Breast Calcifications Research Articles

Evaluation of Breast Calcification, Calcification Characteristics and BI-RADS (Breast Imaging-Reporting and Data System) Categories in Patients with Primary Hyperparathyroidism

Searchable abstracts of presentations at key conferences in endocrinology ISSN 1470-3947 (print) | ISSN 1479-6848 (online)

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.

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. 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. 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%). 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.

Abstract 5561: Molecular imaging of calcification and soft tissue defines prognosis of DCIS to invasive breast cancer

Abstract Introduction: Ductal carcinoma in situ (DCIS) is a non-obligatory precursor to invasive breast cancer (IBC). Currently there are no reliable markers to indicate if DCIS will progress IBC after an initial treatment, or if it will remain as DCIS. Because of this uncertainty, standard treatment for DCIS includes surgery with or without radiotherapy. Breast microcalcifications are a common feature in the mammographic detection of DCIS and occur in around 80% of DCIS and 50% of IBC. Despite this, their potential role in the development of DCIS and with progression to IBC remains largely unexplored. The main aim of the study is to identify novel biomarkers for DCIS prognosis, based on chemical and molecular compositional changes of calcifications and their surrounding soft tissue in DCIS. Methods: Consecutive tissue section from 422 patients were analyzed using mid-infrared and Raman hyperspectral imaging and X-ray diffraction (XRD) and included (i) ‘DCIS controls’ (DCIS without recurrence) (n=193), (ii) ‘DCIS cases’ (DCIS which subsequently recurred as an invasive disease) (n=123), (iii) ‘synchronous DCIS with invasive cancer’ (n=44) and ‘benign’ (n=62) groups. Both parametrized and data mining approaches including cluster analysis, unsupervised and supervised multivariate statistical analysis and biomodelling based on leave-one-sample-out cross-validation were used to classify the data and develop DCIS prediction models. Results: Prediction modelling of 314 calcification and soft tissue spectral images from 170 patients (‘DCIS controls’=118 versus ‘DCIS cases’=52) showed an AUROC mean value of 0.85 in distinguishing DCIS that did not recur from DCIS that recurred as IBC. Prediction modelling of XRD data from 124 patients (‘DCIS controls’=67 versus ‘DCIS cases’=57) showed an AUROC mean value of 0.80. The calcification spectral features showed pathology specific changes in phosphate to carbonate ratio as well as changes in magnesium whitlockite content. The epithelial features showed changes in protein secondary structure and content indicating structural remodeling between the two groups. XRD parametrized data analysis corroborated these observations in terms of difference in whitlockite, as well as crystallinity/unit axis of the measured calcifications. The prediction models are currently being tested independently on the remaining sample data. Conclusion: Complementary chemical and molecular analysis of breast calcifications and soft tissue using spectroscopy and XRD imaging predicts the likely progression of DCIS to IBC. Subject to the ongoing validation of biomarkers, these approaches appear as promising DCIS risk assessment tools that can inform diagnosis, prognosis and treatment options. Citation Format: Jayakrupakar Nallala, Doriana Calabrese, Sarah Gosling, Esther Lips, Rachel Factor, Allison Hall, Sarah Pinder, Ihssane Bouybayoune, Elinor Sawyer, Lorraine King, Jeffrey Marks, Thomas Lynch, Donna Pinto, Jelle Wesseling, Shelley Hwang, Keith Rogers, Nick Stone, Grand Challenge PRECISION consortium. Molecular imaging of calcification and soft tissue defines prognosis of DCIS to invasive breast cancer. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5561.

Role of Ultrasound and Ultrasound Guided Interventional Procedures in the Evaluation of Mammographically Detected Breast Calcifications

Background: Breast calcifications may be the sole observable indicator of early breast cancer, making them a significant finding on a mammography. This research aimed to evaluate the usefulness of ultrasonography and ultrasound-guided interventional treatments in the assessment of breast calcification diagnosed by mammography. Methods: This investigation was done on thirty individuals whose mammograms revealed worrisome microcalcifications. Each patient had a comprehensive history, physical examination, laboratory analysis, mammography, ultrasound, core biopsy under sonographic guidance, and guide wire localisation under sonographic direction. Twenty patients got ultrasound-guided breast biopsies, and ten patients had ultrasound-guided wire localisation. Results: 75 percent of the 20 lesions that underwent guided biopsy were diagnosed sonographically as masses, while the other lesions were classified as parenchymal distortions or calcifications. 75% of the cases were malignant, whereas 25% were benign lesions. In 7/10 (70%) instances, wire localization was successful; in 2 cases, the wire reached the posterior side of the lesion but did not transfix it, and in 1 case, the wire reached only the anterior aspect of the lesion. Conclusions: Based on the findings of the current investigation, we have shown that targeted US is an excellent tool for the characterisation of microcalcification observed on mammography and may be useful for predicting invasive breast tumours. Sonographically detectable microcalcifications appear as small echogenic, non-shading foci, particularly if they are coupled with sonographic hypoechoic lesions.

Amorphous breast calcifications: is BI-RADS 4a appropriate?

Resumo Objetivo: Avaliar o valor preditivo positivo (VPP) das calcificações amorfas e possíveis variáveis clínicas e de imagem que possam influenciar no risco de malignidade deste achado de imagem. Materiais e Métodos: Foram revisados, retrospectivamente, 138 resultados de biópsias percutâneas estereotáxicas a vácuo de calcificações amorfas, entre janeiro de 2012 e dezembro de 2017. Todas as pacientes incluídas apresentavam seguimento radiológico mínimo de um ano (histopatológico benigno) ou tratamento cirúrgico (histopatológico maligno). Resultados: O VPP das calcificações amorfas foi de 9,42%. As lesões malignas corresponderam predominantemente a carcinomas invasivos, indicando doença clinicamente relevante. O risco relativo de malignidade das calcificações amorfas foi 6,15 vezes maior em pacientes com história familiar ou pessoal de neoplasia de mama ou ovário. Status pós-menopausa e mamas densas não foram preditores de malignidade nessas pacientes. Conclusão: As calcificações amorfas na mama apresentaram VPP de malignidade de 9,42%, sugerindo possibilidade de classificação do achado na subcategoria 4a, com necessidade de investigação histopatológica. Em pacientes com história familiar ou pessoal de câncer de mama, o risco de malignidade deste subtipo de calcificações pode ser até 6,15 vezes maior, justificando maior preocupação na correlação clínica, radiológica e histopatológica após biópsia.

Injection mammoplasty: Normal imaging appearances, complications, and implications for mammographic screening.

The normal imaging appearances of the common agents used in injection mammoplasty and the challenges of mammography screening will be reviewed. The local database from a tertiary hospital was accessed for imaging cases of injection mammoplasty. Free silicone is seen as multiple high-density opacities on mammograms. Silicone deposits can often be seen within axillary nodes due to lymphatic migration. Sonographically, a snowstorm appearance is seen when the silicone is diffusely distributed. On MRI, free silicone is hypointense on T1-weighted and hyperintense on T2-weighted images, with no contrast enhancement. Mammograms have a limited role in screening due to the high density of silicone. MRI is often required in these patients.Polyacrylamide gel and hyaluronic acid are seen as multiple collections on mammography. Polyacrylamide gel collections are of the same density as cysts, while hyaluronic acid collections are of higher density but less dense than silicone. On ultrasound, both can appear anechoic or show variable internal echoes. MRI demonstrates fluid signal with hypointense T1-weighted and hyperintense T2-weighted signal. Mammographic screening is possible if the injected material is located predominantly in the retro-glandular space without obscuring the breast parenchyma.On mammograms, autologous fat locules appear as lucent masses. Rim calcification can be seen if fat necrosis had developed. On ultrasound, focal fat collections can demonstrate varying levels of internal echogenicity, depending on the stage of fat necrosis. Mammographic screening is usually possible for patients after autologous fat injection as fat is hypodense compared to breast parenchyma. However, the dystrophic calcification associated with fat necrosis may mimic abnormal breast calcification. In such cases, MRI can be utilized as a problem-solving tool. It is important for the radiologist to recognize the type of injected material on the various imaging modalities and recommend the best modality for screening.

The Prospects of Using Structural Phase Analysis of Microcalcifications in Breast Cancer Diagnostics.

The detection of microcalcifications in the breast by mammography is of great importance for the early diagnostics of breast cancer. This study aimed to establish the basic morphological and crystal-chemical properties of microscopic calcifications and their impact on breast cancer tissue. During the retrospective study, 55 out of 469 breast cancer samples had microcalcifications. The expression of the estrogen and progesterone receptors and Her2-neu showed no significant difference from the non-calcified samples. An in-depth study of 60 tumor samples revealed a higher expression of osteopontin in the calcified breast cancer samples (p ˂ 0.01). The mineral deposits had a hydroxyapatite composition. Within the group of calcified breast cancer samples, we detected six cases of colocalization of oxalate microcalcifications together with biominerals of the usual "hydroxyapatite" phase composition. The simultaneous presence of calcium oxalate and hydroxyapatite was accompanied by a different spatial localization of microcalcifications. Thus, the phase compositions of microcalcifications could not be used as criteria for the differential diagnostics of breast tumors.

Cone-beam breast CT-guided surface location facilitates breast-conserving surgery in breast cancer patients with extensive calcifications: A pilot study.

Extensive malignant-appearing calcifications have traditionally been considered a contraindication for breast-conserving surgery. The evaluation of calcifications largely depends on mammography, which is limited by tissue superimposition and is unable to reveal spatial information about extensive calcifications. Three-dimensional imaging modality is needed to reveal the architecture of extensive calcifications. In the present study, a novel cone-beam breast CT-guided surface location technique was investigated to facilitate breast-conserving surgery in breast cancer patients with extensive malignant breast calcifications. Biopsy-proved early breast cancer patients with extensive malignant-appearing breast calcifications were included. A patient will be considered suitable for breast-conserving surgery if the spatial segmental distribution of calcifications is found by 3D images of cone-beam breast CT. Then, the margins of the calcifications were located in contrast-enhanced cone-beam breast CT images. Next, skin markers were located using radiopaque materials, and cone-beam breast CT was reperformed to confirm the accuracy of surface location. During breast-conserving surgery, lumpectomy was performed according to the previous surface location, and an intraoperative specimen x-ray was applied to double-check that the entire lesion was removed. Margin assessment was made for both intraoperative frozen section and postoperative pathology examination. From May 2019 to Jun 2022, 11 eligible breast cancer patients in our institution were included. Breast-conserving surgery was performed successfully in all patients using the surface location approach mentioned before. All patients achieved negative margins and satisfied cosmetic results. This study proved the feasibility of cone-beam breast CT-guided surface location for facilitating breast-conserving surgery in breast cancer patients with extensive malignant breast calcifications.

QSM Throughout the Body.

Magnetic materials in tissue, such as iron, calcium, or collagen, can be studied using quantitative susceptibility mapping (QSM). To date, QSM has been overwhelmingly applied in the brain, but is increasingly utilized outside the brain. QSM relies on the effect of tissue magnetic susceptibility sources on the MR signal phase obtained with gradient echo sequence. However, in the body, the chemical shift of fat present within the region of interest contributes to the MR signal phase as well. Therefore, correcting for the chemical shift effect by means of water-fat separation is essential for body QSM. By employing techniques to compensate for cardiac and respiratory motion artifacts, body QSM has been applied to study liver iron and fibrosis, heart chamber blood and placenta oxygenation, myocardial hemorrhage, atherosclerotic plaque, cartilage, bone, prostate, breast calcification, and kidney stone.

Role of ultrasound and ultrasound guided biopsy in the evaluation of mammographically proved breast calcifications

Role of ultrasound and ultrasound guided biopsy in the evaluation of mammographically proved breast calcifications

Breast Calcifications and Histopathological Analysis on Tumour Detection by CNN

The most salient argument that needs to be addressed universally is Early Breast Cancer Detection (EBCD), which helps people live longer lives. The Computer-Aided Detection (CADs)/Computer-Aided Diagnosis (CADx) system is indeed a software automation tool developed to assist the health professions in Breast Cancer Detection and Diagnosis (BCDD) and minimise mortality by the use of medical histopathological image classification in much less time. This paper purposes of examining the accuracy of the Convolutional Neural Network (CNN), which can be used to perceive breast malignancies for initial breast cancer detection to determine which strategy is efficient for the early identification of breast cell malignancies formation of masses and Breast microcalcifications on the mammogram. When we have insufficient data for a new domain that is desired to be handled by a pre-trained Convolutional Neural Network of Residual Network (ResNet50) for Breast Cancer Detection and Diagnosis, to obtain the Discriminative Localization, Convolutional Neural Network with Class Activation Map (CAM) has also been used to perform breast microcalcifications detection to find a specific class in the Histopathological image. The test results indicate that this method performed almost 225.15% better at determining the exact location of disease (Discriminative Localization) through breast microcalcifications images. ResNet50 seems to have the highest level of accuracy for images of Benign Tumour (BT)/Malignant Tumour (MT) cases at 97.11%. ResNet50’s average accuracy for pre-trained Convolutional Neural Network is 94.17%.

Efficient breast cancer detection via cascade deep learning network

Breast calcifications or irregular tissue growth are major health concerns that can lead to breast cancer. To enable early management, which significantly lowers death rates, it is crucial to perform screening and determine if a tumor is benign or malignant. Building a cascade network model that bases predictions on the shape, pattern, and spread of the tumor is how this research approaches the challenge. Pre-processing of images, followed by segmentation and classification, are common methods to accomplish this. The strategy in this research employs a cascade network with UNet architecture for segmentation with a ResNet backbone for classification. To enable classification to make predictions, segmentation process involves separating tumor from the image in the form of a mask. The segmentation model's F1-score measurement came out to be 97.30%. The final decision-making layer's neural network is a straightforward 8-layer network, which follows the ResNet50 model. The proposed model's classification accuracy was 98.61%, with F1 score of 98.41%. Comparative evaluations are conducted together with the comprehensive experimental results.

The Role of Calcium in Non-Invasively Imaging Breast Cancer: An Overview of Current and Modern Imaging Techniques.

The landscape of breast cancer diagnostics has significantly evolved over the past decade. With these changes, it is possible to provide a comprehensive assessment of both benign and malignant breast calcifications. The biochemistry of breast cancer and calcifications are thoroughly examined to describe the potential to characterize better different calcium salts composed of calcium carbonate, calcium oxalate, or calcium hydroxyapatite and their associated prognostic implications. Conventional mammographic imaging techniques are compared to available ones, including breast tomosynthesis and contrast-enhanced mammography. Additional methods in computed tomography and magnetic resonance imaging are discussed. The concept of using magnetic resonance imaging particularly magnetic susceptibility to characterize the biochemical characteristics of calcifications is described. As we know magnetic resonance imaging is safe and there is no ionization radiation. Experimental findings through magnetic resonance susceptibility imaging techniques are discussed to illustrate the potential for integrating this technique to provide a quantitative assessment of magnetic susceptibility. Under the right magnetic resonance imaging conditions, a distinct phase variability was isolated amongst different types of calcium salts.

Morphological and Distribution Pattern of Calcifications on Full Field Digital Mammography versus Digital Breast Tomosynthesis and Comparison of Diagnostic Abilities of the Two Modalities: A Retrospective Study

Introduction: Microcalcification (MC) is an effective and sometimes the only indicator of breast cancer. Early detection and characterisation of malignant MC can facilitate early diagnosis and timely treatment of breast cancer. However, due to the small size and low contrast as compared to the background parenchyma, it is difficult and time-consuming for radiologists to accurately evaluate MC. Aim: To compare the diagnostic abilities of Full Field Digital Mammography (FFDM) and Digital Breast Tomosynthesis (DBT) in the detection and characterisation of breast calcifications. Materials and Methods: This retrospective descriptive study was conducted in the year 2022 at the breast imaging unit of Dr. Ram Manohar Lohia Institute of Medical Sciences, Lucknow, Uttar Pradesh, India and data of patients who had undergone FFDM and DBT between March 2019- September 2020 was collected. Mammograms of 702 women with 1217 breasts were evaluated and MC was detected in 622 breasts. Based on the morphology and distribution pattern, Breast Imaging Reporting and Data System (BI-RADS) assessment Category was assigned from 2 to 5. Cases with BI-RADS 2 and 3 were followed-up by repeat Mammograms at 6-month to 1-year intervals. Cases with BI-RADS 4 and 5 were biopsied under stereotactic or ultrasound guidance. Histopathology findings and the stability of the calcifications on sequential mammograms were considered the gold standard for final BI-RADS categorisation. The Chi-square test was applied for the comparison of FFDM and DBT. Results: Typically benign morphology MC was noted in 508 (81.67%) of breasts on FFDM and 505 (80.67%) on DBT. Suspicious morphology MC was noted in 114 (18.33%) of breasts on FFDM and 121 (19.33%) on DBT. Vascular calcification was the most common benign MC seen in 233 cases (37.45%) on FFDM and 244 cases (38.9%) on DBT. Similarly, fine pleomorphic was the most common suspicious morphology MC on FFDM and DBT both seen in 47 cases (7.5%) and 44 cases (7.02%), respectively. The most common distribution pattern was diffuse seen in 582 cases (93.56%) on FFDM and 583 cases (93.13%) on DBT, respectively. No significant difference was observed (p=0.283) in the rate of detection or characterisation of MC by FFDM or DBT. The sensitivity of both modalities were almost similar (97.7% and 97.9%) without any significant difference (p=0.278). Similarly, there was no difference in the specificity (94.9% and 94.4%, respectively, p=0.289). Conclusion: The performance of FFDM and DBT for the detection and characterisation of MC is not significantly different.

Breast Cancer Detection Using Automated Segmentation and Genetic Algorithms.

Breast cancer is the most common cancer among women worldwide, after lung cancer. However, early detection of breast cancer can help to reduce death rates in breast cancer patients and also prevent cancer from spreading to other parts of the body. This work proposes a new method to design a bio-marker integrating Bayesian predictive models, pyRadiomics System and genetic algorithms to classify the benign and malignant lesions. The method allows one to evaluate two types of images: The radiologist-segmented lesion, and a novel automated breast cancer detection by the analysis of the whole breast. The results demonstrate only a difference of 12% of effectiveness for the cases of calcification between the radiologist generated segmentation and the automatic whole breast analysis, and a 25% of difference between the lesion and the breast for the cases of masses. In addition, our approach was compared against other proposed methods in the literature, providing an AUC = 0.86 for the analysis of images with lesions in breast calcification, and AUC = 0.96 for masses.

Application of Support Vector Machines for Breast Calcification Cluster Detection and Mass Classification

Breast cancer has become “the most common cancer worldwide”, and it is an urgent problem in the medical field to improve the detection rate of breast cancer through early diagnosis and treatment. Based on the current research on medical image processing, our work selects breast images from the MIAS database for pre-processing, segmentation, texture feature extraction and classification, and conducts an in-depth investigation and experimental validation on the theoretical basis of support vector machine algorithm, kernel function selection, and key parameter optimization. The results show the effectiveness of support vector machines in detecting abnormal areas and classifying masses in breast images and provide research ideas for breast cancer diagnosis.

Comparison of Diagnostic Mammography-Guided Biopsy and Digital Breast Tomosynthesis-Guided Biopsy of Suspicious Breast Calcifications: Results in 1354 Biopsies.

BACKGROUND. Studies have shown improved targeting and sampling of noncalcified lesions (asymmetries, masses, and architectural distortion) with digital breast tomosynthesis (DBT)-guided biopsy in comparison with digital mammography (DM)-guided stereotactic biopsy. Literature that compares the two techniques specifically for sampling calcifications has been scarce. OBJECTIVE. The purpose of this study was to compare the performance and outcomes of DM- and DBT-guided biopsy of suspicious calcifications. METHODS. This retrospective study included 1310 patients (mean age, 58 ± 12 [SD] years) who underwent a total of 1354 9-gauge vacuum-assisted core biopsies of suspicious calcifications performed at a single institution from May 22, 2017, to December 31, 2021. The decision to use a DM-guided or DBT-guided technique was made at the discretion of the radiologist performing the biopsy. Procedure time, the number of exposures during the procedure, and the histopathologic outcomes were recorded. The two techniques were compared using a two-sample t test for continuous variables and a chi-square test for categoric variables. Additional tests were performed using generalized estimating equations to control for the effect of the individual radiologist performing the biopsy. RESULTS. A total of 348 (26%) biopsies used DM guidance, and 1006 (74%) used DBT guidance. The mean procedure time was significantly lower for DBT-guided biopsy (14.9 ± 8.0 [SD] minutes) than for DM-guided biopsy (24.7 ± 14.3 minutes) (p < .001). The mean number of exposures was significantly lower for DBT-guided biopsy (4.1 ± 1.0 [SD] exposures) than for DM-guided biopsy (9.1 ± 3.3 exposures) (p < .001). The differences in procedure time and number of exposures remained significant (both p < .001) when controlling for the effect of the radiologist performing the biopsy. There were no significant differences (all p > .05) between DM-guided and DBT-guided biopsy in terms of the malignancy rate on initial biopsy (20% vs 19%), the rate of high-risk lesion upgrading (14% vs 22%), or the final malignancy rate (23% vs 22%). CONCLUSION. DBT-guided biopsy of suspicious calcifications can be performed with shorter procedure time and fewer exposures compared with DM-guided biopsy, without a significant difference in rates of malignancy or high-risk lesion upgrading. CLINICAL IMPACT. The use of a DBT-guided, rather than a DM-guided, biopsy technique for suspicious calcifications can potentially reduce patient discomfort and radiation exposure without affecting clinical outcomes.

Dystrophic breast calcifications in a patient with dermatomyositis

Dystrophic breast calcifications in a patient with dermatomyositis

Breast calcification micromorphology classification.

The importance of consistent terminology in describing the appearance of breast calcifications in mammography is well recognised. Imaging of calcifications using electron microscopy is a globally growing field of research. We therefore suggest that the time is ripe to develop a lexicon of terms for classifying the micromorphology of breast calcifications. Calcifications within a wide range of histological sections of breast tissue, both benign and malignant, were imaged by Scanning Electron Microscopy (SEM). These images were examined, and the micromorphology of calcifications present was grouped to create a classification system. Based on the appearance of the calcifications observed, we propose five main categories for classification of the micromorphology of breast calcifications, namely, Dense Homogenous, Punctulate, Banded, Spongy and Aggregate. Use of the descriptive categories outlined here will help to ensure consistency and comparability of published observations on the micromorphology of breast calcifications. This is the first time a lexicon and classification system has been proposed for the micromorphology of breast calcifications, as observed by scanning electron microscopy of histological sections. This will facilitate comparability of observed relationships between micromorphology, mammographic appearance, chemistry and pathology.

Visual bias could impede diagnostic accuracy of breast cancer calcifications.

Purpose: Diagnosing breast cancer based on the distribution of calcifications is a visual task and thus prone to visual biases. We tested whether a recently discovered visual bias that has implications for breast cancer diagnosis would be present in expert radiologists, thereby validating the concern of this bias for accurate diagnoses. Approach: We ran a vision experiment with expert radiologists and untrained observers to test the presence of visual bias when judging the spread of dots that resembled calcifications and when judging the spread of line orientations. We calculated visual bias scores for both groups for both tasks. Results: Participants overestimated the spread of the dots and the spread of the line orientations. This bias, referred to as the variability overestimation effect, was of similar magnitudes in both expert radiologists and untrained observers. Even though the radiologists were better at both tasks, they were similarly biased compared with the untrained observers. Conclusions: The results justify the concern of the variability overestimation effect for accurate diagnoses based on breast calcifications. Specifically, the bias is likely to lead to an increased number of false-negative results, thereby leading to delayed treatments.