Geavanceerde Reconstructie- en Correctiemethoden voor Gallium-68 PET

Abstract

Positron Emission Tomography (PET) is a medical imaging modality measuring the in vivo processes of cells and molecules using radiotracers. Compared to other medical imaging techniques, PET still suffers from limited spatial resolution and signal-to-noise ratio. One key factor to resolution degradation is the distance the emitted positron travels before annihilating with an electron. This distance is called positron range. Radionuclides emitting high-energy positrons are subject to more spatial resolution degradation than radionuclides emitting low-energy positrons. In oncologic PET imaging a well-known and commonly used radionuclide is Fluorine-18 (18F) which features low positron energy. In the last decade, Gallium-68 (68Ga) has been increasingly used in oncologic PET imaging. However, as 68Ga emits high-energy positrons, the spatial resolution of 68Ga PET images is degraded compared to 18F PET images. Goal of this PhD project is to improve 68Ga PET image quality and quantification. For this, we will incorporate the 68Ga positron range in the PET reconstruction algorithm to compensate for the degrading positron range effect to achieve comparable image quality for 68Ga as for 18F. In addition, deep learning techniques will be developed to both speed up the positron range correction process and boost PET image quality of low dose PET acquisitions. These techniques will be validated on already acquired patient data.

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