Literature DB >> 25333307

Introduction of an automated user-independent quantitative volumetric magnetic resonance imaging breast density measurement system using the Dixon sequence: comparison with mammographic breast density assessment.

Georg Johannes Wengert1, Thomas H Helbich, Wolf-Dieter Vogl, Pascal Baltzer, Georg Langs, Michael Weber, Wolfgang Bogner, Stephan Gruber, Siegfried Trattnig, Katja Pinker.   

Abstract

OBJECTIVES: The purposes of this study were to introduce and assess an automated user-independent quantitative volumetric (AUQV) breast density (BD) measurement system on the basis of magnetic resonance imaging (MRI) using the Dixon technique as well as to compare it with qualitative and quantitative mammographic (MG) BD measurements.
MATERIALS AND METHODS: Forty-three women with normal mammogram results (Breast Imaging Reporting and Data System 1) were included in this institutional review board-approved prospective study. All participants were subjected to BD assessment with MRI using the following sequence with the Dixon technique (echo time/echo time, 6 milliseconds/2.45 milliseconds/2.67 milliseconds; 1-mm isotropic; 3 minutes 38 seconds). To test the reproducibility, a second MRI after patient repositioning was performed. The AUQV magnetic resonance (MR) BD measurement system automatically calculated percentage (%) BD. The qualitative BD assessment was performed using the American College of Radiology Breast Imaging Reporting and Data System BD categories. Quantitative BD was estimated semiautomatically using the thresholding technique Cumulus4. Appropriate statistical tests were used to assess the agreement between the AUQV MR measurements and to compare them with qualitative and quantitative MG BD estimations.
RESULTS: The AUQV MR BD measurements were successfully performed in all 43 women. There was a nearly perfect agreement of AUQV MR BD measurements between the 2 MR examinations for % BD (P < 0.001; intraclass correlation coefficient, 0.998) with no significant differences (P = 0.384). The AUQV MR BD measurements were significantly lower than quantitative and qualitative MG BD assessment (P < 0.001).
CONCLUSIONS: The AUQV MR BD measurement system allows a fully automated, user-independent, robust, reproducible, as well as radiation- and compression-free volumetric quantitative BD assessment through different levels of BD. The AUQV MR BD measurements were significantly lower than the currently used qualitative and quantitative MG-based approaches, implying that the current assessment might overestimate breast density with MG.

Entities:  

Mesh:

Year:  2015        PMID: 25333307     DOI: 10.1097/RLI.0000000000000102

Source DB:  PubMed          Journal:  Invest Radiol        ISSN: 0020-9996            Impact factor:   6.016


  12 in total

1.  MRI-based quantification of residual fibroglandular tissue of the breast after conservative mastectomies.

Authors:  Ramona Woitek; Georg Pfeiler; Alex Farr; Panagiotis Kapetas; Julia Furtner; Maria Bernathova; Veronika Schöpf; Paola Clauser; Maria A Marino; Katja Pinker; Pascal A Baltzer; Thomas H Helbich
Journal:  Eur J Radiol       Date:  2018-04-26       Impact factor: 3.528

2.  Automated Segmentation of Tissues Using CT and MRI: A Systematic Review.

Authors:  Leon Lenchik; Laura Heacock; Ashley A Weaver; Robert D Boutin; Tessa S Cook; Jason Itri; Christopher G Filippi; Rao P Gullapalli; James Lee; Marianna Zagurovskaya; Tara Retson; Kendra Godwin; Joey Nicholson; Ponnada A Narayana
Journal:  Acad Radiol       Date:  2019-08-10       Impact factor: 3.173

3.  Association between breast cancer, breast density, and body adiposity evaluated by MRI.

Authors:  Wenlian Zhu; Peng Huang; Katarzyna J Macura; Dmitri Artemov
Journal:  Eur Radiol       Date:  2015-10-21       Impact factor: 5.315

Review 4.  Machine learning in breast MRI.

Authors:  Beatriu Reig; Laura Heacock; Krzysztof J Geras; Linda Moy
Journal:  J Magn Reson Imaging       Date:  2019-07-05       Impact factor: 4.813

5.  Quantitative evaluation of redox ratio and collagen characteristics during breast cancer chemotherapy using two-photon intrinsic imaging.

Authors:  Shulian Wu; Yudian Huang; Qinggong Tang; Zhifang Li; Hannah Horng; Jiatian Li; Zaihua Wu; Yu Chen; Hui Li
Journal:  Biomed Opt Express       Date:  2018-02-28       Impact factor: 3.732

6.  Reproducible automated breast density measure with no ionizing radiation using fat-water decomposition MRI.

Authors:  Jie Ding; Alison T Stopeck; Yi Gao; Marilyn T Marron; Betsy C Wertheim; Maria I Altbach; Jean-Philippe Galons; Denise J Roe; Fang Wang; Gertraud Maskarinec; Cynthia A Thomson; Patricia A Thompson; Chuan Huang
Journal:  J Magn Reson Imaging       Date:  2018-04-06       Impact factor: 4.813

7.  Inter- and intra-observer agreement of BI-RADS-based subjective visual estimation of amount of fibroglandular breast tissue with magnetic resonance imaging: comparison to automated quantitative assessment.

Authors:  G J Wengert; T H Helbich; R Woitek; P Kapetas; P Clauser; P A Baltzer; W-D Vogl; M Weber; A Meyer-Baese; Katja Pinker
Journal:  Eur Radiol       Date:  2016-04-23       Impact factor: 5.315

8.  Ultrasound Tomography Evaluation of Breast Density: A Comparison With Noncontrast Magnetic Resonance Imaging.

Authors:  Elizabeth A M OʼFlynn; Jeremie Fromageau; Araminta E Ledger; Alessandro Messa; Ashley DʼAquino; Minouk J Schoemaker; Maria Schmidt; Neb Duric; Anthony J Swerdlow; Jeffrey C Bamber
Journal:  Invest Radiol       Date:  2017-06       Impact factor: 6.016

9.  Comparison of Dixon Sequences for Estimation of Percent Breast Fibroglandular Tissue.

Authors:  Araminta E W Ledger; Erica D Scurr; Julie Hughes; Alison Macdonald; Toni Wallace; Karen Thomas; Robin Wilson; Martin O Leach; Maria A Schmidt
Journal:  PLoS One       Date:  2016-03-24       Impact factor: 3.240

10.  MRI background parenchymal enhancement, fibroglandular tissue, and mammographic breast density in patients with invasive lobular breast cancer on adjuvant endocrine hormonal treatment: associations with survival.

Authors:  Roberto Lo Gullo; Isaac Daimiel; Carolina Rossi Saccarelli; Almir Bitencourt; Varadan Sevilimedu; Danny F Martinez; Maxine S Jochelson; Elizabeth A Morris; Jeffrey S Reiner; Katja Pinker
Journal:  Breast Cancer Res       Date:  2020-08-20       Impact factor: 6.466

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