Assessment of Background Parenchymal Enhancement at Dynamic Contrast-enhanced MRI in Predicting Breast Cancer Recurrence Risk.

Background Background parenchymal enhancement (BPE) at dynamic contrast-enhanced (DCE) MRI of cancer-free breasts increases the risk of developing breast cancer; implications of quantitative BPE in ipsilateral breasts with breast cancer are largely unexplored. Purpose To determine whether quantitative BPE measurements in one or both breasts could be used to predict recurrence risk in women with breast cancer, using the Oncotype DX recurrence score as the reference standard. Materials and Methods This HIPAA-compliant retrospective single-institution study included women diagnosed with breast cancer between January 2007 and January 2012 (development set) and between January 2012 and January 2017 (internal test set). Quantitative BPE was automatically computed using an in-house-developed computer algorithm in both breasts. Univariable logistic regression was used to examine the association of BPE with Oncotype DX recurrence score binarized into high-risk (recurrence score >25) and low- or intermediate-risk (recurrence score ≤25) categories. Models including BPE measures were assessed for their ability to distinguish patients with high risk versus those with low or intermediate risk and the actual recurrence outcome. Results The development set included 127 women (mean age, 58 years ± 10.2 [SD]; 33 with high risk and 94 with low or intermediate risk) with an actual local or distant recurrence rate of 15.7% (20 of 127) at a minimum 10 years of follow-up. The test set included 60 women (mean age, 57.8 years ± 11.6; 16 with high risk and 44 with low or intermediate risk). BPE measurements quantified in both breasts were associated with increased odds of a high-risk Oncotype DX recurrence score (odds ratio range, 1.27-1.66 [95% CI: 1.02, 2.56]; P < .001 to P = .04). Measures of BPE combined with tumor radiomics helped distinguish patients with a high-risk Oncotype DX recurrence score from those with a low- or intermediate-risk score, with an area under the receiver operating characteristic curve of 0.94 in the development set and 0.79 in the test set. For the combined models, the negative predictive values were 0.97 and 0.93 in predicting actual distant recurrence and local recurrence, respectively. Conclusion Ipsilateral and contralateral DCE MRI measures of BPE quantified in patients with breast cancer can help distinguish patients with high recurrence risk from those with low or intermediate recurrence risk, similar to Oncotype DX recurrence score. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Zhou and Rahbar in this issue.

Addition of Contrast-enhanced Mammography to Tomosynthesis for Breast Cancer Detection in Women with a Personal History of Breast Cancer: Prospective TOCEM Trial Interim Analysis.

Background Digital breast tomosynthesis (DBT) is often inadequate for screening women with a personal history of breast cancer (PHBC). The ongoing prospective Tomosynthesis or Contrast-Enhanced Mammography, or TOCEM, trial includes three annual screenings with both DBT and contrast-enhanced mammography (CEM). Purpose To perform interim assessment of cancer yield, stage, and recall rate when CEM is added to DBT in women with PHBC. Materials and Methods From October 2019 to December 2022, two radiologists interpreted both examinations: Observer 1 reviewed DBT first and then CEM, and observer 2 reviewed CEM first and then DBT. Effects of adding CEM to DBT on incremental cancer detection rate (ICDR), cancer type and node status, recall rate, and other performance characteristics of the primary radiologist decisions were assessed. Results Among the participants (mean age at entry, 63.6 years ± 9.6 [SD]), 1273, 819, and 227 women with PHBC completed year 1, 2, and 3 screening, respectively. For observer 1, year 1 cancer yield was 20 of 1273 (15.7 per 1000 screenings) for DBT and 29 of 1273 (22.8 per 1000 screenings; ICDR, 7.1 per 1000 screenings [95% CI: 3.2, 13.4]) for DBT plus CEM (P < .001). Year 2 plus 3 cancer yield was four of 1046 (3.8 per 1000 screenings) for DBT and eight of 1046 (7.6 per 1000 screenings; ICDR, 3.8 per 1000 screenings [95% CI: 1.0, 7.6]) for DBT plus CEM (P = .001). Year 1 recall rate for observer 1 was 103 of 1273 (8.1%) for (incidence) DBT alone and 187 of 1273 (14.7%) for DBT plus CEM (difference = 84 of 1273, 6.6% [95% CI: 5.3, 8.1]; P < .001). Year 2 plus 3 recall rate was 40 of 1046 (3.8%) for DBT and 92 of 1046 (8.8%) for DBT plus CEM (difference = 52 of 1046, 5.0% [95% CI: 3.7, 6.3]; P < .001). In 18 breasts with cancer detected only at CEM after integration of both observers, 13 (72%) cancers were invasive (median tumor size, 0.6 cm) and eight of nine (88%) with staging were N0. Among 1883 screenings with adequate reference standard, there were three interval cancers (one at the scar, two in axillae). Conclusion CEM added to DBT increased early breast cancer detection each year in women with PHBC, with an accompanying approximately 5.0%-6.6% recall rate increase. Clinical trial registration no. NCT04085510 © RSNA, 2024 Supplemental material is available for this article.

Upgrade Rates of Variant Lobular Carcinoma In Situ Compared to Classic Lobular Carcinoma In Situ Diagnosed in Core Needle Biopsies: A 10-Year Single Institution Retrospective Study.

The primary aim of this study was to determine the upgrade rates of variant lobular carcinoma in situ (V-LCIS, ie, combined florid [F-LCIS] and pleomorphic [P-LCIS]) compared with classic LCIS (C-LCIS) when diagnosed on core needle biopsy (CNB). The secondary goal was to determine the rate of progression/development of invasive carcinoma on long-term follow-up after primary excision. After institutional review board approval, our institutional pathology database was searched for patients with "pure" LCIS diagnosed on CNB who underwent subsequent excision. Radiologic findings were reviewed, radiologic-pathologic (rad-path) correlation was performed, and follow-up patient outcome data were obtained. One hundred twenty cases of LCIS were identified on CNB (C-LCIS = 97, F-LCIS = 18, and P-LCIS = 5). Overall upgrade rates after excision for C-LCIS, F-LCIS, and P-LCIS were 14% (14/97), 44% (8/18), and 40% (2/5), respectively. Of the total cases, 79 (66%) were deemed rad-path concordant. Of these, the upgrade rate after excision for C-LCIS, F-LCIS, and P-LCIS was 7.5% (5 of 66), 40% (4 of 10), and 0% (0 of 3), respectively. The overall upgrade rate for V-LCIS was higher than for C-LCIS (P = .004), even for the cases deemed rad-path concordant (P value: .036). Most upgraded cases (23 of 24) showed pT1a disease or lower. With an average follow-up of 83 months, invasive carcinoma in the ipsilateral breast was identified in 8/120 (7%) cases. Six patients had died: 2 of (contralateral) breast cancer and 4 of other causes. Because of a high upgrade rate, V-LCIS diagnosed on CNB should always be excised. The upgrade rate for C-LCIS (even when rad-path concordant) is higher than reported in many other studies. Rad-path concordance read, surgical consultation, and individualized decision making are recommended for C-LCIS cases. The risk of developing invasive carcinoma after LCIS diagnosis is small (7% with ∼7-year follow-up), but active surveillance is required to diagnose early-stage disease.

Artificial Intelligence for Breast Ultrasound: AJR Expert Panel Narrative Review.

Breast ultrasound is used in a wide variety of clinical scenarios, including both diagnostic and screening applications. Limitations of ultrasound, however, include its low specificity and, for automated breast ultrasound screening, the time necessary to review whole-breast ultrasound images. As of this writing, four AI tools that are approved or cleared by the FDA address these limitations. Current tools, which are intended to provide decision support for lesion classification and/or detection, have been shown to increase specificity among non-specialists and to decrease interpretation times. Potential future applications include triage of patients with palpable masses in low-resource settings, preoperative prediction of axillary lymph node metastasis, and preoperative prediction of neoadjuvant chemotherapy response. Challenges in the development and clinical deployment of AI for ultrasound include: the limited availability of curated training datasets compared to mammography; the high variability in ultrasound image acquisition due to equipment- and operator-related factors (which may limit algorithm generalizability); and the lack of post-implementation evaluation studies. Furthermore, current AI tools for lesion classification were developed based on 2D data, but diagnostic accuracy could potentially be improved if multimodal ultrasound data were used, such as color Doppler, elastography, cine clips, and 3D imaging.

Response in axillary lymph nodes to neoadjuvant chemotherapy for breast cancers: correlation with breast response, pathologic features, and accuracy of radioactive seed localization.

OBJECTIVES: This study examined the accuracy of radioactive seed localization (RSL) of lymph nodes (LNs) following neoadjuvant chemotherapy (NAC) for invasive breast carcinoma, recorded pathologic features of LNs following NAC, evaluated concordance of response between breast and LNs, and identified clinicopathologic factors associated with higher risk of residual lymph node involvement. METHODS: Clinical records, imaging, and pathology reports and slides were retrospectively reviewed for 174 breast cancer patients who received NAC. Chi-square and Fisher's exact tests were used to compare differences in risk of residual lymph node disease. RESULTS: Retrieval of biopsied pre-therapy positive LN was confirmed in 86/93 (88%) cases overall, and in 75/77 (97%) of cases utilizing RSL. Biopsy clip site was the best pathologic feature to confirm retrieval of a biopsied lymph node. Pre-therapy clinical N stage > 0, positive pre-therapy lymph node biopsy, estrogen and progesterone receptor positivity, Ki67 < 50%, HR + /HER2- tumors, and residual breast disease had higher likelihood of residual lymph node disease after NAC (p < 0.001). CONCLUSIONS: RSL-guided LN excision improves retrieval of previously biopsied LNs following NAC. The pathologist can use histologic features to confirm retrieval of targeted LNs, and tumor characteristics can be used to predict a higher risk of residual LN involvement.

Toward AI-supported US Triage of Women with Palpable Breast Lumps in a Low-Resource Setting.

Background Most low- and middle-income countries lack access to organized breast cancer screening, and women with lumps may wait months for diagnostic assessment. Purpose To demonstrate that artificial intelligence (AI) software applied to breast US images obtained with low-cost portable equipment and by minimally trained observers could accurately classify palpable breast masses for triage in a low-resource setting. Materials and Methods This prospective multicenter study evaluated participants with at least one palpable mass who were enrolled in a hospital in Jalisco, Mexico, from December 2017 through May 2021. Orthogonal US images were obtained first with portable US with and without calipers of any findings at the site of lump and adjacent tissue. Then women were imaged with standard-of-care (SOC) US with Breast Imaging Reporting and Data System assessments by a radiologist. After exclusions, 758 masses in 300 women were analyzable by AI, with outputs of benign, probably benign, suspicious, and malignant. Sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were determined. Results The mean patient age ± SD was 50.0 years ± 12.5 (range, 18-92 years) and mean largest lesion diameter was 13 mm ± 8 (range, 2-54 mm). Of 758 masses, 360 (47.5%) were palpable and 56 (7.4%) malignant, including six ductal carcinoma in situ. AI correctly identified 47 or 48 of 49 women (96%-98%) with cancer with either portable US or SOC US images, with AUCs of 0.91 and 0.95, respectively. One circumscribed invasive ductal carcinoma was classified as probably benign with SOC US, ipsilateral to a spiculated invasive ductal carcinoma. Of 251 women with benign masses, 168 (67%) imaged with SOC US were classified as benign or probably benign by AI, as were 96 of 251 masses (38%, P < .001) with portable US. AI performance with images obtained by a radiologist was significantly better than with images obtained by a minimally trained observer. Conclusion AI applied to portable US images of breast masses can accurately identify malignancies. Moderate specificity, which could triage 38%-67% of women with benign masses without tertiary referral, should further improve with AI and observer training with portable US. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Slanetz in this issue.

Deep learning of longitudinal mammogram examinations for breast cancer risk prediction.

Information in digital mammogram images has been shown to be associated with the risk of developing breast cancer. Longitudinal breast cancer screening mammogram examinations may carry spatiotemporal information that can enhance breast cancer risk prediction. No deep learning models have been designed to capture such spatiotemporal information over multiple examinations to predict the risk. In this study, we propose a novel deep learning structure, LRP-NET, to capture the spatiotemporal changes of breast tissue over multiple negative/benign screening mammogram examinations to predict near-term breast cancer risk in a case-control setting. Specifically, LRP-NET is designed based on clinical knowledge to capture the imaging changes of bilateral breast tissue over four sequential mammogram examinations. We evaluate our proposed model with two ablation studies and compare it to three models/settings, including 1) a "loose" model without explicitly capturing the spatiotemporal changes over longitudinal examinations, 2) LRP-NET but using a varying number (i.e., 1 and 3) of sequential examinations, and 3) a previous model that uses only a single mammogram examination. On a case-control cohort of 200 patients, each with four examinations, our experiments on a total of 3200 images show that the LRP-NET model outperforms the compared models/settings.

Breast Density and Risk of Interval Cancers: The Effect of Annual Versus Biennial Screening Mammography Policies in Canada.

Regular screening mammography reduces breast cancer mortality. However, in women with dense breasts, the performance of screening mammography is reduced, which is reflected in higher interval cancer rates (ICR). In Canada, population-based screening mammography programs generally screen women biennially; however, some provinces and territories offer annual mammography for women with dense breast tissue routinely and/or on recommendation of the radiologist. This study compared the ICRs in those breast screening programs with a policy of annual vs. those with biennial screening for women with dense breasts. Among 148,575 women with dense breasts screened between 2008 to 2010, there were 288 invasive interval breast cancers; screening programs with policies offering annual screening for women with dense breasts had fewer interval cancers 63/70,814 (ICR 0.89/1000, 95% CI: 0.67-1.11) compared with those with policies of usual biennial screening 225/77,761 (ICR 1.45 /1000 (annualized), 95% CI: 1.19-1.72) i.e. 63% higher (p = 0.0016). In screening programs where radiologists' screening recommendations were able to be analyzed, a total of 76,103 women were screened, with 87 interval cancers; the ICR was lower for recommended annual (65/69,650, ICR 0.93/1000, 95% CI: 0.71, 1.16) versus recommended biennial screening (22/6,453, ICR 1.70/1000 (annualized), 95%CI: 0.70, 2.71)(p = 0.0605). Screening program policies of annual as compared with biennial screening in women with dense breasts had the greatest impact on reducing interval cancer rates. We review our results in the context of current dense breast notification in Canada.

Cancer Yield Exceeds 2% for BI-RADS 3 Probably Benign Findings in Women Older Than 60 Years in the National Mammography Database.

Background Breast Imaging Reporting and Data System (BI-RADS) category 3 (BR3) (probably benign) mammographic assessments are reserved for imaging findings known to have likelihood of malignancy of 2% or less. Purpose To determine the effect of age, finding type, and prior mammography on cancer yield for BR3 findings in the National Mammography Database (NMD). Materials and Methods This HIPAA-compliant retrospective cohort institutional review board-exempt study evaluated women recalled from screening mammography followed by BR3 assessment at diagnostic evaluation from January 2009 to March 2018 and from 471 NMD facilities. Only the first BR3 occurrence was included for women with biopsy or imaging follow-up of at least 2 years. Women with a history of breast cancer or who underwent biopsy at time of initial BR3 assessment were excluded. Women were stratified by age in 10-year intervals. Cancer yield was calculated for each age group, with (for presumed new findings) and without prior mammographic comparison, and by lesion type, where available. Linear regression with weighted-age binning was performed to assess for differences between groups; P < .05 was indicative of a significant difference. Results A total of 1 380 652 (18.2%) women were recalled after screening mammography, of whom 157 130 (11.4%) were given a BR3 assessment within 90 days after screening. Of these, 43 628 women (median age, 55 years; age range, 25-90 years) had adequate follow-up for analysis. Cancer yield increased with increasing age decile, ranging from 0.51% (six of 1167) in women aged 30-39 years to 4.63% (41 of 885) in women aged 80-90 years; cancer yield exceeded 2% at and after age 59.7 years for baseline findings and at and after age 53.6 years for presumed new findings, although there was no effect on stage distribution. Cancer yield for baseline BR3 masses was 10 of 2111 (0.47% [95% CI: 0.24, 0.90]) versus 47 of 3003 (1.57% [95% CI: 1.16, 2.09]) with prior comparisons (P < .001); cancer yield for baseline calcifications was eight of 929 (0.86% [95% CI: 0.40, 1.76]) versus 84 of 2999 (2.80% [95% CI: 2.23, 3.47]) with prior comparisons (P < .001). Difference in cancer yield was 0.51% (95% CI: 0.16, 0.86) between women with and women without prior comparison at the same age (P = .006). Conclusion Cancer yield exceeded the 2% threshold for women aged 60 years or older and reached 4.6% for women aged 80-89 years. Breast Imaging Reporting and Data System 3 findings in women with a prior comparison had higher cancer yield than in those without a prior comparison at the same age. © RSNA, 2021 Online supplemental material is available for this article.

Screening Algorithms in Dense Breasts: AJR Expert Panel Narrative Review.

Screening mammography reduces breast cancer mortality; however, when used to examine women with dense breasts, its performance and resulting benefits are reduced. Increased breast density is an independent risk factor for breast cancer. Digital breast tomosynthesis (DBT), ultrasound (US), molecular breast imaging (MBI), MRI, and contrast-enhanced mammography (CEM) each have shown improved cancer detection in dense breasts when compared with 2D digital mammography (DM). DBT is the preferred mammographic technique for producing a simultaneous reduction in recalls (i.e., additional imaging). US further increases cancer detection after DM or DBT and reduces interval cancers (cancers detected in the interval between recommended screening examinations), but it also produces substantial additional false-positive findings. MBI improves cancer detection with an effective radiation dose that is approximately fourfold that of DM or DBT but is still within accepted limits. MRI provides the greatest increase in cancer detection and reduces interval cancers and late-stage disease; abbreviated techniques will reduce cost and improve availability. CEM appears to offer performance similar to that of MRI, but further validation is needed. Dense breast notification will soon be a national standard; therefore, understanding the performance of mammography and supplemental modalities is necessary to optimize screening for women with dense breasts.

Cancer Yield and Patterns of Follow-up for BI-RADS Category 3 after Screening Mammography Recall in the National Mammography Database.

Background The literature supports the use of short-interval follow-up as an alternative to biopsy for lesions assessed as probably benign, Breast Imaging Reporting and Data System (BI-RADS) category 3, with an expected malignancy rate of less than 2%. Purpose To assess outcomes from 6-, 12-, and 24-month follow-up of probably benign findings first identified at recall from screening mammography in the National Mammography Database (NMD). Materials and Methods This retrospective study included women recalled from screening mammography with BI-RADS category 3 assessment at additional evaluation from January 2009 through March 2018 from 471 NMD facilities. Only the first BI-RADS category 3 occurrence for women aged 25 years or older with no personal history of breast cancer was analyzed, with biopsy or 2-year imaging follow-up. Cancer yield and positive predictive value of biopsies performed (PPV3) were determined at each follow-up. Results Among 45 202 women (median age, 55 years; range, 25-90 years) with a BI-RADS category 3 lesion, 1574 (3.5%) underwent biopsy at the time of lesion detection, yielding 72 cancers (cancer yield, 4.6%; 72 of 1574 women). For the remaining 43 628 women who accepted surveillance, 922 were seen within 90 days (with 78 lesions biopsied and 12 [15%] classified as malignant). The women still in surveillance (31 465 of 43 381 women [72.5%]) underwent follow-up mammography at 6 months. Of 3001 (9.5%) lesions biopsied, 456 (15.2%) were malignant (cancer yield, 1.5%; 456 of 31 465 women; 95% confidence interval [CI]: 1.3%, 1.6%). Among 18 748 of 25 997 women (72.1%) in surveillance who underwent follow-up at 12 months, 1219 (6.5%) underwent biopsy with 230 (18.9%) malignant lesions found (cancer yield, 1.2%; 230 of 18 748 women; 95% CI: 1.1%, 1.4%). Through 2-year follow-up, the biopsy rate was 11.2% (4894 of 43 628 women) with a cancer yield of 1.86% (810 malignancies found among 43 628 women; 95% CI: 1.73%, 1.98%) and a PPV3 of 16.6% (810 malignancies found among 4894 women). Conclusion In the National Mammography Database, Breast Imaging Reporting and Data System (BI-RADS) category 3 use is appropriate, with 1.86% cumulative cancer yield through 2-year follow-up. Of 810 malignancies, 468 (57.8%) were diagnosed at or before 6 months, validating necessity of short-interval follow-up of mammographic BI-RADS category 3 findings. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Moy in this issue.

Diagnostic Performance of MRI, Molecular Breast Imaging, and Contrast-enhanced Mammography in Women with Newly Diagnosed Breast Cancer.

Background Staging newly diagnosed breast cancer by using dynamic contrast material-enhanced MRI is limited by access, high cost, and false-positive findings. The utility of contrast-enhanced mammography (CEM) and 99mTc sestamibi-based molecular breast imaging (MBI) in this setting is largely unknown. Purpose To compare extent-of-disease assessments by using MRI, CEM, and MBI versus pathology in women with breast cancer. Materials and Methods In this HIPAA-compliant prospective study, women with biopsy-proven breast cancer underwent MRI, CEM, and MBI between October 2014 and April 2018. Eight radiologists independently interpreted each examination result prospectively and were blinded to interpretations of findings with the other modalities. Visibility of index malignancies, lesion size, and additional suspicious lesions (malignant or benign) were compared during pathology review. Accuracy of index lesion sizing and detection of additional lesions in women without neoadjuvant chemotherapy were compared. Results A total of 102 women were enrolled and 99 completed the study protocol (mean age, 51 years ± 11 [standard deviation]; range, 32-77 years). Lumpectomy or mastectomy was performed in 71 women (79 index malignancies) without neoadjuvant chemotherapy and in 28 women (31 index malignancies) with neoadjuvant chemotherapy. Of the 110 index malignancies, MRI, CEM, and MBI depicted 102 (93%; 95% confidence interval [CI]: 86%, 97%), 100 (91%; 95% CI: 84%, 96%), and 101 (92%; 95% CI: 85%, 96%) malignancies, respectively. In patients without neoadjuvant chemotherapy, pathologic size of index malignancies was overestimated with all modalities (P = .02). MRI led to overestimation of 24% (17 of 72) of malignancies by more than 1.5 cm compared with 11% (eight of 70) with CEM and 15% (11 of 72) with MBI. MRI depicted more (P = .007) nonindex lesions, with sensitivity similar to that of CEM or MBI, resulting in lower positive predictive value of additional biopsies (13 of 46 [28%; 95% CI: 17%, 44%] for MRI; 14 of 27 [52%; 95% CI: 32%, 71%] for CEM; and 11 of 25 [44%; 95% CI: 24%, 65%] for MBI (overall P = .01). Conclusion Contrast-enhanced mammography, molecular breast imaging, and MRI showed similar detection of all malignancies. MRI depicted more nonindex suspicious benign lesions than did contrast-enhanced mammography or molecular breast imaging, leading to lower positive predictive value of additional biopsies. All three modalities led to overestimation of index tumor size, particularly MRI. © RSNA, 2019 Online supplemental material is available for this article.

Breast density implications and supplemental screening.

Digital breast tomosynthesis (DBT) has been widely implemented in place of 2D mammography, although it is less effective in women with extremely dense breasts. Breast ultrasound detects additional early-stage, invasive breast cancers when combined with mammography; however, its relevant limitations, including the shortage of trained operators, operator dependence and small field of view, have limited its widespread implementation. Automated breast sonography (ABS) is a promising technique but the time to interpret and false-positive rates need to be improved. Supplemental screening with contrast-enhanced magnetic resonance imaging (MRI) in high-risk women reduces late-stage disease; abbreviated MRI protocols may reduce cost and increase accessibility to women of average risk with dense breasts. Contrast-enhanced digital mammography (CEDM) and molecular breast imaging improve cancer detection but require further validation for screening and direct biopsy guidance should be implemented for any screening modality. This article reviews the status of screening women with dense breasts. KEY POINTS: • The sensitivity of mammography is reduced in women with dense breasts. Supplemental screening with US detects early-stage, invasive breast cancers. • Tomosynthesis reduces recall rate and increases cancer detection rate but is less effective in women with extremely dense breasts. • Screening MRI improves early diagnosis of breast cancer more than ultrasound and is currently recommended for women at high risk. Risk assessment is needed, to include breast density, to ascertain who should start early annual MRI screening.

Grouped Amorphous Calcifications at Mammography: Frequently Atypical but Rarely Associated with Aggressive Malignancy.

Purpose To determine rate of malignancy at stereotactic biopsy of amorphous calcifications with different distributions using current imaging, clinical, and histopathologic criteria. Materials and Methods From January 2009 to September 2013, this retrospective study reviewed a large set of stereotactic biopsies to identify amorphous calcifications and their clinical, imaging, and histopathologic characteristics. Calcification distribution was correlated with malignancy rate after adjusting for known risk factors using logistic regression. Results Of 1903 sequential biopsies, 546 (28.7%) were for amorphous calcifications. After excluding atypical lesions not excised and patients with more than one biopsy in the same year, 497 lesions from 494 women (median age, 52 years; age range, 30-81 years) remained. Fifty-two (10.5%; 95% confidence interval [CI]: 7.9, 13.5) lesions proved malignant, with 17 of 52 (42.7%) being invasive cancers (median, 0.3 cm; range, 0.1-1.3 cm) and all 17 of them being estrogen and progesterone receptor positive and node negative. Malignancy rates in a segmental (six of 21 [28.6%]), linear (eight of 32 [25.0%]), or multiple group same quadrant (nine of 36 [25.0%]) distribution were significantly higher than malignancy rate in a solitary group of amorphous calcifications (25 of 356 [7.0%]) (P = .004, P = .003, and P = .002, respectively). Of 356 grouped amorphous calcifications, 102 (28.7%) yielded atypical results prompting excision, with three of 102 (2.9%) upgraded to ductal carcinoma in situ at excision. In women younger than 50 years without a personal history of cancer, grouped amorphous calcifications showed four of 127 (3.1%) (95% CI: 0.9, 7.9) were malignant and 39 of 127 (30.7%) were atypical at final histopathology. Conclusion Biopsy of amorphous calcifications remains necessary, with an overall malignancy rate of 10.5%; only 17 of 497 (3.4%) biopsies showed invasive cancer, and all of these were estrogen and progesterone receptor positive. Grouped amorphous calcifications in women younger than 50 years without history of breast or ovarian cancer showed a low malignancy rate of 3.1% (four of 127).