3-T dynamic contrast-enhanced MRI of the breast: pharmacokinetic parameters versus conventional kinetic curve...

The purpose of this article is to evaluate the incremental value of pharmacokinetic analysis of dynamic contrast-enhanced (DCE) MRI compared with conventional breast MRI (morphology plus kinetic curve type analysis) in characterizing breast lesions as malignant or benign.

Patients underwent 3D high-resolution T1-weighted contrast-enhanced MRI and DCE-MRI at 3 T and had pathology-proven diagnosis (95%) or more than 2 years of follow-up confirming lesion stability (5%). Lesions were identified using the high-spatial-resolution contrast-enhanced MRI. Morphologic features (margin, enhancement, and pattern) and conventional DCE-MRI results (kinetic curve types 1, 2, or 3) or pharmacokinetic parameters (forward volume transfer constant [K(trans)], reverse volume transfer constant [K(ep)], and the extravascular extracellular space volume per unit volume of tissue), were included in multivariate models for prediction of benign versus malignant diagnosis.

Ninety-five patients with 101 lesions were included: 52% of patients were premenopausal and 48% were postmenopausal. Sixty-eight lesions (67.3%) were malignant and 33 (32.7%) were benign. There was a significant association between K(trans) and K(ep) and the diagnosis of benign versus malignant (p < 0.001). The area under the curve for morphologic features (lesion margin and enhancement pattern) was 0.85, whereas inclusion of K(trans) or K(ep) in the model showed similar modest improvement in performance (area under the curve, 0.88-0.89). For DCE-MRI, both pharmacokinetic modeling and kinetic curve type analysis improved characterization of malignant and benign breast lesions. A diagnostic model including lesion morphology plus either pharmacokinetic parameters or kinetic curve assessment showed similar diagnostic performance in characterizing breast lesions.

The use of kinetic curve type assessment or pharmacokinetic modeling in conjunction with high-resolution 3D breast MRI appears to offer similar improvement in diagnostic performance. Although morphologic analysis alone provides good characterization of breast lesions on MRI as benign or malignant, analysis of the lesion perfusion on DCE-MRI using either kinetic curve shape assessment or a pharmacokinetic modeling approach improves diagnostic accuracy.