Standardization and Optimization of Siemens Biograph Truepoint Pet/Ct Acquisition and Reconstruction Parameters: Simultaneous Qualitative and Quantitative Assessments Publisher



Vosoughi H^{1, 2} ; Emami F³ ; Momennezhad M⁴ ; Geramifar P² ; Rahmim A⁵ Show Affiliations
Source: Iranian Journal of Nuclear Medicine Published:2024

Abstract

Introduction: Data acquisition and image reconstruction protocols affect image quality and quantification accuracy in PET imaging. We aimed to standardize and optimize image acquisition, and reconstruction parameter sets using a simultaneous quantitative and qualitative assessment framework for a lutetium oxyorthosilicate (LSO)-based PET/CT scanner. Methods: The NEMA IEC Body Phantom acquisition was performed in list mode for 10 minutes with four spheres to background ratios (SBRs). Raw PET data were reconstructed using 60 different protocols. Image quality was evaluated for standardization using contrast, CNR, and noise. Recovery coefficient (RC) measurements were performed for different common VOI definitions. Results: No significant differences were observed between RCs for various acquisition durations. The contrast to noise ratio (CNR) increased at all SBRs by expanding the acquisition duration from 60 to 600 seconds. PET scan time was reduced to 90 seconds per bed position while preserving image quality. Up to 50% improvement in CNR for the highest sub-iteration with a high level of smoothing was observed. PSF-based reconstruction produced a positive bias of RCmax in high SBRs (8 and 10) using higher sub-iterations (30 to 60) with Gaussian filters less than 6 mm FWHM. Moreover, a Sub-iteration of more than 32 with a 4-6 mm FWHM Gaussian filter provides optimized reconstruction sets. Conclusion: Our study demonstrates it would be feasible for PET image acquisition and reconstruction settings to simultaneously allow optimal lesion detection with high image quality while providing accurate quantification. Copyright © 2024 The Authors. Published by Tehran University of Medical Sciences. This work is published as an open access article distributed under the terms of the Creative Commons Attribution 4.0 License (http://creativecommons.org/licenses/by-nc/4). Non-commercial uses of the work are permitted, provided the original work is properly cited.