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  • 1
    In: Scientific Reports, Springer Science and Business Media LLC, Vol. 13, No. 1 ( 2023-06-29)
    Abstract: 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.
    Type of Medium: Online Resource
    ISSN: 2045-2322
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 2615211-3
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  • 2
    Online Resource
    Online Resource
    Ovid Technologies (Wolters Kluwer Health) ; 2019
    In:  Investigative Radiology Vol. 54, No. 8 ( 2019-8), p. 524-530
    In: Investigative Radiology, Ovid Technologies (Wolters Kluwer Health), Vol. 54, No. 8 ( 2019-8), p. 524-530
    Abstract: Comparison of the diagnostic value of simultaneous multislice (SMS) accelerated diffusion-weighted echo planar imaging (EPI) of malignant and benign lesions of the breast compared with a reference EPI sequence. Materials and Methods The study was approved by the institutional ethics committee. Sixty-eight patients were examined with a diffusion-weighted EPI (reference EPI; TE = 54 milliseconds; TR = 9000 milliseconds; TA, 3:27 minutes) and a diffusion-weighted SMS accelerated EPI (SMS EPI; acceleration factor 2; TE = 58 milliseconds; TR = 4300 milliseconds; TA, 1:53 minutes) in addition to the standard magnetic resonance imaging (MRI) protocol. Further acquisition parameters were as follows: 3 T MAGNETOM Skyra (Siemens Healthcare, Erlangen, Germany), 2.5-mm isotropic resolution, field of view = 185 to 190 × 350 mm 2 , 62 slices, b = 50 and 800 s/mm 2 with 1 and 4 averages, respectively. A dedicated 16-channel bilateral breast coil was used for imaging. Image quality was evaluated with respect to the presence of artifacts, signal voids, and quality of fat suppression. These parameters were rated using a 5-point Likert scale (1 = very strong to 5 = negligible). The apparent diffusion coefficient (ADC) was measured in 72 focal lesions (46 breast carcinomas and 26 benign lesions), and the diagnostic value of the 2 datasets was statistically evaluated and compared. The evaluation was performed a second time excluding cysts. Results Artifacts and signal voids were negligible in both sequences (mean on Likert scale for reference EPI 4.68 vs SMS EPI 4.65, P = 0.52, and mean on Likert scale for reference EPI 4.85 vs SMS EPI 4.77, P = 0.14). Fat suppression was significantly better in SMS EPI (mean on Likert scale 3.28 vs 2.97, P 〈 0.001, Pearson r = 0.49). For benign lesions, the mean ADC in both EPI sequences was 1.86 · 10 −3 mm 2 /s. For malignant lesions, a mean ADC of 0.90 · 10 −3 mm 2 /s for the reference EPI and 0.89 · 10 −3 mm 2 /s for the SMS EPI was found. No significant difference between the EPI sequences was observed for ADC values ( P = 0.75) and for the area under the curve (SMS, 0.985; no SMS, 0.975). The cutoff for differentiation of benign and malignant lesions was at ADC = 1.42 · 10 −3 mm 2 /s for SMS EPI (sensitivity, 1; specificity, 0.88) and at 1.23 · 10 −3 mm 2 /s for the reference EPI (sensitivity, 1; specificity, 0.92). Excluding the cysts, the cutoff for differentiation of benign and malignant lesions was at ADC = 1.11 · 10 −3 mm 2 /s for SMS EPI (sensitivity, 0.89; specificity, 0.93) and at 1.23 · 10 −3 mm 2 /s for the reference EPI (sensitivity, 1; specificity, 0.87). Conclusions Our data indicate that SMS acceleration can be used for diffusion imaging in breast MRI in clinical practice. Simultaneous multislice EPI achieved the same diagnostic accuracy in breast MRI, but in a substantially reduced scan time.
    Type of Medium: Online Resource
    ISSN: 1536-0210 , 0020-9996
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2019
    detail.hit.zdb_id: 2041543-6
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  • 3
    Online Resource
    Online Resource
    Ovid Technologies (Wolters Kluwer Health) ; 2021
    In:  Investigative Radiology Vol. 56, No. 10 ( 2021-10), p. 629-636
    In: Investigative Radiology, Ovid Technologies (Wolters Kluwer Health), Vol. 56, No. 10 ( 2021-10), p. 629-636
    Abstract: 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/mm 2 (b1500) and 2500 s/mm 2 (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.
    Type of Medium: Online Resource
    ISSN: 1536-0210 , 0020-9996
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2021
    detail.hit.zdb_id: 2041543-6
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  • 4
    In: Acta Radiologica, SAGE Publications
    Abstract: 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.
    Type of Medium: Online Resource
    ISSN: 0284-1851 , 1600-0455
    RVK:
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2023
    detail.hit.zdb_id: 2024579-8
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  • 5
    In: Diagnostics, MDPI AG, Vol. 14, No. 13 ( 2024-07-03), p. 1427-
    Abstract: 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/mm2). 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.
    Type of Medium: Online Resource
    ISSN: 2075-4418
    Language: English
    Publisher: MDPI AG
    Publication Date: 2024
    detail.hit.zdb_id: 2662336-5
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  • 6
    In: Applied Sciences, MDPI AG, Vol. 10, No. 17 ( 2020-08-25), p. 5876-
    Abstract: Besides X-ray and fluoroscopy, a previously introduced X-ray scanner offers a 3D cone beam option (Multitom Rax, Siemens Healthcare). The aim of this study was to evaluate various scan parameters and post-processing steps to optimize image quality and radiation exposure for imaging of the parasinus region. Four human cadaver heads were examined with different tube voltages (90–121 kV), dose levels (DLs) (278–2180 nGy) and pre-filtration methods (none, Cu 0.2 mm, Cu 0.3 mm and Sn 0.4 mm). All images were reconstructed in 2 mm slice thickness with and without a metal artifact reduction algorithm in three different kernels. In total, 80 different scan protocols and 480 datasets were evaluated. Image quality was rated on a 5-point Likert scale. Radiation exposure (mean computed tomography volume index (CTDIvol) and effective dose) was calculated for each scan. The most dose-effective combination for the diagnosis of sinusitis was 121 kV/DL of 278/0.3 mm copper (CTDIvol 1.70 mGy, effective dose 77 µSv). Scan protocols with 121 kV/DL1090/0.3 mm copper were rated sufficient for preoperative sinus surgery planning (CTDIvol 4.66 mGy, effective dose 212 µSv). Therefore, sinusitis and preoperative sinus surgery planning can be performed in diagnostic image quality at low radiation dose levels with a multipurpose X-ray system.
    Type of Medium: Online Resource
    ISSN: 2076-3417
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2704225-X
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  • 7
    Online Resource
    Online Resource
    Elsevier BV ; 2022
    In:  European Journal of Radiology Vol. 157 ( 2022-12), p. 110605-
    In: European Journal of Radiology, Elsevier BV, Vol. 157 ( 2022-12), p. 110605-
    Type of Medium: Online Resource
    ISSN: 0720-048X
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2022
    detail.hit.zdb_id: 2005350-2
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  • 8
    In: Journal of Magnetic Resonance Imaging, Wiley, Vol. 56, No. 5 ( 2022-11), p. 1343-1352
    Abstract: 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 (kurtosis corrected diffusion coefficient) and kurtosis 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 ( in μm 2 /msec), 2.03 vs. 1.26 ( in μm 2 /msec), 0.54 vs. 0.90 (), 0.55 vs. 0.99 (). AUC for voxel‐by‐voxel and volume‐averaged fit were 0.9494 and 0.9508 (); 0.9175 and 0.9298 (). For both, AUC did not differ significantly ( P  = 0.20). Correlation of values between the two approaches was very high ( r  = 0.99 for and r  = 0.97 for ). 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
    Type of Medium: Online Resource
    ISSN: 1053-1807 , 1522-2586
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2022
    detail.hit.zdb_id: 1497154-9
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  • 9
    In: Diagnostics, MDPI AG, Vol. 13, No. 6 ( 2023-03-22), p. 1197-
    Abstract: 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.
    Type of Medium: Online Resource
    ISSN: 2075-4418
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2662336-5
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  • 10
    In: European Journal of Radiology, Elsevier BV, Vol. 145 ( 2021-12), p. 110038-
    Type of Medium: Online Resource
    ISSN: 0720-048X
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2021
    detail.hit.zdb_id: 2005350-2
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