Abstract
In dynamic positron emission tomography data many researchers have attempted to exploit kinetic models within reconstruction such that parametric images are estimated directly from measurements. This work studies a direct parametric maximum likelihood expectation maximization algorithm applied to [F-18]DOPA data using reference-tissue input function. We use a modified version for direct reconstruction with a gradually descending scheme of subsets (i.e. 18-6-1) initialized with the FBP parametric image for faster convergence and higher accuracy. The results compared with analytic reconstructions show quantitative robustness (i.e. minimal bias) and clinical reproducibility within six human acquisitions in the region of clinical interest. Bland-Altman plots for all the studies showed sufficient quantitative agreement between the direct reconstructed parametric maps and the indirect FBP (-0.035x + 0.48E-5). (C) 2011 Elsevier Ltd. All rights reserved.
Original language | English |
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Pages (from-to) | 407-416 |
Number of pages | 10 |
Journal | Computerized medical imaging and graphics |
Volume | 35 |
Issue number | 5 |
DOIs | |
Publication status | Published - Jul-2011 |
Externally published | Yes |
Keywords
- FDOPA
- Kinetic modelling
- Parametric reconstruction
- Physiological parameters
- Patlak plot
- STRIATAL DOPAMINERGIC SYSTEM
- BRAIN TRANSFER CONSTANTS
- IMAGE-RECONSTRUCTION
- DYNAMIC PET
- GRAPHICAL EVALUATION
- PARKINSONS-DISEASE
- NOISE PROPERTIES
- ORDERED-SUBSETS
- LINEAR-MODELS
- EM ALGORITHM