Laplace Transform Method for 11C-PIB Two-Tissue Reversible Compartment Model with Image-Derived Arterial Input Function
Eliete Biasotto Hauser1; Gianina Teribele Venturin1; Evandro Manica2; Samuel Greggio1; Eduardo Zimmer2; Jaderson Costa da Costa1
1 InsCer/PUCRS; 2 UFRGS
doi:10.20906/CPS/CILAMCE2017-1077
Resumo
Positron Emission Tomography (PET) has been of utmost importance for helping the diagnostics of neurodegenerative diseases, such as Alzheimer's disease(AD). Radiolabeled drugs help quantifying the amount of deposition of beta-amyloid in the brain which can be a strong indication for AD. In this work, using data coming from an experiment at the Brain Institute with Pittsburgh Compound-B (11C-PIB) as a marker, we propose a two-tissue reversible compartment model as a mathematical modeling in the quantitative analysis of the 11C-PIB. Laplace Transform is applied to solve the corresponding system of differential equations for each compartment. Using as a reference region the cerebellum, known to be amyloid free, we obtained an analytical solution for the Image Derived Input Function (IDAIF) as well as for the concentration of beta-amyloid in each compartment. Our results corroborate what has been seen in the literature.
Palavras-chave: Laplace Transform; Kinetic Modeling; Image-Derived Arterial Input Function; Alzheimer Desease; Pittsburgh Compound-B (11C-PIB)