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Research ArticleBrief Communication

Optimization of 89Zr PET Imaging for Improved Multisite Quantification and Lesion Detection Using an Anthropomorphic Phantom

Paul E. Christian, Simon-Peter Williams, Lance Burrell, Paulo Castaneda, Justin Albiani, Nicholas Sandella, Andrei Iagaru, John M. Hoffman, Alex de Crespigny and Sandra Sanabria Bohorquez
Journal of Nuclear Medicine Technology March 2020, 48 (1) 54-57; DOI: https://doi.org/10.2967/jnmt.119.230474
Paul E. Christian
1Genentech, Inc., South San Francisco, California
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Simon-Peter Williams
1Genentech, Inc., South San Francisco, California
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Lance Burrell
2Center for Quantitative Cancer Imaging, Huntsman Cancer Institute, University of Utah School of Medicine, Salt Lake City, Utah
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Paulo Castaneda
3Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Stanford University, Palo Alto, California; and
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Justin Albiani
4Invicro, Boston, Massachusetts
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Nicholas Sandella
4Invicro, Boston, Massachusetts
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Andrei Iagaru
3Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Stanford University, Palo Alto, California; and
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John M. Hoffman
2Center for Quantitative Cancer Imaging, Huntsman Cancer Institute, University of Utah School of Medicine, Salt Lake City, Utah
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Alex de Crespigny
1Genentech, Inc., South San Francisco, California
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Sandra Sanabria Bohorquez
1Genentech, Inc., South San Francisco, California
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Abstract

Our objective was to harmonize multicenter 89Zr PET imaging for oncology trials and to evaluate lesion detection. Methods: Seven PET scanners were evaluated using a custom chest oncology phantom with 9 spheric lesions 7–20 mm in diameter. A 4:1 signal-to-background ratio simulated a patient dose of 92.5 MBq. Various image reconstructions were evaluated. Images were assessed for lesion detection, and recovery coefficients and background signal variance were measured. Results: Two scanners failed to provide acceptable images and data. Optimal reconstruction algorithms enabling adequate lesion detection and reliable quantification across the other 5 scanners were determined without compromising the data quality. On average, 95% of the 10-mm lesions were detected, and the 7-mm lesion was visualized by only 1 scanner. Background variance was 8.6%–16%. Conclusion: We established multicenter harmonization procedures for 89Zr PET imaging in oncology, optimizing small-lesion (≥10 mm) detectability and accurate quantification.

  • scanner harmonization
  • scanner validation
  • 89Zr PET imaging

Footnotes

  • Published online Oct. 11, 2019.

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Journal of Nuclear Medicine Technology: 48 (1)
Journal of Nuclear Medicine Technology
Vol. 48, Issue 1
March 1, 2020
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Optimization of 89Zr PET Imaging for Improved Multisite Quantification and Lesion Detection Using an Anthropomorphic Phantom
Paul E. Christian, Simon-Peter Williams, Lance Burrell, Paulo Castaneda, Justin Albiani, Nicholas Sandella, Andrei Iagaru, John M. Hoffman, Alex de Crespigny, Sandra Sanabria Bohorquez
Journal of Nuclear Medicine Technology Mar 2020, 48 (1) 54-57; DOI: 10.2967/jnmt.119.230474

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Optimization of 89Zr PET Imaging for Improved Multisite Quantification and Lesion Detection Using an Anthropomorphic Phantom
Paul E. Christian, Simon-Peter Williams, Lance Burrell, Paulo Castaneda, Justin Albiani, Nicholas Sandella, Andrei Iagaru, John M. Hoffman, Alex de Crespigny, Sandra Sanabria Bohorquez
Journal of Nuclear Medicine Technology Mar 2020, 48 (1) 54-57; DOI: 10.2967/jnmt.119.230474
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Keywords

  • Scanner harmonization
  • Scanner validation
  • 89Zr PET imaging
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