A novel method for pharmacokinetic parameters quantification in DCE-MRI: Application in prostate cancer

Detecting and quantifying tumor vascularity is critical for diagnosing cancer, guiding therapy, and monitoring disease progression.

This study focuses on quantifying pharmacokinetic parameters derived from multi-compartment models by analyzing and processing dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data of prostate cancer lesions.

Previous voxel-based analysis employed the three-time-point method to classify different regions based on kinetic patterns. The key pharmacokinetic parameters-such as $k_{el}$ , the vascular elimination rate, and $k_{ep}$ , the extravascular transfer rate, were extracted using a novel point-wise interpolation method designed for application in compartmental models.

Results from the simple two-compartment model proposed by Brix revealed the presence of both fast and slow exchange regions, suggesting the potential for a more complex multi-compartment model. Parameter distribution maps generated from this analysis appear to correlate with pathological and unaffected glandular regions. Further investigation using a three-compartment model identified an additional exchange rate that lies between the previously observed fast and slow rates, supporting the assumption of tissue heterogeneity beyond the two-compartment framework.

A simple two-compartment model can effectively describe the kinetics of contrast media. When combined with a novel voxel-wise method, it enables the estimation of tissue exchange parameters and their spatial distributions. These results have potential applications in the diagnostic evaluation and therapeutic monitoring of prostate cancer.