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Attenuation Correction for Small Animal PET Images: A Comparison of Two Methods

In order to extract quantitative parameters from PET images, several physical effects such as photon attenuation, scatter, and partial volume must be taken into account. The main objectives of this work were the evaluation of photon attenuation in small animals and the implementation of two attenuat...

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Detalles Bibliográficos
Autores principales: D'Ambrosio, Daniela, Zagni, Federico, Spinelli, Antonello E., Marengo, Mario
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3652124/
https://www.ncbi.nlm.nih.gov/pubmed/23690871
http://dx.doi.org/10.1155/2013/103476
Descripción
Sumario:In order to extract quantitative parameters from PET images, several physical effects such as photon attenuation, scatter, and partial volume must be taken into account. The main objectives of this work were the evaluation of photon attenuation in small animals and the implementation of two attenuation correction methods based on X-rays CT and segmentation of emission images. The accuracy of the first method with respect to the beam hardening effect was investigated by using Monte Carlo simulations. Mouse- and rat-sized phantoms were acquired in order to evaluate attenuation correction in terms of counts increment and recovery of uniform activity concentration. Both methods were applied to mice and rat images acquired with several radiotracers such as(18)F-FDG, (11)C-acetate, (68)Ga-chloride, and (18)F-NaF. The accuracy of the proposed methods was evaluated in heart and tumour tissues using (18)F-FDG images and in liver, kidney, and spinal column tissues using (11)C-acetate, (68)Ga-chloride, and (18)F-NaF images, respectively. In vivo results from animal studies show that, except for bone scans, differences between the proposed methods were about 10% in rats and 3% in mice. In conclusion, both methods provide equivalent results; however, the segmentation-based approach has several advantages being less time consuming and simple to implement.