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
Clustering dynamic PET images on the Gaussian distributed sinogram domain
Computer Methods and Programs in Biomedicine
IEEE Transactions on Information Technology in Biomedicine
Tracer kinetics guided dynamic PET reconstruction
IPMI'07 Proceedings of the 20th international conference on Information processing in medical imaging
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
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Dynamic imaging with positron emission tomography (PET) is widely used for the in-vivo measurement of the regional cerebral metabolic rate for glucose (rCMRGlc) with [ 18F]fluorodeoxy-D-glucose (FDG), and is used for the clinical evaluation of neurological diseases. However, in addition to the acquisition of dynamic images, continuous arterial blood sampling is the conventional method of obtaining the tracer time-activity curve in blood (or plasma) for the numerical estimation of rCMRGlc in mg glucose/100 g tissue/min. The insertion of arterial lines and the subsequent collection and processing of multiple blood samples are impractical for clinical PET studies because it is invasive, it has the remote (but real) potential for producing limb ischemia, and it exposes personnel to additional radiation and the risks associated with handling blood. Based on a method for extracting kinetic parameters from dynamic PET images, we developed a modified version (post-estimation method) to improve the numerical identifiability of the parameter estimates when we deal with data obtained from clinical studies. We applied both methods to dynamic neurological FDG PET studies in three adults. We found that the input function and parameter estimates obtained with our noninvasive methods agreed well with those estimated from the gold-standard method of arterial blood sampling and that rCMRGlc estimates were highly correlated. No significant difference was found between rCMRGlc estimated by our methods and the gold-standard method. We suggest that our proposed noninvasive methods may offer an advance over existing methods.