Statistical Error Analysis Based on Non-Parametric Bootstrap Method of Quantitative MBF Measurement with H{sub}2O(15{sup left}O)_PET

摘要

Knowledg of the precision in the physiological parameters estimated by positron emission tomography (PET) is helpful for optimizing PET study and accurate diagnosis. Nonparametric bootstrap method proposed by Buvat is resampling techniques that can be used to accurately estimate the statistical properties of PET images in one scan and determine statistics of pixel values. The standard deviation (SD) of time activity curves (TAC) generated by region of interests (ROI) also are estimated by using the bootstrap method and the SD would propagate to estimated parameters such as blood flow. In order to evaluate the present method, a PET study for myocardial blood flow (MBF) measurement with H{sub}215{sup left}O_PET was performed. The statistical properties of MBF were estimated and the effects of scan-duration time and ROI size on the SD of MBF were developed.