Aim: The aim of this study was to evaluate an image reconstruction algorithm, including a new maximum-likelihood attenuation correction factor (ML-ACF) for time of flight (TOF) brain positron emission tomography (PET).
Methods: The implemented algorithm combines an ML-ACF method that simultaneously estimates both the emission image and attenuation sinogram from TOF emission data, and a scaling method based on anatomical features. To evaluate the algorithm's quantitative accuracy, three-dimensional brain phantom images were acquired and soft-tissue attenuation coefficients and emission values were analyzed.
Results: The heterogeneous distributions of attenuation coefficients in soft tissue, skull, and nasal cavity were sufficiently visualized. The attenuation coefficient of soft tissue remained within 5% of theoretical value. Attenuation-corrected emission showed no lateral differences, and significant differences among soft tissue were within the error range.
Conclusion: The ML-ACF-based attenuation correction implemented for TOF brain PET worked well and obtained practical levels of accuracy.
Keywords: Attenuation correction; ML-ACF; TOF brain PET.
© 2022. The Author(s) under exclusive licence to The Japanese Society of Nuclear Medicine.