Impact of menopausal status on background parenchymal enhancement and fibroglandular tissue on breast MRI

2012 ◽  
Vol 22 (12) ◽  
pp. 2641-2647 ◽  
Author(s):  
Valencia King ◽  
Yajia Gu ◽  
Jennifer B. Kaplan ◽  
Jennifer D. Brooks ◽  
Malcolm C. Pike ◽  
...  
Keyword(s):  
Menopausal Status ◽  
Breast Mri ◽  
Fibroglandular Tissue ◽  
Background Parenchymal Enhancement ◽  
Parenchymal Enhancement

scholarly journals Motion artifacts, lesion type, and parenchymal enhancement in breast MRI: what does really influence diagnostic accuracy?

2018 ◽  
Vol 60 (1) ◽  
pp. 19-27 ◽  
Author(s):  
Paola Clauser ◽  
Matthias Dietzel ◽  
Michael Weber ◽  
Clemens G Kaiser ◽  
Pascal AT Baltzer
Keyword(s):  
Breast Mri ◽  
Lesion Size ◽  
Motion Artifacts ◽  
Lower Sensitivity ◽  
Fibroglandular Tissue ◽  
Factors Influencing ◽  
Background Parenchymal Enhancement ◽  
Lesion Type ◽  
Sensitivity Specificity ◽  
Parenchymal Enhancement

Background Motion artifacts can reduce image quality of breast magnetic resonance imaging (MRI). There is a lack of data regarding their effect on diagnostic estimates. Purpose To evaluate factors that potentially influence readers’ diagnostic estimates in breast MRI: motion artifacts; amount of fibroglandular tissue; background parenchymal enhancement; lesion size; and lesion type. Material and Methods This Institutional Review Board-approved, retrospective, cross-sectional, single-center study included 320 patients (mean age = 55.1 years) with 334 histologically verified breast lesions (139 benign, 195 malignant) who underwent breast MRI. Two expert breast radiologists evaluated the images considering: motion artifacts (1 = minimal to 4 = marked); fibroglandular tissue (BI-RADS FGT); background parenchymal enhancement (BI-RADS BPE); lesion size; lesion type; and BI-RADS score. Univariate (Chi-square) and multivariate (Generalized Estimation Equations [GEE]) statistics were used to identify factors influencing sensitivity, specificity, and accuracy. Results Lesions were: 230 mass (68.9%) and 59 non-mass (17.7%), no foci. Forty-five lesions (13.5%) did not enhance in MRI but were suspicious or unclear in conventional imaging. Sensitivity, specificity, and accuracy were 93.8%, 83.4%, and 89.8% for Reader 1 and 95.4%, 87.8%, and 91.9% for Reader 2. Lower sensitivity was observed in case of increased motion artifacts ( P = 0.007), non-mass lesions ( P < 0.001), and small lesions ≤ 10 mm ( P < 0.021). No further factors (e.g. BPE, FGT) significantly influenced diagnostic estimates. At multivariate analysis, lesion type and size were retained as independent factors influencing the diagnostic performance ( P < 0.033). Conclusion Motion artifacts can impair lesion characterization with breast MRI, but lesion type and small size have the strongest influence on diagnostic estimates.

The Impact of Bilateral Salpingo-Oophorectomy on Breast MRI Background Parenchymal Enhancement and Fibroglandular Tissue

2013 ◽  
Vol 24 (1) ◽  
pp. 162-168 ◽  
Author(s):  
E. R. Price ◽  
J. D. Brooks ◽  
E. J. Watson ◽  
S. B. Brennan ◽  
E. A. Comen ◽  
...  
Keyword(s):  
Breast Mri ◽  
Fibroglandular Tissue ◽  
Background Parenchymal Enhancement ◽  
The Impact ◽  
Parenchymal Enhancement

scholarly journals Comparison of Radiologist-Assigned Categories and Quantitative Measures of Background Parenchymal Enhancement on Breast MRI

2020 ◽  
Author(s):  
Bethany L Niell ◽  
Mahmoud Abdalah ◽  
Olya Stringfield ◽  
Malesa Pereira ◽  
Dana Ataya ◽  
...  
Keyword(s):  
Active Contours ◽  
Breast Mri ◽  
Automated Segmentation ◽  
Post Contrast ◽  
Fibroglandular Tissue ◽  
Background Parenchymal Enhancement ◽  
Otsu’S Method ◽  
Risk Patients ◽  
Student’S T ◽  
Parenchymal Enhancement

AbstractBackground parenchymal enhancement (BPE) on multi-parametric breast magnetic resonance imaging (mpMRI) reflects the volume and intensity of gadolinium uptake. We developed a semi-automated segmentation algorithm to extract and quantify measures of BPE and investigated the agreement of computed measures of BPE with radiologist-assigned categories. We retrospectively identified 123 high risk patients with breast mpMRI performed for screening indications. Pre- and post-gadolinium T1-weighted series with and without fat suppression were co-registered. Using Otsu’s method and an active contours method, the breast tissue was segmented from the chest wall and non-fat voxels were clustered to identify the amount of fibroglandular tissue. Median and inter-quartile ranges for the absolute volume of BPE (BPE cm3) and the percentage of BPE (BPE%) using a threshold PE of 30% were computed within the segmented FGT on the first post-contrast phase. Student’s t-test was used to evaluate BPE volume and BPE% by radiologist-assigned categories. Both BPE volume and BPE% differed significantly between minimal/mild and moderate/marked radiologist assigned categories (p=0.030 and 0.004, respectively). Using our newly developed semi-automated segmentation pipeline, we quantified fibroglandular tissue and BPE. The overlapping ranges of quantitative BPE corresponding to the radiologist-assigned BPE categories showcases the inter-reader variability with visual estimation of BPE.

scholarly journals Response Predictivity to Neoadjuvant Therapies in Breast Cancer: A Qualitative Analysis of Background Parenchymal Enhancement in DCE-MRI

2021 ◽  
Vol 11 (4) ◽  
pp. 256
Author(s):  
Daniele La Forgia ◽  
Angela Vestito ◽  
Maurilia Lasciarrea ◽  
Maria Colomba Comes ◽  
Sergio Diotaiuti ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Neoadjuvant Therapy ◽  
Menopausal Status ◽  
Therapy Response ◽  
Predictive Marker ◽  
Intermediate Step ◽  
Fibroglandular Tissue ◽  
Background Parenchymal Enhancement ◽  
Pre Treatment ◽  
Parenchymal Enhancement

Background: For assessing the predictability of oncology neoadjuvant therapy results, the background parenchymal enhancement (BPE) parameter in breast magnetic resonance imaging (MRI) has acquired increased interest. This work aims to qualitatively evaluate the BPE parameter as a potential predictive marker for neoadjuvant therapy. Method: Three radiologists examined, in triple-blind modality, the MRIs of 80 patients performed before the start of chemotherapy, after three months from the start of treatment, and after surgery. They identified the portion of fibroglandular tissue (FGT) and BPE of the contralateral breast to the tumor in the basal control pre-treatment (baseline). Results: We observed a reduction of BPE classes in serial MRI checks performed during neoadjuvant therapy, as compared to baseline pre-treatment conditions, in 61.3% of patients in the intermediate step, and in 86.7% of patients in the final step. BPE reduction was significantly associated with sequential anthracyclines/taxane administration in the first cycle of neoadjuvant therapy compared to anti-HER2 containing therapies. The therapy response was also significantly related to tumor size. There were no associations with menopausal status, fibroglandular tissue (FGT) amount, age, BPE baseline, BPE in intermediate, and in the final MRI step. Conclusions: The measured variability of this parameter during therapy could predict therapy effectiveness in early stages, improving decision-making in the perspective of personalized medicine. Our preliminary results suggest that BPE may represent a predictive factor in response to neoadjuvant therapy in breast cancer, warranting future investigations in conjunction with radiomics.

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