Theoretical Study of Benefit of Long Axial Field-of-View PET: Impact on Quantification Performance

Xuezhu Zhang, Ramsey D. Badawi, Simon R. Cherry, Jinyi Qi

DOI:10.12059/Fully3D.2017-11-3104005

Published in:Fully3D 2017 Proceedings

Pages:767-770

Keywords:
We are building a 2-meter long PET scanner, called EXPLORER, that can provide high sensitivity and temporal resolution for total-body PET imaging. The aim of this study is to evaluate the improvement on quantification performance offered by the long axial field-of-view (FOV) of the EXPLORER. We use theoretical formulae based on the Fisher information matrix (FIM) of the penalized maximum likelihood image reconstruction to compute the contrast recovery coefficient (CRC) and the variance for region of interest (ROI) quantification. The CRC versus variance tradeoff curves were compared for a series of human PET scanners with a ring diameter of 83.5 cm and an axial FOV ranging from 22 cm to 220 cm. A series of mini-EXPLORER scanners with a ring diameter of 40 cm and axial FOV ranging from 11 cm to 110 cm was also examined and compared to the human scanners. A uniform cylinder (20 cm diameter and 220 cm long) was used to model the attenuation and background activity. The comparison showed that for imaging a single small ROI at the center of the axial FOV, the EXPLORER offers a 2.7-fold variance reduction over the 22-cm long scanner. For imaging an extended axial FOV of 110 cm, the EXPLORER provides a 30-fold variance reduction over the 22-cm long scanner and a 23 fold variance reduction over the 110-cm long scanner. These theoretical results clearly demonstrate the large possible improvement in image quality for extended FOV imaging and are consistent with our previous results obtained from reconstructions of Monte Carlo simulated human phantom data.
Xuezhu Zhang
University of California, Davis, USA
Ramsey D. Badawi
University of California, Davis, USA
Simon R. Cherry
University of California, Davis, USA
Jinyi Qi
University of California, Davis, USA
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