Optimization of PET activation studies based on the SNR measured in the 3-D Hoffman brain phantom.
This work investigates the noise properties of O-15 water PET images in an attempt to increase the sensitivity of activation studies. A method for computing the amount of noise within a region of interest (ROI) from the uncertainty in the raw data was implemented for three-dimensional (3-D) positron emission tomography (PET). The method was used to study the signal-to-noise ratio (SNR) of regions-of-interest (ROI's) inside a 3-D Hoffman brain phantom. Saturation occurs at an activity concentration of 2.2 mCi/l which corresponds to a 75-mCi O-15 water injection into a normal person of average weight. This establishes the upper limit for injections for human brain studies using 3-D PET on the Siemens ECAT 921 EXACT scanner. Data from human brain activation studies on four normal volunteers using two-dimensional (2-D) PET were analyzed. The biological variation was found to be 5% in 1-ml ROI's. The variance for a complete activation study was calculated, for a variety of protocols, by combining the Poisson noise propagated from the raw data in the phantom experiments with the biological variation. A protocol that is predicted to maximize the SNR in dual-condition activation experiments while remaining below the radiation safety limit is: ten scans with 45 mCi per injection. The data should not be corrected for random or scatter events since they do not help in the identification of activation sites while they do add noise to the image. Due to the lower noise level of 3-D PET, the threshold for detecting a true change in activity concentration is 10%-20% lower than 2-D PET. Because of this, a 3-D activation experiment using the Siemens 921 scanner requires fewer subjects for equal statistical power.
Li
H H
HH
Emory University Center for PET, Atlanta, GA 30322, USA.
Votaw
J R
JR
D001921:Brain / Q000000981:diagnostic imaging*; D006801:Humans; D019047:Phantoms, Imaging; D012680:Sensitivity and Specificity; D014055:Tomography, Emission-Computed / Q000379:methods*