Experimental and Pre-clinical Evaluation of Reconstruction Methods in Dynamic PET: Quantitative Characteristics and Effects on Kinetic Modelling

Turmacu, Valentina (2023) Experimental and Pre-clinical Evaluation of Reconstruction Methods in Dynamic PET: Quantitative Characteristics and Effects on Kinetic Modelling. Bachelor's Thesis, Biomedical Engineering.

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Abstract

The choice of a reconstruction algorithm in PET affects the accuracy of quantitative measurements and image interpretation. This study aimed to evaluate the effects of reconstruction algorithms on image quality (IQ) and activity concentration in both phantom and animal settings. The NEMA NU 4–2008 image quality phantom was used to assess FBP2D, RP3D, and OSEM2D reconstruction methods for the Siemens microPET Focus 220 scanner. Pre-clinical data using the [18F]MC225 radiotracer was used to evaluate the same reconstruction algorithms. IQ metrics like recovery coefficient, activity concentration, and noise were extracted from the phantom scans and analyzed to establish a golden standard. The [18F]MC225 rat data study involved brain dynamic PET scans, blood sample collection, and kinetic modeling analysis. Tissue time-activity curves (TACs) were obtained and the 1-tissue compartment model (1TCM) was applied. The phantom study showed that OSEM2D* (routine protocol) performed best across the IQ metrics and frame durations, prioritizing the activity concentration error. OSEM2D was found to perform very similarly. The [18F]MC225 study showed that no significant differences were found between the TACs across reconstruction methods and some significant differences were found across kinetic parameters for one study subject. The model fit analysis showed that 1TCM fit best on OSEM2D* images, both by the standard error of the kinetic parameters and the Akaike information criterion.

Item Type:	Thesis (Bachelor's Thesis)
Supervisor name:	Tsoumpas, C.
Degree programme:	Biomedical Engineering
Thesis type:	Bachelor's Thesis
Language:	English
Date Deposited:	05 Jul 2023 12:56
Last Modified:	05 Jul 2023 12:56
URI:	https://fse.studenttheses.ub.rug.nl/id/eprint/30176

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