Principal component analysis of breast DCE-MRI adjusted with a model-based method.

Purpose: To investigate a fast, objective, and standardized method for analyzing breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) applying principal component analysis (PCA) adjusted with a model-based method.

Materials And Methods: 3D gradient-echo DCE breast images of 31 malignant and 38 benign lesions, recorded on a 1.5T scanner, were retrospectively analyzed by PCA and by the model-based three-timepoints (3TP) method.

Scan-rescan variability in perfusion assessment of tumors in MRI using both model and data-derived arterial input functions.

Purpose: To evaluate the contribution to scan-rescan coefficient of variation (CV) of patient-specific arterial input function (AIF) measurement in dynamic contrast-enhanced MRI (DCE-MRI) data, and to determine whether any advantage or disadvantage to using a data-derived arterial input function is related to the anatomical location of the target lesion.

Materials And Methods: Two methods are presented for the calculation of perfusion parameters from DCE-MRI data using a two-compartment model. The first method makes use of a single-model AIF across all study data sets, while the second uses an automated process to derive an AIF specific to each data set.