Methods for Motion Correction Evaluation Using ¹⁸F-FDG Human Brain Scans on a High-Resolution PET Scanner

Abstract

Many authors have reported the importance of motion correction (MC) for PET. Patient motion during scanning disturbs kinetic analysis and degrades resolution. In addition, using misaligned transmission for attenuation and scatter correction may produce regional quantification bias in the reconstructed emission images. The purpose of this work was the development of quality control (QC) methods for MC procedures based on external motion tracking (EMT ) for human scanning using an optical motion tracking system. Methods: Two scans with minor motion and 5 with major motion (as reported by the optical motion tracking system) were selected from 18 F-FDG scans acquired on a PET scanner. The motion was measured as the maximum displacement of the markers attached to the subject's head and was considered to be major if larger than 4 mm and minor if less than 2 mm. After allowing a 40-to 60-min uptake time after tracer injection, we acquired a 6-min transmission scan, followed by a 40-min emission list-mode scan. Each emission list-mode dataset was divided into 8 frames of 5 min. The reconstructed time-framed images were aligned to a selected reference frame using either EMT or the AIR (automated image registration) software. The following 3 QC methods were used to evaluate the EMT and AIR MC: a method using the ratio between 2 regions of interest with gray matter voxels (GM) and white matter voxels (WM), called GM/WM; mutual information; and cross correlation. Results: The results of the 3 QC methods were in agreement with one another and with a visual subjective inspection of the image data. Before MC, the QC method measures varied significantly in scans with major motion and displayed limited variations on scans with minor motion. The variation was significantly reduced and measures improved after MC with AIR, whereas EMT MC performed less well. Conclusion: The 3 presented QC methods produced similar results and are useful for evaluating tracer-independent external-tracking motion-correction methods for human brain scans.

The Role of Dopamine in Value-Based Attentional Orienting

“…Emission PET scans were reconstructed using the iterative ordered-subset expectation-maximization algorithm correcting for attenuation, scatter, randoms and dead-time [45] and including inter-frame head motion correction including transmission-emission alignment for the individual frames [46]. The radioactivity was corrected for physical decay to the injection time.…”

Impact of time-of-flight on indirect 3D and direct 4D parametric image reconstruction in the presence of inconsistent dynamic PET data

“…Such motion can occur either between frames or within frames and can cause significant changes in voxel-wise time-activity curves (TACs), especially on the boundaries of regions with significantly different kinetics and high activity gradient. Such blurring across frames could subsequently lead to blurring of the kinetic parameter maps (Herzog et al 2005, Dinelle et al 2011, Keller et al 2012 or even affect the extraction of image-derived input functions from the dynamic emission data (Mourik et al 2011). Furthermore, patient movement will most likely cause an emission/attenuation mismatch in the affected frames, resulting in errors during attenuation correction and scatter estimation (Anton-Rodriguez et al 2010, Häggström et al 2014.…”

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