Direct 4D PET MLEM reconstruction of parametric images using the simplified reference tissue model with the basis function method for [11C]raclopride

Paul Gravel, Andrew J. Reader

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)

Abstract

This work assesses the one-step late maximum likelihood expectation maximization (OSL-MLEM) 4D PET reconstruction algorithm for direct estimation of parametric images from raw PET data when using the simplified reference tissue model with the basis function method (SRTM-BFM) for the kinetic analysis. To date, the OSL-MLEM method has been evaluated using kinetic models based on two-tissue compartments with an irreversible component. We extend the evaluation of this method for two-tissue compartments with a reversible component, using SRTM-BFM on simulated 3D + time data sets (with use of [11C]raclopride time-activity curves from real data) and on real data sets acquired with the high resolution research tomograph. The performance of the proposed method is evaluated by comparing voxel-level binding potential (BPND) estimates with those obtained from conventional post-reconstruction kinetic parameter estimation. For the commonly chosen number of iterations used in practice, our results show that for the 3D + time simulation, the direct method delivers results with lower %RMSE at the normal count level (decreases of 9-10 percentage points, corresponding to a 38-44% reduction), and also at low count levels (decreases of 17-21 percentage points, corresponding to a 26-36% reduction). As for the real 3D data set, the results obtained follow a similar trend, with the direct reconstruction method offering a 21% decrease in %CV compared to the post reconstruction method at low count levels. Thus, based on the results presented herein, using the SRTM-BFM kinetic model in conjunction with the OSL-MLEM direct 4D PET MLEM reconstruction method offers an improvement in performance when compared to conventional post reconstruction methods.

Original languageEnglish
Article number4533
Pages (from-to)4533-4549
Number of pages17
JournalPhysics in Medicine and Biology
Volume60
Issue number11
Early online date20 May 2015
DOIs
Publication statusPublished - 2015

Keywords

  • binding potential
  • image reconstruction
  • positron emission tomography
  • tracer kinetic modeling

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