Abstract
Objectives
To evaluate diffusion-weighted imaging (DWI) and diffusion kurtosis imaging (DKI) in the differentiation and characterisation of breast lesions.
Methods
Thirty-six women underwent breast magnetic resonance imaging (MRI) including a DWI sequence with multiple b-values (50–3,000 s/mm2). Mean values for apparent diffusion coefficient (ADC), mean diffusivity (MD) and mean kurtosis (MK) were calculated by lesion type and histological subtype. Differences and correlation between parameters were determined.
Results
Forty-four lesions were found. There were significant differences between benign and malignant lesions for all parameters (ADC, p = 0.017; MD, p = 0.028; MK, p = 0.017). ADC and MD were higher for benign (1.96 ± 0.41 × 10−3 and 2.17 ± 0.42 × 10−3 mm2/s, respectively) than for malignant lesions (1.33 ± 0.18 × 10−3 and 1.52 ± 0.50 × 10−3 mm2/s). MK was higher for malignant (0.61 ± 0.27) than benign lesions (0.37 ± 0.18). We found differences between invasive ductal carcinoma (IDC) and fibroadenoma (FA) for all parameters (ADC, MD and MK): p = 0.016, 0.022 and 0.016, respectively. FA and fibrocystic change (FC) showed differences only in MK (p = 0.016).
Conclusions
Diffusion in breast lesions follows a non-Gaussian distribution. MK enables differentiation and characterisation of breast lesions, providing new insights into microstructural complexity. To confirm these results, further investigation in a broader sample should be performed.
Key Points
• The diffusion kurtosis model provides new information regarding breast lesions
• MD and MK are valid parameters to characterise tissue microstructure
• MK enables improved lesion differentiation
• MK is able to differentiate lesions that display similar ADC values
Abbreviations
- DWI:
-
Diffusion-weighted imaging
- ADC:
-
Apparent diffusion coefficient
- PDF:
-
Probability of displacement function
- DKI:
-
Diffusion kurtosis imaging
- MD:
-
Mean diffusivity
- MK:
-
Mean kurtosis
- IDC:
-
Invasive ductal carcinoma
- ILC:
-
Invasive lobular carcinoma
References
Guo Y, Cai YQ, Cai ZL, Gao YG, An NY, Ma L (2002) Differentiation of clinically benign and malignant breast lesions using diffusion-weighted imaging. J Magn Reson Imaging 16:172–178
Bogner W, Gruber S, Pinker K et al (2009) Diffusion-weighted MR for differentiation of breast lesions at 3.0 T: how does selection of diffusion protocols affect diagnosis? Radiology 253:341–351
Peters N, Vincken K, Van den Bosch M, Luijten P, Mali W, Bartels L (2010) Quantitative diffusion weighted imaging for differentiation of benign and malignant breast lesions: the influence of the choice of b-values. J Magn Reson Imaging 31:1100–1105
El Khouli R, Jacobs AM, Mezban DS, Huang P, Kamel JK, Bluemke AD (2010) Diffusion-weighted imaging improves the diagnostic accuracy of conventional 3.0-T breast MR imaging. Radiology 256:64–73
Lo G, Ai V, Chan J et al (2009) Diffusion-weighted magnetic resonance imaging of breast lesions: first experiences at 3 T. J Comput Assist Tomogr 33:63–69
Pereira F, Martins G, Oliveira R (2011) Diffusion magnetic resonance imaging of the breast. Magn Reson Imaging Clin N Am 19:95–110
Basser PJ, Jones DK (2002) Diffusion-tensor MRI: theory, experimental design and data analysis—a technical review. NMR Biomed 15:456–67
Gillies R, Raghunand N, Karczmar G, Bhujwalla Z (2002) MRI of the tumor microenvironment. J Magn Reson Imaging 16:430–450
Jensen J, Helpern J, Ramani A, Lu H, Kaczynski K (2005) Diffusion kurtosis imaging: the quantification of non-Gaussian water diffusion by means of magnetic resonance imaging. Magn Reson Med 53:1432–1440
Tamura T, Usui S, Murakami S et al (2012) Comparisons of multi b-value DWI signal analysis with pathological specimen of breast cancer. Magn Reson Med 68:890–897
Poot DH, Den Dekker AJ, Achten E, Verhoye M, Sijbers J (2010) Optimal experimental design for diffusion kurtosis imaging. IEEE Trans Med Imaging 29:3
Jansen J, Stambuk H, Koutcher J, Shukla-Dave A (2010) Non-Gaussian analysis of diffusion-weighted MR imaging in head and neck squamous cell carcinoma: a feasibility study. AJNR Am J Neuroradiol 31:741–748
Quentin M, Blondin D, Klasen J et al (2012) Comparison of different mathematical models of diffusion-weighted prostate MR imaging. Magn Reson Imaging 30:1468–1474
Cheung M, Hui E, Chan K, Helpen J, Qi L, Wu E (2009) Does diffusion kurtosis imaging lead to better neural tissue characterization? A rodent brain maturation study. Neuroimage 45:386–392
Falangola MF, Jensen JH, Babb JS et al (2008) Age-related non-Gaussian diffusion patterns in the prefrontal brain. J Magn Reson Imaging 28:1345–50
Chen S, Pickard JD, Harris NG (2003) Time course of cellular pathology after controlled cortical impact injury. Exp Neurol 1:87–102
Raab P, Hattingen E, Franz K, Zanella FE, Lanferman H (2010) Cerebral gliomas: diffusional kurtosis imaging analysis of microstructural differences. Radiology 254:876–81
Trampel R, Jensen JH, Lee RF, Kamenetskiy I, McGuinness G, Johnson G (2006) Diffusional kurtosis imaging in the lung using hyperpolarized 3He. Magn Reson Med 56:733–737
Borlinhas F, Lacerda L, Andrade A, Ferreira HA (2012) Diffusional kurtosis as a biomarker of breast tumors (E-poster presentation). European Congress of Radiology 2012, 1–5 March 2012, Vienna, Austria. doi:10.1594/erc2012/C-1369
Ikeda DM, Hylton NM, Kuhl CK et al (2003) BI-RADS: magnetic resonance imaging, 1st edn. In: D’Orsi CJ, Mendelson EB, Ikeda DM et al (eds) Breast imaging reporting and data system: ACR BI-RADS—breast imaging atlas. American College of Radiology, Reston
Marquardt DW (1963) An algorithm for least-squares estimation of nonlinear parameters. J Soc Ind Appl Math 11:431–441
Costantini M, Belli P, Rinaldi P (2010) Diffusion-weighted imaging in breast cancer: relationship between apparent diffusion coefficient and tumour aggressiveness. Clin Radiol 65:1008–1012
Paran Y, Bendel P, Margalit R, Degani H (2004) Water diffusion in the different microenvironments of breast cancer. NMR Biomed 17:170–180
Lyng H, Haraldseth O, Rofstad EK (2000) Measurement of cell density and necrotic fraction in human melanoma xenografts by diffusion weighted magnetic resonance imaging. Magn Reson Med 43:828–836
Sukstanskii AL, Yablonskiy DA (2002) Effects of restricted diffusion on MR signal formation. J Magn Reson 157:92–105
Kiselev VG, Il’yasov KA (2007) Is the “biexponential diffusion” biexponential? Magn Reson Med 57:464–469
Pereira F, Martins G, Oliveira R (2011) Diffusion magnetic resonance imaging of the breast. Magn Reson Imaging Clin N Am 19:95–110
De Santis S, Gabrielli A, Palombo M, Maraviglia B, Capuani S (2011) Non-Gaussian diffusion imaging: a brief practical review. Magn Reson Imaging 29:1410–1416
Fornasa F (2011) Diffusion-weighted magnetic resonance imaging: what makes water run fast or slow? J Clin Imaging Sci 1:1–7
Roth Y, Ocherashvilli A, Daniels D et al (2008) Quantification of water compartmentation in cell suspensions by diffusion-weighted and T2-weighted MRI. Magn Reson Imaging 26:88–102
Koh D, Collins D (2007) Diffusion-weighted MRI in the body: applications and challenges in oncology. AJR Am J Roentgenol 188:1622–1635
Acknowledgments
The scientific guarantor of this publication is Isabel Maria Amorim Pereira Ramos. The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article. This work was sponsored by Foundation of Science and Technology (FCT)/School of Health Technology of Porto (ESTSP)/Polytechnic Institute of Porto (IPP) with grant number: SFRH/BD/50027/2009 and grant number: PEst-OE/SAU/UI0645/2011. One of the authors has significant statistical expertise. Institutional Review Board approval was obtained. Written informed consent was obtained from all subjects (patients) in this study. Methodology: prospective, diagnostic or prognostic study, performed at one institution.
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Nogueira, L., Brandão, S., Matos, E. et al. Application of the diffusion kurtosis model for the study of breast lesions. Eur Radiol 24, 1197–1203 (2014). https://doi.org/10.1007/s00330-014-3146-5
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DOI: https://doi.org/10.1007/s00330-014-3146-5