ArticleEJNMMI physics2026
Optimization of brain PET markerless head motion correction in a large human cohort.
Article in EJNMMI physics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
Abstract
purposeUncorrected 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).
methodsWe 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.
resultsIn 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.
conclusionOptimized UMT achieved comparable performance to Vicra and significantly improved quantification over PRR.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.