Impact of motion correction on [18F]-MK6240 tau PET imaging - Tiss, Amal; Marin, Thibault; Chemli, Yanis; Spangler-Bickell, Matthew; Gong, Kuang; Lois, Cristina; Petibon, Yoann; Landes, Vanessa; Grogg, Kira; Normandin, Marc; Becker, Alex; Thibault, Emma; et al. (Physics in medicine & biology, 2023)
Objective . Positron emission tomography (PET) imaging of tau deposition using [ 18 F]-MK6240 often involves long acquisitions in older subjects, many of whom exhibit dementia symptoms. The resulting unavoidable head motion can greatly degrade image quality. Motion increases the variability of PET quantitation for longitudinal studies across subjects, resulting in larger sample sizes in clinical trials of Alzheimer’s disease (AD) treatment. Approach . After using an ultra-short frame-by-frame motion detection method based on the list-mode data, we applied an event-by-event list-mode reconstruction to generate the motion-corrected images from 139 scans acquired in 65 subjects. This approach was initially validated in two phantoms experiments against optical tracking data. We developed a motion metric based on the average voxel displacement in the brain to quantify the level of motion in each scan and consequently evaluate the effect of motion correction on images from studies with substantial motion. We estimated the rate of tau accumulation in longitudinal studies (51 subjects) by calculating the difference in the ratio of standard uptake values in key brain regions for AD. We compared the regions’ standard deviations across subjects from motion and non-motion-corrected images. Main results . Individually, 14% of the scans exhibited notable motion quantified by the proposed motion metric, affecting 48% of the longitudinal datasets with three time points and 25% of all subjects. Motion correction decreased the blurring in images from scans with notable motion and improved the accuracy in quantitative measures. Motion correction reduced the standard deviation of the rate of tau accumulation by −49%, −24%, −18%, and −16% in the entorhinal, inferior temporal, precuneus, and amygdala regions, respectively. Significance . The list-mode-based motion correction method is capable of correcting both fast and slow motion during brain PET scans. It leads to improved brain PET quantitation, which is crucial for imaging AD.