Publications by authors named "Evelyn Wenkel"

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).

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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.

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Article Synopsis
  • A study evaluated the effectiveness of contrast-enhanced spiral breast computed tomography (CE-SBCT) versus traditional mammography in detecting breast cancer in 90 women with confirmed malignant lesions.
  • CE-SBCT showed significantly higher detectability rates (99.1%) compared to mammography (83.8%) and non-CE-SBCT (66.7%), regardless of breast density.
  • Although CE-SBCT was highly effective in detecting masses, it was less effective for certain features like architectural distortions and microcalcifications, and confidence in the diagnosis was very high for CE-SBCT (97.2%) compared to mammography (81.4%).
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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.

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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.

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  • The study examines the use of diffusion-weighted imaging (DWI) to differentiate skin pathologies related to breast conditions in MRI scans.
  • It included 88 female patients and compared the apparent diffusion coefficients (ADCs) among various conditions, such as inflammatory breast cancer and benign skin inflammation.
  • Findings showed that while there were significant ADC differences between skin-involved breast cancer and benign skin inflammation, more extensive research is needed to determine the effectiveness of DWI for accurately diagnosing these skin pathologies.
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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.

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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.

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Article Synopsis
  • - Breast MRI is a crucial tool in breast imaging, providing valuable insights for diagnosis and treatment.
  • - Updated recommendations for conducting breast MRI include a useful table that summarizes key points and offers additional detailed commentary.
  • - The "classic" breast MRI can be performed following these updated guidelines, with specific tips for addressing clinical issues like implant rupture and lymph node status.
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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.

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Article Synopsis
  • The study looked at how having an MRI before surgery affects the chances of needing a mastectomy or having to have more surgery for women with ductal carcinoma in situ (DCIS), a type of breast cancer.
  • They compared two groups of patients: one that had MRIs before surgery and one that didn't, looking closely at various factors that could affect the results.
  • The results showed that women who had the MRI were more likely to have a mastectomy but were less likely to need additional surgeries afterwards.
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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.

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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.

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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.

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Article Synopsis
  • The study aimed to use deep learning to detect MRI artifacts in breast images derived from diffusion weighted imaging (DWI) protocols.
  • The dataset included 1,309 MRI exams from 1,158 individuals, with a median age of 50, conducted between March 2017 and June 2020, revealing an artifact prevalence of 37%.
  • A DenseNet model achieved impressive results in identifying artifacts, with a precision-recall area of 0.921, indicating the potential for improving quality assurance in breast MRI examinations.
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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.

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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.

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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.

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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.

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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.

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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.

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