4.3 Article

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

Journal

EJNMMI PHYSICS
Volume 8, Issue 1, Pages -

Publisher

SPRINGER
DOI: 10.1186/s40658-021-00352-z

Keywords

Zr-89-immunoPET; Reconstruction algorithms; Q.Clear; BSREM; OSEM

Funding

  1. Department of Defense Breast Cancer Research Program Breakthrough Award [BC132676]
  2. Leukemia & Lymphoma Society [RTF6004-19]
  3. National Institutes of Health (NIH) [R01 CA204167]
  4. Memorial Sloan Kettering Cancer Center Radiochemistry and Molecular Imaging Probe Core (NIH) [P30 CA08748]

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The Bayesian penalized likelihood reconstruction algorithm Q.Clear improved the quality of Zr-89-immunoPET images, offering potential for future studies to enhance image quality and/or decrease the administered activity of Zr-89-immunoPET tracers.
Purpose The aim of this study was to evaluate the use of a Bayesian penalized likelihood reconstruction algorithm (Q.Clear) for Zr-89-immunoPET image reconstruction and its potential to improve image quality and reduce the administered activity of Zr-89-immunoPET tracers. Methods Eight Zr-89-immunoPET whole-body PET/CT scans from three Zr-89-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 [Zr-89]Zr-DFO-daratumumab, [Zr-89]Zr-DFO-pertuzumab, or [Zr-89]Zr-DFO-trastuzumab. List-mode PET data was retrospectively reconstructed using Q.Clear with incremental beta-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. SUVmax for normal liver and sites of disease and liver signal-to-noise ratio were measured. Results Q.Clear reconstructions with beta = 3600 provided the highest scores for image quality. Images reconstructed with beta-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 Zr-89-immunoPET images. This could be used in future studies to improve image quality and/or decrease the administered activity of Zr-89-immunoPET tracers.

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