Dynamic and metabolic quantification of nuclear medicine images in the PET/CT modality

Imaging using nuclear medicine is one of the most common procedures in medical centers. Its great advantage is its capacity to analyze the metabolism of the patient, resulting in early diagnosis. However, quantification in nuclear medicine is complicated by many factors, including degradation due to attenuation, scattering, reconstruction algorithms, and assumed models. This project seeks to improve the accuracy and the precision of quantification in PET/CT images. We developed a framework, comprising consecutively interlinked steps initiated with the simulation of 3D anthropomorphic phantoms. These phantoms were used to generate realistic PET/CT projections by applying the Geant4 Application for Tomography Emission platform using Monte Carlo simulation. Then, a 3D image reconstruction was created, followed by an Anscombe/Wiener filter and a fuzzy connectedness segmentation process. After defining the region of interest, input activity and response activity curves were generated as excitation functions of the compartment model to enable metabolic quantification of the selected organ or structure. Finally, real PET/CT images provided by the Heart Institute of Hospital das Clinicas, School of Medicine of the University of Sao Paulo were analyzed using the method. Metabolic parameters of the three-compartment model based on the MASH anthropomorphic phantom and real PET images were computed for each of the approaches used in this project; the results were similar to the theoretically characteristic values. The three-dimensional filtering step using the Ascombe/Wiener filter was preponderant and had a high impact on the metabolic quantification process and on other important stages of the whole project.