scholarly journals A Gradient-Based Approach for Breast DCE-MRI Analysis

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
L. Losurdo ◽  
T. M. A. Basile ◽  
A. Fanizzi ◽  
R. Bellotti ◽  
U. Bottigli ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Magnetic Resonance Imaging ◽  
High Risk ◽  
Breast Tissue ◽  
Normal Breast Tissue ◽  
Normal Breast ◽  
Resonance Imaging ◽  
Background Parenchymal Enhancement ◽  
Parenchymal Enhancement ◽  
Tissue Enhancement

Breast cancer is the main cause of female malignancy worldwide. Effective early detection by imaging studies remains critical to decrease mortality rates, particularly in women at high risk for developing breast cancer. Breast Magnetic Resonance Imaging (MRI) is a common diagnostic tool in the management of breast diseases, especially for high-risk women. However, during this examination, both normal and abnormal breast tissues enhance after contrast material administration. Specifically, the normal breast tissue enhancement is known as background parenchymal enhancement: it may represent breast activity and depends on several factors, varying in degree and distribution in different patients as well as in the same patient over time. While a light degree of normal breast tissue enhancement generally causes no interpretative difficulties, a higher degree may cause difficulty to detect and classify breast lesions at Magnetic Resonance Imaging even for experienced radiologists. In this work, we intend to investigate the exploitation of some statistical measurements to automatically characterize the enhancement trend of the whole breast area in both normal and abnormal tissues independently from the presence of a background parenchymal enhancement thus to provide a diagnostic support tool for radiologists in the MRI analysis.

scholarly journals Quantitative background parenchymal enhancement to predict recurrence after neoadjuvant chemotherapy for breast cancer

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Sebastien Moliere ◽  
Isabelle Oddou ◽  
Vincent Noblet ◽  
Francis Veillon ◽  
Carole Mathelin
Keyword(s):  
Breast Cancer ◽  
Neoadjuvant Chemotherapy ◽  
Breast Tissue ◽  
Normal Breast Tissue ◽  
Normal Breast ◽  
Pathological Response ◽  
Background Parenchymal Enhancement ◽  
Therapeutic Value ◽  
Before And After ◽  
Parenchymal Enhancement

AbstractBreast background parenchymal enhancement (BPE) is an increasingly studied MRI parameter that reflects the microvasculature of normal breast tissue, which has been shown to change during neoadjuvant chemotherapy (NAC) for breast cancer. We aimed at evaluating the BPE in patients undergoing NAC and its prognostic value to predict recurrence. MRI BPE was visually and quantitatively evaluated before and after NAC in a retrospective cohort of 102 women with unilateral biopsy-proven invasive breast cancer. Pre-therapeutic BPE was not predictive of pathological response or recurrence. Quantitative post-therapeutic BPE was significantly decreased compared to pre-therapeutic value. Post-therapeutic quantitative BPE significantly predicted recurrence (HR = 6.38 (0.71, 12.06), p < 0.05).

scholarly journals Breast cancer and background parenchymal enhancement at breast magnetic resonance imaging: a meta-analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Na Hu ◽  
Jinghao Zhao ◽  
Yong Li ◽  
Quanshui Fu ◽  
Linwei Zhao ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Breast Magnetic Resonance Imaging ◽  
Meta Analysis ◽  
Resonance Imaging ◽  
High Background ◽  
Background Parenchymal Enhancement ◽  
Breast Magnetic Resonance ◽  
Parenchymal Enhancement

Abstract Background The background parenchymal enhancement at breast magnetic resonance imaging use to predict breast cancer attracts many searchers to draw a possible relationship. However, the results of their relationships were conflicting. This meta-analysis was performed to assess breast cancer frequency associations with background parenchymal enhancement. Methods A systematic literature search up to January 2020 was performed to detect studies recording associations between breast cancer frequency and background parenchymal enhancement. We found thirteen studies including 13,788 women at the start with 4046 breast cancer. We calculated the odds ratio (OR) and the 95% confidence intervals (CIs) between breast cancer frequency and background parenchymal enhancement by the dichotomous technique with a random or fixed-effect model. Results Women with minimal or mild background parenchymal enhancement at breast magnetic resonance imaging did not have any risk of breast cancer compared to control women (OR, 1.20; 95% CI 0.54–2.67). However, high background parenchymal enhancement at breast magnetic resonance imaging (OR, 2.66; 95% CI 1.36–5.19) and moderate (OR, 2.51; 95% CI 1.49–4.21) was associated with a significantly higher rate of breast cancer frequency compared to control women. Conclusions Our meta-analysis showed that the women with high and moderate background parenchymal enhancement at breast magnetic resonance imaging have higher risks, up to 2.66 fold, of breast cancer. We suggest that women with high or moderate background parenchymal enhancement at breast magnetic resonance imaging to be scheduled for more frequent follow-up and screening for breast cancer to avoid any complications.

scholarly journals Correlation Between Mammographic Breast Density, Breast Tissue Type in Ultrasonography, Fibroglandular Tissue, and Background Parenchymal Enhancement in Magnetic Resonance Imaging

2018 ◽  
Vol 12 ◽  
pp. 117822341877197 ◽  
Author(s):  
Afsaneh Alikhassi ◽  
Seyedeh Nooshin Miratashi Yazdi ◽  
Hedieh Akbari ◽  
Sona Akbari Kia ◽  
Masoud Baikpour
Keyword(s):  
Breast Cancer ◽  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Breast Density ◽  
Menopausal Status ◽  
Mammographic Breast Density ◽  
Resonance Imaging ◽  
Imaging Studies ◽  
Background Parenchymal Enhancement ◽  
Parenchymal Enhancement

Objective: Breast cancer is the most common malignancy in the female population, and imaging studies play a critical role for its early detection. Mammographic breast density (MBD) is one of the markers used to predict the risk stratification of breast cancer in patients. We aimed to assess the correlations among MBD, ultrasound breast composition (USBC), fibroglandular tissue (FGT), and the amount of background parenchymal enhancement (BPE) in magnetic resonance imaging, after considering the subjects’ menopausal status. Methods: In this retrospective cross-sectional study, the medical records’ archives in a tertiary referral hospital were reviewed. Data including age, menopausal status, their mammograms, and ultrasound assessments were extracted from their records. All of their imaging studies were reviewed, and MBD, USBC, FGT, and BPE were determined, recorded, and entered into SPSS software for analysis. Results: A total of 121 women (mean age = 42.7 ± 11.0 years) were included, of which 35 out of 115 (30.4%) had reached menopause. Using the Jonckheere-Terpstra test for evaluating the trends among above mentioned 4 radiologic characteristics in the total sample population, a significant positive relation was found between each of these paired variables: (1) USBC-MBD ( P = .006), (2) FGT-MBD ( P = .001), (3) USBC-BPE ( P = .046), (4) USBC-FGT ( P = .036), and (5) BPE-FGT ( P < .001). These trends were not found to be significant among premenopausal subjects. Conclusions: Considering the trends between different measures of breast density in the 3 radiologic modalities, these factors can be used interchangeably in certain settings.

scholarly journals Genomic Changes in Normal Breast Tissue in Women at Normal Risk or at High Risk for Breast Cancer

2016 ◽  
Vol 10 ◽  
pp. BCBCR.S39384 ◽  
Author(s):  
David N. Danforth
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
High Risk ◽  
Breast Tissue ◽  
Sporadic Breast Cancer ◽  
Normal Breast Tissue ◽  
Normal Breast ◽  
Breast Carcinogenesis ◽  
Molecular Changes ◽  
Breast Tissues

Sporadic breast cancer develops through the accumulation of molecular abnormalities in normal breast tissue, resulting from exposure to estrogens and other carcinogens beginning at adolescence and continuing throughout life. These molecular changes may take a variety of forms, including numerical and structural chromosomal abnormalities, epigenetic changes, and gene expression alterations. To characterize these abnormalities, a review of the literature has been conducted to define the molecular changes in each of the above major genomic categories in normal breast tissue considered to be either at normal risk or at high risk for sporadic breast cancer. This review indicates that normal risk breast tissues (such as reduction mammoplasty) contain evidence of early breast carcinogenesis including loss of heterozygosity, DNA methylation of tumor suppressor and other genes, and telomere shortening. In normal tissues at high risk for breast cancer (such as normal breast tissue adjacent to breast cancer or the contralateral breast), these changes persist, and are increased and accompanied by aneuploidy, increased genomic instability, a wide range of gene expression differences, development of large cancerized fields, and increased proliferation. These changes are consistent with early and long-standing exposure to carcinogens, especially estrogens. A model for the breast carcinogenic pathway in normal risk and high-risk breast tissues is proposed. These findings should clarify our understanding of breast carcinogenesis in normal breast tissue and promote development of improved methods for risk assessment and breast cancer prevention in women.

scholarly journals Correlation of Background Parenchymal Enhancement on Breast Magnetic Resonance Imaging with Quantitative Mammographic Parameters Derived using fully Automated Volumetric Software

2021 ◽  
Author(s):  
Gayeong Lim ◽  
Kyoungkyg Bae ◽  
Soyeoun Lim ◽  
Gyoungmin Park ◽  
Minseo Bang
Keyword(s):  
Breast Cancer ◽  
Magnetic Resonance Imaging ◽  
Mammographic Density ◽  
Breast Mri ◽  
Mammographic Breast Density ◽  
Resonance Imaging ◽  
Volumetric Density ◽  
Background Parenchymal Enhancement ◽  
The Relationship ◽  
Parenchymal Enhancement

Abstract Background: Background parenchymal enhancement (BPE) and mammographic breast density are risk factors for breast cancer. However, existing evidence regarding the association between these risk factors is inconclusive. This study aimed to evaluate the relationship between BPE and quantitative and subdivided mammographic density parameters, such as fibroglandular tissue (FGT) volume, entire breast volume, and volumetric density (%), measured using a fully automated volumetric software.Methods: From July 2017 to August 2018, patients with newly diagnosed breast cancer who had undergone preoperative mammography and magnetic resonance imaging (MRI) at our hospital were identified. Mammographic density analysis was performed using a fully automated volumetric software. Two breast radiologists consensually rated BPE and the amount of FGT in each contralateral normal breast MRI based on four categories of the Breast Imaging-Reporting and Data System. The Pearson correlation coefficient was used to analyze the relationship between mammographic density and the FGT and BPE observed on breast MRI.Results: A total of 364 women were included, of whom 153 (42%) were premenopausal (mean age, 44.22±6.29 years) and 211 (58%) were postmenopausal (mean age, 57.91±9.59 years).The premenopause group had significantly higher levels of BPE and FGT on MRI and FGT volume and volumetric density (%) on mammography. FGT and BPE observed on breast MRI were correlated in the overall sample and postmenopause group(r=0.352and 0.265, respectively). The FGT volume on mammography was significantly correlated with BPE in the overall sample and in the pre- and postmenopause groups (r=0.290, 0.166, and 0.294, respectively). Volumetric density (%) on mammography and BPE were correlated in the total sample and postmenopause group(r=0.369 and 0.281, respectively). Conclusion: Mammographic breast density and BPE on MRI are significantly correlated in patients with breast cancer. The mammographic FGT volume is particularly correlated with BPE on MRI, regardless of the patient’s menopausal state.

scholarly journals Identification of high-risk genes in triple-negative breast cancer by bioinformatics

2021 ◽  
Author(s):  
Lu Xiang ◽  
Caiping Chen ◽  
Guihong Ni ◽  
Min Tao
Keyword(s):  
Breast Cancer ◽  
High Risk ◽  
Breast Tissue ◽  
Target Genes ◽  
Triple Negative ◽  
Normal Breast Tissue ◽  
Normal Breast ◽  
Risk Genes ◽  
Online Tool ◽  
Free Survival

Abstract Background Current research has failed to find a target gene for triple-negative breast cancer (TNBC), which has resulted in the treatment for TNBC being less effective than that for other types of breast cancer. Finding high-risk genes for TNBC by bioinformatics may help to identify target genes for TNBC. Methods The gene expression data of 4 chips (GSE7904, GSE31448, GSE45827, GSE65194) which contains of normal breast tissue and TNBC tissue were obtained from the Gene Expression Omnibus. The differentially expressed genes (DEGs) between normal breast tissue and TNBC tissue were identified. Gene Ontology (GO) functional annotation analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs were performed by the DAVID website. Protein-protein interaction network analysis of DEGs was carried out by the STRING website, and the results were imported into Cytoscape. Then, module analysis was carried out by using the MCODE app. The online tool of the Kaplan-Meier Plotter website was used to analyse associations between relapse-free survival (RFS) and the expression of genes obtained by MCODE, and the metastasis-free survival (MFS) data from GSE58812 were used for survival verification. The difference in the expression of the identified genes was verified by the online tool of the UALCAN website. Results There were 127 upregulated and 293 downregulated genes in the DEGs. The GO and KEGG analysis showed that the DEGs were particularly enriched in mitotic nuclear division, extracellular space, heparin binding, and ECM-receptor interaction. MCODE obtained a total of 47 genes in 4 gene clusters, 29 of which were related to RFS. Survival verification indicated that 14 out of 29 genes were related to MFS, namely, CCNB1, AURKB, KIF20A, BUB1B, DLGAP5, CXCL11, CXCL9, CXCL10, CXCL12, IGF1, FN1, CFD, SGO2 and CDCA5. Conclusions We identified 14 genes as the high-risk genes for TNBC. Further research on these genes may identify the target genes of TNBC.

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