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


CONCLUSIONS
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.
Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.|St. Olavs University Hospital, Trondheim, Norway.
Jose R
JR
Teruel
Department of Physics, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
Pål E
PE
Goa
Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
Torill E
TE
Sjøbakk
Clinic of Radiology and Nuclear Medicine, St. Olavs University Hospital, Trondheim, Norway.
Agnes
A
Østlie
Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.|Department of Surgery, St. Olavs University Hospital, Trondheim, Norway.
Hans E
HE
Fjøsne
Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
Tone F
TF
Bathen
D000293:Adolescent; D000328:Adult; D016880:Anisotropy; D019540:Area Under Curve; D001940:Breast / Q000000981:diagnostic imaging* / Q000473:pathology*; D001943:Breast Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology*; D038524:Diffusion Magnetic Resonance Imaging; D056324:Diffusion Tensor Imaging; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D007091:Image Processing, Computer-Assisted; D008875:Middle Aged; D015233:Models, Statistical; D012372:ROC Curve; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D055815:Young Adult
apparent diffusion coefficient; benign breast tumors; breast cancer; diffusion tensor imaging; diffusion weighted imaging