Literature DB >> 19711411

Diffusion-weighted imaging of breast cancer: correlation of the apparent diffusion coefficient value with prognostic factors.

Sung Hun Kim1, Eun Suk Cha, Hyeon Sook Kim, Bong Joo Kang, Jae Jeong Choi, Ji Han Jung, Yong Gyu Park, Young Jin Suh.   

Abstract

PURPOSE: To evaluate the role of diffusion-weighted imaging (DWI) in the detection of breast cancers, and to correlate the apparent diffusion coefficient (ADC) value with prognostic factors.
MATERIALS AND METHODS: Sixty-seven women with invasive cancer underwent breast MRI. Histological specimens were analyzed for tumor size and grade, and expression of estrogen receptors (ER), progesterone receptors, c-erbB-2, p53, Ki-67, and epidermal growth factor receptors. The computed mean ADC values of breast cancer and normal breast parenchyma were compared. Relationships between the ADC values and prognostic factors were determined using Wilcoxon signed rank test and Kruskal-Wallis test.
RESULTS: DWI detected breast cancer as a hyperintense area in 62 patients (92.5 %). A statistically significant difference in the mean ADC values of breast cancer (1.09 +/- 0.27 x 10(-5) mm(2)/s) and normal parenchyma (1.59 +/- 0.27 x 10(-5) mm(2)/s) was detected (P < 0.0001). There were no correlations between the ADC value and prognostic factors. However, the median ADC value was lower in the ER-positive group than the ER negative group, and this difference was marginally significant (1.09 x 10(-5) mm(2)/s versus 1.15 x 10(-5) mm(2)/s, P = 0.053).
CONCLUSION: The ADC value was a helpful parameter in detecting malignant breast tumors, but ADC value could not predict patient prognosis.

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Year:  2009        PMID: 19711411     DOI: 10.1002/jmri.21884

Source DB:  PubMed          Journal:  J Magn Reson Imaging        ISSN: 1053-1807            Impact factor:   4.813


  52 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

2.  Distortion correction in diffusion-weighted imaging of the breast: Performance assessment of prospective, retrospective, and combined (prospective + retrospective) approaches.

Authors:  Ileana Hancu; Seung-Kyun Lee; Keith Hulsey; Robert Lenkinski; Dominic Holland; Jonathan I Sperl; Ek T Tan
Journal:  Magn Reson Med       Date:  2016-07-12       Impact factor: 4.668

3.  Diffusion-weighted magnetic resonance imaging of breast lesions: the influence of different fat-suppression techniques on quantitative measurements and their reproducibility.

Authors:  P Mürtz; M Tsesarskiy; A Kowal; F Träber; J Gieseke; W A Willinek; C C Leutner; A Schmiedel; H H Schild
Journal:  Eur Radiol       Date:  2014-06-05       Impact factor: 5.315

4.  MRI in the differential diagnosis of primary architectural distortion detected by mammography.

Authors:  Lifang Si; Renyou Zhai; Xiaojuan Liu; Kaiyan Yang; Li Wang; Tao Jiang
Journal:  Diagn Interv Radiol       Date:  2016 Mar-Apr       Impact factor: 2.630

5.  Diffusion weighted MRI and spectroscopy in invasive carcinoma of the breast at 3Tesla. Correlation with dynamic contrast enhancement and pathologic findings.

Authors:  G Boulogianni; I Chryssogonidis; A Drevelegas
Journal:  Hippokratia       Date:  2016 Jul-Sep       Impact factor: 0.471

6.  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

7.  Nasopharyngeal carcinoma: correlation of apparent diffusion coefficient value with prognostic parameters.

Authors:  Ahmed Abdel Khalek Abdel Razek; Elsharawey Kamal
Journal:  Radiol Med       Date:  2012-10-22       Impact factor: 3.469

Review 8.  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

9.  Diffusion magnetic resonance imaging in breast cancer characterisation: correlations between the apparent diffusion coefficient and major prognostic factors.

Authors:  Paolo Belli; Melania Costantini; Enida Bufi; Giuseppe Giovanni Giardina; Pierluigi Rinaldi; Gianluca Franceschini; Lorenzo Bonomo
Journal:  Radiol Med       Date:  2014-08-06       Impact factor: 3.469

10.  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

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