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Optimization of brain PET markerless head motion correction in a large human cohort
Tianyi Zeng1, Jiazhen Zhang2, Jean-Dominique Gallezot3
1Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA. tianyi.zeng@yale.edu.
Purpose:
Uncorrected head motion in brain PET degrades image resolution and biases quantification. Previously, we evaluated the United Imaging Healthcare markerless motion tracking (UMT) system for brain PET (Baseline UMT). This study provides an expanded validation in a large cohort compared to the Vicra with improved methodology (Optimized UMT).
Methods:
We developed automatic processing to define the upper face region and added a 2-step Iterative Closest Points registration to reduce non-rigid motion effects. Optimized and Baseline UMT were first compared with simulations using measured motion and intentional facial expressions. In the human study, we evaluated 51 dynamic human studies (Siemens mCT) using 5 radiopharmaceuticals. Vicra data were used as the gold standard, after assessment of motion data quality using motion-corrected centroid-of-distribution. Comparisons between Optimized UMT, no motion correction (NMC), Post-Reconstruction Registration (PRR), and Baseline UMT were performed. Static and dynamic analyses assessed the differences of region-of-interest standardized uptake values (SUV) compared to Vicra. Time activity curve (TAC) analysis was performed to quantify uncorrected motion from the residual standard deviation (SD) around fitted TACs.
Results:
In simulation studies, optimized UMT reduced error by 20% relative to NMC and by 9% relative to Baseline UMT under intentional facial expressions, reflecting the impact of the updated UMT registration. In the human static analysis of SUV, optimized UMT outperformed PRR (+ 1.6%) and NMC (+ 6.5%) on average grey matter difference. Similar results were found in the dynamic analysis. In the TAC analysis, optimized UMT consistently yielded lower residual variability than NMC and PRR across tracers and ROIs, with a narrower range of median %SD values (0.3-1.8%) compared with NMC (1.6-6.5%) and PRR (0.5-1.9%), while demonstrating performance comparable to the reference Vicra-based correction.
Conclusion:
Optimized UMT achieved comparable performance to Vicra and significantly improved quantification over PRR.
