DOI QR코드

DOI QR Code

68Ga 표지 PET/CT 검사의 최적화된 매개변수에 대한 연구

Study of 68Ga Labelled PET/CT Scan Parameters Optimization

  • In Suk Kwak (Department of Nuclear Medicine, Samsung Medical Center) ;
  • Hyuk Lee (Department of Nuclear Medicine, Samsung Medical Center) ;
  • Si Hwal Kim (Department of Nuclear Medicine, Samsung Medical Center) ;
  • Seung Cheol Moon (GE Healthcare Korea)
  • 투고 : 2023.08.11
  • 심사 : 2023.09.19
  • 발행 : 2023.11.30

초록

Purpose: Gallium-68 (68Ga) is increasingly used in nuclear medicine imaging for various conditions such as lymphoma and neuroendocrine tumors by labeling tracers like Prostate Specific Membrane Antigen (PSMA) and DOTA-TOC. However, compared to Fluorine-18 (18F) used in conventional nuclear medicine imaging, 68Ga has lower spatial resolution and relatively higher Signal to Background Ratio (SBR). Therefore, this study aimed to investigate the optimized parameters and reconstruction methods for PET/CT imaging using the 68Ga radiotracer through model-based image evaluation. Materials and Methods: Based on clinical images of 68Ga-PSMA PET/CT, a NEMA/IEC 2008 PET phantom model was prepared with a Hot vs Background (H/B) ratio of 10:1. Images were acquired for 9 minutes in list mode using DMIDR (GE, Milwaukee WI, USA). Subsequently, reconstructions were performed for 1 to 8 minutes using OS-EM (Ordered Subset Expectation Maximization) + TOF (Time of Flight) + Sharp IR (VPFX-S), and BSREM (Block Sequential Regularized Expectation Maximization) + TOF + Sharp IR (QCFX-S-400), followed by comparative evaluation. Based on the previous experimental results, images were reconstructed for BSREM + TOF + Sharp IR / 2 minutes (QCFX-S-2min) with varying β-strength values from 100 to 700. The image quality was evaluated using AMIDE (freeware, Ver.1.0.1) and Advanced Workstation (GE, USA). Results: Images reconstructed with QCFX-S-400 showed relatively higher values for SNR (Signal to Noise Ratio), CNR (Contrast to Noise Ratio), count, RC (Recovery Coefficient), and SUV (Standardized Uptake Value) compared to VPFX-S. SNR, CNR, and SUV exhibited the highest values at 2 minutes/bed acquisition time. RC showed the highest values for a 10 mm sphere at 2 minutes/bed acquisition time. For small spheres of 10 mm and 13 mm, an inverse relationship between β-strength increase and count was observed. SNR and CNR peaked at β-strength 400 and then decreased, while SUV and RC exhibited a normal distribution based on sphere size for β-strength values of 400 and above. Conclusion: Based on the experiments, PET/CT imaging using the 68Ga radiotracer yielded the most favorable quantitative and qualitative results with a 2 minutes/bed acquisition time and BSREM reconstruction, particularly when applying β-strength 400. The application of BSREM can enhance accurate quantification and image quality in 68Ga PET/CT imaging, and an optimization process tailored to each institution's imaging objectives appears necessary.

키워드

참고문헌

  1. Kim IY, Lee YK, Ahn SM. Effect of Glucose Level on Brain FDG-PET Images. Journal of Radiological Science and Technology. 2017;40(2):275-80 https://doi.org/10.17946/JRST.2017.40.2.13
  2. Jeong JM, Kim YJ, Lee YS, Lee DS, Chung JK, Lee MC. Radiolabeling of NOTA and DOTA with Positron Emitting 68Ga and Investigation of in vitro properties. Nuclear Medicine and Molecular Imaging.2009;43(4):330-6
  3. YoonSH. Evaluation of PET Image for Fluorine-18 and Gallium-68 using Phantom in PET/CT. Journal of Radiological Science and Technology, 41(4):321-327
  4. ShinCM, LeeDS, KimYJ, SulAR, ChoiWJ, LeeWS. Ga-68 Prostate Specific Membrane Antigen-11 Positron Emission Tomography/Positron Emission Computed Tomography Ga-68 PSMA-11 PET/PET-CT (Ga-68 전립선특이막항원-11 양전자방출단층촬영/양전자방출전산화단층촬영Ga-68 PSMA-11 PET/PET-CT). New Medical Technology Assessment Report (신의료기술평가 보고서). 2021;1(63):1-328. KMID: 9000120210010630001.
  5. Ahn S, Ross SG, Asma E, Miao J, Jin X, Cheng L, et al. Quantitative comparison of OSEM and penalized likelihood image reconstruction using relative difference penalties for clinical PET. Phys Med Biol. 2015;60(15):5733
  6. Teoh EJ, McGowan DR, Macpherson RE, Bradley KM, Gleeson FV. Phantom and clinical evaluation of the Bayesian penalized likelihood reconstruction algorithm Q.Clear on an LYSO PET/CT system. J Nucl Med. 2015;56(9):1447-52 https://doi.org/10.2967/jnumed.115.159301
  7. Lindstrom E, Sundin A, Trampal C, Lindsjo L, Ilan E, Danfors T, et. al. Evaluation of penalized-likelihood estimation reconstruction on a digital time-of-flight PET/CT scanner for 18F-FDG whole-body examinations. J Nucl Med. 2018;59:1152-1158 https://doi.org/10.2967/jnumed.117.200790
  8. Boellaard R, van Lingen A, Lammertsma AA. Experimental and clinical evaluation of iterative reconstruction (OSEM) in dynamic PET: quantitative characteristics and effects on kinetic modeling. J Nucl Med. 2001;42(5):808-17
  9. Elin Lindstrom, Lars Lindsjo, Anders Sundin, Jens Sorensen and Mark Lubberink. Evaluation of block-sequential regularized expectation maximization reconstruction of 68Ga-DOTATOC, 18F-fluoride, and 11C-acetate whole-body examinations acquired on a digital time-of-flight PET/CT scanner. EJNMMI Physics. 2020 volume 7, Article number: 40. p. 1-2 https://doi.org/10.1186/s40658-020-00310-1
  10. Edwin E. G. W.ter Voert, Urs J. Muehlematter, Gaspar Delso, Daniele A.Pizzuto, Julian Muller, Hannes W. Nagel and Irene A. Burger, Quantitative performance and optimal regularization parameter in block sequential regularized expectation maximization reconstructions in clinical 68Ga-PSMA PET/MR. EJNMMI Research (2018) 8;70. p. 2
  11. Ahn S, Ross SG, Asma E, Miao J, Jin X, Cheng L, et al. Quantitative comparison of OSEM and penalized likelihood image reconstruction using relative difference penalties for clinical PET. Phys Med Biol. 2015;60(15):5733
  12. Lindstrom E, Sundin A, Trampal C, Lindsjo L, Ilan E, Danfors T, et. al. Evaluation of penalized-likelihood estimation reconstruction on a digital time-of-flight PET/CT scanner for 18F-FDG whole-body examinations. J Nucl Med. 2018;59:1152-1158 https://doi.org/10.2967/jnumed.117.200790
  13. Nuyts J, Beque D, Dupont P, Mortelmans L. A concave prior penalizing relative differences for maximum-a-posteriori reconstruction in emission tomography. IEEE Trans Nucl Sci. 2002;49:56-60 https://doi.org/10.1109/TNS.2002.998681
  14. Nuyts J, Fessler JA. A penalized-likelihood image reconstruction method for emission tomography, compared to post smoothed maximum-likelihood with matched spatial resolution. IEEE Trans Med Imaging. 2003;22:1042-52 https://doi.org/10.1109/TMI.2003.816960
  15. De Pierro AR, Yamagishi MEB. Fast EM-like methods for maximum 'a posteriori' estimates in emission tomography. IEEE Trans Med Imaging. 2001;20:280-8 https://doi.org/10.1109/42.921477
  16. Ross S. Q.Clear white paper. Chicago, IL; GE Healthcare; 2013. Accessed Oct. 19, 2017.
  17. Ahn S, Fessler JA. Globally convergent image reconstruction for emission tomography using relaxed ordered subsets algorithm. IEEE Trans Med Imaging. 2003;22:613-26 https://doi.org/10.1109/TMI.2003.812251
  18. Eugene J. Teoh, Daniel R. McGowan, Ruth E. Macpherson, Kevin M. Bradley, and Fergus V. Gleeson. Phantom and Clinical Evaluation of the Bayesian Penalized Likelihood Reconstruction Algorithm Q.Clear on an LYSO PET/CT System. J Nucl Med. 2015; 56:1447-1452
  19. Wolfgang P. Fendler, Matthias Eiber, Mohsen Beheshti, Jamshed Bomanji, Francesco Ceci, Steven Cho, Frederik Giesel, Uwe Haberkorn, Thomas A. Hope, Klaus Kopka, Bernd J. Krause, Felix M. Mottaghy, Heiko Schoder, John Sunderland, Simon Wan, Hans-Jurgen Wester, Stefano Fanti, Ken Herrmann. 68Ga-PSMA PET/CT: Joint EANM and SNMMI procedure guideline for prostate cancer imaging: version 1.0. Eur J Nucl Med Mol Imaging. (2017) 44:1014-1024. DOI 10.1007/s00259-017-3670-z
  20. Habibollah Dadgar, Manouchehr Seyedi Vafaee, Nasim Norouzbeigi, Esmail Jafari, Ali Gholamrezanezhad and Majid Assadi. Dual-phase 68Ga-PSMA-11 PET/CT may increase the rate of detected lesions in prostate cancer patients. Urologia Journal. 2021, Vol. 88(4) 355-361 https://doi.org/10.1177/0391560321993544
  21. Eugene J. Teoh, Daniel R. McGowan, Kevin M. Bradley, Elizabeth Belcher, Edward Black, Fergus V. Gleeson. Novel penalised likelihood reconstruction of PET in the assessment of histologically verified small pulmonary nodules. Eur Radiol (2016) 26:576-584 https://doi.org/10.1007/s00330-015-3832-y
  22. Elin Lindstrom, Irina Velikyan, Naresh Regula, Ali Alhuseinalkhudhur, Anders Sundin, Jens Sorensen, Mark Lubberink. Regularized reconstruction of digital time-of-flight 68Ga-PSMA-11 PET/CT for the detection of recurrent disease in prostate cancer patients. Theranostics. 2019;9(12): 3476-3484. doi: 10.7150/thno.31970
  23. Daphne M. V. Huizing1, Danielle Koopman2, Jorn A. van Dalen3, Martin Gotthardt4, Ronald Boellaard5,6,7,Terez Sera7, Michiel Sinaasappel8, Marcel P. M. Stokkel1 and Berlinda J. de Wit-van der Veen. Multicentre quantitative 68Ga PET/CT performance harmonization. EJNMMI Physics (2019) volume 6, Article number: 19, p. 4