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Diffusion weighted imaging for the differentiation of breast tumors: From apparent diffusion coefficient to high order diffusion tensor imaging
Author(s) -
Teruel Jose R.,
Goa Pål E.,
Sjøbakk Torill E.,
Østlie Agnes,
Fjøsne Hans E.,
Bathen Tone F.
Publication year - 2016
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.25067
Subject(s) - diffusion mri , fractional anisotropy , effective diffusion coefficient , anisotropy , receiver operating characteristic , medicine , nuclear medicine , tensor (intrinsic definition) , isotropy , nuclear magnetic resonance , radiology , magnetic resonance imaging , pathology , physics , mathematics , geometry , optics
Background To compare “standard” diffusion weighted imaging, and diffusion tensor imaging (DTI) of 2 nd and 4 th ‐order for the differentiation of malignant and benign breast lesions. Methods Seventy‐one patients were imaged at 3 Tesla with a 16‐channel breast coil. A diffusion weighted MRI sequence including b = 0 and b = 700 in 30 directions was obtained for all patients. The image data were fitted to three different diffusion models: isotropic model – apparent diffusion coefficient (ADC), 2 nd ‐order tensor model (the standard model used for DTI) and a 4 th ‐order tensor model, with increased degrees of freedom to describe anisotropy. The ability of the fitted parameters in the different models to differentiate between malignant and benign tumors was analyzed. Results Seventy‐two breast lesions were analyzed, out of which 38 corresponded to malignant and 34 to benign tumors. ADC (using any model) presented the highest discriminative ability of malignant from benign tumors with a receiver operating characteristic area under the curve (AUC) of 0.968, and sensitivity and specificity of 94.1% and 94.7% respectively for a 1.33 × 10 −3 mm 2 /s cutoff. Anisotropy measurements presented high statistical significance between malignant and benign tumors ( P < 0.001), but with lower discriminative ability of malignant from benign tumors than ADC (AUC of 0.896 and 0.897 for fractional anisotropy and generalized anisotropy respectively). Statistical significant difference was found between generalized anisotropy and fractional anisotropy for cancers ( P < 0.001) but not for benign lesions ( P = 0.87). Conclusion While anisotropy parameters have the potential to provide additional value for breast applications as demonstrated in this study, ADC exhibited the highest differentiation power between malignant and benign breast tumors. J. Magn. Reson. Imaging 2016;43:1111–1121.