Quantitative analysis of multi‐slice Gd‐DTPA enhanced dynamic MR images using an automated simplex minimization procedure

Abstract

Quantitative analysis of Gd‐DTPA enhanced dynamic MR images has potential for discriminating lesions, especially because the introduction of clinical fast imaging techniques has enabled good sampling of the relatively rapid Gd‐DTPA wash‐in curves. Analysis of such data requires curve fitting to a nonlinear model, which to date has been performed using a nonlinear least squares (NLLS) fitting procedure. However, this method often fails to converge to the appropriate minima without good initial parameter estimates when multi‐exponential models are involved, making automated analysis of complete multislice or volume data sets problematic. In this report we demonstrate the robust performance of a simplex minimization procedure compared with NLLS, by the method of Marquardt, using a Monte Carlo simulation. Further, we illustrate the applicability of such a technique to the analysis of dynamic contrast enhanced images on a pixel‐by‐pixel basis. As a preliminary example, the technique is applied to a breast lesion but is expected to be suitable for examination of many lesion types.