Alexandre Chicheportiche1, Elinor Goshen2, Jeremy Godefroy3, Simona Grozinsky-Glasberg4, Kira Oleinikov4, Amichay Meirovitz5, David J Gross4, Simona Ben-Haim3,6,7. 1. Department of Nuclear Medicine & Biophysics, Hadassah-Hebrew University Medical Center, 91120, Jerusalem, Israel. alexandre@hadassah.org.il. 2. Department of Nuclear Medicine, Wolfson Medical Center, 58100, Holon, Israel. 3. Department of Nuclear Medicine & Biophysics, Hadassah-Hebrew University Medical Center, 91120, Jerusalem, Israel. 4. Neuroendocrine Tumor Unit, ENETS Center of Excellence, Endocrinology and Metabolism Department, Hadassah-Hebrew University Medical Center, 91120, Jerusalem, Israel. 5. Oncology Department and Radiation Therapy Unit, Hadassah-Hebrew University Medical Center, 91120, Jerusalem, Israel. 6. Faculty of Medicine, Hebrew University of Jerusalem, 91120, Jerusalem, Israel. 7. Institute of Nuclear Medicine, University College London and UCL Hospitals NHS Trust, London, UK.
Abstract
BACKGROUND: Image quality and quantitative accuracy of positron emission tomography (PET) depend on several factors such as uptake time, scanner characteristics and image reconstruction methods. Ordered subset expectation maximization (OSEM) is considered the gold standard for image reconstruction. Penalized-likelihood estimation (PL) algorithms have been recently developed for PET reconstruction to improve quantitation accuracy while maintaining or even improving image quality. In PL algorithms, a regularization parameter β controls the penalization of relative differences between neighboring pixels and determines image characteristics. In the present study, we aim to compare the performance of Q.Clear (PL algorithm, GE Healthcare) and OSEM (3 iterations, 8 subsets, 6-mm post-processing filter) for 68Ga-DOTATATE (68Ga-DOTA) PET studies, both visually and quantitatively. Thirty consecutive whole-body 68Ga-DOTA studies were included. The data were acquired in list mode and were reconstructed using 3D OSEM and Q.Clear with various values of β and various acquisition times per bed position (bp), thus generating images with reduced injected dose (1.5 min/bp: β = 300-1100; 1.0 min/bp: β = 600-1400 and 0.5 min/bp: β = 800-2200). An additional analysis adding β values up to 1500, 1700 and 3000 for 1.5, 1.0 and 0.5 min/bp, respectively, was performed for a random sample of 8 studies. Evaluation was performed using a phantom and clinical data. Two experienced nuclear medicine physicians blinded to the variables assessed the image quality visually. RESULTS: Clinical images reconstructed with Q.Clear, set at 1.5, 1.0 and 0.5 min/bp using β = 1100, 1300 and 3000, respectively, resulted in images with noise equivalence to 3D OSEM (1.5 min/bp) with a mean increase in SUVmax of 14%, 13% and 4%, an increase in SNR of 30%, 24% and 10%, and an increase in SBR of 13%, 13% and 2%. Visual assessment yielded similar results for β values of 1100-1400 and 1300-1600 for 1.5 and 1.0 min/bp, respectively, although for 0.5 min/bp there was no significant improvement compared to OSEM. CONCLUSION: 68Ga-DOTA reconstructions with Q.Clear, 1.5 and 1.0 min/bp, resulted in increased tumor SUVmax and in improved SNR and SBR at a similar level of noise compared to 3D OSEM. Q.Clear with β = 1300-1600 enables one-third reduction of acquisition time or injected dose, with similar image quality compared to 3D OSEM.
BACKGROUND: Image quality and quantitative accuracy of positron emission tomography (PET) depend on several factors such as uptake time, scanner characteristics and image reconstruction methods. Ordered subset expectation maximization (OSEM) is considered the gold standard for image reconstruction. Penalized-likelihood estimation (PL) algorithms have been recently developed for PET reconstruction to improve quantitation accuracy while maintaining or even improving image quality. In PL algorithms, a regularization parameter β controls the penalization of relative differences between neighboring pixels and determines image characteristics. In the present study, we aim to compare the performance of Q.Clear (PL algorithm, GE Healthcare) and OSEM (3 iterations, 8 subsets, 6-mm post-processing filter) for 68Ga-DOTATATE (68Ga-DOTA) PET studies, both visually and quantitatively. Thirty consecutive whole-body 68Ga-DOTA studies were included. The data were acquired in list mode and were reconstructed using 3D OSEM and Q.Clear with various values of β and various acquisition times per bed position (bp), thus generating images with reduced injected dose (1.5 min/bp: β = 300-1100; 1.0 min/bp: β = 600-1400 and 0.5 min/bp: β = 800-2200). An additional analysis adding β values up to 1500, 1700 and 3000 for 1.5, 1.0 and 0.5 min/bp, respectively, was performed for a random sample of 8 studies. Evaluation was performed using a phantom and clinical data. Two experienced nuclear medicine physicians blinded to the variables assessed the image quality visually. RESULTS: Clinical images reconstructed with Q.Clear, set at 1.5, 1.0 and 0.5 min/bp using β = 1100, 1300 and 3000, respectively, resulted in images with noise equivalence to 3D OSEM (1.5 min/bp) with a mean increase in SUVmax of 14%, 13% and 4%, an increase in SNR of 30%, 24% and 10%, and an increase in SBR of 13%, 13% and 2%. Visual assessment yielded similar results for β values of 1100-1400 and 1300-1600 for 1.5 and 1.0 min/bp, respectively, although for 0.5 min/bp there was no significant improvement compared to OSEM. CONCLUSION:68Ga-DOTA reconstructions with Q.Clear, 1.5 and 1.0 min/bp, resulted in increased tumor SUVmax and in improved SNR and SBR at a similar level of noise compared to 3D OSEM. Q.Clear with β = 1300-1600 enables one-third reduction of acquisition time or injected dose, with similar image quality compared to 3D OSEM.
Entities:
Keywords:
68Ga-DOTATATE; Image quality; Q.Clear reconstruction; Reduced acquisition time or injected dose; Visual evaluation
Authors: Julian M M Rogasch; Frank Hofheinz; Lutz van Heek; Conrad-Amadeus Voltin; Ronald Boellaard; Carsten Kobe Journal: Diagnostics (Basel) Date: 2022-02-10
Authors: Abolfazl Mehranian; Scott D Wollenweber; Matthew D Walker; Kevin M Bradley; Patrick A Fielding; Kuan-Hao Su; Robert Johnsen; Fotis Kotasidis; Floris P Jansen; Daniel R McGowan Journal: Eur J Nucl Med Mol Imaging Date: 2021-07-28 Impact factor: 9.236