Expanded pharmacokinetic model for population studies in breast magnetic resonance imaging

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ABSTRACT:A method for pharmacokinetic analysis, including: receiving time-series medical image data of a patient introduced with a contrast agent (505); identifying a reference region in the medical image data (510); identifying a plurality of points of interest in the medical image data (515); measuring an intensity of voxels in the reference region (520); and for each point of interest, measure an intensity of voxels therein (525), use the measured reference region and point of interest intensities to obtain an expression relating the point of interest's voxel concentration to that of the reference region (530), wherein the expression is a five-parameter nonlinear model with no reference to an arterial input function; and obtain values for each of the five-parameters by solving the expression (535) and use the obtained values to determine whether the point of interest is malignant (540).

BACKGROUND OF THE INVENTION

1. Technical Field

The present invention relates to pharmacokinetic (PK) analysis.

2. Discussion of the Related Art

The diagnosis of breast cancer from Magnetic Resonance Imaging (MRI) data is a tough problem exacerbated by the fact that a malignant lesion often displays intensity patterns similar to benign tissues and other structures (such as the heart) in the field of view. However, malignant tissues differ from benign tissues in how Contrast Agents (CAs) flow in and leak out. These molecules affect the observed intensity patterns because they change the longitudinal relaxation times at the voxels in the image. Unlike their behavior with respect to intensity itself, malignant tissues display a characteristic pattern with regard to how much of the CA they take up, and also with regard to the rates of entry and wash-out of the CA. Dynamic Contrast-Enhanced (DCE) MRI uses this property to identify regions of interest. Pharmacokinetic (PK) analysis then aims to quantify the wash-in and wash-out of the CA towards differentiating malignant and benign lesions. The ideal goal of PK analysis in the context of breast MRI is to provide a framework where the kinetics of the CA within the tissue of interest can be quantitatively described, and compared across data sets from one or more patients and/or MR systems. However, current systems do not meet this requirement due to difficulties in the normalization that the system can perform on the input image data, which impairs the effectiveness of any population studies conducted.

Existing literature on PK analysis for breast MR can be categorized into two broad classes of models - compartmental and heuristic. The first class attempts to describe the microscopic view of the breast tissues as a set of compartments and then models the interaction between these compartments with respect to the entry and exit of the CA. Within this class, the models differ in the number of compartments they use to model the tissue and the equations that describe the interactions. Heuristic models attempt to model the wash-in and wash-out phenomena - as growing(/decaying) exponentials for example - and quantify the extents and rates of the same. Of the compartmental models, the Tofts model is the most commonly used. A comparative study of different PK models for DCE-MRI can be found, for example, in [R. Srikanchana, D. Thomasson, P. Choyke, and A. Dwyer. A comparison of pharmacokinetic models of dynamic contrast-enhanced MRI. CBMS 2004. Proceedings. 17th EEEE Symposium on Computer-Based Medical Systems, 2004., pages 361-366, 2004]. The challenges in estimating the quantity of CA in the vascular space and the unsatisfactory normalization which impairs population studies are key issues that need to be addressed.

SUMMARY OF THE INVENTION

In an exemplary embodiment of the present invention, a method for pharmacokinetic analysis, comprises: receiving time-series medical image data of a patient introduced with a contrast agent; identifying a reference region in the medical image data; identifying a plurality of points of interest in the medical image data; measuring an intensity of voxels in the reference region; and for each point of interest, measure an intensity of voxels therein, use the measured reference region and point of interest intensities to obtain an expression relating the point of interest's voxel concentration to that of the reference region, wherein the expression is a five-parameter nonlinear model with no reference to an arterial input function; and obtain values for each of the five-parameters by solving the expression and use the obtained values to determine whether or not the point of interest is malignant.

The medical image data is magnetic resonance (MR) image data. The medical image data includes the patient's breast. The reference region is the breast nipple. The point of interest is a potential tumor in the patient's breast.