Decoupling Iterative Algorithm for Rapid Calculation of Standard Tofts Model Physiological Parameters

Motivation: Standard Tofts model (STM) is widely used to extract physiological parameters (Ktrans and ve) from DCE-MRI. However, it's time-consuming for pixel-by-pixel analysis of 3D DCE-MRI using STM. Goal(s): To develop a decoupling iterative algorithm, prediction-correction method (PCM), for rapid calculation of STM parameters. Approach: By decoupling Ktrans and ve, each parameter is iteratively calculated separately using early and late portion of contrast agent concentration curve. The QIBA data used for validation and clinical data used as application and compared with conventional way to fitting the STM. Results: By using our PCM, Ktrans and ve can be calculated rapidly for 3D DCE-MRI. Impact: The novel prediction-correction method was significantly reduced the computation time for pixel-by-pixel analysis of 3D DCE-MRI using the standard Tofts model. It can be used clinically to quickly generate Ktrans and ve maps for cancer diagnosis.