Is There a Correlation between the Presence of a Spiculated Mass on Mammogram and Luminal A Subtype Breast Cancer?

Mammographic features differ with body composition in women with breast cancer

OBJECTIVES

There are several breast cancer (BC) risk factors-many related to body composition, hormonal status, and fertility patterns. However, it is not known if risk factors in healthy women are associated with specific mammographic features at the time of BC diagnosis. Our aim was to assess the potential association between pre-diagnostic body composition and mammographic features in the diagnostic BC image.

MATERIALS AND METHODS

The prospective Malmö Diet and Cancer Study includes women with invasive BC from 1991 to 2014 (n = 1116). BC risk factors at baseline were registered (anthropometric measures, menopausal status, and parity) along with mammography data from BC diagnosis (breast density, mammographic tumor appearance, and mode of detection). We investigated associations between anthropometric measures and mammographic features via logistic regression analyses, yielding odds ratios (OR) with 95% confidence intervals (CI).

RESULTS

There was an association between high body mass index (BMI) (≥ 30) at baseline and spiculated tumor appearance (OR 1.370 (95% CI: 0.941-2.010)), primarily in women with clinically detected cancers (OR 2.240 (95% CI: 1.280-3.940)), and in postmenopausal women (OR 1.580 (95% CI: 1.030-2.440)). Furthermore, an inverse association between high BMI (≥ 30) and high breast density (OR 0.270 (95% CI: 0.166-0.438)) was found.

CONCLUSION

This study demonstrated an association between obesity and a spiculated mass on mammography-especially in women with clinically detected cancers and in postmenopausal women. These findings offer insights on the relationship between risk factors in healthy women and related mammographic features in subsequent BC.

CLINICAL RELEVANCE STATEMENT

With increasing numbers of both BC incidence and women with obesity, it is important to highlight mammographic findings in women with an unhealthy weight.

KEY POINTS

Women with obesity and BC may present with certain mammographic features. Spiculated masses were more common in women with obesity, especially postmenopausal women, and those with clinically detected BCs. Insights on the relationship between obesity and related mammographic features will aid mammographic interpretation.

Radiologic-Pathologic Correlation of Nonmass Enhancement Contiguous with Malignant Index Breast Cancer Masses at Preoperative Breast MRI

Purpose To determine the pathologic features of nonmass enhancement (NME) directly adjacent to biopsy-proven malignant masses (index masses) at preoperative MRI and determine imaging characteristics that are associated with a malignant pathologic condition. Materials and Methods This retrospective study involved the review of breast MRI and mammography examinations performed for evaluating disease extent in patients newly diagnosed with breast cancer from July 1, 2016, to September 30, 2019. Inclusion criteria were limited to patients with an index mass and the presence of NME extending directly from the mass margins. Wilcoxon rank sum test, Fisher exact test, and χ2 test were used to analyze cancer, patient, and imaging characteristics associated with the NME diagnosis. Results Fifty-eight patients (mean age, 58 years ± 12 [SD]; all women) were included. Malignant pathologic findings for mass-associated NME occurred in 64% (37 of 58) of patients, 43% (16 of 37) with ductal carcinoma in situ and 57% (21 of 37) with invasive carcinoma. NME was more likely to be malignant when associated with an index cancer that had a low Ki-67 index (<20%) (P = .04). The presence of calcifications at mammography correlating with mass-associated NME was not significantly associated with malignant pathologic conditions (P = .19). The span of suspicious enhancement measured at MRI overestimated the true span of disease at histologic evaluation (P < .001), while there was no evidence of a difference between span of calcifications at mammography and true span of disease at histologic evaluation (P = .27). Conclusion Mass-associated NME at preoperative MRI was malignant in most patients with newly diagnosed breast cancer. The span of suspicious enhancement measured at MRI overestimated the true span of disease found at histologic evaluation. Keywords: Breast, Mammography © RSNA, 2024 See also the commentary by Newell in this issue.

Evaluation of architectural distortion with contrast-enhanced mammography

Architectural distortion (AD) is the third most common abnormality detected on mammograms. In the absence of an accurate non-invasive tool to evaluate ADs, clinical management often requires surgical excision for histological diagnosis. This problem is expected to worsen with the growing use of digital breast tomosynthesis (DBT) and the resultant increasing detection of ADs. There is therefore a great clinical need for a diagnostic imaging tool to complement non-enhanced mammography for the evaluation of AD. Contrast-enhanced mammography (CEM) is an emerging breast imaging method that uses contrast media and the principle of dual-energy subtraction to evaluate vascularity of suspicious breast lesions. CEM, a cost-effective alternative to breast magnetic resonance imaging (MRI), can be used to evaluate AD by juxtaposing CEM images with non-enhanced mammograms for comparison. In this review, the authors aim to provide readers with an overview of the interpretation of AD on CEM using imaging examples. Relevant imaging features of CEM and their respective significance will be matched with information from a literature review. Finally, the authors would like to highlight the added value of CEM in relevant clinical applications in the assessment of AD.

Classifying Breast Cancer Metastasis Based on Imaging of Tumor Primary and Tumor Biology

The molecular classification of breast cancer has allowed for a better understanding of both prognosis and treatment of breast cancer. Imaging of the different molecular subtypes has revealed that biologically different tumors often exhibit typical features in mammography, ultrasound, and MRI. Here, we introduce the molecular classification of breast cancer and review the typical imaging features of each subtype, examining the predictive value of imaging with respect to distant metastases.

Retracted: Microcalcification-associated breast cancer: HER2-enriched molecular subtype is associated with mammographic features

OBJECTIVE

To investigate whether the mammographic features were different between breast cancer HER2-enriched molecular subtype and non-HER2-enriched molecular subtype.

METHODS

283 microcalcification-associated breast cancers were identified (HER2-enriched: n = 57; non-HER2-enriched: n = 226). Mammographic tumor mass and calcification features in relation to HER2 molecular subtype were analyzed.

RESULTS

On univariate analysis, HER2-enriched molecular subtype rates were significantly higher (a) in tumor size ≤2 cm [33 of 57 (57.9%)] than in tumor size >2 cm lesions [22 of 226 (9.7%)] (p = 0.007), (b) in non-spiculated mass [39 of 57 (68.4%)] than in spiculated mass lesions [18 of 226 (7.9%)] (p = 0.034)，(c) in calcifications extent >2 cm [41 of 57 (71.9%)] lesions than in calcifications extent ≤2 cm lesions [16 of 226 (7.1%)] (p < 0.001) and (d) in calcification density ＞20 cm-2 [44 of 57 (71.2%)] lesions than in calcification density ≤20 cm-2 lesions [13 of 226 (5.8%)] (p = 0.034).On multivariate analysis, three mammographic features [tumor size >2 cm vs size ≤2 cm odds ratio (OR): 0.415 95% confidence interval (CI) (0.215 to 0.802), p = 0.009, spiculated mass vs non-spiculated mass OR: 0.226 95% CI (0.114 to 0.446), p < 0.001 and calcifications extent >2 cm vs calcifications extent ≤2 cm OR: 7.754, 95% CI (3.100 to 19.339) p< 0.001] were independent predictors. Our results indicated that small tumor size, non-spiculated mass and calcification extent >2 cm are more likely to be HER2 molecular subtype. The discrimination of this model, as quantified by the area under the curve, was 0.751 [95% CI (0.701 to 0.854)].

CONCLUSION

Our study presents a prediction model that incorporates the mammographic features of tumor size, non-spiculated mass and calcification extent, which can potentially be used to preoperative predict breast cancer HER2-enriched subtype.

ADVANCES IN KNOWLEDGE

Mammographic features can noninvasively visualize breast tumor phenotype characteristics.

Plane wave elastography: a frequency-domain ultrasound shear wave elastography approach

In this paper, we propose plane wave elastography (PWE), a novel ultrasound shear wave elastography (SWE) approach. Currently, commercial methods for SWE rely on directional filtering based on the prior knowledge of the wave propagation direction, to remove complicated wave patterns formed due to reflection and refraction. The result is a set of decomposed directional waves that are separately analyzed to construct shear modulus fields that are then combined through compounding. Instead, PWE relies on a rigorous representation of the wave propagation using the frequency-domain scalar wave equation to automatically select appropriate propagation directions and simultaneously reconstruct shear modulus fields. Specifically, assuming a homogeneous, isotropic, incompressible, linear-elastic medium, we represent the solution of the wave equation using a linear combination of plane waves propagating in arbitrary directions. Given this closed-form solution, we formulate the SWE problem as a nonlinear least-squares optimization problem which can be solved very efficiently. Through numerous phantom studies, we show that PWE can handle complicated waveforms without prior filtering and is competitive with state-of-the-art that requires prior filtering based on the knowledge of propagation directions.

Mammographic features and screening outcome in a randomized controlled trial comparing digital breast tomosynthesis and digital mammography

PURPOSE

To compare the distribution of mammographic features among women recalled for further assessment after screening with digital breast tomosynthesis (DBT) versus digital mammography (DM), and to assess associations between features and final outcome of the screening, including immunohistochemical subtypes of the tumour.

METHODS

This randomized controlled trial was performed in Bergen, Norway, and included 28,749 women, of which 1015 were recalled due to mammographic findings. Mammographic features were classified according to a modified BI-RADS-scale. The distribution were compared using 95 % confidence intervals (CI).

RESULTS

Asymmetry was the most common feature of all recalls, 24.3 % (108/444) for DBT and 38.9 % (222/571) for DM. Spiculated mass was most common for breast cancer after screening with DBT (36.8 %, 35/95, 95 %CI: 27.2-47.4) while calcifications (23.0 %, 20/87, 95 %CI: 14.6-33.2) was the most frequent after DM. Among women screened with DBT, 0.13 % (95 %CI: 0.08-0.21) had benign outcome after recall due to indistinct mass while the percentage was 0.28 % (95 %CI: 0.20-0.38) for DM. The distributions were 0.70 % (95 %CI: 0.57-0.85) versus 1.46 % (95 %CI: 1.27-1.67) for asymmetry and 0.24 % (95 %CI: 0.16-0.33) versus 0.54 % (95 %CI: 0.43-0.68) for obscured mass, among women screened with DBT versus DM, respectively. Spiculated mass was the most common feature among women diagnosed with non-luminal A-like cancer after DBT and after DM.

CONCLUSIONS

Spiculated mass was the dominant feature for breast cancer among women screened with DBT while calcifications was the most frequent feature for DM. Further studies exploring the clinical relevance of mammographic features visible particularly on DBT are warranted.

Predicting Molecular Subtypes of Breast Cancer with Mammography and Ultrasound Findings: Introduction of Sono-Mammometry Score

We studied the correlation of sonographic and digital mammographic features with molecular classification of breast cancer. Imaging features from 313 patients with preliminary ultrasound and digital mammogram between November 2017 and May 2020 were compared with histopathology and immunohistochemical analysis for the prediction of molecular classification of breast cancer. We also devised a score called “sono-mammometry” score consisting of few simple imaging features which can easily be performed in outpatient settings. We studied that non-triple-negative breast cancers are predominantly hypoechoic and strongly correlate with the presence of irregular spiculated margins along with peripheral echogenic halo, posterior shadowing, and microcalcifications, while there is considerable variation in imaging features of TNBC as some of its imaging features overlap with those of typical benign tumors. Although imaging characteristics are helpful in the prediction of molecular classification, the prognostication value of these imaging features is still weak. There is considerable variation in imaging features which warrants vigilance towards improved diagnostic performance. To help better understand these features, our sono-mammometry score can serve as straightforward test which is assumed to be functional and productive in resource-limited settings.

SAP-cGAN: Adversarial learning for breast mass segmentation in digital mammogram based on superpixel average pooling

PURPOSE

Breast mass segmentation is a prerequisite step in the use of computer-aided tools designed for breast cancer diagnosis and treatment planning. However, mass segmentation remains challenging due to the low contrast, irregular shapes, and fuzzy boundaries of masses. In this work, we propose a mammography mass segmentation model for improving segmentation performance.

METHODS

We propose a mammography mass segmentation model called SAP-cGAN, which is based on an improved conditional generative adversarial network (cGAN). We introduce a superpixel average pooling layer into the cGAN decoder, which utilizes superpixels as a pooling layout to improve boundary segmentation. In addition, we adopt a multiscale input strategy to enable the network to learn scale-invariant features with increased robustness. The performance of the model is evaluated with two public datasets: CBIS-DDSM and INbreast. Moreover, ablation analysis is conducted to evaluate further the individual contribution of each block to the performance of the network.

RESULTS

Dice and Jaccard scores of 93.37% and 87.57%, respectively, are obtained for the CBIS-DDSM dataset. The Dice and Jaccard scores for the INbreast dataset are 91.54% and 84.40%, respectively. These results indicate that our proposed model outperforms current state-of-the-art breast mass segmentation methods. The superpixel average pooling layer and multiscale input strategy has improved the Dice and Jaccard scores of the original cGAN by 7.8% and 12.79%, respectively.

CONCLUSIONS

Adversarial learning with the addition of a superpixel average pooling layer and multiscale input strategy can encourage the Generator network to generate masks with increased realism and improve breast mass segmentation performance through the minimax game between the Generator network and Discriminator network.

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

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

Learning Latent Spiculated Features for Lung Nodule Characterization

Computer-aided Diagnosis (CAD) systems have long aimed to be used in clinical practice to help doctors make decisions by providing a second opinion. However, most machine learning based CAD systems make predictions without explicitly showing how their predictions were generated. Since the cognitive process of the diagnostic imaging interpretation involves various visual characteristics of the region of interest, the explainability of the results should leverage those characteristics. We encode visual characteristics of the region of interest based on pairs of similar images rather than the image content by itself. Using a Siamese convolutional neural network (SCNN), we first learn the similarity among nodules, then encode image content using the SCNN similarity-based feature representation, and lastly, we apply the K-nearest neighbor (KNN) approach to make diagnostic characterizations using the Siamese-based image features. We demonstrate the feasibility of our approach on spiculation, a visual characteristic that radiologists consider when interpreting the degree of cancer malignancy, and the NIH/NCI Lung Image Database Consortium (LIDC) dataset that contains both spiculation and malignancy characteristics for lung nodules.Clinical Relevance - This establishes that spiculation can be quantified to automate the diagnostic characterization of lung nodules in Computed Tomography images.

A multicenter study on radiomic features from T2 -weighted images of a customized MR pelvic phantom setting the basis for robust radiomic models in clinics

PURPOSE

To investigate the repeatability and reproducibility of radiomic features extracted from MR images and provide a workflow to identify robust features.

METHODS

T₂ -weighted images of a pelvic phantom were acquired on three scanners of two manufacturers and two magnetic field strengths. The repeatability and reproducibility of features were assessed by the intraclass correlation coefficient and the concordance correlation coefficient, respectively, and by the within-subject coefficient of variation, considering repeated acquisitions with and without phantom repositioning, and with different scanner and acquisition parameters. The features showing intraclass correlation coefficient or concordance correlation coefficient >0.9 were selected, and their dependence on shape information (Spearman's ρ > 0.8) analyzed. They were classified for their ability to distinguish textures, after shuffling voxel intensities of images.

RESULTS

From 944 two-dimensional features, 79.9% to 96.4% showed excellent repeatability in fixed position across all scanners. A much lower range (11.2% to 85.4%) was obtained after phantom repositioning. Three-dimensional extraction did not improve repeatability performance. Excellent reproducibility between scanners was observed in 4.6% to 15.6% of the features, at fixed imaging parameters. In addition, 82.4% to 94.9% of the features showed excellent agreement when extracted from images acquired with echo times 5 ms apart, but decreased with increasing echo-time intervals, and 90.7% of the features exhibited excellent reproducibility for changes in pulse repetition time. Of nonshape features, 2.0% was identified as providing only shape information.

CONCLUSION

We showed that radiomic features are affected by MRI protocols and propose a general workflow to identify repeatable, reproducible, and informative radiomic features to ensure robustness of clinical studies.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Abbreviated Magnetic Resonance Imaging (MRI) for Breast Cancer Screening: Rationale, Concept, and Transfer to Clinical Practice

Given the increasing understanding of cancer as a heterogeneous group of diseases, detection methods should offer a sensitivity profile that ensures perfect sensitivity for biologically important cancers while screening out self-limiting pseudocancers. However, mammographic screening is biased toward detection of ductal carcinoma in situ and slowly growing cancers-and thus frequently fails to detect biologically aggressive cancers. This explains the persistently high rates of interval cancers and high rates of breast cancer mortality observed in spite of decades of mammographic screening. Magnetic resonance imaging (MRI), in contrast, has a sensitivity profile that matches clinical needs. Conventional MRI is not suitable for population-wide screening due to high cost, limited tolerability, and lack of availability. We introduced abbreviated MRI in 2014. Abbreviated MRI will change the way MRI is used in clinical medicine. This article describes the rationale to use MRI in general, and abbreviated MRI in particular, for breast cancer screening.

Are baseline ultrasound and mammographic features associated with rates of pathological completes response in patients receiving neoadjuvant chemotherapy for breast cancer?

Background

Increasing numbers of breast cancer patients receive neoadjuvant chemotherapy (NACT). We seek to investigate whether baseline mammographic and ultrasound features are associated with complete pathological response (pCR) after NACT.

Methods

A database of NACT patients was reviewed. Baseline imaging parameters assessed were ultrasound: posterior effect; echo pattern; margin and lesion diameter; mammography: spiculation and microcalcification. Core biopsy grade and immunophenotype were documented. Data were analysed for the whole study group and by immunophenotype.

Results

Of the 222 cancers, 83 (37%) were triple negative (TN), 61 (27%) ER positive/HER-2 negative and 78 (35%) HER-2 positive. A pCR occurred in 46 of 222 cancers (21%). For the whole group, response was associated with high core biopsy grade (grade 3 vs. grade 1 or 2) (26% vs. 9%, p = 0.0044), absence of posterior shadowing on ultrasound (26% vs. 10%, p <  0.001) and the absence of mammographic spiculation (26 vs. 6%, p <  0.001). Within the HER-2 positive group; the absence of shadowing and spiculation remained highly associated with pCR, in addition to small ultrasound size (AUC = 0.71, p < 0.001) and the absence of microcalcification (39% vs. 21%, p < 0.02). On multivariable analysis absence of spiculation and core grade remained significant for the whole cohort, size and absence of spiculation remained significant for HER-2 positive tumours. No feature predicted pCR in TN tumours.

Conclusion

A pCR is less likely when there is mammographic spiculation. Small ultrasound size is associated with pCR in HER-2 positive tumours. These findings may be helpful when discussing NACT and surgical options with patients.

Trial registration

UK Clinical Trials Gateway: registration number 16712.

Optoacoustic imaging of the breast: correlation with histopathology and histopathologic biomarkers

Aim

This study was conducted in order to investigate the role of gray-scale ultrasound (US) and optoacoustic imaging combined with gray-scale ultrasound (OA/US) to better differentiate between breast cancer molecular subtypes.

Materials and methods

All 67 malignant masses included in the Maestro trial were retrospectively reviewed to compare US and OA/US feature scores and histopathological findings. Kruskal–Wallis tests were used to analyze the relationship between US and OA/US features and molecular subtypes of breast cancer. If a significant relationship was found, additional Wilcoxon–Mann–Whitney tests were used to identify the differences between molecular subtype groups.

Results

US sound transmission helped to differentiate between LUMA and LUMB, LUMB and TNBC, and LUMB and all other molecular subtypes combined (p values < 0.05). Regarding OA/US features, the sum of internal features helped to differentiate between TNBC and HER2-enriched subtypes (p = 0.049). Internal vessels (p = 0.025), sum of all internal features (p = 0.019), and sum of internal and external features (p = 0.028) helped to differentiate between LUMA and LUMB. All internal features, the sum of all internal features, the sum of all internal and external features, and the ratio of internal and external features helped to differentiate between LUMA and TNBC. The same features also helped to differentiate between LUMA and TNBC from other molecular subtypes (p values < 0.05).

Conclusions

The use of OA/US might help radiologists to better differentiate between breast cancer molecular subtypes. Further studies need to be carried out in order to validate these results.

Key Points

• The combination of functional and morphologic information provided by optoacoustic imaging (OA) combined with gray-scale US helped to differentiate between breast cancer molecular subtypes.

Electronic supplementary material

The online version of this article (10.1007/s00330-019-06262-0) contains supplementary material, which is available to authorized users.

Sonographic Features of Estrogen-Negative Breast Cancers: A Correlation Study With Human Epidermal Growth Factor Type II Overexpression

The purpose of this study was to retrospectively review sonographic imaging features of estrogen-negative breast cancers and compare tumors with and without human epidermal growth factor type II (HER2) overexpression. Breast sonography findings from a sample of 54 patients with estrogen-negative breast cancer as well as pathological data and HER2 status were reviewed. Sonographic features including size, depth shapes, margin, location, patterns of internal echoes, posterior echoes, orientation, and presence of halo and clinicopathologic data and imaging features were correlated with tumor HER2 status. Based on these 54 patients with estrogen-negative breast cancers, 21 patients were positive for HER2 receptor, and 33 patients were negative for HER2 receptor. Among HER2 positive cancers, irregular shape, microlobulation, indistinct margins, posterior shadowing, a thin halo, heterogeneous internal echoes, and parallel orientation were the most frequent sonographic features. No associations were found between HER-2 status and tumor size, shape, margins, posterior feature, halo, internal echoes, or orientation on sonography.

BI-RADS 3-5 microcalcifications: prediction of lymph node metastasis of breast cancer

Purpose

To determine whether the clinicopathological parameters and Breast Imaging Reporting and Data System (BI-RADS) 3–5 microcalcifications differed between lymph node positive (LN (+)) and lymph node negative (LN (−)) invasive ductal carcinoma (IDC).

Results

For microcalcification-associated breast cancers, seven selected features (age, tumor size, Ki-67 status, lymphovascular invasion, calcification range, calcification diameter and calcification density) were significantly associated with LN status (all P < 0.05). Multivariate logistic regression analysis found that three risk factors (age: older vs. younger OR: 0.973 P = 0.006, tumor size: larger vs. smaller OR: 1.671, P < 0.001 and calcification density: calcifications > 20/cm² vs. calcifications ≤ 20/cm² OR: 1.698, P < 0.001) were significant independent predictors. This model had an area under the receiver operating characteristic curve (AUC) of 0.701. The nodal staging (N0 and N1 χ² = 5.701, P = 0.017; N0 and N2 χ² = 6.614, P = 0.013) was significantly positively associated with calcification density. The luminal B subtype had the highest risk of LN metastasis. Multivariate analysis demonstrated that calcification > 2 cm in range (OR: 2.209) and larger tumor size (OR: 1.882) were independently predictive of LN metastasis in the luminal B subtype (AUC = 0.667).

Materials and Methods

Mammographic images of 419 female breast cancer patients were included. Associations between the risk factors and LN status were evaluated using a Chi-square test, ANOVA and binary logistic regression analysis.

Conclusions

This study found that age, tumor size and calcifications density can be conveniently used to facilitate the preoperative prediction of LN metastasis. The luminal B subtype has the highest risk of LN metastasis among the microcalcification-associated breast cancers.