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      Breast Density Assessment Using a 3T MRI System: Comparison among Different Sequences

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          Abstract

          Purpose

          To compare MRI sequences for breast density measurements on a 3T MRI system using IDEAL (Iterative Decomposition of water and fat with Echo Asymmetry and Least squares estimation) as possible physiology-like reference.

          Materials and Methods

          MRI examination was performed in 48 consecutive patients (mean age 41, years; range, 35–67 years) on a 3.0T scanner and 46 were included. All (fertile) women, were examined between days 5 and 15 of their menstrual cycle. MRI protocol included: T1-turbo spin-echo (T1-tSE), T2-turbo spin-echo (T2-tSE), VIBRANT (Volume Imaging for Breast Assessment) before and after injection of contrast media and IDEAL. Breast density was calculated with semi-automated software. Statistical analysis was performed with non-parametric tests.

          Results

          Mean percentage of breast density calculated in each sequence was: T1-tSE  = 56%; T2-tSE  = 52%; IDEAL FatOnly  = 55%; IDEAL WaterOnly  = 53%, VIBRANT  = 55%. Significant differences were observed between T2-tSE and both T1-tSE (p<0.001), VIBRANT sequences (p = 0.009), T1-tSE and both IDEAL WaterOnly (p = 0.007) and IDEAL FatOnly (p = 0.047). Breast density percentage showed a positive linear correlation among different sequences: r≥0.93.

          Conclusions

          Differences exist between MRI sequences used to assess breast density percentage. T1-weighted sequences values were similar to IDEAL sequences.

          Related collections

          Most cited references30

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          Magnetic resonance imaging of the breast: recommendations from the EUSOMA working group.

          The use of breast magnetic resonance imaging (MRI) is rapidly increasing. EUSOMA organised a workshop in Milan on 20-21st October 2008 to evaluate the evidence currently available on clinical value and indications for breast MRI. Twenty-three experts from the disciplines involved in breast disease management - including epidemiologists, geneticists, oncologists, radiologists, radiation oncologists, and surgeons - discussed the evidence for the use of this technology in plenary and focused sessions. This paper presents the consensus reached by this working group. General recommendations, technical requirements, methodology, and interpretation were firstly considered. For the following ten indications, an overview of the evidence, a list of recommendations, and a number of research issues were defined: staging before treatment planning; screening of high-risk women; evaluation of response to neoadjuvant chemotherapy; patients with breast augmentation or reconstruction; occult primary breast cancer; breast cancer recurrence; nipple discharge; characterisation of equivocal findings at conventional imaging; inflammatory breast cancer; and male breast. The working group strongly suggests that all breast cancer specialists cooperate for an optimal clinical use of this emerging technology and for future research, focusing on patient outcome as primary end-point. Copyright (c) 2010 Elsevier Ltd. All rights reserved.
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            Mammographic density. Potential mechanisms of breast cancer risk associated with mammographic density: hypotheses based on epidemiological evidence

            There is now extensive evidence that mammographic density is an independent risk factor for breast cancer that is associated with large relative and attributable risks for the disease. The epidemiology of mammographic density, including the influences of age, parity and menopause, is consistent with it being a marker of susceptibility to breast cancer, in a manner similar to the concept of 'breast tissue age' described by the Pike model. Mammographic density reflects variations in the tissue composition of the breast. It is associated positively with collagen and epithelial and nonepithelial cells, and negatively with fat. Mammographic density is influenced by some hormones and growth factors as well as by several hormonal interventions. It is also associated with urinary levels of a mutagen. Twin studies have shown that most of the variation in mammographic density is accounted for by genetic factors. The hypothesis that we have developed from these observations postulates that the combined effects of cell proliferation (mitogenesis) and genetic damage to proliferating cells by mutagens (mutagenesis) may underlie the increased risk for breast cancer associated with extensive mammographic density. There is clearly a need for improved understanding of the specific factors that are involved in these processes and of the role played by the several breast tissue components that contribute to density. In particular, identification of the genes that are responsible for most of the variance in percentage density (and of their biological functions) is likely to provide insights into the biology of the breast, and may identify potential targets for preventative strategies in breast cancer.
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              Multicoil Dixon chemical species separation with an iterative least-squares estimation method.

              This work describes a new approach to multipoint Dixon fat-water separation that is amenable to pulse sequences that require short echo time (TE) increments, such as steady-state free precession (SSFP) and fast spin-echo (FSE) imaging. Using an iterative linear least-squares method that decomposes water and fat images from source images acquired at short TE increments, images with a high signal-to-noise ratio (SNR) and uniform separation of water and fat are obtained. This algorithm extends to multicoil reconstruction with minimal additional complexity. Examples of single- and multicoil fat-water decompositions are shown from source images acquired at both 1.5T and 3.0T. Examples in the knee, ankle, pelvis, abdomen, and heart are shown, using FSE, SSFP, and spoiled gradient-echo (SPGR) pulse sequences. The algorithm was applied to systems with multiple chemical species, and an example of water-fat-silicone separation is shown. An analysis of the noise performance of this method is described, and methods to improve noise performance through multicoil acquisition and field map smoothing are discussed. Copyright 2003 Wiley-Liss, Inc.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2014
                3 June 2014
                : 9
                : 6
                : e99027
                Affiliations
                [1 ]Institute of Anatomy, Department of Experimental Medicine, University of Genova, Genova, Italy
                [2 ]Radiology Department, University of Genova, Genova, Italy
                [3 ]CNR-IMATI, Consiglio Nazionale delle Ricerche, Istituto di Matematica Applicata e Tecnologie Informatiche, Genova, Italy
                [4 ]Institute of Statistics, Department of Health Sciences, University of Genova, Genova, Italy
                [5 ]Screening and Test Evaluation Program (STEP), School of Public Health, Sydney Medical School, University of Sydney, Sydney, Australia
                [6 ]Department of Diagnostic Senology, Ist Istituto Nazionale per la Ricerca sul Cancro, IRCCS Azienda Ospedaliera Universitaria San Martino, Genova, Italy
                University Medical Center (UMC) Utrecht, Netherlands
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: AT BB GT DA LM SA AS MPS NH MC. Performed the experiments: MC AT BB DA LM. Analyzed the data: AS MPS AT. Contributed reagents/materials/analysis tools: GT. Wrote the paper: AT LM DA.

                Article
                PONE-D-14-01613
                10.1371/journal.pone.0099027
                4044003
                24892933
                de47f075-dd8d-4f19-8fe5-eeab1d305cf7
                Copyright @ 2014

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 15 January 2014
                : 9 May 2014
                Page count
                Pages: 6
                Funding
                The authors have no support or funding to report.
                Categories
                Research Article
                Medicine and Health Sciences
                Diagnostic Medicine
                Diagnostic Radiology
                Magnetic Resonance Imaging
                Radiology and Imaging

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