Reconstruction of kinetic parameter images directly from dynamic PET sinograms

Mustafa E. Kamasak*, Charles A. Bouman, Evan D. Morris, Ken Sauer

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

2 Citations (Scopus)


Recently, there has been interest in estimating kinetic model parameters for each voxel in a PET image. To do this, the activity images are first reconstructed from PET sinogram frames at each measurement time, and then the kinetic parameters are estimated by fitting a model to the reconstructed time-activity response of each voxel. However, this indirect approach to kinetic parameter estimation tends to reduce signal-to-noise ratio (SNR) because of the requirement that the sinogram data be divided into individual time frames. In 1985, Carson and Lange proposed, 1 but did not implement, a method based on the EM algorithm for direct parametric reconstruction. More recently, researchers have developed semi-direct methods which use spline-based reconstruction, or direct methods for estimation of kinetic parameters from image regions. However, direct voxel-wise parametric reconstruction has remained a challenge due to the unsolved complexities of inversion and required spatial regularization. In this work, we demonstrate an efficient method for direct voxel-wise reconstruction of kinetic parameters (as a parametric image) from all frames of the PET data. The direct parametric image reconstruction is formulated in a Bayesian framework, and uses the parametric iterative coordinate descent (PICD) algorithm to solve the resulting optimization problem. 2 This PICD algorithm is computationally efficient and allows the physiologically important kinetic parameters to be spatially regularized. Our experimental simulations demonstrate that direct parametric reconstruction can substantially reduce estimation error of kinetic parameters as compared to indirect methods.

Original languageEnglish
Article number42
Pages (from-to)400-411
Number of pages12
JournalProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Issue numberI
Publication statusPublished - 2005
Externally publishedYes
EventMedical Imaging 2005 - Image Processing - San Diego, CA, United States
Duration: 13 Feb 200517 Feb 2005


  • Dynamic PET
  • Iterative reconstruction
  • Kinetic modeling
  • Regularization
  • Tomography


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