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Objectives: To evaluate the detectability of non-contrast-enhanced and contrast-enhanced spiral breast computed tomography ([non]-CE-SBCT) compared with mammography. Secondary objectives are to determine detectability depending on breast density and to evaluate appearance of breast malignancies according to BI-RADS descriptors., Methods: This retrospective institutional review board-approved study included 90 women with 105 biopsy-proven malignant breast lesions. Breast density, BI-RADS descriptors, and detectability were evaluated by 2 independent readers. Diagnostic confidence was rated on a 4-point Likert scale., Results: For readers 1 and 2, detectability was 83.8% and 80.0% for mammography, 99.1% and 99.1% for CE-SBCT ( P < 0.05), and 66.7% and 61.9% for non-CE-SBCT ( P < 0.05). With both readers, detectability in CE-SBCT was high for density A/B/C/D (both 100%/100%/100%/87.5%). Detectability of readers declined with increasing density for mammography (density A = 100%, B = 89.1% and 95.1%, C = 73.1%, D = 50.0% and 71.4%; P < 0.05) and for non-CE-SBCT (density A = 87.5% and 90.7%, B = 65.5% and 69.1%, C = 54.8% and 60.0%, D = 37.5%; P < 0.05). Mass lesions were detected with CT as often as with mammography, whereas architectural distortions and microcalcifications were detected less often with SBCT. Diagnostic confidence was very high or high in 97.2% for CE-SBCT, in 74.1% for non-CE-SBCT, and in 81.4% for mammography., Conclusions: Detectability and diagnostic confidence were very high in CE-SBCT, regardless of breast density. The detectability of non-CE-SBCT was lower than that of mammography and declined with increasing breast density., Competing Interests: Conflicts of interest and sources of funding: M.W. is part of the speaker bureau of Siemens Healthineers AG. E.W. is part of the speaker bureau of Siemens Healthineers AG and is a member of the advisory board of AB-CT and of Becton Dickinson GmbH. For the remaining authors, none were declared., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Objectives: Clinical experience regarding the use of dedicated photon-counting breast CT (PC-BCT) for diagnosis of breast microcalcifications is scarce. This study systematically compares the detection and classification of breast microcalcifications using a dedicated breast photon-counting CT, especially designed for examining the breast, in comparison with digital breast tomosynthesis (DBT)., Materials and Methods: This is a prospective intraindividual study on women with DBT screening-detected BI-RADS-4/-5 microcalcifications who underwent PC-BCT before biopsy. PC-BCT images were reconstructed with a noninterpolated spatial resolution of 0.15 × 0.15 × 0.15 mm (reconstruction mode 1 [RM-1]) and with 0.3 × 0.3 × 0.3 mm (reconstruction mode 2 [RM-2]), plus thin-slab maximum intensity projection (MIP) reconstructions. Two radiologists independently rated the detection of microcalcifications in direct comparison with DBT on a 5-point scale. The distribution and morphology of microcalcifications were then rated according to BI-RADS. The size of the smallest discernible microcalcification particle was measured. For PC-BCT, the average glandular dose was determined by Monte Carlo simulations; for DBT, the information provided by the DBT system was used., Results: Between September 2022 and July 2023, 22 participants (mean age, 61; range, 42-85 years) with microcalcifications (16 malignant; 6 benign) were included. In 2/22 with microcalcifications in the posterior region, microcalcifications were not detectable on PC-BCT, likely because they were not included in the PC-BCT volume. In the remaining 20 participants, microcalcifications were detectable. With high between-reader agreement (κ > 0.8), conspicuity of microcalcifications was rated similar for DBT and MIPs of RM-1 (mean, 4.83 ± 0.38 vs 4.86 ± 0.35) ( P = 0.66), but was significantly lower ( P < 0.05) for the remaining PC-BCT reconstructions: 2.11 ± 0.92 (RM-2), 2.64 ± 0.80 (MIPs of RM-2), and 3.50 ± 1.23 (RM-1). Identical distribution qualifiers were assigned for PC-BCT and DBT in 18/20 participants, with excellent agreement (κ = 0.91), whereas identical morphologic qualifiers were assigned in only 5/20, with poor agreement (κ = 0.44). The median size of smallest discernible microcalcification particle was 0.2 versus 0.6 versus 1.1 mm in DBT versus RM-1 versus RM-2 ( P < 0.001), likely due to blooming effects. Average glandular dose was 7.04 mGy (PC-BCT) versus 6.88 mGy (DBT) ( P = 0.67)., Conclusions: PC-BCT allows reliable detection of in-breast microcalcifications as long as they are not located in the posterior part of the breast and allows assessment of their distribution, but not of their individual morphology., Competing Interests: Conflicts of interest: none declared., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Competing Interests: Die Autorinnen/Autoren geben an, dass kein Interessenkonflikt besteht.

Objective: To investigate how different combinations of T1-weighted (T1w), T2-weighted (T2w), and diffusion-weighted imaging (DWI) impact the performance of virtual contrast-enhanced (vCE) breast MRI., Materials and Methods: The IRB-approved, retrospective study included 1064 multiparametric breast MRI scans (age: 52 ± 12 years) obtained from 2017 to 2020 (single site, two 3-T MRI). Eleven independent neural networks were trained to derive vCE images from varying input combinations of T1w, T2w, and multi-b-value DWI sequences (b-value = 50-1500 s/mm 2 ). Three readers evaluated the vCE images with regard to qualitative scores of diagnostic image quality, image sharpness, satisfaction with contrast/signal-to-noise ratio, and lesion/non-mass enhancement conspicuity. Quantitative metrics (SSIM, PSNR, NRMSE, and median symmetrical accuracy) were analyzed and statistically compared between the input combinations for the full breast volume and both enhancing and non-enhancing target findings., Results: The independent test set consisted of 187 cases. The quantitative metrics significantly improved in target findings when multi-b-value DWI sequences were included during vCE training (p < 0.05). Non-significant effects (p > 0.05) were observed for the quantitative metrics on the full breast volume when comparing input combinations including T1w. Using T1w and DWI acquisitions during vCE training is necessary to achieve high satisfaction with contrast/SNR and good conspicuity of the enhancing findings. The input combination of T1w, T2w, and DWI sequences with three b-values showed the best qualitative performance., Conclusion: vCE breast MRI performance is significantly influenced by input sequences. Quantitative metrics and visual quality of vCE images significantly benefit when multi b-value DWI is added to morphologic T1w-/T2w sequences as input for model training., Key Points: Question How do different MRI sequences impact the performance of virtual contrast-enhanced (vCE) breast MRI? Findings The input combination of T1-weighted, T2-weighted, and diffusion-weighted imaging sequences with three b-values showed the best qualitative performance. Clinical relevance While in the future neural networks providing virtual contrast-enhanced images might further improve accessibility to breast MRI, the significant influence of input data needs to be considered during translational research., (© 2024. The Author(s).)

· Breast MRI is an essential part of breast imaging. · The recommendations for performing breast MRI have been updated. · A table provides a compact and quick overview. More detailed comments supplement the table.. · The "classic" breast MRI can be performed based on the recommendations. Tips for special clinical questions, such as implant rupture, mammary duct pathology or local lymph node status, are included.. CITATION FORMAT: · Wenkel E, Wunderlich P, Fallenberg E et al. Aktualisierung der Empfehlungen der AG Mammadiagnostik der Deutschen Röntgengesellschaft zur Durchführung der Mamma-MRT. Fortschr Röntgenstr 2024; 196: 939 - 944., Competing Interests: Die Autorinnen/Autoren geben an, dass kein Interessenkonflikt besteht., (Thieme. All rights reserved.)

Diffusion-weighted imaging (DWI) combined with radiomics can aid in the differentiation of breast lesions. Segmentation characteristics, however, might influence radiomic features. To evaluate feature stability, we implemented a standardized pipeline featuring shifts and shape variations of the underlying segmentations. A total of 103 patients were retrospectively included in this IRB-approved study after multiparametric diagnostic breast 3T MRI with a spin-echo diffusion-weighted sequence with echoplanar readout (b-values: 50, 750 and 1500 s/mm 2 ). Lesion segmentations underwent shifts and shape variations, with >100 radiomic features extracted from apparent diffusion coefficient (ADC) maps for each variation. These features were then compared and ranked based on their stability, measured by the Overall Concordance Correlation Coefficient (OCCC) and Dynamic Range (DR). Results showed variation in feature robustness to segmentation changes. The most stable features, excluding shape-related features, were FO (Mean, Median, RootMeanSquared), GLDM (DependenceNonUniformity), GLRLM (RunLengthNonUniformity), and GLSZM (SizeZoneNonUniformity), which all had OCCC and DR > 0.95 for both shifting and resizing the segmentation. Perimeter, MajorAxisLength, MaximumDiameter, PixelSurface, MeshSurface, and MinorAxisLength were the most stable features in the Shape category with OCCC and DR > 0.95 for resizing. Considering the variability in radiomic feature stability against segmentation variations is relevant when interpreting radiomic analysis of breast DWI data.

Objectives: To evaluate whether artifacts on contrast-enhanced (CE) breast MRI maximum intensity projections (MIPs) might already be forecast before gadolinium-based contrast agent (GBCA) administration during an ongoing examination by analyzing the unenhanced T1-weighted images acquired before the GBCA injection., Materials and Methods: This IRB-approved retrospective analysis consisted of n = 2884 breast CE MRI examinations after intravenous administration of GBCA, acquired with n = 4 different MRI devices at different field strengths (1.5 T/3 T) during clinical routine. CE-derived subtraction MIPs were used to conduct a multi-class multi-reader evaluation of the presence and severity of artifacts with three independent readers. An ensemble classifier (EC) of five DenseNet models was used to predict artifacts for the post-contrast subtraction MIPs, giving as the input source only the pre-contrast T1-weighted sequence. Thus, the acquisition directly preceded the GBCA injection. The area under ROC (AuROC) and diagnostics accuracy scores were used to assess the performance of the neural network in an independent holdout test set (n = 285)., Results: After majority voting, potentially significant artifacts were detected in 53.6% (n = 1521) of all breast MRI examinations (age 49.6 ± 12.6 years). In the holdout test set (mean age 49.7 ± 11.8 years), at a specificity level of 89%, the EC could forecast around one-third of artifacts (sensitivity 31%) before GBCA administration, with an AuROC = 0.66., Conclusion: This study demonstrates the capability of a neural network to forecast the occurrence of artifacts on CE subtraction data before the GBCA administration. If confirmed in larger studies, this might enable a workflow-blended approach to prevent breast MRI artifacts by implementing in-scan personalized predictive algorithms., Clinical Relevance Statement: Some artifacts in contrast-enhanced breast MRI maximum intensity projections might be predictable before gadolinium-based contrast agent injection using a neural network., Key Points: • Potentially significant artifacts can be observed in a relevant proportion of breast MRI subtraction sequences after gadolinium-based contrast agent administration (GBCA). • Forecasting the occurrence of such artifacts in subtraction maximum intensity projections before GBCA administration for individual patients was feasible at 89% specificity, which allowed correctly predicting one in three future artifacts. • Further research is necessary to investigate the clinical value of such smart personalized imaging approaches., (© 2023. The Author(s).)

Axillary lymphadenopathy (LA) after COVID-19 vaccination is now known to be a common side effect. In these cases, malignancy cannot always be excluded on the basis of morphological imaging criteria.Narrative review for decision-making regarding control and follow-up intervals for axillary LA according to currently published research. This article provides a practical overview of the management of vaccine-associated LA using image examples and a flowchart and provides recommendations for follow-up intervals. A particular focus is on patients presenting for diagnostic breast imaging. The diagnostic criteria for pathological lymph nodes (LN) are explained.Axillary LA is a common adverse effect after COVID-19 vaccination (0.3-53%). The average duration of LA is more than 100 days. LA is also known to occur after other vaccinations, such as the seasonal influenza vaccine. Systematic studies on this topic are missing. Other causes of LA after vaccination (infections, autoimmune diseases, malignancies) should be considered for the differential diagnosis. If the LA persists for more than 3 months after COVID-19 vaccination, a primarily sonographic follow-up examination is recommended after another 3 months. A minimally invasive biopsy of the LA is recommended if a clinically suspicious LN persists or progresses. In the case of histologically confirmed breast cancer, a core biopsy without a follow-up interval is recommended regardless of the vaccination, as treatment appropriate to the stage should not be influenced by follow-up intervals. For follow-up after breast cancer, the procedure depends on the duration of the LA and the woman's individual risk of recurrence.Vaccination history should be well documented and taken into account when evaluating suspicious LN. Biopsy of abnormal, persistent, or progressive LNs is recommended. Preoperative staging of breast cancer should not be delayed by follow-up. The risk of false-positive findings is accepted, and the suspicious LNs are histologically examined in a minimally invasive procedure. · The vaccination history must be documented (vaccine, date, place of application).. · If axillary LA persists for more than 3 months after vaccination, a sonographic follow-up examination is recommended after 3 months.. · Enlarged LNs that are persistent, progressive in size, or are suspicious on control sonography should be biopsied.. · Suspicious LNs should be clarified before starting oncological therapy, irrespective of the vaccination status, according to the guidelines and without delaying therapy.. · Wilpert C, Wenkel E, Baltzer PA et al. Vaccine-associated axillary lymphadenopathy with a focus on COVID-19 vaccines. Fortschr Röntgenstr 2024; DOI 10.1055/a-2328-7536., Competing Interests: The authors declare that they have no conflict of interest., (Thieme. All rights reserved.)

Objectives: To investigate the influence of preoperative breast MRI on mastectomy and reoperation rates in patients with pure ductal carcinoma in situ (DCIS)., Methods: The MIPA observational study database (7245 patients) was searched for patients aged 18-80 years with pure unilateral DCIS diagnosed at core needle or vacuum-assisted biopsy (CNB/VAB) and planned for primary surgery. Patients who underwent preoperative MRI (MRI group) were matched (1:1) to those who did not receive MRI (noMRI group) according to 8 confounding covariates that drive referral to MRI (age; hormonal status; familial risk; posterior-to-nipple diameter; BI-RADS category; lesion diameter; lesion presentation; surgical planning at conventional imaging). Surgical outcomes were compared between the matched groups with nonparametric statistics after calculating odds ratios (ORs)., Results: Of 1005 women with pure unilateral DCIS at CNB/VAB (507 MRI group, 498 noMRI group), 309 remained in each group after matching. First-line mastectomy rate in the MRI group was 20.1% (62/309 patients, OR 2.03) compared to 11.0% in the noMRI group (34/309 patients, p = 0.003). The reoperation rate was 10.0% in the MRI group (31/309, OR for reoperation 0.40) and 22.0% in the noMRI group (68/309, p < 0.001), with a 2.53 OR of avoiding reoperation in the MRI group. The overall mastectomy rate was 23.3% in the MRI group (72/309, OR 1.40) and 17.8% in the noMRI group (55/309, p = 0.111)., Conclusions: Compared to those going directly to surgery, patients with pure DCIS at CNB/VAB who underwent preoperative MRI had a higher OR for first-line mastectomy but a substantially lower OR for reoperation., Clinical Relevance Statement: When confounding factors behind MRI referral are accounted for in the comparison of patients with CNB/VAB-diagnosed pure unilateral DCIS, preoperative MRI yields a reduction of reoperations that is more than twice as high as the increase in overall mastectomies., Key Points: • Confounding factors cause imbalance when investigating the influence of preoperative MRI on surgical outcomes of pure DCIS. • When patient matching is applied to women with pure unilateral DCIS, reoperation rates are significantly reduced in women who underwent preoperative MRI. • The reduction of reoperations brought about by preoperative MRI is more than double the increase in overall mastectomies., (© 2023. The Author(s).)

Several breast pathologies can affect the skin, and clinical pathways might differ significantly depending on the underlying diagnosis. This study investigates the feasibility of using diffusion-weighted imaging (DWI) to differentiate skin pathologies in breast MRIs. This retrospective study included 88 female patients who underwent diagnostic breast MRI (1.5 or 3T), including DWI. Skin areas were manually segmented, and the apparent diffusion coefficients (ADCs) were compared between different pathologies: inflammatory breast cancer (IBC; n = 5), benign skin inflammation (BSI; n = 11), Paget's disease (PD; n = 3), and skin-involved breast cancer (SIBC; n = 11). Fifty-eight women had healthy skin (H; n = 58). The SIBC group had a significantly lower mean ADC than the BSI and IBC groups. These differences persisted for the first-order features of the ADC (mean, median, maximum, and minimum) only between the SIBC and BSI groups. The mean ADC did not differ significantly between the BSI and IBC groups. Quantitative DWI assessments demonstrated differences between various skin-affecting pathologies, but did not distinguish clearly between all of them. More extensive studies are needed to assess the utility of quantitative DWI in supplementing the diagnostic assessment of skin pathologies in breast imaging.

Purpose: Broader clinical adoption of breast magnetic resonance imaging (MRI) faces challenges such as limited availability and high procedural costs. Low-field technology has shown promise in addressing these challenges. We report our initial experience using a next-generation scanner for low-field breast MRI at 0.55T., Methods: This initial cases series was part of an institutional review board-approved prospective study using a 0.55T scanner (MAGNETOM Free.Max, Siemens Healthcare, Erlangen/Germany: height < 2 m, weight < 3.2 tons, no quench pipe) equipped with a seven-channel breast coil (Noras, Höchberg/Germany). A multiparametric breast MRI protocol consisting of dynamic T1-weighted, T2-weighted, and diffusion-weighted sequences was optimized for 0.55T. Two radiologists with 12 and 20 years of experience in breast MRI evaluated the examinations., Results: Twelve participants (mean age: 55.3 years, range: 36-78 years) were examined. The image quality was diagnostic in all examinations and not impaired by relevant artifacts. Typical imaging phenotypes were visualized. The scan time for a complete, non-abbreviated breast MRI protocol ranged from 10:30 to 18:40 min., Conclusion: This initial case series suggests that low-field breast MRI is feasible at diagnostic image quality within an acceptable examination time., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: M. Dietzel: no competing interest, S. Ohlmeyer: no competing interest, F. Laun: no competing interest, S. Bickelhaupt: no competing interest, R. Heiss and M. Uder: Member of speakers bureau of Siemens Healthineers., (Copyright © 2024. Published by Elsevier B.V.)

The purpose of this feasibility study is to investigate if latent diffusion models (LDMs) are capable to generate contrast enhanced (CE) MRI-derived subtraction maximum intensity projections (MIPs) of the breast, which are conditioned by lesions. We trained an LDM with n = 2832 CE-MIPs of breast MRI examinations of n = 1966 patients (median age: 50 years) acquired between the years 2015 and 2020. The LDM was subsequently conditioned with n = 756 segmented lesions from n = 407 examinations, indicating their location and BI-RADS scores. By applying the LDM, synthetic images were generated from the segmentations of an independent validation dataset. Lesions, anatomical correctness, and realistic impression of synthetic and real MIP images were further assessed in a multi-rater study with five independent raters, each evaluating n = 204 MIPs (50% real/50% synthetic images). The detection of synthetic MIPs by the raters was akin to random guessing with an AUC of 0.58. Interrater reliability of the lesion assessment was high both for real (Kendall's W = 0.77) and synthetic images (W = 0.85). A higher AUC was observed for the detection of suspicious lesions (BI-RADS ≥ 4) in synthetic MIPs (0.88 vs. 0.77; p = 0.051). Our results show that LDMs can generate lesion-conditioned MRI-derived CE subtraction MIPs of the breast, however, they also indicate that the LDM tended to generate rather typical or 'textbook representations' of lesions., (© 2024. The Author(s).)

Competing Interests: Die Autorinnen/Autoren geben an, dass kein Interessenkonflikt besteht.

Competing Interests: Die Autorinnen/Autoren geben an, dass kein Interessenkonflikt besteht.

Background: Contrast-enhanced mammography (CEM) is an imaging method that is able to improve visualization of intramammary tumors after peripheral venous administration of an iodine-containing contrast medium (ICM)., Objectives and Methods: The current significance of CEM is discussed., Results: Studies were able to show an advantage of CEM in the diagnosis of breast cancer compared to mammography, especially for women with dense breasts. Indications for CEM currently depend on the availability of magnetic resonance imaging (MRI). If MRI is available, CEM is indicated in those cases when MRI cannot be performed. Use of CEM for breast cancer screening is currently viewed critically. This view can change when results and updated assessments of large CEM studies in Europe and USA become available. Patients must be informed about the use of an ICM. As ICM administration for CEM is carried out in a similar manner to established imaging methods, the authors expect the use of ICM for CEM to be unproblematic as long as general contraindications are adhered to., Conclusions: In the future, CEM could have greater importance for the diagnosis of breast cancer, as this imaging method has diagnostic advantages compared to conventional mammography. A great advantage of CEM is its availability. For those who use breast MRI, CEM is helpful when MRI is not feasible due to contraindications or other reasons., (© 2023. The Author(s).)

Background: Magnetic resonance imaging (MRI) provides high diagnostic sensitivity for breast cancer. However, MRI artifacts may impede the diagnostic assessment. This is particularly important when evaluating maximum intensity projections (MIPs), such as in abbreviated MRI (AB-MRI) protocols, because high image quality is desired as a result of fewer sequences being available to compensate for problems., Purpose: To describe the prevalence of artifacts on dynamic contrast enhanced (DCE) MRI-derived MIPs and to investigate potentially associated attributes., Material and Methods: For this institutional review board approved retrospective analysis, MIPs were generated from subtraction series and cropped to represent the left and right breasts as regions of interest. These images were labeled by three independent raters regarding the presence of MRI artifacts. MRI artifact prevalence and associations with patient characteristics and technical attributes were analyzed using descriptive statistics and generalized linear models (GLMMs)., Results: The study included 2524 examinations from 1794 patients (median age 50 years), performed on 1.5 and 3.0 Tesla MRI systems. Overall inter-rater agreement was kappa = 0.54. Prevalence of significant unilateral artifacts was 29.2% (736/2524), whereas bilateral artifacts were present in 37.8% (953/2524) of all examinations. According to the GLMM, artifacts were significantly positive associated with age (odds ratio [OR] = 1.52) and magnetic field strength (OR = 1.55), whereas a negative effect could be shown for body mass index (OR = 0.95)., Conclusion: MRI artifacts on DCE subtraction MIPs of the breast, as used in AB-MRI, are a relevant topic. Our results show that, besides the magnetic field strength, further associated attributes are patient age and body mass index, which can provide possible targets for artifact reduction., Competing Interests: Declaration of conflicting interestsThe author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: As the clinical routine MRI systems in the hospital are manufactured by the company Siemens Healthcare GmbH, the following individual COIs are disclosed. The University Hospital Erlangen receives funding from Siemens Healthcare GmbH that is partially contributing to the job position of Lorenz Kapsner. Sebastian Bickelhaupt discloses the following relationships: grant support from governmental and non-governmental funding institutions; received lecture fees from Siemens Healthcare GmbH; holds (pending) patent applications in MRI; the University Hospital Erlangen receives funding from Siemens Healthcare GmbH that is partially contributing to the job position. Michael Uder is part of the Speakers Bureau of the Siemens Healthcare GmbH. Eva Balbach received lecture fees from Siemens Healthcare GmbH. Evelyn Wenkel discloses the following relationships: received lecture fees from Siemens Healthcare GmbH and C. R. Bard GmbH; participation in the advisory boards of Hologic GmbH and Bayer AG; chair (non-paid) of the DRG AG Mammadiagnostik. Frederik B Laun, Lukas Baumann, and Sabine Ohlmeyer has no conflicts of interest to be disclosed.

Background: Radiopaque breast markers cause artifacts in dedicated spiral breast-computed tomography (SBCT). This study investigates the extent of artifacts in different marker types and the feasibility of reducing artifacts through a metal artifact reduction (MAR) algorithm., Methods: The pilot study included 18 women who underwent contrast-enhanced SBCT. In total, 20 markers of 4 different types were analyzed for artifacts. The extent of artifacts with and without MAR was measured via the consensus of two readers. Image noise was quantitatively evaluated, and the effect of MAR on the detectability of breast lesions was evaluated on a 3-point Likert scale., Results: Breast markers caused significant artifacts that impaired image quality and the detectability of lesions. MAR decreased artifact size in all analyzed cases, even in cases with multiple markers in a single slice. The median length of in-plain artifacts significantly decreased from 31 mm (range 11-51 mm) in uncorrected to 2 mm (range 1-5 mm) in corrected images ( p ≤ 0.05). Artifact size was dependent on marker size. Image noise in slices affected by artifacts was significantly lower in corrected (13.6 ± 2.2 HU) than in uncorrected images (19.2 ± 6.8 HU, p ≤ 0.05). MAR improved the detectability of lesions affected by artifacts in 5 out of 11 cases., Conclusion: MAR is feasible in SBCT and improves the image quality and detectability of lesions.

Objectives: To report mastectomy and reoperation rates in women who had breast MRI for screening (S-MRI subgroup) or diagnostic (D-MRI subgroup) purposes, using multivariable analysis for investigating the role of MRI referral/nonreferral and other covariates in driving surgical outcomes., Methods: The MIPA observational study enrolled women aged 18-80 years with newly diagnosed breast cancer destined to have surgery as the primary treatment, in 27 centres worldwide. Mastectomy and reoperation rates were compared using non-parametric tests and multivariable analysis., Results: A total of 5828 patients entered analysis, 2763 (47.4%) did not undergo MRI (noMRI subgroup) and 3065 underwent MRI (52.6%); of the latter, 2441/3065 (79.7%) underwent MRI with preoperative intent (P-MRI subgroup), 510/3065 (16.6%) D-MRI, and 114/3065 S-MRI (3.7%). The reoperation rate was 10.5% for S-MRI, 8.2% for D-MRI, and 8.5% for P-MRI, while it was 11.7% for noMRI (p ≤ 0.023 for comparisons with D-MRI and P-MRI). The overall mastectomy rate (first-line mastectomy plus conversions from conserving surgery to mastectomy) was 39.5% for S-MRI, 36.2% for P-MRI, 24.1% for D-MRI, and 18.0% for noMRI. At multivariable analysis, using noMRI as reference, the odds ratios for overall mastectomy were 2.4 (p < 0.001) for S-MRI, 1.0 (p = 0.957) for D-MRI, and 1.9 (p < 0.001) for P-MRI., Conclusions: Patients from the D-MRI subgroup had the lowest overall mastectomy rate (24.1%) among MRI subgroups and the lowest reoperation rate (8.2%) together with P-MRI (8.5%). This analysis offers an insight into how the initial indication for MRI affects the subsequent surgical treatment of breast cancer., Key Points: • Of 3065 breast MRI examinations, 79.7% were performed with preoperative intent (P-MRI), 16.6% were diagnostic (D-MRI), and 3.7% were screening (S-MRI) examinations. • The D-MRI subgroup had the lowest mastectomy rate (24.1%) among MRI subgroups and the lowest reoperation rate (8.2%) together with P-MRI (8.5%). • The S-MRI subgroup had the highest mastectomy rate (39.5%) which aligns with higher-than-average risk in this subgroup, with a reoperation rate (10.5%) not significantly different to that of all other subgroups., (© 2023. The Author(s).)

Purpose: Breast imaging represents an integral part of radiology and is subject to strict quality controls. Regarding this, precise diagnostics including multimodal assessment by mammography, sonography, and MRI, including image-guided biopsy and localization procedures, is often decisive and must be performed by experts with profound knowledge and skills in all of these procedures.However, due to numerous restructurings, breast imaging has been shifted more and more towards large, specialized centers, resulting in less patient exposition and training opportunities for radiologists in smaller sites. The following whitepaper summarizes the current circumstances and discusses opinions of the participating societies., Materials: Under the leadership of the German Roentgen Society (DRG) and with the participation of the DRG's AG Mammadiagnostik, the CAFRAD (Chefarztforum Radiologie), the KLR (Konferenz der Lehrstuhlinhaber für Radiologie e. V.), the DRG's Forum Junge Radiologie (FJR) and the Berufsverband der Deutschen Radiologen e. V. (BDR), possible solutions were discussed and consented for a structured training in breast radiology in the future., Results: In addition to the teaching provided at the primary workplace, qualified training should be ensured through flexible, multi-institutional, interdisciplinary, and cross-sectoral collaboration. Furthermore, the integration of online case collections and close cooperation with certified breast cancer centers and mammography screening units is recommended. It is indispensible that online courses and case collections adhere to the standards of the national societies and include a maximum of one third of the required cases., Conclusion: In order to provide training in breast radiology at a high professional level, a paradigm shift with closer cooperation of all participants is necessary. This includes close collaboration of the breast imaging societies with the federal medical associations to establish new teaching concepts like e-learning in the training schedule of radiologists., Key Points: · Breast diagnostics is an integral part of radiology training.. · Due to recent restructurings, smaller training centers have difficulties in meeting the case numbers demanded by the Specialist Training Regulations (WBO). Improved integration of the new structures and their adaptation to the needs of education are necessary to guarantee standardized high-quality training of young radiologists.. · The integration of certified case collections enables quality-assured training, even across regions in online-based formats. In accordance with the "blended learning principle", up to one-third of the required number of patient studies can be substituted with cases from a certified case collection.. · Legally secured short- and medium-term internships may complement training in radiology.., Citation Format: · Sauer ST, Bley TA, Wenkel E et al. Whitepaper: Training in Diagnostic and Interventional Breast Radiology. Fortschr Röntgenstr 2023; 195: 699 - 706., Competing Interests: The authors declare that they have no conflict of interest., (Thieme. All rights reserved.)

The objective of this IRB approved retrospective study was to apply deep learning to identify magnetic resonance imaging (MRI) artifacts on maximum intensity projections (MIP) of the breast, which were derived from diffusion weighted imaging (DWI) protocols. The dataset consisted of 1309 clinically indicated breast MRI examinations of 1158 individuals (median age [IQR]: 50 years [16.75 years]) acquired between March 2017 and June 2020, in which a DWI sequence with a high b-value equal to 1500 s/mm 2 was acquired. From these, 2D MIP images were computed and the left and right breast were cropped out as regions of interest (ROI). The presence of MRI image artifacts on the ROIs was rated by three independent observers. Artifact prevalence in the dataset was 37% (961 out of 2618 images). A DenseNet was trained with a fivefold cross-validation to identify artifacts on these images. In an independent holdout test dataset (n = 350 images) artifacts were detected by the neural network with an area under the precision-recall curve of 0.921 and a positive predictive value of 0.981. Our results show that a deep learning algorithm is capable to identify MRI artifacts in breast DWI-derived MIPs, which could help to improve quality assurance approaches for DWI sequences of breast examinations in the future., (© 2023. The Author(s).)

Background: In the German Mammography Screening Program, 62% of ductal carcinoma in situ (DCIS) and 38% of invasive breast cancers are associated with microcalcifications (MCs). Vacuum-assisted stereotactic breast biopsies are necessary to distinguish precancerous lesions from benign calcifications because mammographic discrimination is not possible. The aim of this study was to investigate if breast magnetic resonance imaging (MRM) could assist the evaluation of MCs and thus help reduce biopsy rates., Methods: In this IRB-approved study, 58 women (mean age 58 +/- 24 years) with 59 suspicious MC clusters in the MG were eligible for this prospective single-center trial. Additional breast magnetic resonance imaging (MRI) was conducted before biopsy., Results: The breast MRI showed a sensitivity of 86%, a specificity of 84%, a positive predictive value (PPV) of 75% and a negative predictive value (NPV) of 91% for the differentiation between benign and malignant in these 59 MCs found with MG. Breast MRI in addition to MG could increase the PPV from 36% to 75% compared to MG alone. The MRI examination led to nine additional suspicious classified lesions in the study cohort. A total of 55% (5/9) of them turned out to be malignant. A total of 32 of 59 (54 %) women with suspicious MCs and benign histology were classified as non-suspicious by MRI., Conclusion: An additionally performed breast MRI could have increased the diagnostic reliability in the assessment of MCs. Further, in our small cohort, a considerable number of malignant lesions without mammographically visible MCs were revealed.

Male breast cancer is an unknown field for many practitioners. Patients often see different doctors before the correct diagnosis is made - often too late. This article is intended to point out risk factors, initiation of diagnostics and therapy. In the dawning age of molecular medicine, we will also take a look at genetics., Competing Interests: Erklärung zu finanziellen Interessen Forschungsförderung erhalten: nein; Honorar/geldwerten Vorteil für Referententätigkeit erhalten: ja, von einer anderen Institution (Pharma- oder Medizintechnikfirma usw.); Bezahlter Berater/interner Schulungsreferent/Gehaltsempfänger: ja, von einer anderen Institution (Pharma- oder Medizintechnikfirma usw.); Patent/Geschäftsanteile/Aktien (Autor/Partner, Ehepartner, Kinder) an im Bereich der Medizin aktiven Firma: nein; Patent/Geschäftsanteile/Aktien (Autor/Partner, Ehepartner, Kinder) an zu Sponsoren dieser Fortbildung bzw. durch die Fortbildung in ihren Geschäftsinteressen berührten Firma: nein. Erklärung zu nichtfinanziellen Interessen Die Autorinnen/Autoren geben an, dass kein Interessenkonflikt besteht., (Thieme. All rights reserved.)

Competing Interests: Erklärung zu finanziellen Interessen Forschungsförderung erhalten: nein; Honorar/geldwerten Vorteil für Referententätigkeit erhalten: ja, von einer anderen Institution (Pharma- oder Medizintechnikfirma usw.); Bezahlter Berater/interner Schulungsreferent/Gehaltsempfänger: ja, von einer anderen Institution (Pharma- oder Medizintechnikfirma usw.); Patent/Geschäftsanteile/Aktien (Autor/Partner, Ehepartner, Kinder) an im Bereich der Medizin aktiven Firma: nein; Patent/Geschäftsanteile/Aktien (Autor/Partner, Ehepartner, Kinder) an zu Sponsoren dieser Fortbildung bzw. durch die Fortbildung in ihren Geschäftsinteressen berührten Firma: nein. Erklärung zu nichtfinanziellen Interessen Die Autorinnen/Autoren geben an, dass kein Interessenkonflikt besteht.

Dedicated breast computed tomography (BCT) is an emerging breast imaging modality. The latest development has been the introduction of a spiral breast computed tomography scanner equipped with a photon-counting detector (SBCT). SBCT promises multiple advantages: Unlike conventional mammography, contrast enhanced spectral mammography (CESM: both 2D), and digital breast tomosynthesis (DBT: pseudo 3D), SBCT enables 3D breast imaging without tissue overlap. SBCT achieves high isotropic spatial resolution of breast tissue enabling the assessment of both soft tissue and microcalcifications. Similar to CESM and MRI, SBCT supports contrast-enhanced imaging, enabling the assessment of breast neovascularization. Unlike mammography and its derived methods (CESM, DBT), SBCT does not require compression of the breast. Accordingly, women consistently report significantly increased patient comfort compared to mammography in a previous investigation. Radiation safety is crucial in breast imaging. Studies showed different results in terms of dose, with some staying within the limits of two-view FFDM defined by the ACR and others exceeding the limit by up to 21%. Therefore, a higher radiation dose compared to state-of-the-art mammography and DBT systems has to be acknowledged. SBCT is currently under scientific investigation in multiple trials. Three major indications are currently explored: Whereas our colleagues in Zurich/Switzerland investigate the role of SBCT for opportunistic screening, in our department SBCT is mainly indicated for the work-up of equivocal lesions, and for preoperative staging. In this narrative review, we summarize the concepts of SBCT and potential implications for patient care. We report on our initial clinical experience with the technology and outline future developments of SBCT., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022. Published by Elsevier B.V.)

Background: Diffusion kurtosis imaging (DKI) is used to differentiate between benign and malignant breast lesions. DKI fits are performed either on voxel-by-voxel basis or using volume-averaged signal., Purpose: Investigate and compare DKI parameters' diagnostic performance using voxel-by-voxel and volume-averaged signal fit approach., Study Type: Retrospective., Study Population: A total of 104 patients, aged 24.1-86.4 years., Field Strength/sequence: A 3 T Spin-echo planar diffusion-weighted sequence with b-values: 50 s/mm 2 , 750 s/mm 2 , and 1500 s/mm 2 . Dynamic contrast enhanced (DCE) sequence., Assessment: Lesions were manually segmented by M.P. under supervision of S.O. (2 and 5 years of experience in breast MRI). DKI fits were performed on voxel-by-voxel basis and with volume-averaged signal. Diagnostic performance of DKI parameters D K (kurtosis corrected diffusion coefficient) and kurtosis K was compared between both approaches., Statistical Tests: Receiver operating characteristics analysis and area under the curve (AUC) values were computed. Wilcoxon rank sum and Students t-test tested DKI parameters for significant (P <0.05) difference between benign and malignant lesions. DeLong test was used to test the DKI parameter performance for significant fit approach dependency. Correlation between parameters of the two approaches was determined by Pearson correlation coefficient., Results: DKI parameters were significantly different between benign and malignant lesions for both fit approaches. Median benign vs. malignant values for voxel-by-voxel and volume-averaged approach were 2.00 vs. 1.28 ( D K in μm 2 /msec), 2.03 vs. 1.26 ( D K in μm 2 /msec), 0.54 vs. 0.90 ( K ), 0.55 vs. 0.99 ( K ). AUC for voxel-by-voxel and volume-averaged fit were 0.9494 and 0.9508 ( D K ); 0.9175 and 0.9298 ( K ). For both, AUC did not differ significantly (P = 0.20). Correlation of values between the two approaches was very high (r = 0.99 for D K and r = 0.97 for K )., Data Conclusion: Voxel-by-voxel and volume-averaged signal fit approach are equally well suited for differentiating between benign and malignant breast lesions in DKI., Evidence Level: 3 TECHNICAL EFFICACY: Stage 3., (© 2022 The Authors. Journal of Magnetic Resonance Imaging published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

Objectives: To automatically detect MRI artifacts on dynamic contrast-enhanced (DCE) maximum intensity projections (MIPs) of the breast using deep learning., Methods: Women who underwent clinically indicated breast MRI between October 2015 and December 2019 were included in this IRB-approved retrospective study. We employed two convolutional neural network architectures (ResNet and DenseNet) to detect the presence of artifacts on DCE MIPs of the left and right breasts. Networks were trained on images acquired up to and including the year 2018 using a 5-fold cross-validation (CV). Ensemble classifiers were built with the resulting CV models and applied to an independent holdout test dataset, which was formed by images acquired in 2019., Results: Our study sample contained 2265 examinations from 1794 patients (median age at first acquisition: 50 years [IQR: 17 years]), corresponding to 1827 examinations of 1378 individuals in the training dataset and 438 examinations of 416 individuals in the holdout test dataset with a prevalence of image-level artifacts of 53% (1951/3654 images) and 43% (381/876 images), respectively. On the holdout test dataset, the ResNet and DenseNet ensembles demonstrated an area under the ROC curve of 0.92 and 0.94, respectively., Conclusion: Neural networks are able to reliably detect artifacts that may impede the diagnostic assessment of MIPs derived from DCE subtraction series in breast MRI. Future studies need to further explore the potential of such neural networks to complement quality assurance and improve the application of DCE MIPs in a clinical setting, such as abbreviated protocols., Key Points: • Deep learning classifiers are able to reliably detect MRI artifacts in dynamic contrast-enhanced protocol-derived maximum intensity projections of the breast. • Automated quality assurance of maximum intensity projections of the breast may be of special relevance for abbreviated breast MRI, e.g., in high-throughput settings, such as cancer screening programs., (© 2022. The Author(s).)

Objectives: Preoperative breast magnetic resonance imaging (MRI) can inform surgical planning but might cause overtreatment by increasing the mastectomy rate. The Multicenter International Prospective Analysis (MIPA) study investigated this controversial issue., Methods: This observational study enrolled women aged 18-80 years with biopsy-proven breast cancer, who underwent MRI in addition to conventional imaging (mammography and/or breast ultrasonography) or conventional imaging alone before surgery as routine practice at 27 centers. Exclusion criteria included planned neoadjuvant therapy, pregnancy, personal history of any cancer, and distant metastases., Results: Of 5896 analyzed patients, 2763 (46.9%) had conventional imaging only (noMRI group), and 3133 (53.1%) underwent MRI that was performed for diagnosis, screening, or unknown purposes in 692/3133 women (22.1%), with preoperative intent in 2441/3133 women (77.9%, MRI group). Patients in the MRI group were younger, had denser breasts, more cancers ≥ 20 mm, and a higher rate of invasive lobular histology than patients who underwent conventional imaging alone (p < 0.001 for all comparisons). Mastectomy was planned based on conventional imaging in 22.4% (MRI group) versus 14.4% (noMRI group) (p < 0.001). The additional planned mastectomy rate in the MRI group was 11.3%. The overall performed first- plus second-line mastectomy rate was 36.3% (MRI group) versus 18.0% (noMRI group) (p < 0.001). In women receiving conserving surgery, MRI group had a significantly lower reoperation rate (8.5% versus 11.7%, p < 0.001)., Conclusions: Clinicians requested breast MRI for women with a higher a priori probability of receiving mastectomy. MRI was associated with 11.3% more mastectomies, and with 3.2% fewer reoperations in the breast conservation subgroup., Key Points: • In 19% of patients of the MIPA study, breast MRI was performed for screening or diagnostic purposes. • The current patient selection to preoperative breast MRI implies an 11% increase in mastectomies, counterbalanced by a 3% reduction of the reoperation rate. • Data from the MIPA study can support discussion in tumor boards when preoperative MRI is under consideration and should be shared with patients to achieve informed decision-making., (© 2021. The Author(s).)

Purpose: To intra-individually compare patient comfort of spiral breast computed tomography (SBCT) versus digital mammography (DM)., Method: This prospective IRB approved study included 79 patients undergoing both SBCT and DM for the assessment of BI-RADS 4 - 6 lesions. Following SBCT and DM patients answered a standardized questionnaire regarding "Overall patient comfort" and "Pain" on a 5-point Likert Scale. On the same Likert Scale, experienced radiologic technicians rated the workflow of the SBCT regarding patients' "Mobility", ease of patient "Positioning", patients' adherence to the examination ("Compliance") and expected image quality. Visibility of fibroglandular tissue in SBCT was independently rated by two breast radiologists on a 10-point Likert Scale. Subgroups stratified by menopausal status and body mass index (BMI) were analyzed., Results: Patients reported significantly lower pain during SBCT (4.73 ± 0.57) compared to DM (4.09 ± 0.90; P < 0.01). This effect was independent from BMI. However, pain reduction by SBCT was most pronounced in premenopausal (SBCT vs. DM: 4.79 ± 0.50 vs. 3.89 ± 0.99) compared to postmenopausal patients (4.71 ± 0.77 vs. 4.20 ± 0.89). Overall patient comfort in premenopausal patients tended to be higher in SBCT compared to DM (P = 0.08). Radiologic technicians rated the SBCT procedure generally as positive (average: 4.62 ± 0.56). Coverage of fibroglandular tissue in SBCT was generally high (9.82 ± 0.43) and interrater agreement was good (κ = 0.77)., Conclusions: Patients experience less pain during spiral breast computed tomography compared to DM, especially in premenopausal women. Imaging is feasible at a high level of anatomical breast coverage and without problems with the clinical workflow., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Objectives: Contrast-enhanced (CE) magnetic resonance imaging (MRI) is the most effective imaging modality for breast cancer detection. A contrast agent-free examination technique would be desirable for breast MRI screening. The purpose of this study was to evaluate the capability to detect and characterize suspicious breast lesions with an abbreviated, non-contrast-enhanced MRI protocol featuring ultra-high b-value diffusion-weighted imaging (DWI) compared with CE images., Materials and Methods: The institutional review board-approved prospective study included 127 female subjects with different clinical indications for breast MRI. Magnetic resonance imaging examinations included DWI sequences with b-values of 1500 s/mm2 (b1500) and 2500 s/mm2 (b2500), native T1- and T2-weighted images, and CE sequences at 1.5 T and 3 T scanners. Two reading rounds were performed, including either the b1500 or the b2500 DWI in consecutive assessment steps: (A) maximum intensity projections (MIPs) of DWI, (B) DWI and apparent diffusion coefficient maps, (C) as (B) but with additional native T1- and T2-weighted images, and (D) as (C) but with additional CE images (full-length protocol). Two readers independently determined the presence of a suspicious lesion. Histological confirmation was obtained for conspicuous lesions, whereas the full MRI data set was obtained for inconspicuous and clearly benign lesions. Statistical analysis included calculation of diagnostic accuracy and interrater agreement via the intraclass correlation coefficient., Results: The cohort comprised 116 cases with BI-RADS 1 findings and 138 cases with BI-RADS ≥2 findings, including 38 histologically confirmed malignancies. For (A), breasts without pathological findings could be recognized with high diagnostic accuracy (negative predictive value, ≥97.0%; sensitivity, ≥92.1% for both readers), but with a limited specificity (≥58.3%; positive predictive value, ≥28.6%). Within the native readings, approach (C) with b2500 performed best (negative predictive value, 99.5%; sensitivity, 97.4%; specificity, 88.4%). The intraclass correlation coefficient was between 0.683 (MIP b1500) and 0.996 (full protocol)., Conclusions: A native abbreviated breast MRI protocol with advanced high b-value DWI might allow nearly equivalent diagnostic accuracy as CE breast MRI and seems to be well suited for lesion detection purposes., Competing Interests: Conflicts of interest and sources of funding: The authors have no conflicts of interest to declare. Funding for the positions of F.B.L. and T.P. by the Deutsche Forschungsgemeinschaft (LA 2804/12-1, project 326944748) is gratefully acknowledged., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)

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.

Despite its high diagnostic performance, the use of breast MRI in the preoperative setting is controversial. It has the potential for personalized surgical management in breast cancer patients, but two of three randomized controlled trials did not show results in favor of its introduction for assessing the disease extent before surgery. Meta-analyses showed a higher mastectomy rate in women undergoing preoperative MRI compared to those who do not. Nevertheless, preoperative breast MRI is increasingly used and a survey from the American Society of Breast Surgeons showed that 41% of respondents ask for it in daily practice. In this context, a large-scale observational multicenter international prospective analysis (MIPA study) was proposed under the guidance of the European Network for the Assessment of Imaging in Medicine (EuroAIM). The aims were (1) to prospectively and systematically collect data on consecutive women with a newly diagnosed breast cancer, not candidates for neoadjuvant therapy, who are offered or not offered breast MRI before surgery according to local practice; (2) to compare these two groups in terms of surgical and clinical endpoints, adjusting for covariates. The underlying hypotheses are that MRI does not cause additional mastectomies compared to conventional imaging, while reducing the reoperation rate in all or in subgroups of patients. Ninety-six centers applied to a web-based call; 36 were initially selected based on volume and quality standards; 27 were active for enrollment. On November 2018, the target of 7000 enrolled patients was reached. The MIPA study is presently at the analytic phase. Key Points • Breast MRI has a high diagnostic performance but its utility in the preoperative setting is controversial. • A large-scale observational multicenter prospective study was launched to compare women receiving with those not receiving preoperative MRI. • Twenty-seven centers enrolled more than 7000 patients. The study is presently at the analytic phase.

Background: Mammography can identify calcifications up to 50-100 μm in size as a surrogate parameter for breast cancer or ductal carcinoma in situ (DCIS). Microcalcifications measuring <50 µm are also associated with breast cancer or DCIS and are frequently not detected on mammography, although they can be detected with dark-field imaging. This study examined whether additional breast examination using X-ray dark-field imaging can increase the detection rate of calcifications. Advances in knowledge: (1) evaluation of additional modality of breast imaging; (2) specific evaluation of breast calcifications.Implications for patient care: the addition of X-ray dark-field imaging to conventional mammography could detect additional calcifications., Methods: Talbot-Lau X-ray phase-contrast imaging and X-ray dark-field imaging were used to acquire images of breast specimens. The radiation dosage with the technique is comparable with conventional mammography. Three X-ray gratings with periods of 5-10 µm between the X-ray tube and the flat-panel detector provide three different images in a single sequence: the conventional attenuation image, differential phase image, and dark-field image. The images were read by radiologists. Radiological findings were marked and examined pathologically. The results were described in a descriptive manner., Results: A total of 81 breast specimens were investigated with the two methods; 199 significant structures were processed pathologically, consisting of 123 benign and 76 malignant lesions (DCIS or invasive breast cancer). X-ray dark-field imaging identified 15 additional histologically confirmed carcinoma lesions that were visible but not declared suspicious on digital mammography alone. Another four malignant lesions that were not visible on mammography were exclusively detected with X-ray dark-field imaging., Conclusions: Adding X-ray dark-field imaging to digital mammography increases the detection rate for breast cancer and DCIS associated lesions with micrometer-sized calcifications.The use of X-ray dark-field imaging may be able to provide more accurate and detailed radiological classification of suspicious breast lesions.Adding X-ray dark-field imaging to mammography may be able to increase the detection rate and improve preoperative planning in deciding between mastectomy or breast-conserving therapy, particularly in patients with invasive lobular breast cancer., Competing Interests: Conflict of interest statement: MR is an employee of Siemens Healthcare GmbH, Erlangen, Germany. All other authors declare that they do not have any conflicts of interest., (© The Author(s), 2020.)

Background: BRCA1/2 deleterious variants account for most of the hereditary breast and ovarian cancer cases. Prediction models and guidelines for the assessment of genetic risk rely heavily on criteria with high variability such as family cancer history. Here we investigated the efficacy of MRI (magnetic resonance imaging) texture features as a predictor for BRCA mutation status., Methods: A total of 41 female breast cancer individuals at high genetic risk, sixteen with a BRCA1/2 pathogenic variant and twenty five controls were included. From each MRI 4225 computer-extracted voxels were analyzed. Non-imaging features including clinical, family cancer history variables and triple negative receptor status (TNBC) were complementarily used. Lasso-principal component regression (L-PCR) analysis was implemented to compare the predictive performance, assessed as area under the curve (AUC), when imaging features were used, and lasso logistic regression or conventional logistic regression for the remaining analyses., Results: Lasso-selected imaging principal components showed the highest predictive value (AUC 0.86), surpassing family cancer history. Clinical variables comprising age at disease onset and bilateral breast cancer yielded a relatively poor AUC (~ 0.56). Combination of imaging with the non-imaging variables led to an improvement of predictive performance in all analyses, with TNBC along with the imaging components yielding the highest AUC (0.94). Replacing family history variables with imaging components yielded an improvement of classification performance of ~ 4%, suggesting that imaging compensates the predictive information arising from family cancer structure., Conclusions: The L-PCR model uncovered evidence for the utility of MRI texture features in distinguishing between BRCA1/2 positive and negative high-risk breast cancer individuals, which may suggest value to diagnostic routine. Integration of computer-extracted texture analysis from MRI modalities in prediction models and inclusion criteria might play a role in reducing false positives or missed cases especially when established risk variables such as family history are missing.