Simplified gamma-variate fitting of perfusion curves

Most methods that fit gamma-variate functions to perfusion curves suffer from convergence problems and lengthy processing times. In this paper, a technique that robustly and feasibly fits perfusion curves with a simplified form of the gamma-variate function is presented. The performance of the technique, as measured by its sensitivity to noise and tracer recirculation, was assessed by Monte Carlo methods with simulated curves. The algorithm was also applied to perfusion curves from 20 glioma patients and evaluated based on the fitting error during the first-pass phase. This technique may elucidate the clinical role of perfusion-weighted imaging in the future.