Diagnostic performance of contrast-enhanced mammography and MRI for breast non-mass microcalcifications: a novel Malignant Calcification Score in contrast-enhanced mammography

Introduction

Microcalcifications refer to the accumulation of calcium deposits within female breast tissue. These indicators often manifest in the initial stages of breast cancer and are frequently associated with ductal carcinoma in situ and invasive cancer (1). Microcalcifications are the primary mammographic indicator in approximately 55% of non-palpable breast cancers, occurring without other accompanying abnormalities (2). Furthermore, over 80% of in situ breast neoplasms are detected solely through microcalcifications (3). Mammography (MG), as a cost-effective screening modality, demonstrates high sensitivity in identifying suspicious malignant microcalcifications. When microcalcifications exhibit morphological features warranting classification as American College of Radiology (ACR) Breast Imaging Reporting and Data System (BI-RADS) category 4 on mammograms, a biopsy is recommended due to the associated malignancy risk, which ranges from 2% to 95% (4). Whether this phenomenon contributes to overdiagnosis and unwarranted invasive procedures remains contentious, prompting extensive clinical and research efforts to refine diagnostic strategies. This debate has fueled the pursuit of novel methods aimed at improving the accuracy of characterizing suspicious non-mass microcalcifications.

Contrast-enhanced MG (CEM), an emerging digital imaging technology, was introduced into clinical practice in 2011. CEM is based on the principle of cancer angiogenesis, similar to contrast-enhanced magnetic resonance imaging (CE-MRI). This technique allows contrast media to infiltrate the tumor interstitium, thereby enhancing the visualization of malignant tissues (5). Previous studies have found that the additional enhancement provided by CEM for suspicious microcalcifications has a certain clinical value (4,6). The predictive value of associated enhancement is greater for intermediate- or high-concern microcalcifications compared to low-concern microcalcifications (6). However, this additional enhancement relies on qualitative and visual classification analysis, which may not yield comprehensive and accurate objective results. The aim of this study was to develop a novel diagnostic approach, termed the Malignant Calcification Score (MCS) in CEM, which incorporates multi-index and quantitative analysis to characterize non-mass suspicious microcalcifications. A comparative analysis was performed to evaluate the predictive performance of CEM scores vs. BI-RADS classifications of MG and MRI in distinguishing malignant non-mass microcalcifications from benign lesions. We present this article in accordance with the STARD reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1-2579/rc).

Methods

Patients

This retrospective study consecutively identified 354 patients with breast microcalcifications who underwent CEM between May 2019 and April 2024. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study protocol was approved by the Ethics Committee of The Fourth Hospital of Hebei Medical University (No. 2023KS083) and informed consent for this retrospective analysis was waived. After applying exclusion criteria—including mass enhancement (n=116), absence of pathological results (n=109), prior chemoradiotherapy (n=15), biopsy performed before CEM (n=8), and poor image quality (n=7)—a total of 99 female patients (mean age: 47.88±9.59 years; age range, 30–73 years) with 105 lesions were included in the final analysis. In this study, biopsy specimens were obtained from microcalcifications detected through digital MG or stereotactic guidance. X-ray imaging was performed on the excised breast specimens following surgical resection. All pathological specimens were reviewed and confirmed by radiologists and pathologists. We identified bilateral breast lesions in six cases and unilateral breast lesions in 93 cases. For cases with multiple lesions, the area exhibiting the highest suspicion of malignancy was selected for analysis. Among these, 63 lesions underwent additional MRI scans as part of a subgroup study (see Figure 1). And the clinical data, including age, onset time, marital status, and other relevant factors, were collected.

Figure 1 Flowchart of the study. CEM, contrast-enhanced mammography; MRI, magnetic resonance imaging.

Image analysis

CEM was performed using a Senographe Essential system (GE Healthcare, Chicago, IL, USA). Following a standardized protocol, an iodine-based contrast agent (iopromide, 370 mgI/mL) was administered intravenously using a Bayer Mark 7 high-pressure syringe at a dose of 1.22 mL/kg of body weight, with an injection rate of 3 mL/s. The imaging sequence commenced post-injection, initiating with the contralateral breast, followed by the affected breast. Both craniocaudal (CC) and mediolateral oblique (MLO) projections were obtained for each breast. Referring to Kang’s research (7), the initial CC projection of the affected breast at 3 minutes, combined with the delayed CC projection at 6 minutes, effectively highlights enhanced features associated with microcalcifications in clinical practice. For diagnostic purposes at the workstation, two types of images are available: low-energy images, which resemble those produced by full-field digital MG (FFDM), and recombined images, which are generated by applying a specialized algorithm that integrates data from both low- and high-energy images.

MRI was performed using both 1.5-T (Signa HDe, GE Healthcare) and 3.0-T (Magnetom Skyra, Siemens, Forchheim, Germany) scanners. The standardized imaging protocol included T1-weighted imaging [repetition time (TR)/echo time (TE) =5.6/2.2 ms], T2-weighted imaging (TR/TE =8,250/85 ms), diffusion-weighted imaging (DWI; TR/TE =6,500/85 ms; b-values =0 and 800 s/mm²), and dynamic contrast-enhanced (DCE) MRI. The DCE-MRI acquisition consisted of one pre-contrast phase followed by five consecutive post-contrast phases, using a fat-suppressed T1-weighted gradient-echo sequence (TR/TE =5.6/1.0 ms).

Two radiologists—one with 6 years and the other with 8 years of experience in breast imaging—independently analyzed CEM and MRI images without knowledge of the histopathological results. Any disagreements between the two readers were resolved through consensus with a third radiologist who has 12 years of experience in breast imaging. For the low-energy images, the following descriptors were evaluated: breast density (dense, non-dense); microcalcification location (upper-outer quadrant, other); microcalcification morphology (amorphous/coarse, pleomorphic, linear/branching) (6,8); microcalcification distribution (diffuse, regional, grouped/clustered, segmental/linear) (6,8,9); and accompanying architectural distortion or asymmetries. For the recombined images, the following predefined descriptors were assessed: background parenchymal enhancement (BPE; minimal, mild, moderate, marked), lesion size (maximum cross-sectional enhancement area in recombined CEM images on the CC projection), and the percentage signal difference (%RS). The %RS, which quantifies the relative degree of enhancement, was calculated as %RS = (S'c − S'b)/S'b × 100%, where S'c and S'b represent the signal intensities in the most homogeneously enhancing lesion area and the most homogeneous background fatty tissue, respectively. Kinetic features were characterized using a modified time-intensity curve (mTIC) classification system. Based on the change in %RS from the initial to the delayed CC phase, mTICs were categorized as type I (ascending), type II (steady), or type III (descending) (10). In our study, only five cases of calcifications lacked associated enhancement, and all 5 cases (100%) were confirmed to be benign based on the final pathological diagnosis. Given the very small sample size (n=5), this variable likely has wide confidence intervals and low statistical power. All five cases of calcifications without associated enhancement were classified as type I. Morphology was further detailed by evaluating the enhancement morphological distribution (diffuse, regional, focal, segmental/linear) and the internal enhancement pattern (homogeneous, heterogeneous, clumped, clustered ring) (9,11). In accordance with the BI-RADS 5th edition, all low-energy and MRI images were retrospectively reviewed and assigned a BI-RADS category by readers blinded to the histopathological diagnoses (12). According to the ACR BI-RADS^® CEM [2022] supplement and previous literature review, the classification criteria for BI-RADS category 3 in CEM are clearly defined. BI-RADS categories 1–3 were defined as benign, while categories 4–5 were considered malignant, with categories above 3 constituting a recommendation for biopsy (13,14).

Statistical analysis

The statistical analysis was conducted using SPSS Version 22.0 (IBM) and MedCalc Version 19.0.4. Descriptive statistics for categorical variables are presented as frequencies and percentages, with group comparisons performed using the Chi-squared test or Fisher’s exact test. For continuous variables, data are reported as mean ± standard deviation for normally distributed data or as median and interquartile range (IQR) for non-normally distributed data. The independent samples t-test and the Mann-Whitney U test were applied accordingly. Logistic multiple regression and receiver operating characteristic (ROC) analysis were performed to determine independent enhancement predictors and establish MCS. The diagnostic performance of MCS was evaluated and compared with BI-RADS (MG) and BI-RADS (MRI) using ROC analysis and DeLong’s test. Inter-reader agreement for MCS and BI-RADS was assessed using Cohen’s kappa (κ) coefficient. A P value of less than 0.05 was considered statistically significant.

Results

In the present study, we analyzed a total of 105 cases involving non-mass microcalcifications. Among these, 29.52% (31/105) were diagnosed as benign, 39.05% (41/105) as carcinoma in situ, and 31.43% (33/105) as invasive carcinoma (including four mixed carcinomas: one case of lobular carcinoma, one case of papillary carcinoma, and two cases of mucinous carcinoma), based on surgical or biopsy pathology. Additionally, we conducted a subgroup analysis of 63 lesions, which revealed that 22.22% (14/63) were diagnosed as benign, 33.33% (21/63) as carcinoma in situ, and 44.44% (28/63) as invasive carcinoma. In this study, no significant differences were observed in clinical data or imaging features between patients who underwent only CEM examinations and those who underwent concurrent MRI examinations (see Table S1). There were no significant differences in age, onset time, marital status, childbearing history, menopausal status, and family history of breast cancer between benign and malignant microcalcifications (all P>0.05) (see Table 1).

In the low-energy imaging, the patterns of microcalcification morphology and distribution showed significant statistical differences between benign and malignant lesions (P=0.047 and P=0.002) (Table 1). In the recombined images, there were significant statistical differences between benign and malignant lesions, including BPE (P=0.03), size (P=0.01), %RS (in the CC oblique view) [%RS(CC)] (P<0.001), mTIC (P<0.001), enhancement morphological distribution (P=0.007), and internal enhancement pattern (P=0.001). While the delayed %RS(CC) of malignant lesions was greater than that of benign lesions, but is not significant (P=0.053) (see Table 1 and Figures S1,S2).

The multivariate regression analysis of the enhancement descriptors in the recombined images revealed that %RS(CC), mTIC, enhancement morphological distribution, and internal enhancement pattern were independent predictors of malignant lesions (all P≤0.017) (see Table 2). The analysis of significant descriptors in the low-energy and recombined images using ROC curves demonstrated that the descriptors of microcalcification morphology, distribution, %RS(CC), mTIC, enhancement morphological distribution, and internal enhancement pattern were significantly associated with malignant microcalcifications, exhibiting an area under the curve (AUC) ranging from 0.648 to 0.862 (all P≤0.017) (see Table 3). When the categorical descriptors exceeded the cut-off value, a malignancy risk score of one point was assigned (high-risk type). Conversely, if the categorical descriptors fell below the cut-off value, the score was recorded as 0 (low-risk type). The MCS was established through a synthesis analysis of significant descriptors in the low-energy and recombined images (see Table 4).

For all non-mass microcalcifications, the AUC value of MCS to distinguish malignant microcalcifications was 0.930, which is significantly higher than the AUC values of BI-RADS (MG) (AUC: 0.678) (DeLong’s test: P<0.001). For the subgroup analysis, the AUC value of MCS was 0.908, which is significantly higher than the AUC values of BI-RADS (MG) and BI-RADS (MRI) (AUC: 0.679 and 0.724, respectively) (DeLong’s test: P=0.001 and P=0.01). While there was no significant difference between BI-RADS (MG) and BI-RADS (MRI) (DeLong’s test: P=0.67) (see Table 5 and Figure 2).

Figure 2 ROC curves for MCS and BI-RADS. (A) The AUC values for MCS in CEM and BI-RADS (MG) for all lesions; (B) the AUC values for MCS, BI-RADS (MG), and BI-RADS (MRI) in the subgroup. AUC, area under the curve; BI-RADS, Breast Imaging Reporting and Data System; CEM, contrast-enhanced mammography; MCS, Malignant Calcification Score; MG, mammography; MRI, magnetic resonance imaging; ROC, receiver operating characteristic.

There were no significant differences in the calcification descriptors from low-energy imaging—including calcification location, morphology, distribution, or any accompanying architectural distortion or asymmetry—between carcinoma in situ and invasive carcinoma (all P>0.05). In contrast, significant statistical differences were observed in the recombined images between carcinoma in situ and invasive carcinoma, specifically in size (P=0.02), %RS(CC) (P=0.02), mTIC (P=0.007), and internal enhancement pattern (P=0.002). The multivariate regression analysis of these significant enhancement descriptors revealed that only %RS(CC) was an independent predictor of invasive carcinoma (P=0.007), with an AUC of 0.730, 92.1% sensitivity, and 50.0% specificity (see Table 6).

Good inter-reader agreement was observed across all imaging evaluations, with κ values of 0.816 for MCS, 0.792 for BI-RADS (MG), and 0.754 for BI-RADS (MRI).

Discussion

Our study demonstrated that microcalcification morphology, distribution, %RS(CC), mTIC, enhancement morphological distribution, and internal enhancement pattern were significantly associated with malignant microcalcifications. However, only %RS(CC) emerged as an independent predictor of invasive carcinoma. The MCS, which integrates features of calcification and enhancement, significantly improves diagnostic accuracy compared to BI-RADS (MG) and BI-RADS (MRI).

Beyond its diagnostic efficacy, CEM offers practical advantages, including faster examination times that increase patient throughput and reduce costs compared to MRI. A significant technical benefit is that its low-energy images, acquired during the same procedure, provide diagnostic information equivalent to conventional FFDM, including the critical assessment of microcalcifications (15,16). Microcalcification formation is an active, cell-mediated process that reflects the pathway of calcification deposition along necrotic ducts or tumor cell nests. It serves as a direct morphological indicator of tumor structural destruction and abnormal mineral deposition. According to the ACR BI-RADS guidelines, the morphology and distribution of calcifications are critical diagnostic factors in evaluating the likelihood of malignancy (12). The positive predictive value (PPV) of coarse heterogeneous calcifications is approximately 15%, while the PPV of amorphous calcifications is approximately 20%. The PPV of pleomorphic calcifications is about 29%, and the PPV of fine linear and branching calcifications is approximately 70% (12). Based on these rates, the study conducted by Long et al. (8) classified the morphology of calcifications into two categories: high-risk types (including fine linear and branching calcifications) and low-risk types (including amorphous, coarse heterogeneous, and fine pleomorphic calcifications). This classification is consistent with the results of our ROC analysis. Additionally, Long et al. (8) also classified the distribution of calcifications into two categories: high-risk type (including linear and segmental calcifications) and low-risk type (including regional and grouped calcifications). However, grouped/clustered calcifications, defined as the presence of at least five calcifications within a cubic centimeter of tissue, are typically of intermediate concern regarding breast malignancy (17). In contrast to the aforementioned studies, our ROC analysis results classified the distribution of grouped or clustered calcifications as a high-risk type. Previous studies indicate that calcification formation is associated with a higher prevalence of intraductal cancers and necrosis, but not with invasive features or histological grade (18,19). Supporting these findings, as well as the results of Hua et al. (9), our analysis revealed no significant differences in the morphology or distribution of microcalcifications between invasive carcinoma and carcinoma in situ (P=0.78 and P=0.57, respectively).

Breast MRI, as an adjunct diagnostic tool, can be used to differentiate between benign and malignant mammographic microcalcifications. When the criterion of enhancement presence on MRI was applied to microcalcifications, the PPV increased to 58.5–82.0% (20,21). CEM utilizes iodinated contrast media and, similar to CE-MRI, can also provide supplementary information regarding enhancement resulting from cancer angiogenesis and perfusion (22). Cheung et al. (4) reported that using CEM enhancement significantly improved cancer prediction accuracy. The PPV was 46.15% for amorphous microcalcifications, while it reached 90% for pleomorphic microcalcifications. Our results indicate that, in addition to enhancement intensity [%RS(CC)], other enhancement descriptors—such as mTIC, enhancement morphological distribution, and internal enhancement pattern—were also independent predictors of malignant microcalcifications, with the AUCs ranging from 0.692 to 0.808. The biological characteristics of invasive breast carcinoma, particularly invasive ductal carcinoma, underlie its imaging features. The tumor promotes the formation of abundant, structurally abnormal, and highly permeable neovessels by secreting factors such as vascular endothelial growth factor. Simultaneously, activated cancer-associated fibroblasts contribute not only to fibrosis but also to the stimulation of angiogenesis. This dense yet immature neovascular network, combined with a pronounced peritumoral desmoplastic reaction, collectively influences the complex dynamic behavior of contrast agents within the lesion—resulting in either rapid inflow and outflow or delayed entry. These characteristics manifest as early rapid enhancement, a high percentage of relative signal change curve (%RS) values, and washout- or plateau-type time-intensity curves. Morphologically, high-grade ductal carcinoma in situ with microinvasion, as well as classic invasive ductal carcinoma, often exhibits a propensity for invasive growth along the ductal system. This growth pattern typically appears on imaging as a “ductal” or “segmental” enhancement pattern that follows the anatomical distribution of the ducts. Additionally, when central necrosis occurs within the lesion, the avascular necrotic core contrasts sharply with the surrounding well-vascularized rim of viable tumor cells, resulting in the characteristic imaging finding of rim or peripheral enhancement. Previous studies have indicated that the stronger enhancement intensity was positively correlated with cancer aggressiveness. Marzogi et al. (23) found that invasive carcinoma presented predominantly (61.8%) with distinct enhancement. Cheung et al. (24) found that IDC showed more enhanced masses (72.2% vs. 27.8%) and solid enhancement texture (83.33% vs. 16.67%) than pure DCIS for suspicious microcalcifications. Our results also indicated that %RS(CC) was an independent predictor of invasive carcinoma, with an AUC of 0.730, which is consistent with the aforementioned research.

Scholars have large disputes regarding the diagnostic performance of CEM compared to MG for breast calcifications. Houben et al. (25) showed that CEM only slightly improves the diagnostic accuracy of breast calcifications, which had no added value compared to MG [sensitivity: 93.8% vs. 90.3%; specificity: 36.6% vs. 39.0%; PPV: 54% vs. 54.1%; negative predictive value (NPV): 88.2% vs. 84.2%]. However, in the study by Long et al. (8), the PPV of CEM was significantly higher, and MDR was significantly lower compared to MG for low-risk morphology or distribution types (P<0.05). The NPV of CEM in our dataset was high (73.53%), indicating a significant advantage of this imaging modality. This suggests that if a lesion shows no enhancement on CEM, there is a very high probability that it is benign. These findings imply that CEM can effectively rule out malignancy in cases with suspicious calcifications on conventional MG but no associated contrast uptake. Besides, by employing a machine learning approach, the CEM radiomics model achieved a satisfying performance (AUC: 0.88), which is significantly better than that of MG (AUC: 0.78) (DeLong’s test: P=0.02) (8). Considering the complexity of feature extraction and data interpretation in radiomic models, we have established a straightforward, intuitive, and multiparametric diagnostic approach known as MCS. The MCS, which integrates microcalcifications and multiple enhancement features, demonstrated impressive performance (AUC: 0.908–0.930), significantly higher than that of BI-RADS (MG) (AUC: 0.678–0.679) and BI-RADS (MRI) (AUC: 0.724) (DeLong’s test: all P<0.050). The MCS is a clinically valuable tool for reducing misdiagnoses and unnecessary biopsies of non-mass microcalcifications.

Limitations

Several limitations of this study should be acknowledged. First, the retrospective, single-center design may have introduced selection bias. And the limited sample size and lack of external validation, the currently proposed MCS scale requires further validation in larger-scale, multicenter prospective cohorts before clinical adoption. Second, by design, cases presenting with masses accompanied by microcalcifications were excluded. This exclusion limits the generalizability of the MCS classification to such lesions, restricting its current applicability to pure non-mass microcalcifications. Third, patients identified with abnormalities through MG or ultrasound screenings were recommended for CEM or MRI in clinical practice. Most patients in this study were complex cases detected through MG or ultrasound screenings, which introduced bias in the initial selection process. However, for breast non-mass microcalcifications originating from community health centers that did not implement any screening, the diagnostic accuracy of the MCS may have been underestimated. Therefore, a large cohort of breast non-mass microcalcifications from community health centers is needed to validate the diagnostic accuracy of MCS. Finally, microcalcification is not merely a “sign” on imaging but a complex biomarker that reflects local tumor biology, microenvironmental interactions, and potential invasiveness. A comprehensive understanding of its biophysical, morphological, and molecular characteristics, combined with automated analytical technologies, is expected to facilitate earlier and more accurate breast cancer diagnosis and risk stratification in the future.

Conclusions

The MCS system provides superior diagnostic performance for non-mass microcalcifications compared to BI-RADS (MG) and BI-RADS (MRI), due to its integrated analysis of calcifications and enhancement features. Its clinical application helps reduce diagnostic uncertainty and decreases the rate of unnecessary biopsies.

Acknowledgments

We would like to express our gratitude to all those who helped us during the writing of this thesis.

Footnote

Reporting Checklist: The authors have completed the STARD reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1-2579/rc

Data Sharing Statement: Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1-2579/dss

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1-2579/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of The Fourth Hospital of Hebei Medical University (No. 2023KS083) and informed consent for this retrospective analysis was waived.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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