Literature DB >> 24156797

Differentiation between benign and malignant breast lesions using quantitative diffusion-weighted sequence on 3 T MRI.

S L L Tan1, K Rahmat2, F I Rozalli1, M N Mohd-Shah1, Y F A Aziz1, C H Yip3, A Vijayananthan1, K H Ng1.   

Abstract

AIM: To investigate the capability and diagnostic accuracy of diffusion-weighted imaging (DWI) in differentiating benign from malignant breast lesions using 3 T magnetic resonance imaging (MRI).
MATERIALS AND METHODS: Women with suspicious or indeterminate breast lesions detected at MRI, mammogram and/or ultrasound were recruited for dynamic contrast-enhanced (DCE)-MRI and DWI prior to their biopsy. Image fusion of DCE-MRI with apparent diffusion coefficient (ADC) map was utilized to select the region of interest (ROI) for ADC calculation in the area that showed the most avid enhancement. DWI was performed using two sets of b-values at 500 and 1000 s/mm(2), respectively.
RESULTS: Fifty women were recruited and the final analysis comprised 44 breast lesions, 31 of which were malignant and 13 were benign. Significant results were obtained between ADC values of benign and malignant lesions (p < 0.001). The cut-off ADC values for benign and malignant lesions were 1.21 × 10(-3) mm(2)/s for b = 500 s/mm(2) and 1.22 × 10(-3) mm(2)/s for b = 1000 s/mm(2), respectively. The sensitivity of DCE-MRI alone was 100% with a specificity of 66.7%. When DCE-MRI was combined with b = 1000 s/mm(2), the specificity rose to 100%, while only mildly affecting sensitivity (90.6%). No significant correlation was found between ADC values and prognostic factors, such as lymph node metastasis, tumour size, oestrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) status, and tumour grades.
CONCLUSION: The present study provides consistent evidence to support DWI as a diagnostic tool for breast lesion characterization. A combination of DCE-MRI with DWI is suggested to improve the sensitivity and specificity of lesion characterization.
Copyright © 2013 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

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Year:  2013        PMID: 24156797     DOI: 10.1016/j.crad.2013.08.007

Source DB:  PubMed          Journal:  Clin Radiol        ISSN: 0009-9260            Impact factor:   2.350


  15 in total

1.  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

Review 2.  The Efficiency of Diffusion Weighted MRI and MR Spectroscopy On Breast MR Imaging.

Authors:  Canan Altay; Pınar Balcı
Journal:  J Breast Health       Date:  2014-10-01

3.  A 32-channel receive array coil for bilateral breast imaging and spectroscopy at 7T.

Authors:  Romina Del Bosque; Jiaming Cui; Stephen Ogier; Sergey Cheshkov; Ivan E Dimitrov; Craig Malloy; Steven M Wright; Mary McDougall
Journal:  Magn Reson Med       Date:  2020-08-09       Impact factor: 4.668

4.  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 5.  Magnetic resonance imaging in breast cancer: A literature review and future perspectives.

Authors:  Gisela Lg Menezes; Floor M Knuttel; Bertine L Stehouwer; Ruud M Pijnappel; Maurice Aaj van den Bosch
Journal:  World J Clin Oncol       Date:  2014-05-10

6.  Potential of Diffusion-Weighted Imaging in the Characterization of Malignant, Benign, and Healthy Breast Tissues and Molecular Subtypes of Breast Cancer.

Authors:  Uma Sharma; Rani G Sah; Khushbu Agarwal; Rajinder Parshad; Vurthaluru Seenu; Sandeep R Mathur; Smriti Hari; Naranamangalam R Jagannathan
Journal:  Front Oncol       Date:  2016-05-23       Impact factor: 6.244

7.  Role of exponential apparent diffusion coefficient in characterizing breast lesions by 3.0 Tesla diffusion-weighted magnetic resonance imaging.

Authors:  Shweta Kothari; Archana Singh; Utpalendu Das; Diptendra K Sarkar; Chhanda Datta; Avijit Hazra
Journal:  Indian J Radiol Imaging       Date:  2017 Apr-Jun

8.  Dynamic properties of water in breast pathology depend on the histological compounds: distinguishing tissue malignancy by water diffusion coefficients.

Authors:  Rustem F Baikeev; Roman A Gubanov; Kamil K Sadikov; Sufiya Z Safina; Farhat F Muhamadiev; Timur A Sibgatullin
Journal:  BMC Res Notes       Date:  2014-12-08

9.  Diffusion-Weighted Imaging in 3.0 Tesla Breast MRI: Diagnostic Performance and Tumor Characterization Using Small Subregions vs. Whole Tumor Regions of Interest.

Authors:  Otso Arponen; Otso Arponent; Mazen Sudah; Amro Masarwah; Mikko Taina; Suvi Rautiainen; Mervi Könönen; Reijo Sironen; Veli-Matti Kosma; Anna Sutela; Juhana Hakumäki; Ritva Vanninen
Journal:  PLoS One       Date:  2015-10-12       Impact factor: 3.240

10.  Diagnostic Performance of Fused Diffusion-Weighted Imaging Using Unenhanced or Postcontrast T1-Weighted MR Imaging in Patients With Breast Cancer.

Authors:  Hee Jung Shin; Eun Young Chae; Woo Jung Choi; Su Min Ha; Jin Young Park; Ki Chang Shin; Joo Hee Cha; Hak Hee Kim
Journal:  Medicine (Baltimore)       Date:  2016-04       Impact factor: 1.889

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