Literature DB >> 22894415

Consistency of breast density measured from the same women in four different MR scanners.

Jeon-Hor Chen1, Siwa Chan, Yi-Jui Liu, Dah-Cherng Yeh, Chih-Kai Chang, Li-Kuang Chen, Wei-Fan Pan, Chih-Chen Kuo, Muqing Lin, Daniel H E Chang, Peter T Fwu, Min-Ying Su.   

Abstract

PURPOSE: To compare the breast volume (BV), fibroglandular tissue volume (FV), and percent density (PD) measured from breast MRI of the same women using four different MR scanners.
METHODS: The study was performed in 34 healthy Asian volunteers using two 1.5T (GE and Siemens) and two 3T (GE and Philips) MR scanners. The BV, FV, and PD were measured on nonfat-suppressed T1-weighted images using a comprehensive computer algorithm-based segmentation method. The scanner-to-scanner measurement difference, and the coefficient of variation (CV) among the four scanners were calculated. The measurement variation between two density morphological patterns presenting as the central type and the intermingled type was separately analyzed and compared.
RESULTS: All four scanners provided satisfactory image quality allowing for successful completion of the segmentation processes. The measured parameters between each pair of MR scanners were highly correlated, with R(2) ≥ 0.95 for BV, R(2) ≥ 0.99 for FV, and R(2) ≥ 0.97 for PD in all comparisons. The mean percent differences between each pair of scanners were 5.9%-7.8% for BV, 5.3%-6.5% for FV, 4.3%-7.3% for PD; with the overall CV of 5.8% for BV, 4.8% for FV, and 4.9% for PD. The variation of FV was smaller in the central type than in the intermingled type (p = 0.04).
CONCLUSIONS: The results showed that the variation of FV and PD measured from four different MR scanners is around 5%, suggesting the parameters measured using different scanners can be used for a combined analysis in a multicenter study.

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Year:  2012        PMID: 22894415      PMCID: PMC3411588          DOI: 10.1118/1.4736824

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  33 in total

1.  Comparison of breast density measured on MR images acquired using fat-suppressed versus nonfat-suppressed sequences.

Authors:  Daniel H-E Chang; Jeon-Hor Chen; Muqing Lin; Shadfar Bahri; Hon J Yu; Rita S Mehta; Ke Nie; David J B Hsiang; Orhan Nalcioglu; Min-Ying Su
Journal:  Med Phys       Date:  2011-11       Impact factor: 4.071

2.  A fuzzy c-means (FCM)-based approach for computerized segmentation of breast lesions in dynamic contrast-enhanced MR images.

Authors:  Weijie Chen; Maryellen L Giger; Ulrich Bick
Journal:  Acad Radiol       Date:  2006-01       Impact factor: 3.173

3.  Volumetric breast density estimation from full-field digital mammograms.

Authors:  Saskia van Engeland; Peter R Snoeren; Henkjan Huisman; Carla Boetes; Nico Karssemeijer
Journal:  IEEE Trans Med Imaging       Date:  2006-03       Impact factor: 10.048

4.  Effect of B1 inhomogeneity on breast MR imaging at 3.0 T.

Authors:  Christiane K Kuhl; Hendrik Kooijman; Juergen Gieseke; Hans H Schild
Journal:  Radiology       Date:  2007-09       Impact factor: 11.105

5.  A nonparametric method for automatic correction of intensity nonuniformity in MRI data.

Authors:  J G Sled; A P Zijdenbos; A C Evans
Journal:  IEEE Trans Med Imaging       Date:  1998-02       Impact factor: 10.048

6.  Quantitative imaging test approval and biomarker qualification: interrelated but distinct activities.

Authors:  Andrew J Buckler; Linda Bresolin; N Reed Dunnick; Daniel C Sullivan; Hugo J W L Aerts; Bernard Bendriem; Claus Bendtsen; Ronald Boellaard; John M Boone; Patricia E Cole; James J Conklin; Gary S Dorfman; Pamela S Douglas; Willy Eidsaunet; Cathy Elsinger; Richard A Frank; Constantine Gatsonis; Maryellen L Giger; Sandeep N Gupta; David Gustafson; Otto S Hoekstra; Edward F Jackson; Lisa Karam; Gary J Kelloff; Paul E Kinahan; Geoffrey McLennan; Colin G Miller; P David Mozley; Keith E Muller; Rick Patt; David Raunig; Mark Rosen; Haren Rupani; Lawrence H Schwartz; Barry A Siegel; A Gregory Sorensen; Richard L Wahl; John C Waterton; Walter Wolf; Gudrun Zahlmann; Brian Zimmerman
Journal:  Radiology       Date:  2011-02-15       Impact factor: 11.105

7.  Quantitative analysis of breast parenchymal patterns using 3D fibroglandular tissues segmented based on MRI.

Authors:  Ke Nie; Daniel Chang; Jeon-Hor Chen; Chieh-Chih Hsu; Orhan Nalcioglu; Min-Ying Su
Journal:  Med Phys       Date:  2010-01       Impact factor: 4.071

8.  Age- and race-dependence of the fibroglandular breast density analyzed on 3D MRI.

Authors:  Ke Nie; Min-Ying Su; Man-Kwun Chau; Siwa Chan; Hoanglong Nguyen; Tiffany Tseng; Yuhong Huang; Christine E McLaren; Orhan Nalcioglu; Jeon-Hor Chen
Journal:  Med Phys       Date:  2010-06       Impact factor: 4.071

9.  A pilot study of compositional analysis of the breast and estimation of breast mammographic density using three-dimensional T1-weighted magnetic resonance imaging.

Authors:  Michael Khazen; Ruth M L Warren; Caroline R M Boggis; Emilie C Bryant; Sadie Reed; Iqbal Warsi; Linda J Pointon; Gek E Kwan-Lim; Deborah Thompson; Ros Eeles; Doug Easton; D Gareth Evans; Martin O Leach
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2008-09       Impact factor: 4.254

10.  Breast MRI: guidelines from the European Society of Breast Imaging.

Authors:  R M Mann; C K Kuhl; K Kinkel; C Boetes
Journal:  Eur Radiol       Date:  2008-04-04       Impact factor: 5.315

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  5 in total

1.  Impact of positional difference on the measurement of breast density using MRI.

Authors:  Jeon-Hor Chen; Siwa Chan; Yi-Ting Tang; Jia Shen Hon; Po-Chuan Tseng; Angela T Cheriyan; Nikita Rakesh Shah; Dah-Cherng Yeh; San-Kan Lee; Wen-Pin Chen; Christine E McLaren; Min-Ying Su
Journal:  Med Phys       Date:  2015-05       Impact factor: 4.071

2.  Breast density evaluation using spectral mammography, radiologist reader assessment, and segmentation techniques: a retrospective study based on left and right breast comparison.

Authors:  Sabee Molloi; Huanjun Ding; Stephen Feig
Journal:  Acad Radiol       Date:  2015-05-29       Impact factor: 3.173

3.  Automatic Breast and Fibroglandular Tissue Segmentation in Breast MRI Using Deep Learning by a Fully-Convolutional Residual Neural Network U-Net.

Authors:  Yang Zhang; Jeon-Hor Chen; Kai-Ting Chang; Vivian Youngjean Park; Min Jung Kim; Siwa Chan; Peter Chang; Daniel Chow; Alex Luk; Tiffany Kwong; Min-Ying Su
Journal:  Acad Radiol       Date:  2019-01-31       Impact factor: 3.173

4.  Quantification of Regional Breast Density in Four Quadrants Using 3D MRI-A Pilot Study.

Authors:  Peter T Fwu; Jeon-Hor Chen; Yifan Li; Siwa Chan; Min-Ying Su
Journal:  Transl Oncol       Date:  2015-08       Impact factor: 4.243

Review 5.  Imaging Breast Density: Established and Emerging Modalities.

Authors:  Jeon-Hor Chen; Gultekin Gulsen; Min-Ying Su
Journal:  Transl Oncol       Date:  2015-12       Impact factor: 4.243

  5 in total

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