VIP '00 Selected papers from the Pan-Sydney workshop on Visualisation - Volume 2
VIP '01 Proceedings of the Pan-Sydney area workshop on Visual information processing - Volume 11
Molecular imaging and biomedical process modeling
APBC '04 Proceedings of the second conference on Asia-Pacific bioinformatics - Volume 29
Journal of Biomedical Imaging
Fast parametric imaging algorithm for dual-input biomedical system parameter estimation
Computer Methods and Programs in Biomedicine
Propagation of blood function errors to the estimates of kinetic parameters with dynamic PET
Journal of Biomedical Imaging - Special issue on modern mathematics in biomedical imaging
SAKE: A new quantification tool for positron emission tomography studies
Computer Methods and Programs in Biomedicine
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Positron emission tomography (PET) is an important tool for enabling quantification of human brain function. However, quantitative studies using tracer kinetic modeling require the measurement of the tracer time-activity curve in plasma (PTAC) as the model input function. It is widely believed that the insertion of arterial lines and the subsequent collection and processing of the biomedical signal sampled from the arterial blood are not compatible with the practice of clinical PET, as it is invasive and exposes personnel to the risks associated with the handling of patient blood and radiation dose. Therefore, it is of interest to develop practical noninvasive measurement techniques for tracer kinetic modeling with PET. In this paper, a technique is proposed to extract the input function together with the physiological parameters from the brain dynamic images alone. The identifiability of this method is tested rigorously by using Monte Carlo simulation. The results show that the proposed method is able to quantify all the required parameters by using the information obtained from two or more regions of interest (ROIs) with very different dynamics in the PET dynamic images. There is no significant improvement in parameter estimation for the local cerebral metabolic rate of glucose (LCMRGlc) if there are more than three ROIs. The proposed method can provide very reliable estimation of LCMRGlc, which is our primary interest in this study.