Evidence map›Paper›PMID 39422495›Full record

ArticleMedical physics2025

High-resolution motion compensation for brain PET imaging using real-time electromagnetic motion tracking.

Wanbin Tan, Zipai Wang, Xinjie Zeng, Anthony Boccia, Xiuyuan Wang, Yixin Li, Yi Li, Edward K Fung, Jinyi Qi, Tianyi Zeng and 2 more

Abstract read
In one paragraph

Article in Medical physics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Wanbin TanDepartment of Radiology, Weill Cornell Medical College, Cornell University, New York, New York, USA.
Zipai WangDepartment of Radiology, Weill Cornell Medical College, Cornell University, New York, New York, USA.
Xinjie ZengDepartment of Radiology, Weill Cornell Medical College, Cornell University, New York, New York, USA.
Anthony BocciaDepartment of Radiology, Renaissance School of Medicine, Stony Brook University, Stony Brook, New York, USA.
Xiuyuan WangDepartment of Radiology, Weill Cornell Medical College, Cornell University, New York, New York, USA.
Yixin LiDepartment of Radiology, Weill Cornell Medical College, Cornell University, New York, New York, USA.
Yi LiDepartment of Radiology, Weill Cornell Medical College, Cornell University, New York, New York, USA.
Edward K FungDepartment of Radiology, Weill Cornell Medical College, Cornell University, New York, New York, USA.
Jinyi QiDepartment of Biomedical Engineering, University of California, Davis, California, USA.
Tianyi ZengDepartment of Radiology and Biomedical Imaging, Yale University, New Haven, Connecticut, USA.
Ajay GuptaDepartment of Radiology, Columbia University Irving Medical Center, New York, New York, USA.
Amir H GoldanDepartment of Radiology, Weill Cornell Medical College, Cornell University, New York, New York, USA.

Funding

Prism-PET: A TOF-DOI-Compton PET detector technology for total-body PET imagingR01EB030413 · NIBIB · WEILL MEDICAL COLL OF CORNELL UNIV · PI GOLDAN, AMIRHOSSEIN · 2021 to 2024
$2.5M
NIBIB NIH HHS R01 EB030413NIH HHS R01EB030413
6 · The paper itself

Abstract

backgroundSubstantial improvements in spatial resolution in brain positron emission tomography (PET) scanners have greatly reduced partial volume effect, making head movement the main source of image blur. To achieve high-resolution PET neuroimaging, precise real-time estimation of both head position and orientation is essential for accurate motion compensation. PURPOSE: A high-resolution electromagnetic motion tracking (EMMT) system with an event-by-event motion correction is developed for PET-CT scanners.

methodsEMMT is comprised of a source, an array of sensors, and a readout electronic unit (REU). The source acts as a transmitter and emits an EM dipole field. It is placed in close proximity to the sensor array and detects changes in EM flux density due to sensor movement. The REU digitizes signals from each sensor and captures precise rotational and translational movements in real time. Tracked motion in the EMMT coordinate system is synchronized with the PET list-mode data and transformed into the scanner coordinate system by locating paired positions in both systems. The optimal rigid motion is estimated using singular value decomposition. The rigid motion and depth-of-interaction (DOI) parallax effect are corrected by event-by-event rebinning of mispositioned lines-of-response (LORs). We integrated the EMMT with our recently developed ultra-high resolution Prism-PET prototype brain scanner and a commercial Siemens Biograph mCT PET-CT scanner. We assessed the imaging performance of the Prism-PET/EMMT system using multi-frame motion of point sources and phantoms. The mCT/EMMT system was validated using a set of point sources attached to both a mannequin head and a human volunteer, for simulating multiframe and continuous motions, respectively. Additionally, a human subject for [

resultsThe tracking accuracy of the Prism-PET/EMMT system was quantified as a root-mean-square (RMS) error of 0.49

conclusionsThe proposed EMMT system is a cost-effective, high frame-rate, and none-line-of-sight alternative to infrared camera-based tracking systems and is capable of achieving high rotational and translational tracking accuracies for mitigating motion-induced blur in high-resolution brain dedicated PET scanners.

Indexed as

BrainImage Processing, Computer-AssistedMovementPhantoms, ImagingPositron-Emission TomographyElectromagnetic PhenomenaHumansMotionPositron Emission Tomography Computed TomographyTime Factorselectromagnetic motion trackingevent‐by‐event motion correctionPrism‐PET

Identifiers

PMID39422495
PMCPMC11716701

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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.