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 @entity1 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 @entity1 . 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 @entity5 was analyzed. RESULTS: Seventy-two breast lesions were analyzed, out of which 38 corresponded to malignant and 34 to @entity5 . ADC (using any model) presented the highest discriminative ability of malignant from @entity5 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 @entity5 (P < 0.001), but with lower discriminative ability of malignant from @entity5 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 @entity5 (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 @entity0 . J. Magn. Reson. Imaging 2015.

Diffusion weighted imaging for the differentiation of XXXX : From apparent diffusion coefficient to high order diffusion tensor imaging.

@entity1 :: ('9606', 'Species') :: ['patients'] @entity0 :: ('MESH:D001943', 'Disease') :: ['benign breast tumors'] @entity5 :: ('MESH:D009369', 'Disease') :: ['malignant and benign tumors', 'cancers', 'benign tumors']
@entity0 :: (MESH:D001943,Disease) :: ['breast tumors']
