Evaluation of the Characteristics of Short Acquisition Times Using the Clear Adaptive Low-Noise Method and Advanced Intelligent Clear-IQ Engine

This study aimed to evaluate the characteristics of short acquisition times using the Clear adaptive Low-noise Method (CaLM) and Advanced intelligent clear-IQ engine (AiCE) reconstructions in a semiconductor-based positron emission tomography (PET)/computed tomography system. PET data were acquired for 30 min in list mode and resampled into time frames ranging from 15 to 120 s. Images were reconstructed using three-dimensional ordinary Poisson ordered-subset expectation maximization (OSEM) with time of flight (TOF) and OSEM with TOF and point spread function modeling (PSF) algorithms, with OSEM iterations adjusted from 1 to 20 and CaLM applied under Mild, Standard, and Strong settings. AiCE reconstruction allows for the modification of only the acquisition time. The images were evaluated based on the coefficient of variation, recovery coefficient, % background variability (N10mm), % contrast-to-% background variability ratio (QH10mm/N10mm), and contrast-to-noise ratio. While OSEM with TOF reconstruction did not significantly reduce the acquisition time, the addition of PSF correction suggested the potential for further reduction. Given that the AiCE characteristics may vary depending on the equipment used, further investigation is required.