Standard OSEM vs. regularized PET image reconstruction: qualitative and quantitative comparison using phantom data and various clinical radiopharmaceuticals

American Journal of Nuclear Medicine and Molecular Imaging

Andrei Iagaru¹  Craig S Levin²  Erik S Mittra³  Judit Lantos⁴ 

[1] Department of Bioengineering, Stanford University, Stanford 94305, CA, USA;Department of Electrical Engineering, Stanford University, Stanford 94305, CA, USA;Department of Physics, Stanford University, Stanford 94305, CA, USA;Department of Radiology, Stanford University, Stanford 94305, CA, USA

关键词: OSEM;    BSREM;    PET;    image;    reconstruction;   

DOI  :  

学科分类：过敏症与临床免疫学

来源: e-Century Publishing Corporation

【 摘 要 】

We investigated the block sequential regularized expectation maximization (BSREM) algorithm. ACR phantom measurements with different count statistics and 60 PET/CT research scans from the GE Discovery 600 and 690 scanners were reconstructed using BSREM and the standard-of-care OSEM algorithm. Hot concentration recovery and cold contrast recovery were measured from the phantom data. Two experienced nuclear medicine physicians reviewed the clinical images blindly. Liver SNR liver and SUVmax of the smallest lesion detected in each patient were also measured. The relationship between the maximum and mean hot concentration recovery remained monotonic below 1.5 maximum concentration recovery. The mean cold contrast recovery remained stable even for decreasing statistics with a highest absolute difference of 4% in air and 2% in bone for each reconstruction method. The D600 images resulted in an average 30% higher SNR than the D690 data for BSREM; there was no difference in SNR results between the two scanners with OSEM. The small lesion SUVmax values on the BSREM images with β of 250, 350 and 450, respectively were on average 80%, 60% and 43% (D690) and 42%, 29%, and 21% (D600) higher than in the case of OSEM. In conclusion, BSREM can outperform OSEM in terms of contrast recovery and organ uniformity over a range of PET tracers, but a task dependent regularization strength parameter (beta) selection may be necessary. To avoid image noise and artifacts, our results suggest that using higher beta values (at least 350) may be appropriate, especially if the data has low count statistics.

【 授权许可】

CC BY-NC