Literature DB >> 20574085

Diffusion-weighted imaging improves the diagnostic accuracy of conventional 3.0-T breast MR imaging.

Riham H Ei Khouli1, Michael A Jacobs, Sarah D Mezban, Peng Huang, Ihab R Kamel, Katarzyna J Macura, David A Bluemke.   

Abstract

PURPOSE: To evaluate the incremental value of diffusion-weighted (DW) imaging and apparent diffusion coefficient (ADC) mapping in relation to conventional breast magnetic resonance (MR) imaging in the characterization of benign versus malignant breast lesions at 3.0 T.
MATERIALS AND METHODS: This retrospective HIPAA-compliant study was approved by the institutional review board, with the requirement for informed patient consent waived. Of 550 consecutive patients who underwent bilateral breast MR imaging over a 10-month period, 93 women with 101 lesions met the following study inclusion criteria: They had undergone three-dimensional (3D) high-spatial-resolution T1-weighted contrast material-enhanced MR imaging, dynamic contrast-enhanced MR imaging, and DW imaging examinations at 3.0 T and either had received a pathologic analysis-proven diagnosis (96 lesions) or had lesion stability confirmed at more than 2 years of follow-up (five lesions). DW images were acquired with b values of 0 and 600 sec/mm(2). Regions of interest were drawn on ADC maps of breast lesions and normal glandular tissue. Morphologic features (margin, enhancement pattern), dynamic contrast-enhanced MR results (semiquantitative kinetic curve data), absolute ADCs, and glandular tissue-normalized ADCs were included in multivariate models to predict a diagnosis of benign versus malignant lesion.
RESULTS: Forty-one (44%) of the 93 patients were premenopausal, and 52 (56%) were postmenopausal. Thirty-three (32.7%) of the 101 lesions were benign, and 68 (67.3%) were malignant. Normalized ADCs were significantly different between the benign (mean ADC, 1.1 x 10(-3) mm(2)/sec +/- 0.4 [standard deviation]) and malignant (mean ADC, 0.55 x 10(-3) mm(2)/sec +/- 0.16) lesions (P < .001). Adding normalized ADCs to the 3D T1-weighted and dynamic contrast-enhanced MR data improved the diagnostic performance of MR imaging: The area under the receiver operating characteristic curve improved from 0.89 to 0.98, and the false-positive rate decreased from 36% (nine of 25 lesions) to 24% (six of 25 lesions).
CONCLUSION: DW imaging with glandular tissue-normalized ADC assessment improves the characterization of breast lesions beyond the characterization achieved with conventional 3D T1-weighted and dynamic contrast-enhanced MR imaging at 3.0 T.

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Year:  2010        PMID: 20574085      PMCID: PMC2897691          DOI: 10.1148/radiol.10091367

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  28 in total

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2.  A combined architectural and kinetic interpretation model for breast MR images.

Authors:  M D Schnall; S Rosten; S Englander; S G Orel; L W Nunes
Journal:  Acad Radiol       Date:  2001-07       Impact factor: 3.173

3.  In vivo diffusion-weighted MRI of the breast: potential for lesion characterization.

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4.  Comparing the sensitivities and specificities of two diagnostic procedures performed on the same group of patients.

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5.  MR imaging of intravoxel incoherent motions: application to diffusion and perfusion in neurologic disorders.

Authors:  D Le Bihan; E Breton; D Lallemand; P Grenier; E Cabanis; M Laval-Jeantet
Journal:  Radiology       Date:  1986-11       Impact factor: 11.105

6.  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

7.  Dynamic contrast-enhanced MRI of the breast: quantitative method for kinetic curve type assessment.

Authors:  Riham H El Khouli; Katarzyna J Macura; Michael A Jacobs; Tarek H Khalil; Ihab R Kamel; Andrew Dwyer; David A Bluemke
Journal:  AJR Am J Roentgenol       Date:  2009-10       Impact factor: 3.959

8.  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
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9.  Detection of breast malignancy: diagnostic MR protocol for improved specificity.

Authors:  Wei Huang; Paul R Fisher; Khaldoon Dulaimy; Luminita A Tudorica; Brian O'Hea; Terry M Button
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10.  Differentiation of benign from malignant breast masses by time-intensity evaluation of contrast enhanced MRI.

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  111 in total

1.  Comparative analysis of nonlinear dimensionality reduction techniques for breast MRI segmentation.

Authors:  Alireza Akhbardeh; Michael A Jacobs
Journal:  Med Phys       Date:  2012-04       Impact factor: 4.071

2.  Comparison between diffusion-weighted imaging, T2-weighted, and postcontrast T1-weighted imaging after MR-guided, high intensity, focused ultrasound treatment of uterine leiomyomata: preliminary results.

Authors:  Michael A Jacobs; David H Gultekin; Hyun S Kim
Journal:  Med Phys       Date:  2010-09       Impact factor: 4.071

3.  Diffusion-Weighted Imaging-guided MR Spectroscopy in Breast Lesions using Readout-Segmented Echo-Planar Imaging.

Authors:  Kun Sun; Weimin Chai; Caixia Fu; Ying Zhan; Kunwei Shen; Xianfu Luo; Fuhua Yan
Journal:  Eur Radiol       Date:  2015-09-19       Impact factor: 5.315

4.  Diagnostic performance of ADCs in different ROIs for breast lesions.

Authors:  Wei Zhang; Guan-Qiao Jin; Jun-Jie Liu; Dan-Ke Su; Ning-Bin Luo; Dong Xie; Shao-Lv Lai; Xiang-Yang Huang; Wei-Li Huang
Journal:  Int J Clin Exp Med       Date:  2015-08-15

5.  Diffusion-Weighted Imaging With Apparent Diffusion Coefficient Mapping for Breast Cancer Detection as a Stand-Alone Parameter: Comparison With Dynamic Contrast-Enhanced and Multiparametric Magnetic Resonance Imaging.

Authors:  Katja Pinker; Linda Moy; Elizabeth J Sutton; Ritse M Mann; Michael Weber; Sunitha B Thakur; Maxine S Jochelson; Zsuzsanna Bago-Horvath; Elizabeth A Morris; Pascal At Baltzer; Thomas H Helbich
Journal:  Invest Radiol       Date:  2018-10       Impact factor: 6.016

6.  Multiparametric Whole-body MRI with Diffusion-weighted Imaging and ADC Mapping for the Identification of Visceral and Osseous Metastases From Solid Tumors.

Authors:  Michael A Jacobs; Katarzyna J Macura; Atif Zaheer; Emmanuel S Antonarakis; Vered Stearns; Antonio C Wolff; Thorsten Feiweier; Ihab R Kamel; Richard L Wahl; Li Pan
Journal:  Acad Radiol       Date:  2018-04-04       Impact factor: 3.173

7.  Nonmalignant breast lesions: ADCs of benign and high-risk subtypes assessed as false-positive at dynamic enhanced MR imaging.

Authors:  Sana Parsian; Habib Rahbar; Kimberly H Allison; Wendy B Demartini; Matthew L Olson; Constance D Lehman; Savannah C Partridge
Journal:  Radiology       Date:  2012-10-02       Impact factor: 11.105

8.  Utility of Diffusion-weighted Imaging to Decrease Unnecessary Biopsies Prompted by Breast MRI: A Trial of the ECOG-ACRIN Cancer Research Group (A6702).

Authors:  Habib Rahbar; Zheng Zhang; Thomas L Chenevert; Justin Romanoff; Averi E Kitsch; Lucy G Hanna; Sara M Harvey; Linda Moy; Wendy B DeMartini; Basak Dogan; Wei T Yang; Lilian C Wang; Bonnie N Joe; Karen Y Oh; Colleen H Neal; Elizabeth S McDonald; Mitchell D Schnall; Constance D Lehman; Christopher E Comstock; Savannah C Partridge
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9.  High-resolution diffusion-weighted imaging for the separation of benign from malignant BI-RADS 4/5 lesions found on breast MRI at 3T.

Authors:  Dorota J Wisner; Nathan Rogers; Vibhas S Deshpande; David N Newitt; Gerhard A Laub; David A Porter; John Kornak; Bonnie N Joe; Nola M Hylton
Journal:  J Magn Reson Imaging       Date:  2013-11-08       Impact factor: 4.813

Review 10.  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

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