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

Area of Science:

• Radiology and Imaging Science
• Oncology Diagnostics
• Medical Physics

Background:

• Differentiating malignant and benign breast lesions is crucial for effective patient management.
• Standard diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI) are MRI techniques used for tissue characterization.
• Higher-order DTI models offer potential for improved lesion differentiation.

Purpose of the Study:

• To compare the efficacy of standard DWI and 2nd/4th-order DTI models in differentiating malignant from benign breast lesions.
• To evaluate the diagnostic performance of apparent diffusion coefficient (ADC) and anisotropy parameters derived from these models.

Main Methods:

• Seventy-one patients with breast lesions underwent 3 Tesla MRI.
• Diffusion-weighted MRI data were acquired and fitted to isotropic (ADC), 2nd-order DTI, and 4th-order DTI models.
• The discriminative ability of parameters from each model to differentiate tumor types was analyzed using receiver operating characteristic (ROC) curves.

Main Results:

• Apparent diffusion coefficient (ADC) demonstrated the highest diagnostic performance (AUC 0.968, sensitivity 94.1%, specificity 94.7%).
• Anisotropy measurements (fractional anisotropy and generalized anisotropy) showed statistical significance (P < 0.001) but lower discriminative ability (AUC ~0.897).
• A significant difference in anisotropy was observed between malignant and benign cancers, but not benign lesions.

Conclusions:

• Apparent diffusion coefficient (ADC) mapping provides superior differentiation between malignant and benign breast tumors compared to anisotropy parameters.
• While anisotropy parameters offer potential additional value in breast MRI applications, ADC remains the primary metric for diagnostic power.
• Further research into higher-order DTI models may enhance understanding of tissue microstructure in breast lesions.