The clinical value of detecting microcalcifications on a mammogram

Tot, Tibor; Gere, Mária; Hofmeyer, Syster; Bauer, Annette; Pellas, Ulrika

doi:10.1016/j.semcancer.2019.10.024

Cited by 46 publications

(42 citation statements)

References 60 publications

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“…5 In contrast, the formation of benign microcalcifications are considered to be explained by cell necrosis and debris. 6 The few studies that have attempted to investigate predictors of microcalcifications [7][8][9][10][11][12][13][14] have important limitations, such as including only breast cancer cases, 9,11,12 using case-control or case-report study designs rather than prospective cohort design, 7,9,11,12 using a qualitative and crude measure of microcalcifications (Breast Imaging-Reporting and Data System [BI-RADS score]), 9,11,12 or inability to exclude breast arterial calcifications. 7,8,10,13,14 Breast arterial calcifications are potential surrogate marker of atherosclerotic cardiovascular disease but are not associated with breast cancer.…”

Section: Introductionmentioning

confidence: 99%

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Predictors of mammographic microcalcifications

Azam

Eriksson

Sjölander

et al. 2020

Intl Journal of Cancer

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We examined the association between established risk factors for breast cancer and microcalcification clusters and their asymmetry. A cohort study of 53 273 Swedish women aged 30 to 80 years, with comprehensive information on breast cancer risk factors and mammograms, was conducted. Total number of microcalcification clusters and the average mammographic density area were measured using a Computer Aided Detection system and the STRATUS method, respectively. A polygenic risk score for breast cancer, including 313 single nucleotide polymorphisms, was calculated for those women genotyped (N = 7387). Odds ratios (ORs) and 95% confidence intervals (CIs), with adjustment for potential confounders, were estimated. Age was strongly associated with microcalcification clusters. Both high mammographic density (>40 cm2), and high polygenic risk score (80‐100 percentile) were associated with microcalcification clusters, OR = 2.08 (95% CI = 1.93‐2.25) and OR = 1.22 (95% CI = 1.06‐1.48), respectively. Among reproductive risk factors, life‐time breastfeeding duration >1 year was associated with microcalcification clusters OR = 1.22 (95% CI = 1.03‐1.46). The association was confined to postmenopausal women. Among lifestyle risk factors, women with a body mass index ≥30 kg/m2 had the lowest risk of microcalcification clusters OR = 0.79 (95% CI = 0.73‐0.85) and the association was stronger among premenopausal women. Our results suggest that age, mammographic density, genetic predictors of breast cancer, having more than two children, longer duration of breast‐feeding are significantly associated with increased risk of microcalcification clusters. However, most lifestyle risk factors for breast cancer seem to protect against presence of microcalcification clusters. More research is needed to study biological mechanisms behind microcalcifications formation.

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Section: Introductionmentioning

confidence: 99%

“…It has been hypothesized that epithelial cells that acquire mesenchymal characteristics become capable of producing breast microcalcifications 5 . In contrast, the formation of benign microcalcifications are considered to be explained by cell necrosis and debris 6 …”

Section: Introductionmentioning

confidence: 99%

Predictors of mammographic microcalcifications

Azam

Eriksson

Sjölander

et al. 2020

Intl Journal of Cancer

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“…The SBCT scanner was equipped with a cadmium telluride photon-counting detector (AB-CT: Advanced Breast-CT GmbH, in cooperation with Direct Conversion Group, Erlangen, Germany). The detector had a pixel size of (0.1 mm) 2 and converted x-ray photons directly into electric charge. X-ray generation was performed at a fixed tube voltage of 60 kV and a focal spot size of 0.3.…”

Section: Imaging Techniquementioning

confidence: 99%

“…A study coordinator evaluated each quadrant in FFDM for the presence of MCs, type of MC (cluster, diffuse), maximum diameter of diffuse microcalcifications within a quadrant, and long and short diameter of a whole cluster (Figure 3). For this study, a cluster was individually defined as ≥ 4 microcalcifications within an area less than (0.1 cm) 2 . This definition of a cluster appeared to be useful in this experimental setting for distinguishing between singular and grouped microcalcifications, since grouped microcalcifications are associated with a higher rate of precancerous lesions [23].…”

Section: Reference Standardmentioning

confidence: 99%

“…Their importance for the detection of malignant breast lesions is well known. In a review of the Swedish screening program, 74% of ductal carcinomas in situ (DCIS) and 30% of invasive breast cancers were associated with microcalcifications [ 2 ]. Furthermore, in 32% of cases, microcalcifications are the only imaging feature of invasive breast cancer or DCIS [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2021

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

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Clinical and pathological features analysis of invasive breast cancer with microcalcification

Tian

Gui

et al. 2023

Cancer Medicine

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Purpose Microcalcification (MC) is a valuable diagnostic indicator to detect invasive breast cancer (IBC). This study aimed to determine the clinicopathological features of IBC with MC and detect biomarkers related to the potential mechanism of the MC formation in IBC. Methods Data from 364 patients with IBC were collected for the clinical characteristic analysis. The analysis of clinical data helped us to establish a predictive model of axillary node metastasis (ANM) before surgery. In addition, 49 tissue samples of IBC patients were collected to test the protein levels of osteocalcin (OCN) and hypoxia‐inducible factor‐1α (HIF‐1α) by immunohistochemistry. Results Significant differences were observed in tumor size, age, ANM, HER2+, TNM stage, and mutant P53 between samples from IBC patients with MC and samples from IBC patients without MC. Younger age, a larger tumor size, a higher number of childbirths, and MC were independent predictors for ANM in IBC. HIF‐1α protein level was higher in tumor tissue than in normal tissue. High protein levels of OCN and HIF‐1α are related to the complication of MC in IBC. Of the patients that exhibited high HIF‐1α protein levels, the percentage of high OCN protein levels was larger in patients with ANM. Conclusion Based on this study, we concluded that patients with MC had a comparatively poor prognosis. MC was an independent predictive factor associated with the risk of ANM. High protein levels of OCN and HIF‐1α were associated with MC and ANM, which were also related to poor prognosis. OCN and HIF‐1α had a positive correlation in IBC.

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The clinical value of detecting microcalcifications on a mammogram

Cited by 46 publications

References 60 publications

Predictors of mammographic microcalcifications

Predictors of mammographic microcalcifications

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

Clinical and pathological features analysis of invasive breast cancer with microcalcification

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