Youngho Seo1,2,3,4, Mohammad Mehdi Khalighi5,6, Kristen A Wangerin5, Timothy W Deller5, Yung-Hua Wang5, Salma Jivan7, Maureen P Kohi7, Rahul Aggarwal8, Robert R Flavell7,9, Spencer C Behr7, Michael J Evans7,9. 1. Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, 94143-0946, USA. Youngho.Seo@ucsf.edu. 2. Department of Radiation Oncology, University of California, San Francisco, CA, USA. Youngho.Seo@ucsf.edu. 3. UC Berkeley - UCSF Graduate Program in Bioengineering, University of California, Berkeley and San Francisco, California, CA, USA. Youngho.Seo@ucsf.edu. 4. Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA. Youngho.Seo@ucsf.edu. 5. GE Healthcare, Waukesha, WI, USA. 6. Department of Radiology, Stanford University, Stanford, CA, USA. 7. Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, 94143-0946, USA. 8. Division of Hematology and Oncology, Department of Medicine, University of California, San Francisco, CA, USA. 9. Department of Pharmaceutical Chemistry, University of California, San Francisco, CA, USA.
Abstract
PURPOSE: There are several important positron emission tomography (PET) imaging scenarios that require imaging with very low photon statistics, for which both quantitative accuracy and visual quality should not be neglected. For example, PET imaging with the low photon statistics is closely related to active efforts to significantly reduce radiation exposure from radiopharmaceuticals. We investigated two examples of low-count PET imaging: (a) imaging [90Y]microsphere radioembolization that suffers the very small positron emission fraction of Y-90's decay processes, and (b) cancer imaging with [68Ga]citrate with uptake time of 3-4 half-lives, necessary for visualizing tumors. In particular, we investigated a type of penalized likelihood reconstruction algorithm, block sequential regularized expectation maximization (BSREM), for improving both image quality and quantitative accuracy of these low-count PET imaging cases. PROCEDURES: The NEMA/IEC Body phantom filled with aqueous solution of Y-90 or Ga-68 was scanned to mimic the low-count scenarios of corresponding patient data acquisitions on a time-of-flight (TOF) PET/magnetic resonance imaging system. Contrast recovery, background variation, and signal-to-noise ratio were evaluated in different sets of count densities using both conventional TOF ordered subset expectation (TOF-OSEM) and TOF-BSREM algorithms. The regularization parameter, beta, in BSREM that controls the tradeoff between image noise and resolution was evaluated to find a value for improved confidence in image interpretation. Visual quality assessment of the images obtained from patients administered with [68Ga]citrate (n = 6) was performed. We also made preliminary visual image quality assessment for one patient with [90Y]microspheres. In Y-90 imaging, the effect of 511-keV energy window selection for minimizing the number of random events was also evaluated. RESULTS: Quantitatively, phantom images reconstructed with TOF-BSREM showed improved contrast recovery, background variation, and signal-to-noise ratio values over images reconstructed with TOF-OSEM. Both phantom and patient studies of delayed imaging of [68Ga]citrate show that TOF-BSREM with beta = 500 gives the best tradeoff between image noise and image resolution based on visual assessment by the readers. The NEMA-IQ phantom study with [90Y]microspheres shows that the narrow energy window (460-562 keV) recovers activity concentrations in small spheres better than the regular energy window (425-650 keV) with the beta value of 2000 using the TOF-BSREM algorithm. For the images obtained from patients with [68Ga]citrate using TOF-BSREM with beta = 500, the visual analogue scale (VAS) was improved by 17 % and the Likert score was increased by 1 point on average, both in comparison to corresponding scores for images reconstructed using TOF-OSEM. CONCLUSION: Our investigation shows that the TOF-BSREM algorithm improves the image quality and quantitative accuracy in low-count PET imaging scenarios. However, the beta value in this algorithm needed to be adjusted for each radiopharmaceutical and counting statistics at the time of scans.
PURPOSE: There are several important positron emission tomography (PET) imaging scenarios that require imaging with very low photon statistics, for which both quantitative accuracy and visual quality should not be neglected. For example, PET imaging with the low photon statistics is closely related to active efforts to significantly reduce radiation exposure from radiopharmaceuticals. We investigated two examples of low-count PET imaging: (a) imaging [90Y]microsphere radioembolization that suffers the very small positron emission fraction of Y-90's decay processes, and (b) cancer imaging with [68Ga]citrate with uptake time of 3-4 half-lives, necessary for visualizing tumors. In particular, we investigated a type of penalized likelihood reconstruction algorithm, block sequential regularized expectation maximization (BSREM), for improving both image quality and quantitative accuracy of these low-count PET imaging cases. PROCEDURES: The NEMA/IEC Body phantom filled with aqueous solution of Y-90 or Ga-68 was scanned to mimic the low-count scenarios of corresponding patient data acquisitions on a time-of-flight (TOF) PET/magnetic resonance imaging system. Contrast recovery, background variation, and signal-to-noise ratio were evaluated in different sets of count densities using both conventional TOF ordered subset expectation (TOF-OSEM) and TOF-BSREM algorithms. The regularization parameter, beta, in BSREM that controls the tradeoff between image noise and resolution was evaluated to find a value for improved confidence in image interpretation. Visual quality assessment of the images obtained from patients administered with [68Ga]citrate (n = 6) was performed. We also made preliminary visual image quality assessment for one patient with [90Y]microspheres. In Y-90 imaging, the effect of 511-keV energy window selection for minimizing the number of random events was also evaluated. RESULTS: Quantitatively, phantom images reconstructed with TOF-BSREM showed improved contrast recovery, background variation, and signal-to-noise ratio values over images reconstructed with TOF-OSEM. Both phantom and patient studies of delayed imaging of [68Ga]citrate show that TOF-BSREM with beta = 500 gives the best tradeoff between image noise and image resolution based on visual assessment by the readers. The NEMA-IQ phantom study with [90Y]microspheres shows that the narrow energy window (460-562 keV) recovers activity concentrations in small spheres better than the regular energy window (425-650 keV) with the beta value of 2000 using the TOF-BSREM algorithm. For the images obtained from patients with [68Ga]citrate using TOF-BSREM with beta = 500, the visual analogue scale (VAS) was improved by 17 % and the Likert score was increased by 1 point on average, both in comparison to corresponding scores for images reconstructed using TOF-OSEM. CONCLUSION: Our investigation shows that the TOF-BSREM algorithm improves the image quality and quantitative accuracy in low-count PET imaging scenarios. However, the beta value in this algorithm needed to be adjusted for each radiopharmaceutical and counting statistics at the time of scans.
Authors: Sangtae Ahn; Steven G Ross; Evren Asma; Jun Miao; Xiao Jin; Lishui Cheng; Scott D Wollenweber; Ravindra M Manjeshwar Journal: Phys Med Biol Date: 2015-07-09 Impact factor: 3.609
Authors: Konstantinos G Zeimpekis; Felipe Barbosa; Martin Hüllner; Edwin ter Voert; Helen Davison; Patrick Veit-Haibach; Gaspar Delso Journal: Mol Imaging Biol Date: 2015-10 Impact factor: 3.488
Authors: Ferdinand Seith; Holger Schmidt; Julia Kunz; Thomas Küstner; Sergios Gatidis; Konstantin Nikolaou; Christian la Fougère; Nina Schwenzer Journal: J Nucl Med Date: 2017-03-30 Impact factor: 10.057
Authors: Bert-Ram Sah; Paul Stolzmann; Gaspar Delso; Scott D Wollenweber; Martin Hüllner; Yahya A Hakami; Marcelo A Queiroz; Felipe de Galiza Barbosa; Gustav K von Schulthess; Carsten Pietsch; Patrick Veit-Haibach Journal: Nucl Med Commun Date: 2017-01 Impact factor: 1.690
Authors: Stefan Wampl; Ivo Rausch; Tatjana Traub-Weidinger; Thomas Beyer; Martin Gröschl; Jacobo Cal-González Journal: Eur J Radiol Date: 2017-08-26 Impact factor: 3.528
Authors: M D Walker; M-C Asselin; P J Julyan; M Feldmann; P S Talbot; T Jones; J C Matthews Journal: Phys Med Biol Date: 2011-01-20 Impact factor: 3.609
Authors: Edwin E G W Ter Voert; Urs J Muehlematter; Gaspar Delso; Daniele A Pizzuto; Julian Müller; Hannes W Nagel; Irene A Burger Journal: EJNMMI Res Date: 2018-07-27 Impact factor: 3.138
Authors: Julian M M Rogasch; Ronald Boellaard; Lucy Pike; Peter Borchmann; Peter Johnson; Jürgen Wolf; Sally F Barrington; Carsten Kobe Journal: Eur J Nucl Med Mol Imaging Date: 2021-05-14 Impact factor: 9.236
Authors: Nicolas Aide; Charline Lasnon; Adam Kesner; Craig S Levin; Irene Buvat; Andrei Iagaru; Ken Hermann; Ramsey D Badawi; Simon R Cherry; Kevin M Bradley; Daniel R McGowan Journal: Eur J Nucl Med Mol Imaging Date: 2021-06-03 Impact factor: 9.236