Abstract
Head motion during brain PET imaging can significantly degrade the quality of the reconstructed image, leading to reduced diagnostic value and inaccurate quantitation. A fully data-driven motion correction approach was recently demonstrated to produce highly accurate motion estimates (<1 mm) with high temporal resolution (≥1 Hz), which can then be used for a motion-corrected reconstruction. This can be applied retrospectively with no impact on the clinical image acquisition protocol. We present a reader-based evaluation and an atlas-based quantitative analysis of this motion correction approach within a clinical cohort. Methods: Clinical patient data were collected over 2019-2020 and processed retrospectively. Motion was estimated using image-based registration on reconstructions of ultrashort frames (0.6-1.8 s), after which list-mode reconstructions that were fully motion-corrected were performed. Two readers graded the motion-corrected and uncorrected reconstructions. An atlas-based quantitative analysis was performed. Paired Wilcoxon tests were used to test for significant differences in reader scores and SUVs between reconstructions. The Levene test was used to determine whether motion correction had a greater impact on quantitation in the presence of motion than when motion was low. Results: Fifty standard clinical 18F-FDG brain PET datasets (age range, 13-83 y; mean ± SD, 59 ± 20 y; 27 women) from 3 scanners were collected. The reader study showed a significantly different, diagnostically relevant improvement by motion correction when motion was present (P = 0.02) and no impact in low-motion cases. Eight percent of all datasets improved from diagnostically unacceptable to acceptable. The atlas-based analysis demonstrated a significant difference between the motion-corrected and uncorrected reconstructions in cases of high motion for 7 of 8 regions of interest (P < 0.05). Conclusion: The proposed approach to data-driven motion estimation and correction demonstrated a clinically significant impact on brain PET image reconstruction.
Highlights
The atlas-based analysis demonstrated a significant difference between the motion corrected and uncorrected reconstructions in cases of high motion for 7 of 8 regions of interest (ROIs) (p < 0.05)
As the spatial resolution of modern whole-body positron emission tomography (PET) scanners reaches 2-4 mm full-width at half-maximum (FWHM), together with improved sensitivity and time of flight (TOF) resolution, it is becoming increasingly likely that even small head motion may substantially degrade the reconstructed image
The motion estimation used a temporal resolution of ~1 s and detected motion of more than 1 mm in 70% (35/50) of the data sets and more than 2 mm in 24% (12/50) of cases, the latter of which usually resulted in visually obvious differences between the motion corrected (MoCo) and no MoCo reconstructions
Summary
As the spatial resolution of modern whole-body positron emission tomography (PET) scanners reaches 2-4 mm full-width at half-maximum (FWHM), together with improved sensitivity and time of flight (TOF) resolution, it is becoming increasingly likely that even small head motion may substantially degrade the reconstructed image. Various motion tracking and correction techniques have been presented to account for head motion [2,3,4,5,6,7] These usually use an external tracking device (such as a camera) to track a marker attached to the head [5] or directly track the head [6]. The motion estimates can be used to perform frame-based reconstructions [8] or a full eventby-event motion corrected reconstruction [9,10] None of these motion correction approaches have been implemented into wide-spread standard clinical routine. Most motion tracking methods rely upon external hardware around the scanner (such as cameras) and/or attached to the patient (such as head markers), which complicate routine clinical protocols. Until recently there has not been a substantial effort from vendors to incorporate motion correction into their products and it has remained predominantly within the research setting
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