Literature DB >> 24758685

Diffusion-weighted MRI: association between patient characteristics and apparent diffusion coefficients of normal breast fibroglandular tissue at 3 T.

Elizabeth S McDonald1, Jennifer G Schopp, Sue Peacock, Wendy B DeMartini, Wendy D DeMartini, Habib Rahbar, Constance D Lehman, Savannah C Partridge.   

Abstract

OBJECTIVE: The purpose of this study is to assess associations between patient characteristics and apparent diffusion coefficient (ADC) values of normal breast fibroglandular tissue on diffusion-weighted imaging (DWI) at 3 T.
MATERIALS AND METHODS: The retrospective study included 103 women with negative bilateral findings on 3-T breast MRI examinations (BI-RADS category 1). DWI was acquired during clinical breast MRI scans using b = 0 and b = 800 s/mm(2). Mean ADC of normal breast fibroglandular tissue was calculated for each breast using a semiautomated software tool in which parenchyma pixels were selected by interactive thresholding of the b = 0 s/mm(2) image to exclude fat. Intrasubject right- and left-breast ADC values were compared and averaged together to evaluate the association of mean breast ADC with age, mammographic breast density, and background parenchymal enhancement.
RESULTS: Overall mean ± SD breast ADC was 1.62 ± 0.30 × 10(-3) mm(2)/s. Intrasubject right- and left-breast ADC measurements were highly correlated (R(2) = 0.89; p < 0.0001). Increased breast density was strongly associated with increased ADC (p ≤ 0.0001). Age and background parenchymal enhancement were not associated with ADC.
CONCLUSION: Normal breast parenchymal ADC values increase with mammographic density but are independent of age and background parenchymal enhancement. Because breast malignancies have been shown to have low ADC values, DWI may be particularly valuable in women with dense breasts owing to greater contrast between lesion and normal tissue.

Entities:  

Mesh:

Year:  2014        PMID: 24758685      PMCID: PMC4080610          DOI: 10.2214/AJR.13.11159

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  29 in total

1.  Diffusion imaging of human breast.

Authors:  S A Englander; A M Uluğ; R Brem; J D Glickson; P C van Zijl
Journal:  NMR Biomed       Date:  1997-10       Impact factor: 4.044

2.  Healthy premenopausal breast parenchyma in dynamic contrast-enhanced MR imaging of the breast: normal contrast medium enhancement and cyclical-phase dependency.

Authors:  C K Kuhl; H B Bieling; J Gieseke; B P Kreft; T Sommer; G Lutterbey; H H Schild
Journal:  Radiology       Date:  1997-04       Impact factor: 11.105

3.  Breast density and parenchymal patterns as markers of breast cancer risk: a meta-analysis.

Authors:  Valerie A McCormack; Isabel dos Santos Silva
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2006-06       Impact factor: 4.254

4.  Menstrual cycle variation of apparent diffusion coefficients measured in the normal breast using MRI.

Authors:  S C Partridge; G C McKinnon; R G Henry; N M Hylton
Journal:  J Magn Reson Imaging       Date:  2001-10       Impact factor: 4.813

5.  Differentiation of clinically benign and malignant breast lesions using diffusion-weighted imaging.

Authors:  Yong Guo; You-Quan Cai; Zu-Long Cai; Yuan-Gui Gao; Ning-Yu An; Lin Ma; Srikanth Mahankali; Jia-Hong Gao
Journal:  J Magn Reson Imaging       Date:  2002-08       Impact factor: 4.813

6.  The role of diffusion-weighted imaging and the apparent diffusion coefficient (ADC) values for breast tumors.

Authors:  Mi Jung Park; Eun Suk Cha; Bong Joo Kang; Yon Kwon Ihn; Jun Hyun Baik
Journal:  Korean J Radiol       Date:  2007 Sep-Oct       Impact factor: 3.500

7.  Effects of age, breast density, ethnicity, and estrogen replacement therapy on screening mammographic sensitivity and cancer stage at diagnosis: review of 183,134 screening mammograms in Albuquerque, New Mexico.

Authors:  R D Rosenberg; W C Hunt; M R Williamson; F D Gilliland; P W Wiest; C A Kelsey; C R Key; M N Linver
Journal:  Radiology       Date:  1998-11       Impact factor: 11.105

8.  Relation between cancer cellularity and apparent diffusion coefficient values using diffusion-weighted magnetic resonance imaging in breast cancer.

Authors:  Miho I Yoshikawa; Shozo Ohsumi; Shigenori Sugata; Masaaki Kataoka; Shigemitsu Takashima; Teruhito Mochizuki; Hirohiko Ikura; Yutaka Imai
Journal:  Radiat Med       Date:  2008-05-29

9.  Enhanced mass on contrast-enhanced breast MR imaging: Lesion characterization using combination of dynamic contrast-enhanced and diffusion-weighted MR images.

Authors:  Hidetake Yabuuchi; Yoshio Matsuo; Takashi Okafuji; Takeshi Kamitani; Hiroyasu Soeda; Taro Setoguchi; Shuji Sakai; Masamitsu Hatakenaka; Makoto Kubo; Noriaki Sadanaga; Hidetaka Yamamoto; Hiroshi Honda
Journal:  J Magn Reson Imaging       Date:  2008-11       Impact factor: 4.813

10.  Mammographic features and breast cancer risk: effects with time, age, and menopause status.

Authors:  C Byrne; C Schairer; J Wolfe; N Parekh; M Salane; L A Brinton; R Hoover; R Haile
Journal:  J Natl Cancer Inst       Date:  1995-11-01       Impact factor: 13.506

View more
  17 in total

1.  Diffusion-weighted MRI characteristics associated with prognostic pathological factors and recurrence risk in invasive ER+/HER2- breast cancers.

Authors:  Nita Amornsiripanitch; Vicky T Nguyen; Habib Rahbar; Daniel S Hippe; Vijayakrishna K Gadi; Mara H Rendi; Savannah C Partridge
Journal:  J Magn Reson Imaging       Date:  2017-11-27       Impact factor: 4.813

2.  High-Spatial-Resolution Multishot Multiplexed Sensitivity-encoding Diffusion-weighted Imaging for Improved Quality of Breast Images and Differentiation of Breast Lesions: A Feasibility Study.

Authors:  Isaac Daimiel Naranjo; Roberto Lo Gullo; Elizabeth A Morris; Toni Larowin; Maggie M Fung; Arnaud Guidon; Katja Pinker; Sunitha B Thakur
Journal:  Radiol Imaging Cancer       Date:  2020-05-29

3.  Multiparametric 18F-FDG PET/MRI of the Breast: Are There Differences in Imaging Biomarkers of Contralateral Healthy Tissue Between Patients With and Without Breast Cancer?

Authors:  Doris Leithner; Thomas H Helbich; Blanca Bernard-Davila; Maria Adele Marino; Daly Avendano; Danny F Martinez; Maxine S Jochelson; Panagiotis Kapetas; Pascal A T Baltzer; Alexander Haug; Marcus Hacker; Yasemin Tanyildizi; Elizabeth A Morris; Katja Pinker
Journal:  J Nucl Med       Date:  2019-06-28       Impact factor: 10.057

Review 4.  Diffusion-weighted breast MRI: Clinical applications and emerging techniques.

Authors:  Savannah C Partridge; Noam Nissan; Habib Rahbar; Averi E Kitsch; Eric E Sigmund
Journal:  J Magn Reson Imaging       Date:  2016-09-30       Impact factor: 4.813

5.  Diffusion-Weighted Breast Magnetic Resonance Imaging: A Semiautomated Voxel Selection Technique Improves Interreader Reproducibility of Apparent Diffusion Coefficient Measurements.

Authors:  Habib Rahbar; Brenda F Kurland; Matthew L Olson; Averi E Kitsch; John R Scheel; Xiaoyu Chai; Joshua Usoro; Constance D Lehman; Savannah C Partridge
Journal:  J Comput Assist Tomogr       Date:  2016 May-Jun       Impact factor: 1.826

6.  Diffusion tensor imaging in the normal breast: influences of fibroglandular tissue composition and background parenchymal enhancement.

Authors:  Michael Jonathan Plaza; Elizabeth A Morris; Sunitha B Thakur
Journal:  Clin Imaging       Date:  2015-12-08       Impact factor: 1.605

7.  Apparent diffusion coefficient mapping using diffusion-weighted MRI: impact of background parenchymal enhancement, amount of fibroglandular tissue and menopausal status on breast cancer diagnosis.

Authors:  Joao V Horvat; Manuela Durando; Soledad Milans; Sujata Patil; Jessica Massler; Girard Gibbons; Dilip Giri; Katja Pinker; Elizabeth A Morris; Sunitha B Thakur
Journal:  Eur Radiol       Date:  2018-01-12       Impact factor: 5.315

Review 8.  Diffusion-weighted magnetic resonance imaging in cancer: Reported apparent diffusion coefficients, in-vitro and in-vivo reproducibility.

Authors:  Maysam M Jafar; Arman Parsai; Marc E Miquel
Journal:  World J Radiol       Date:  2016-01-28

9.  Development of patient-specific 3D-printed breast phantom using silicone and peanut oils for magnetic resonance imaging.

Authors:  Rooa Sindi; Yin How Wong; Chai Hong Yeong; Zhonghua Sun
Journal:  Quant Imaging Med Surg       Date:  2020-06

10.  Removing silicone artifacts in diffusion-weighted breast MRI by means of shift-resolved spatiotemporally encoding.

Authors:  Eddy Solomon; Noam Nissan; Rita Schmidt; Edna Furman-Haran; Uriel Ben-Aharon; Lucio Frydman
Journal:  Magn Reson Med       Date:  2015-06-22       Impact factor: 4.668

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.