A Review of Diffusion Magnetic Resonance Imaging in Characterization of Breast Cancers
-
Mohammad Reza Alviri
,
Anahita Fathi Kazerooni
,
Soheila Koopaee
,
Hamidreza Saligheh Rad
,
Masoumeh Gity
Abstract
Diffusion Magnetic Resonance Imaging (dMRI) has widely been used as a part of breast MRI protocols throughout the world, providing valuable information about breast tissue structures. This method has the potential to improve the characterization of benign and malignant breast lesions thereby guiding treatment decisions. DMRI as a non-contrast approach has certain benefits in comparison with the Dynamic Contrast Enhanced (DCE) method. Particularly, dMRI does not need intravenous contrast, which makes the imaging process faster and easier. Although there are still concerns about dMRI images quality, advances in the acquisition methods seem to be promising. More advanced dMRI strategies, such as Diffusion Tensor Imaging (DTI) and Intravoxel Incoherent Motion (IVIM), not only improve diagnosis accuracy, but also present new information about tissue perfusion. This review will present an overview of dMRI in the characterization of breast cancers.
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18- Fathi Kazerooni A, Pozo JM, McCloskey EV, Saligheh Rad H, and Frangi AF, "Diffusion MRI for Assessment of Bone Quality; A Review of Findings in Healthy Aging and Osteoporosis." Vol. 51 (No. 4), pp. 975-92, (2020).
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20- Partridge SC, Murthy RS, Ziadloo A, White SW, Allison KH, and Lehman CD, "Diffusion tensor magnetic resonance imaging of the normal breast." Vol. 28 (No. 3), pp. 320-8, (2010).
21- Kim JY et al., "Diffusion tensor magnetic resonance imaging of breast cancer: associations between diffusion metrics and histological prognostic factors." Vol. 28 (No. 8), pp. 3185-93, (2018).
22- Luo J, Hippe D, Rahbar H, Parsian S, Rendi M, and Partridge S, "Diffusion tensor imaging for characterizing tumor microstructure and improving diagnostic performance on breast MRI: a prospective observational study." (2019).
23- Kinoshita M et al., "Fractional anisotropy and tumor cell density of the tumor core show positive correlation in diffusion tensor magnetic resonance imaging of malignant brain tumors." Vol. 43 (No. 1), pp. 29-35, (2008).
24- Le Bihan D, Turner R, and MacFall JR, "Effects of intravoxel incoherent motions(IVIM) in steady-state free precession (SSFP) imaging: application to molecular diffusion imaging." Vol. 10 (No. 3), pp. 324-37, (1989).
25- Rosen EL, Smith-Foley SA, DeMartini WB, Eby PR, Peacock S, and Lehman CD, "BI-RADS MRI enhancement characteristics of ductal carcinoma in situ." Vol. 13 (No. 6), pp. 545-50, (2007).
26- Kvistad KA et al., "Breast lesions: evaluation with dynamic contrast-enhanced T1-weighted MR imaging and with T2*-weighted first-pass perfusion MR imaging." Vol. 216 (No. 2), pp. 545-53, (2000).
27- Amornsiripanitch N, Lam DL, and Rahbar H, "Advances in Breast MRI in the Setting of Ductal Carcinoma In Situ." Vol. 53 (No. 4), pp. 261-9, (2018).
28- Schmadeka R, Harmon BE, and Singh M, "Triple-negative breast carcinoma: current and emerging concepts." Vol. 141 (No. 4), pp. 462-77, (2014).
29- SN Abdul Rashid, K Rahmat, KJ Jayaprasagam, K Alli, and F Moosa, "Medullary carcinoma of the breast: Role of contrast-enhanced MRI in the diagnosis of multiple breast lesions." Vol. 5 (No. 4), (2009).
30- Liberman L, LaTrenta LR, Samli B, Morris EA, Abramson AF, and Dershaw DD, "Overdiagnosis of medullary carcinoma: a mammographic-pathologic correlative study." Vol. 201 (No. 2), pp. 443-6, (1996).
31- Jeong SJ et al., "Medullary carcinoma of the breast: MRI findings." Vol. 198 (No. 5), pp. 482-7, (2012).
32- Kawashima M et al., "MR imaging of mucinous carcinoma of the breast." Vol. 179 (No. 1), pp. 179-83, (2002).
33- Yamamoto S, Maki DD, Korn RL, and Kuo MD, "Radiogenomic analysis of breast cancer using MRI: a preliminary study to define the landscape." Vol. 199 (No. 3), pp. 654-63, (2012).
34- Sutton EJ et al., "Breast cancer subtype intertumor heterogeneity: MRI-based features predict results of a genomic assay." Vol. 42 (No. 5), pp. 1398-406, (2015).
35- Koo HR et al., "Correlation of perfusion parameters on dynamic contrast-enhanced MRI with prognostic factors and subtypes of breast cancers." Vol. 36 (No. 1), pp. 145-51, (2012).
36- Grimm LJ, Zhang J, and Mazurowski MA, "Computational approach to radiogenomics of breast cancer: Luminal A and luminal B molecular subtypes are associated with imaging features on routine breast MRI extracted using computer vision algorithms." Vol. 42 (No. 4), pp. 902-7, (2015).
37- Ming Fan, Hui Li, Shijian Wang, Bin Zheng, Juan Zhang, and Lihua Li, "Radiomic analysis reveals DCE-MRI features for prediction of molecular subtypes of breast cancer." Vol. 12 (No. 2), (2017).
38- Rahbar H et al., "Characterization of ductal carcinoma in situ on diffusion weighted breast MRI." Vol. 21 (No. 9), (2011).
39- Yılmaz R et al., "MR Imaging Features of Tubular Carcinoma: Preliminary Experience in Twelve Masses." Vol. 14 (No. 1), pp. 39-45, (2018).
40- Sharma U et al., "Potential of Diffusion-Weighted Imaging in the Characterization of Malignant, Benign, and Healthy Breast Tissues and Molecular Subtypes of Breast Cancer." Vol. 6 (No. 126), (2016).
41- Woodhams R et al., "Diffusion-weighted imaging of mucinous carcinoma of the breast: evaluation of apparent diffusion coefficient and signal intensity in correlation with histologic findings." Vol. 193 (No. 1), pp. 260-6, (2009).
42- Yuan C, Jin F, Guo X, Zhao S, Li W, and Guo H, "Correlation Analysis of Breast Cancer DWI Combined with DCE-MRI Imaging Features with Molecular Subtypes and Prognostic Factors." Vol. 43 (No. 4), (2019).
43- Baba S et al., "Diagnostic and prognostic value of pretreatment SUV in 18F-FDG/PET in breast cancer: comparison with apparent diffusion coefficient from diffusion-weighted MR imaging." Vol. 55 (No. 5), pp. 736-42, (2014).
44- Meng L and Ma P, "Apparent diffusion coefficient value measurements with diffusion magnetic resonance imaging correlated with the expression levels of estrogen and progesterone receptor in breast cancer: A meta-analysis." Vol. 12 (No. 1), pp. 36-42, (2016).
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| Files | ||
| Issue | Vol 9 No 2 (2022) | |
| Section | Literature (Narrative) Review(s) | |
| DOI | https://doi.org/10.18502/fbt.v9i2.8853 | |
| Keywords | ||
| Breast Cancer Diffusion Weighted Imaging Magnetic Resonance Imaging | ||
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How to Cite
1.
Alviri MR, Fathi Kazerooni A, Koopaee S, Saligheh Rad H, Gity M. A Review of Diffusion Magnetic Resonance Imaging in Characterization of Breast Cancers. Frontiers Biomed Technol. 2022;9(2):134-148.
