identify independent predictors of malignant microcalcifications. A mammographic nomogram (M nomogram) and mammographic-ultrasonographic nomogram (M-U nomogram) were established based on multivariate logistic regression models. The discriminatory ability and clinical utility of both nomograms were compared by the receiver operating characteristics curve and decision curve analysis. The calibration ability was evaluated using a calibration curve.

RESULTS

Among the cases, 68.2% (324/475) were pathologically diagnosed as breast cancer and 31.8% (151/475) were benign lesions. Based on multivariate logistic regression analysis, age, clinical manifestation, morphology and distribution of microcalcifications on MG and lesions associated with microcalcifications on US were confirmed as independent predictors of malignant microcalcifications. In terms of discrimination ability, the C-index of the M-U nomogram was significantly higher than that of the M nomogram (0.917 vs 0.897, p = 0.006). The bias-corrected curve was close to the ideal line in the calibration curve. Decision curve analysis suggested that the M-U nomogram was superior to M nomogram.

CONCLUSIONS

Combining mammographic parameters with ultrasonographic findings in a nomogram provided better performance than an M nomogram alone, especially for dense breasts, which suggests the value of ultrasonographic finding for individualized prediction of malignancy in patients with microcalcifications.

Radio-guided and clip-guided preoperative localization for malignant microcalcifications offer similar performances in breast-conserving surgery

Obtaining a tailored breast resection is challenging in microcalcifications detected on screening mammography, and an accurate localization is required. The aim of this study was to compare the efficacy of radio-guided localization (ROLL) versus ultrasound localization of a titanium clip with collagen (TCC) in terms of clear margins, re-intervention rates, excess of resected breast tissue, and operative times in pure malignant microcalcifications detected on screening mammography. Two hundred and twenty-one consecutive patients with malignant microcalcifications detected on screening mammography from a tertiary breast unit were reviewed: 177 patients were localized by TCC and 44 patients by stereotactic ROLL. A propensity score-matched analysis was performed, followed by a logistic regression model, to avoid selection bias. Adequacy of resection was expressed as the calculated resection ratio considering lesion size. No differences were found in clear margins with ROLL versus TCC (77.3% vs 81.8%, adjusted OR 2, P = 0.27). Re-operation rates were similar, being 11.3% with ROLL and 7.4% with TCC (P = 0.627). Mean resection volume was 46.2 cm³ with ROLL versus 54.2 cm³ with TCC (P = 0.222). Adjusted mean calculated resection ratio was 1.8 with ROLL and 2.1 with TCC (P = 0.38). Surgery time was longer with TCC compared to ROLL (69.6 vs 52.7 minutes, P < 0.0001). ROLL and TCC are equally effective to excise malignant microcalcifications with clear margins, providing similar re-intervention rates and resection volumes.

Features of Microcalcifications on Screening Mammography in Young Women

Background: There is no decrease in the number of breast cancer deaths if screening mammography is performed in women aged <40 years. However, NCCN guidelines recommend screening mammography in young women at risk of hereditary breast cancer. Therefore, more accurate screening mammography for young women is needed. Objective: To evaluate the features of screening mammographic findings, particularly microcalcifications, in women aged <50 years to increase the positive predictive value of screening mammography in young women. Methods: We retrospectively reviewed the data of consecutive women who underwent opportunistic and organized breast cancer screening at the Sakuragaoka Hospital (Shizuoka, Japan) between April 2013 and March 2015. We compared the mammographic findings and features of microcalcifications between women aged <40 and 40–49 years and those aged 50–74 years. Results: The study included 3645 women. Of these 3645 women, 415 (11.4%) were aged <40 years, 1219 (33.4%) were aged 40–49 years, and 2011 (55.2%) were aged 50–74 years. Women aged <50 years were more likely to be recalled for microcalcifications than those aged 50–74 years (<40 years, 4.8%; 40–49 years, 4.3%; 50–74 years, 3.3%). Young women were more likely to be recalled for small round and segmental microcalcifications [<40 years, odds ratio (OR): 1.799 (95% CI: 0.751–2.846); 40–49 years, OR: 1.394 (95% CI: 0.714–2.074)] and less likely to be recalled for small round and grouped microcalcifications [<40 years, OR: 0.603 (95% CI: 0.181–1.025); 40–49 years, OR: 0.961 (95% CI: 0.496–1.428)] compared with women aged 50–74 years. Conclusions: On screening mammography, women aged <50 years had a higher tendency to be recalled for microcalcifications, particularly small round and segmental microcalcifications. False-positive results may be reduced by reflecting the characteristics of microcalcification findings among young women without breast cancer in the future.

Molecular subtypes of screen-detected breast cancer

BACKGROUND

Detection of breast cancers by mammographic screening confers a survival advantage of 20-50% compared to symptomatic presentations. The improved prognosis is only partly explained by stage migration. The distribution of the molecular subtypes of screen-detected breast cancer (SDBC) or their HER2 status has not been studied extensively. We wished to address these issues through the study of a large series of SDBC, with other presentations serving as controls.

DESIGN

Deidentified cases of female invasive cancer, diagnosed in Australia and New Zealand during 2005-2015, were retrieved from the BreastSurgANZ Quality Audit (BQA). Method of detection and selected patient, tumour and treatment data were assessed. Immunohistochemical surrogates for molecular subtypes were defined as Luminal A (ER+ and/or PR+, HER2-), Luminal B (ER+ and/or PR+, HER2+), HER2-enriched (ER-, PR- and HER2+) and basal-like (triple negative). Results were compared with the findings of controls and previous studies.

RESULT

100983 invasive cancers were diagnosed, including 32493 (32.7%) SDBC and 66907 (67.3%) with other presentations. The biomarker profile for SDBC versus other presentations in the same population was ER 89.3 versus 80.3%, PR 78.8 versus 69.8% and for HER2 11 versus 15.6%. The distribution of molecular subtypes was Luminal A 81.9 versus 70.74%, Luminal B 7.39 versus 9.52%, HER2-enriched 3.63 versus 6.06% and Basal-like 7.08 versus 13.68%. These differences were significant (p < 0.0001).

CONCLUSION

Molecular profiles of SDBC are significantly different from those of symptomatic cancers, with over-representation of the Luminal A and proportionately lower rates of all other subtypes. We have shown, for the first time, significantly lower rates of HER2 positivity in SDBC. These differences may contribute to the better survival of SDBC and have implications for prognostication, targeted therapy decisions and for laboratory quality assurance programs in setting target ranges for proportions of ER-positive and HER2 results in heavily screened populations.

Active surveillance of women diagnosed with atypical ductal hyperplasia on core needle biopsy may spare many women potentially unnecessary surgery, but at the risk of undertreatment for a minority: 10-year surgical outcomes of 114 consecutive cases from a single center

A needle core biopsy diagnosis of atypical ductal hyperplasia is an indication for open biopsy. The launch of randomized clinical trials of active surveillance for low-risk ductal carcinoma in situ leads to the paradoxical situation of women with low-grade ductal carcinoma in situ being observed, whereas those with atypical ductal hyperplasia have surgery. If the malignancies diagnosed after surgery for atypical ductal hyperplasia are dominated by low-risk ductal carcinoma in situ, women with atypical ductal hyperplasia may also be considered for surveillance. This 10-year prospective observational study includes women diagnosed with atypical ductal hyperplasia on core biopsy after screening mammography. We retrieved their clinical, imaging and histologic data and carried out a blind review of core biopsy histology, sub-classifying the atypical ductal hyperplasia along a spectrum from hyperplasia to ductal carcinoma in situ. Using the final surgical pathology data, we calculated: (1) The proportion and grades of ductal carcinoma in situ and invasive cancers diagnosed at open biopsy. (2) The histologic extent of the malignancy at surgery. (3) The biomarker profile and nodal status of any invasive cancers. (4) Ascertained any independent predictors of (i) any malignancy, (ii) high-risk malignancy, defined in this study as invasive cancer, or high-grade ductal carcinoma in situ, or intermediate grade ductal carcinoma in situ with any necrosis. (5) Extrapolated the above to simulate active surveillance for women with screen-detected atypical ductal hyperplasia. Between January 2005 and December 2014, 114 women, mean age 59 years (range 40-79 years) were included. Surgical pathology, available in 110 (97%), confirmed malignancy in 46 (40%). All 46 malignant cases had ductal carcinoma in situ, accompanied by invasive carcinoma in 9 (8%) women. Together, 21 (19%) women had either invasive cancer (9%), high-grade ductal carcinoma in situ (6%), or necrotizing, intermediate grade ductal carcinoma in situ (6%). Only one of nine invasive breast cancers was grade 1, 3 were multifocal, all were ≤8 mm, node negative, and ER positive but two were HER2 amplified. The mean extent of the ductal carcinoma in situ in any one specimen was 19.8 mm, median 13 mm, range 2-110 mm. Overall 32 women, 29% of the whole cohort and 70% of those 46 with malignancy, required further surgery, including mastectomy in 12 (11%). A multivariable model for predicting the likelihood of any malignancy showed a statistically significant association only with the post review subtype of atypical ductal hyperplasia, adjusting for lesion size. Independent predictors of high-risk malignancy (invasive cancer or non-low-grade ductal carcinoma in situ) were not identified. If active surveillance is adopted for screen-detected atypical ductal hyperplasia diagnosed on core biopsy, 60% of women will avoid unnecessary surgery and a further 24% would meet eligibility criteria for ductal carcinoma in situ surveillance trials. However, 18% of women will have undiagnosed invasive breast cancer or non-low-risk ductal carcinoma in situ. These women with high-risk lesions are not reliably identified pre-operatively.

Adjunctive Breast-Specific Gamma Imaging for Detecting Cancer in Women with Calcifications at Mammography

BACKGROUND

Mammography detects calcium deposits sensitively, but the specificity for differentiating malignancy from benign calcifications is low. Thus, we investigated whether adjunctive breast-specific gamma imaging (BSGI) has incremental value for detecting cancer in women with suspicious calcifications detected by mammography, and compared BSGI with adjunctive ultrasonography (US).

METHODS

The medical records of women without a personal history of breast cancer who underwent mammography for breast evaluation from 2009 to 2014 were reviewed retrospectively. Patients who had calcifications detected by mammography, with a result of Breast Imaging Reporting and Data System (BI-RADS) categories 3-5, underwent adjunctive US and BSGI and were included in this study. A total of 302 breast lesions in 266 women (mean age ± standard deviation 49 ± 9 years) were selected for this study.

RESULTS

For detecting breast cancer using mammography plus BSGI, the sensitivity, specificity, positive predictive value, negative predictive value, and area under the receiver operating curve with 95% confidence intervals were 94% (91-96), 90% (86-93), 91% (87-94), 94% (90-96), and 0.92 (0.89-0.95), respectively. For mammography plus US, the respective values were 97% (94-98), 51% (46-57), 68% (63-73), 94% (90-96), and 0.74 (0.70-0.78).

CONCLUSIONS

Adjunctive BSGI had higher specificity than adjunctive US without loss of sensitivity. This finding suggests that adjunctive BSGI may be a useful complementary initial imaging method to improve the detection of breast cancer in women who have calcifications with suspicious morphology at mammography.

Imaging With Synthesized 2D Mammography: Differences, Advantages, and Pitfalls Compared With Digital Mammography

OBJECTIVE

Synthesized 2D (s2D) mammography is rapidly replacing digital mammography in breast imaging with digital breast tomosynthesis (DBT) to reduce radiation dose and maintain screening outcomes. We illustrate variations in the appearance of s2D and digital mammograms to aid in implementation of this technology.

CONCLUSION

Despite subjective differences in the appearance of s2D and digital mammograms, early outcomes of screening using s2D mammography and DBT are not inferior to those achieved with digital mammography and DBT. Understanding these variations may aid in implementing this technique and improving patient outcomes.

Computer-Aided Breast Cancer Diagnosis with Optimal Feature Sets: Reduction Rules and Optimization Techniques

This chapter introduces a new method for knowledge extraction from databases for the purpose of finding a discriminative set of features that is also a robust set for within-class classification. Our method is generic and we introduce it here in the field of breast cancer diagnosis from digital mammography data. The mathematical formalism is based on a generalization of the k-Feature Set problem called (α, β)-k-Feature Set problem, introduced by Cotta and Moscato (J Comput Syst Sci 67(4):686-690, 2003). This method proceeds in two steps: first, an optimal (α, β)-k-feature set of minimum cardinality is identified and then, a set of classification rules using these features is obtained. We obtain the (α, β)-k-feature set in two phases; first a series of extremely powerful reduction techniques, which do not lose the optimal solution, are employed; and second, a metaheuristic search to identify the remaining features to be considered or disregarded. Two algorithms were tested with a public domain digital mammography dataset composed of 71 malignant and 75 benign cases. Based on the results provided by the algorithms, we obtain classification rules that employ only a subset of these features.

Improved Diagnostics by Assessing the Micromorphology of Breast Calcifications via X-Ray Dark-Field Radiography

Breast microcalcifications play an essential role in the detection and evaluation of early breast cancer in clinical diagnostics. However, in digital mammography, microcalcifications are merely graded with respect to their global appearance within the mammogram, while their interior microstructure remains spatially unresolved and therefore not considered in cancer risk stratification. In this article, we exploit the sub-pixel resolution sensitivity of X-ray dark-field contrast for clinical microcalcification assessment. We demonstrate that the micromorphology, rather than chemical composition of microcalcification clusters (as hypothesised by recent literature), determines their absorption and small-angle scattering characteristics. We show that a quantitative classification of the inherent microstructure as ultra-fine, fine, pleomorphic and coarse textured is possible. Insights underlying the micromorphological nature of breast calcifications are verified by comprehensive high-resolution micro-CT measurements. We test the determined microtexture of microcalcifications as an indicator for malignancy and demonstrate its potential to improve breast cancer diagnosis, by providing a non-invasive tool for sub-resolution microcalcification assessment. Our results indicate that dark-field imaging of microcalcifications may enhance the diagnostic validity of current microcalcification analysis and reduce the number of invasive procedures.

Microcalcification on mammography: approaches to interpretation and biopsy

This article discusses the significance of microcalcifications on mammography and the changes in technology that have influenced management; it also describes a pragmatic approach to investigation of microcalcification in a UK screening programme.

Effect of Calcifications on Breast Ultrasound Shear Wave Elastography: An Investigational Study

Purpose

To investigate the effects of macrocalcifications and clustered microcalcifications associated with benign breast masses on shear wave elastography (SWE).

Methods

SuperSonic Imagine (SSI) and comb-push ultrasound shear elastography (CUSE) were performed on three sets of phantoms to investigate how calcifications of different sizes and distributions influence measured elasticity. To demonstrate the effect in vivo, three female patients with benign breast masses associated with mammographically-identified calcifications were evaluated by CUSE.

Results

Apparent maximum elasticity (E_max) estimates resulting from individual macrocalcifications (with diameters of 2mm, 3mm, 5mm, 6mm, 9mm, 11mm, and 15mm) showed values over 50 kPa for all cases, which represents more than 100% increase over background (~21kPa). We considered a 2cm-diameter circular region of interest for all phantom experiments. Mean elasticity (E_mean) values varied from 26 kPa to 73 kPa, depending on the macrocalcification size. Highly dense clusters of microcalcifications showed higher E_max values than clusters of microcalcification with low concentrations, but the difference in E_mean values was not significant.

Conclusions

Our results demonstrate that the presence of large isolated macrocalcifications and highly concentrated clusters of microcalcifications can introduce areas with apparent high elasticity in SWE. Considering that benign breast masses normally have significantly lower elasticity values than malignant tumors, such areas with high elasticity appearing due to presence of calcification in benign breast masses may lead to misdiagnosis.

Microcalcifications Detected as an Abnormality on Screening Mammography: Outcomes and Followup over a Five-Year Period

Objectives. This study reviewed the outcome of women attending a breast screening program recalled for assessment of microcalcifications and examined the incidence of a breast carcinoma detected during the following five years in any of the women who were given a benign diagnosis at assessment. Method. A retrospective study consisted of 235 clients attending an Australian BreastScreen program in 2003, who were recalled for investigation of microcalcifications detected on screening mammography. Records for the following five years were available for 168 women in the benign outcome group including those who did not require biopsy at initial assessment. Results. Malignant disease was detected in 26.0% (n = 146) of the women who underwent biopsy. None of the women in the benign outcome group, with available five-year follow-up records, developed a subsequent breast cancer, arising from the calcifications initially recalled in 2003. Conclusions. This study highlights the effectiveness of an Australian screening program in diagnosing malignancy in women with screen detected microcalcification. This has been achieved by correctly determining 38% (n = 235) of the women as benign without the need for biopsy or early recall. A low rate of open surgical biopsies was performed with no cancer diagnoses missed at the time of initial assessment.

Bias in breast cancer research in the screening era

Screening aims to detect breast cancer at an earlier stage than would occur if symptoms developed. The characteristics of breast cancer that are detectable at screening depend on both the physical properties of the screening test and specific anatomical features of breast cancer. As a result, breast cancer detected by screening is a select subset of all breast cancer existing in the population. Therefore, biomedical, clinical and epidemiological research into breast cancer using populations with access to screening can result in major bias. The biases, with examples, are explained.