Direct Parametric Image Reconstruction in Reduced Parameter Space for Rapid Multi-Tracer PET Imaging

Cheng X, Li Z, Liu Z, Navab N, Huang SC, Keller U, Ziegler SI, Shi K (2015)

Publication Type: Journal article

Publication year: 2015

Journal

IEEE Transactions on Medical Imaging Institute of Electrical and Electronics Engineers (IEEE)

Book Volume: 34

Pages Range: 1498-1512

Article Number: 7041178

Journal Issue: 7

DOI: 10.1109/TMI.2015.2403300

Abstract

The separation of multiple PET tracers within an overlapping scan based on intrinsic differences of tracer pharmacokinetics is challenging, due to limited signal-to-noise ratio (SNR) of PET measurements and high complexity of fitting models. In this study, we developed a direct parametric image reconstruction (DPIR) method for estimating kinetic parameters and recovering single tracer information from rapid multi-tracer PET measurements. This is achieved by integrating a multi-tracer model in a reduced parameter space (RPS) into dynamic image reconstruction. This new RPS model is reformulated from an existing multi-tracer model and contains fewer parameters for kinetic fitting. Ordered-subsets expectation-maximization (OSEM) was employed to approximate log-likelihood function with respect to kinetic parameters. To incorporate the multi-tracer model, an iterative weighted nonlinear least square (WNLS) method was employed. The proposed multi-tracer DPIR (MT-DPIR) algorithm was evaluated on dual-tracer PET simulations ([¹⁸F]FDG and [¹¹C]MET) as well as on preclinical PET measurements ([¹⁸F]FLT and [¹⁸F]FDG). The performance of the proposed algorithm was compared to the indirect parameter estimation method with the original dual-tracer model. The respective contributions of the RPS technique and the DPIR method to the performance of the new algorithm were analyzed in detail. For the preclinical evaluation, the tracer separation results were compared with single [¹⁸F]FDG scans of the same subjects measured two days before the dual-tracer scan. The results of the simulation and preclinical studies demonstrate that the proposed MT-DPIR method can improve the separation of multiple tracers for PET image quantification and kinetic parameter estimations.

Involved external institutions

Technische Universität München (TUM)

Germany (DE) University of California Los Angeles (UCLA)

United States (USA) (US)

How to cite

APA:

Cheng, X., Li, Z., Liu, Z., Navab, N., Huang, S.-C., Keller, U.,... Shi, K. (2015). Direct Parametric Image Reconstruction in Reduced Parameter Space for Rapid Multi-Tracer PET Imaging. IEEE Transactions on Medical Imaging, 34(7), 1498-1512. https://doi.org/10.1109/TMI.2015.2403300

MLA:

Cheng, Xiaoyin, et al. "Direct Parametric Image Reconstruction in Reduced Parameter Space for Rapid Multi-Tracer PET Imaging." IEEE Transactions on Medical Imaging 34.7 (2015): 1498-1512.

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