Analysis of Dynamic PET Data

AbstractIn dynamic positron emission tomography (PET) an artery sampling is needed for assessment and validation of parameters in kinetic models. The sampling can be uncomfortable and painful for the patient and technically demanding for the personnel performing the sampling. Noninvasive estimation of the artery time activity curve (TAC) is thus very useful, since the sampling then can be avoided.

Methods are tested on simulated data which is an approximation to PET data. The results from the simulated data are used to quantify how will the different methods perform and to illustrate their limitations. The methods are then used on real PET data, and the estimated TACs are compared to the sampled artery TAC.

Non-negative matrix factorization (NMF) and independent component analysis (ICA) show the best results with correlations around 0.95 with the artery sampled TAC. However, the scaling of the resulting components is lost in the deconvolution so a rescaling scheme is used to get the correct scale in the results. A factor is calculated to solve this scaling problem. The peaks found in the NMF and ICA components are higher than the ones found by the other methods.

The ICA and the NMF results are very similar when applied to real PET data. Therefore, the NMF is chosen as the most appropriate method as it is more stable and not as complicated as the ICA.
TypeMaster's thesis [Academic thesis]
PublisherInformatics and Mathematical Modelling, Technical University of Denmark, DTU
AddressRichard Petersens Plads, Building 321, DK-2800 Kgs. Lyngby
NoteSupervised by Lars Kai Hansen, IMM.
Electronic version(s)[pdf]
BibTeX data [bibtex]
IMM Group(s)Intelligent Signal Processing