Experimental approach for optimizing dose regimen of ⁶⁸Ga-DOTATATE PET/CT for neuroendocrine tumor (NET) imaging in current high sensitivity scanners: Phantom and Patient Study

Abstract

Aim

This study aimed to determine the optimized scan time and injected activity regimen for clinical ⁶⁸Ga DOTATATE PET/CT in neuroendocrine tumor imaging through an experimental approach without using machine learning techniques.

Methods

A NEMA PET body phantom was used with Ga-⁶⁸ to simulate a 9:1 sphere-to-background ratio. PET data were acquired on a high-sensitivity scanner at various scan times (15–300 s/bed). For each scan time, coefficient of variation (COV) and contrast-to-noise ratio (CNR) were calculated. The minimum scan time (T_min) needed to meet the Rose Criterion (CNR > 5) for the smallest sphere was identified. This T_min was then applied to patient scans with neuroendocrine tumors (originally acquired at 120 s/bed) to evaluate image quality and determine an optimized activity regimen for clinical ⁶⁸Ga-DOTATATE PET imaging.

Results

Phantom experiments showed that a COV_max of 20% is the highest acceptable noise level for detecting the smallest lesions, corresponding to a minimum scan time of about 1 minute per bed position. Patient image analysis confirmed that all tumors visible at routine scan times were still detectable at this minimum duration. This supports the use of a lower activity regimen (~1 MBq/kg), which can reduce patient radiation exposure compared to the standard 1.85 MBq/kg protocol.

Conclusion

This work demonstrated that scan time and activity for ⁶⁸Ga-DOTATATE NET imaging can be significantly minimized without compromising image interpretation and quantification.

Keywords

Ga-68-DOTATATE - Neuroendocrine tumors - PET/CT - injected dose optimization

• References

• 1 Gultekin MA, Turk HM, Yurtsever I. et al. Apparent Diffusion Coefficient Values for Neuroendocrine Liver Metastases. Acad Radiol 2021; 28: S81-S86
• 2 Cox CPW, Segbers M, Graven LH. et al. Standardized image quality for ⁶⁸Ga-DOTA-TATE PET/CT. EJNMMI Res 2020; 10: 27
• 3 Oronsky B, Ma PC, Morgensztern D. et al. Nothing But NET: A Review of Neuroendocrine Tumors and Carcinomas. Neoplasia 2017; 19: 991-1002
• 4 Haug A, Auernhammer CJ, Wängler B. et al. Intraindividual comparison of ⁶⁸Ga-DOTA-TATE and ¹⁸F-DOPA PET in patients with well-differentiated metastatic neuroendocrine tumours. Eur J Nucl Med Mol Imaging 2009; 36: 765-770
• 5 Fallahi B, Manafi-Farid R, Eftekhari M. et al. Diagnostic efficiency of ⁶⁸Ga-DOTATATE PET/CT as compared to ^99mTc-Octreotide SPECT/CT and conventional morphologic modalities in neuroendocrine tumors. Asia Ocean J Nucl Med Biol 2019; 7
• 6 Geijer H, Breimer LH. Somatostatin receptor PET/CT in neuroendocrine tumours: update on systematic review and meta-analysis. Eur J Nucl Med Mol Imaging 2013; 40: 1770-1780
• 7 Ragab A, Wu J, Ding X. et al. ⁶⁸Ga-DOTATATE PET/CT: The Optimum Standardized Uptake Value (SUV) Internal Reference. Acad Radiol 2022; 29: 95-106
• 8 Saade C, Ammous A, Abi-Ghanem AS. et al. Body Weight-Based Protocols During Whole Body FDG PET/CT Significantly Reduces Radiation Dose without Compromising Image Quality:Findings in a Large Cohort Study. Acad Radiol 2019; 26: 658-663
• 9 Xiao J, Yu H, Sui X. et al. A personal acquisition time regimen of ⁶⁸Ga-DOTATATE total-body PET/CT in patients with neuroendocrine tumor (NET): a feasibility study. Cancer Imaging 2022; 22: 78
• 10 Al-Fatlawi M, Pak F, Farzanefar S. et al. Optimization of the Acquisition Time and Injected Dose of ¹⁸F-Fluorodeoxyglucose Based on Patient Specifications for High-Sensitive Positron Emission Tomography/Computed Tomography Scanner. World J Nucl Med 2023; 22: 196-202
• 11 Task Group of Committee 3 of the International Commission on Radiological Protection, Hrsg. Protection of the patient in nuclear medicine. Oxford: Pergamon Pr; 1987
• 12 Bozkurt MF, Virgolini I, Balogova S. et al. Guideline for PET/CT imaging of neuroendocrine neoplasms with 68Ga-DOTA-conjugated somatostatin receptor targeting peptides and ¹⁸F–DOPA. Eur J Nucl Med Mol Imaging 2017; 44: 1588-1601
• 13 Wielaard J, Habraken JBA, Brinks P. et al. Optimization of injected ⁶⁸Ga-PSMA activity based on list-mode phantom data and clinical validation. EJNMMI Phys 2020; 7: 20
• 14 Koopman D, Van Osch JAC, Jager PL. et al. Technical note: how to determine the FDG activity for tumour PET imaging that satisfies European guidelines. EJNMMI Phys 2016; 3: 22
• 15 Pain CD, Egan GF, Chen Z. Deep learning-based image reconstruction and post-processing methods in positron emission tomography for low-dose imaging and resolution enhancement. Eur J Nucl Med Mol Imaging 2022; 49: 3098-3118
• 16 Weyts K, Lasnon C, Ciappuccini R. et al. Artificial intelligence-based PET denoising could allow a two-fold reduction in [¹⁸F]FDG PET acquisition time in digital PET/CT. Eur J Nucl Med Mol Imaging 2022; 49: 3750-3760
• 17 Bonardel G, Dupont A, Decazes P. et al. Clinical and phantom validation of a deep learning based denoising algorithm for F-18-FDG PET images from lower detection counting in comparison with the standard acquisition. EJNMMI Phys 2022; 9: 36
• 18 Reynés-Llompart G, Gámez-Cenzano C, Romero-Zayas I. et al. Performance Characteristics of the Whole-Body Discovery IQ PET/CT System. J Nucl Med 2017; 58: 1155-1161
• 19 National Electrical Manufacturers Association. NEMA Standards Publication NU 2–2018: Performance Measurements of Positron Emission Tomographs. 2018
• 20 Monsef A, Ay MR, Sheikhzadeh P. et al. Harmonization based on quantitative analysis of standardized uptake value variations across PET/CT scanners: a multicenter phantom study. Nucl Med Commun 2022; 43: 1004-1014
• 21 Te Riet J, Rijnsdorp S, Roef MJ. et al. Evaluation of a Bayesian penalized likelihood reconstruction algorithm for low-count clinical ¹⁸F-FDG PET/CT. EJNMMI Phys 2019; 6: 32
• 22 Sadeghi F, Sheikhzadeh P, Farzanehfar S. et al. The effects of various penalty parameter values in Q.Clear algorithm for rectal cancer detection on ¹⁸F-FDG images using a BGO-based PET/CT scanner: a phantom and clinical study. EJNMMI Phys 2023; 10: 63
• 23 Sadeghi F, Sheikhzadeh P, Kasraie N. et al. Phantom and clinical evaluation of Block Sequential Regularized Expectation Maximization (BSREM) reconstruction algorithm in ⁶⁸Ga-PSMA PET-CT studies. Phys Eng Sci Med 2023; 46: 1297-1308
• 24 Burgess AE. The Rose model, revisited. J Opt Soc Am A 1999; 16: 633
• 25 Byrd D, Doot R, Allberg K. et al. Evaluation of Cross-Calibrated ⁶⁸Ge/⁶⁸Ga Phantoms for Assessing PET/CT Measurement Bias in Oncology Imaging for Single- and Multicenter Trials. Tomography 2016; 2: 353-360
• 26 Huizing DMV, Koopman D, Van Dalen JA. et al. Multicentre quantitative ⁶⁸Ga PET/CT performance harmonisation. EJNMMI Phys 2019; 6: 19
• 27 Prager EM, Chambers KE, Plotkin JL. et al. Improving transparency and scientific rigor in academic publishing. Brain Behav 2019; 9: e01141
• 28 World Medical Association Declaration of Helsinki. Ethical Principles for Medical Research Involving Human Subjects. JAMA 2013; 310: 2191
• 29 Jönsson L, Stenvall A, Mattsson E. et al. Quantitative analysis of phantom studies of 111In and 68Ga imaging of neuroendocrine tumours. EJNMMI Phys 2018; 5: 5
• 30 Seyyedi N, Ghafari A, Seyyedi N. et al. Deep learning-based techniques for estimating high-quality full-dose positron emission tomography images from low-dose scans: a systematic review. BMC Med Imaging 2024; 24: 238
• 31 De Groot EH, Post N, Boellaard R. et al. Optimized dose regimen for whole-body FDG-PET imaging. EJNMMI Res 2013; 3: 63