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Monte Carlo simulation of PET images for injection dose optimization
J. Boldyš, J. Dvořák, M. Skopalová, O. Bělohlávek,
Language English Country England, Great Britain
Document type Journal Article, Research Support, Non-U.S. Gov't
PubMed
23281273
DOI
10.1002/cnm.2527
Knihovny.cz E-resources
- MeSH
- Models, Biological MeSH
- Radiation Dosage * MeSH
- Phantoms, Imaging MeSH
- Body Mass Index MeSH
- Humans MeSH
- Monte Carlo Method * MeSH
- Tomography, X-Ray Computed MeSH
- Computer Simulation MeSH
- Image Processing, Computer-Assisted MeSH
- Positron-Emission Tomography methods MeSH
- Radioactive Tracers MeSH
- Torso physiology radiography MeSH
- Body Size physiology MeSH
- Drug Dosage Calculations * MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
When a patient is examined by positron emission tomography (PET), radiotracer dose amount (activity) has to be determined. However, the rules for activity correction according to patients' weight used nowadays do not correspond with practical experience. Very high image quality is achieved for slim patients, whereas noisy images are produced for obese patients. There is opportunity to modify the correction rule with the aim to equalize image quality within the broad spectrum of patients and to diminish radiation risk to slim patients, with special importance for children. We have built a model of a particular PET scanner and approximated human trunk, which is our region of interest, by a cylindrical model with segments of liver, outer adipose tissue, and the rest. We have performed Monte Carlo simulations of PET imaging using the GATE simulation package. Under reasonably simplifying assumptions and for special parameters, we have developed curves that recommend amount of injected activity based on body parameters to give PET images of constant quality, the quality being expressed in terms of noise equivalent counts. The dependence qualitatively differs from the rules used in clinical practice nowadays, and the results indicate potential for improvement.
References provided by Crossref.org
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