Can a penalized-likelihood estimation algorithm be used to reduce the injected dose or the acquisition time in 68Ga-DOTATATE PET/CT studies?
نویسندگان
چکیده
Abstract Background Image quality and quantitative accuracy of positron emission tomography (PET) depend on several factors such as uptake time, scanner characteristics image reconstruction methods. Ordered subset expectation maximization (OSEM) is considered the gold standard for reconstruction. Penalized-likelihood estimation (PL) algorithms have been recently developed PET to improve quantitation while maintaining or even improving quality. In PL algorithms, a regularization parameter ? controls penalization relative differences between neighboring pixels determines characteristics. present study, we aim compare performance Q.Clear (PL algorithm, GE Healthcare) OSEM (3 iterations, 8 subsets, 6-mm post-processing filter) 68 Ga-DOTATATE ( Ga-DOTA) studies, both visually quantitatively. Thirty consecutive whole-body Ga-DOTA studies were included. The data acquired in list mode reconstructed using 3D with various values acquisition times per bed position (bp), thus generating images reduced injected dose (1.5 min/bp: = 300–1100; 1.0 600–1400 0.5 800–2200). An additional analysis adding up 1500, 1700 3000 1.5, min/bp, respectively, was performed random sample studies. Evaluation phantom clinical data. Two experienced nuclear medicine physicians blinded variables assessed visually. Results Clinical Q.Clear, set at min/bp 1100, 1300 3000, resulted noise equivalence min/bp) mean increase SUV max 14%, 13% 4%, an SNR 30%, 24% 10%, SBR 13%, 2%. Visual assessment yielded similar results 1100–1400 1300–1600 1.5 although there no significant improvement compared OSEM. Conclusion reconstructions increased tumor improved level enables one-third reduction time dose,
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ژورنال
عنوان ژورنال: EJNMMI Physics
سال: 2021
ISSN: ['2197-7364']
DOI: https://doi.org/10.1186/s40658-021-00359-6