Literature DB >> 24034833

Intravoxel incoherent motion (IVIM) in evaluation of breast lesions: comparison with conventional DWI.

Chunling Liu1, Changhong Liang, Zaiyi Liu, Shuixing Zhang, Biao Huang.   

Abstract

OBJECTIVES: To obtain perfusion as well as diffusion information in normal breast tissues and breast lesions from intravoxel incoherent motion (IVIM) imaging with biexponential analysis of multiple b-value diffusion-weighted imaging (DWI) and compare these parameters to apparent diffusion coefficient (ADC) obtained with monoexponential analysis in their ability to discriminate benign lesions and malignant tumors.
MATERIALS AND METHODS: In this prospective study, informed consent was acquired from all patients. Eighty-four patients with 40 malignant tumors, 41 benign lesions, 30 simple cysts and 39 normal breast tissues were imaged at 1.5 T utilizing contrast-enhanced magnetic resonance imaging (MRI) and DWI using 12 b values (range: 0-1000 s/mm(2)). Tissue diffusivity (D), perfusion fraction (f) and pseudo-diffusion coefficient (D*) were calculated using segmented biexponential analysis. ADC (b = 0 and 1000 s/mm(2)) was calculated with monoexponential fitting of the DWI data. D, f, D* and ADC values were obtained for normal breast tissues, simple cysts, benign lesions and malignant tumors. Receiver operating characteristic analysis was performed for all DWI parameters.
RESULTS: There was good interobserver agreement on the measurements between the 2 observers. D values were significantly different among malignant tumors, benign lesions, simple cysts and normal breast tissues (P = 0.000) and it was the same result for f, D* and ADC values. Further comparisons of these 4 parameters between every single pair were as the following. D and ADC values of malignant tumors were significantly smaller than those of benign lesions, simple cysts and normal tissues (P = 0.000, respectively). The f value of malignant tumors was significantly higher than that of benign lesions, simple cysts and normal breast tissues (P = 0.001, P = 0.000, and P = 0.000). D and ADC values demonstrated higher sensitivity and specificity in differentiating benign lesions and malignant tumors, with area under the curve (AUC) of 0.952 and 0.945, respectively, while f and D* with the lower AUC of 0.723 and 0.630, respectively. Combining f and D values had a sensitivity up to 98.75%.
CONCLUSION: DWI response curves in malignant tumors, benign lesions and normal fibroglandular tissues are found to be biexponential fit in comparison with the monoexponential fit for simple cysts. IVIM provides separate quantitative measurement of D for cellularity and f and D* for vascularity and is helpful for differentiation between benign and malignant breast lesions.
Copyright © 2013. Published by Elsevier Ireland Ltd.

Entities:  

Keywords:  Apparent diffusion coefficient; Biexpoential signal attenuation; Breast neoplasma; Diffusion-weighted imaging; Intravoxel incoherent motion; Magnetic resonance imaging

Mesh:

Year:  2013        PMID: 24034833     DOI: 10.1016/j.ejrad.2013.08.006

Source DB:  PubMed          Journal:  Eur J Radiol        ISSN: 0720-048X            Impact factor:   3.528


  57 in total

1.  Intravoxel incoherent motion diffusion-weighted magnetic resonance imaging of focal vertebral bone marrow lesions: initial experience of the differentiation of nodular hyperplastic hematopoietic bone marrow from malignant lesions.

Authors:  Sunghoon Park; Kyu-Sung Kwack; Nam-Su Chung; Jinwoo Hwang; Hyun Young Lee; Jae Ho Kim
Journal:  Skeletal Radiol       Date:  2017-03-06       Impact factor: 2.199

2.  Breast cancer: a new imaging approach as an addition to existing guidelines.

Authors:  Monique D Dorrius; Erik F J de Vries; Riemer H J A Slart; Andor W J M Glaudemans
Journal:  Eur J Nucl Med Mol Imaging       Date:  2015-03-12       Impact factor: 9.236

3.  Initial experience of correlating parameters of intravoxel incoherent motion and dynamic contrast-enhanced magnetic resonance imaging at 3.0 T in nasopharyngeal carcinoma.

Authors:  Qian-Jun Jia; Shui-Xing Zhang; Wen-Bo Chen; Long Liang; Zheng-Gen Zhou; Qian-Hui Qiu; Zai-Yi Liu; Qiong-Xin Zeng; Chang-Hong Liang
Journal:  Eur Radiol       Date:  2014-07-23       Impact factor: 5.315

4.  Contribution of mono-exponential, bi-exponential and stretched exponential model-based diffusion-weighted MR imaging in the diagnosis and differentiation of uterine cervical carcinoma.

Authors:  Meng Lin; Xiaoduo Yu; Yan Chen; Han Ouyang; Bing Wu; Dandan Zheng; Chunwu Zhou
Journal:  Eur Radiol       Date:  2016-09-27       Impact factor: 5.315

5.  A comparison of fitting algorithms for diffusion-weighted MRI data analysis using an intravoxel incoherent motion model.

Authors:  Roberta Fusco; Mario Sansone; Antonella Petrillo
Journal:  MAGMA       Date:  2016-09-26       Impact factor: 2.310

6.  Intravoxel Incoherent Motion MR Imaging in the Differentiation of Benign and Malignant Sinonasal Lesions: Comparison with Conventional Diffusion-Weighted MR Imaging.

Authors:  Z Xiao; Z Tang; J Qiang; S Wang; W Qian; Y Zhong; R Wang; J Wang; L Wu; W Tang; Z Zhang
Journal:  AJNR Am J Neuroradiol       Date:  2018-01-25       Impact factor: 3.825

Review 7.  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

8.  Intravoxel incoherent motion diffusion-weighted MR imaging of breast cancer: association with histopathological features and subtypes.

Authors:  Yunju Kim; Kyounglan Ko; Daehong Kim; Changki Min; Sungheon G Kim; Jungnam Joo; Boram Park
Journal:  Br J Radiol       Date:  2016-05-20       Impact factor: 3.039

9.  Evaluation of breast cancer using intravoxel incoherent motion (IVIM) histogram analysis: comparison with malignant status, histological subtype, and molecular prognostic factors.

Authors:  Gene Young Cho; Linda Moy; Sungheon G Kim; Steven H Baete; Melanie Moccaldi; James S Babb; Daniel K Sodickson; Eric E Sigmund
Journal:  Eur Radiol       Date:  2015-11-28       Impact factor: 5.315

Review 10.  Multiparametric MR Imaging of Breast Cancer.

Authors:  Habib Rahbar; Savannah C Partridge
Journal:  Magn Reson Imaging Clin N Am       Date:  2016-02       Impact factor: 2.266

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