Dataset Information

Improved image reconstruction of ⁸⁹Zr-immunoPET studies using a Bayesian penalized likelihood reconstruction algorithm.

ABSTRACT:

Purpose

The aim of this study was to evaluate the use of a Bayesian penalized likelihood reconstruction algorithm (Q.Clear) for ⁸⁹Zr-immunoPET image reconstruction and its potential to improve image quality and reduce the administered activity of ⁸⁹Zr-immunoPET tracers.

Methods

Eight ⁸⁹Zr-immunoPET whole-body PET/CT scans from three ⁸⁹Zr-immunoPET clinical trials were selected for analysis. On average, patients were imaged 6.3?days (range 5.0-8.0?days) after administration of 69?MBq (range 65-76?MBq) of [⁸⁹Zr]Zr-DFO-daratumumab, [⁸⁹Zr]Zr-DFO-pertuzumab, or [⁸⁹Zr]Zr-DFO-trastuzumab. List-mode PET data was retrospectively reconstructed using Q.Clear with incremental ?-values from 150 to 7200, as well as standard ordered-subset expectation maximization (OSEM) reconstruction (2-iterations, 16-subsets, a 6.4-mm Gaussian transaxial filter, "heavy" z-axis filtering and all manufacturers' corrections active). Reduced activities were simulated by discarding 50% and 75% of original counts in each list mode stream. All reconstructed PET images were scored for image quality and lesion detectability using a 5-point scale. SUV_max for normal liver and sites of disease and liver signal-to-noise ratio were measured.

Results

Q.Clear reconstructions with ? = 3600 provided the highest scores for image quality. Images reconstructed with ?-values of 3600 or 5200 using only 50% or 25% of the original counts provided comparable or better image quality scores than standard OSEM reconstruction images using 100% of counts.

Conclusion

The Bayesian penalized likelihood reconstruction algorithm Q.Clear improved the quality of ⁸⁹Zr-immunoPET images. This could be used in future studies to improve image quality and/or decrease the administered activity of ⁸⁹Zr-immunoPET tracers.

SUBMITTER: Kirchner J

PROVIDER: S-EPMC7815860 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Publications

Improved image reconstruction of <sup>89</sup>Zr-immunoPET studies using a Bayesian penalized likelihood reconstruction algorithm.

Kirchner Julian J O'Donoghue Joseph A JA Becker Anton S AS Ulaner Gary A GA

EJNMMI physics 20210119 1

<h4>Purpose</h4>The aim of this study was to evaluate the use of a Bayesian penalized likelihood reconstruction algorithm (Q.Clear) for <sup>89</sup>Zr-immunoPET image reconstruction and its potential to improve image quality and reduce the administered activity of <sup>89</sup>Zr-immunoPET tracers.<h4>Methods</h4>Eight <sup>89</sup>Zr-immunoPET whole-body PET/CT scans from three <sup>89</sup>Zr-immunoPET clinical trials were selected for analysis. On average, patients were imaged 6.3 days (rang ...[more]

PMID: 33469848

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