Azimeh Noorizadeh1, Hassan Bagher-Ebadian2,3, Reza Faghihi1, Jayant Narang4, Rajan Jain4, James Russel Ewing2,3
1Department of Nuclear Engineering, Shiraz University, Shiraz, Fars, Iran; 2Department of Neurology, Henry Ford Hospital, Detroit, MI, United States; 3Department of Physics, Oakland University, Rochester, MI, United States; 4Department of Radiology, Henry Ford Hospital, Detroit, MI, United States
MR Quantification of the hemodynamic maps such as Cerebral Blood Volume, Mean Transit Time, and Cerebral Blood Flow in perfusion studies is highly susceptible to selection of the correct Arterial Input Function (AIF) and a correct AIF selection could substantially reduce bias in hemodynamic parameters. This study uses a blood circulatory model to construct an automatic and model-based algorithm for AIF detection in MR perfusion studies. The algorithm is used to detect the AIF from MR perfusion of four patients with 19 slices. This study introduces a new and reliable (performance: 84%) algorithm for AIF detection in MR perfusion studies.