Large scale comparison of maximum likelihood scatter scaling and tail-fitted scatter scaling in LAFOV PET/CT

Scatter scaling during the reconstruction of Positron Emission Tomography (PET) data is a crucial element for obtaining clinically applicable images with accurate quantification and high image quality. The current clinical standard for scatter scaling is fitting the tail regions of the single scatter simulation (SSS) estimate, which is termed Tail-Fitted Scatter Scaling (TFSS). This study aims to compare a Maximum Likelihood Scatter Scaling (MLSS) algorithm relative to TFSS using a NEMA IQ phantom investigation and a patient cohort including 500 patients using long axial Field-of-View (LAFOV) PET. The relative difference between the two scatter scaling algorithms was investigated using uptake values of 12 organs. Furthermore, the proximity of known regions showing high activity relative to the surrounding tissue was analysed.

The NEMA image quality phantom study showed agreement between the expected activity concentration and the MLSS reconstructions. MLSS showed uptake values of 137.3 ± 3.4 kBq/mL in the largest sphere and 34.6 ± 0.5 kBq/mL in the background, closely matching the true concentrations of 136.6 kBq/mL and 35.0 kBq/mL, respectively. TFSS provided uptake values of 133.7 ± 3.5 kBq/mL in the largest sphere and 33.0 ± 0.9 kBq/mL in the background. MLSS showed higher uptake in the cold areas relative to TFSS. Mean recovery coefficients (RC_mean) showed that MLSS generally had coefficients closer to 1 relative to TFSS across the spheres of the phantom. The findings of the patient study showed a numeric relative difference below 2% when investigating organ uptake through the 12 organs.

MLSS provided results of high image quality comparable to the standard method of choice, TFSS, in the clinical routine. The phantom study showed that MLSS provided uptake values accurately relative to the known activity concentration, however less accurate within the cold sphere and insert. MLSS was found to provide robust results across a large patient cohort and is suggested as a suitable substitution for TFSS in the PET image reconstruction process.