Evidence map›Paper›PMID 33635449›Full record

ArticleEJNMMI physics2021

Cross-validation study between the HRRT and the PET component of the SIGNA PET/MRI system with focus on neuroimaging.

Julia G Mannheim, Ju-Chieh Kevin Cheng, Nasim Vafai, Elham Shahinfard, Carolyn English, Jessamyn McKenzie, Jing Zhang, Laura Barlow, Vesna Sossi

Open access · goldAbstract read
In one paragraph

Article in EJNMMI physics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.1field-weighted citation impact, top 23% of its field
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

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.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 10 citations in OpenAlex.

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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

9 authors at 4 institutions in 2 countries.

Julia G Mannheim *Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada. julia.mannheim@med.uni-tuebingen.de.ORCID http://orcid.org/0000-0003-2380-1145
Ju-Chieh Kevin Cheng *Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.
Nasim VafaiPacific Parkinson's Research Centre, University of British Columbia, Vancouver, British Columbia, Canada.
Elham ShahinfardPacific Parkinson's Research Centre, University of British Columbia, Vancouver, British Columbia, Canada.
Carolyn EnglishPacific Parkinson's Research Centre, University of British Columbia, Vancouver, British Columbia, Canada.
Jessamyn McKenzieDjavad Mowafaghian Centre for Brain Health, Pacific Parkinson's Research Centre, University of British Columbia & Vancouver Coastal Health, Vancouver, British Columbia, Canada.
Jing ZhangGlobal MR Applications & Workflow, GE Healthcare Canada, Vancouver, British Columbia, Canada.
Laura BarlowUBC MRI Research Centre, University of British Columbia, Vancouver, British Columbia, Canada.
Vesna SossiDepartment of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.
University of British Columbia · CASiemens (Germany) · DEUniversity of British Columbia Hospital · CAVancouver Coastal Health · CA

Funding

Natural Sciences and Engineering Research Council grant 240670-13
6 · The paper itself

Abstract

backgroundThe Siemens high-resolution research tomograph (HRRT - a dedicated brain PET scanner) is to this day one of the highest resolution PET scanners; thus, it can serve as useful benchmark when evaluating performance of newer scanners. Here, we report results from a cross-validation study between the HRRT and the whole-body GE SIGNA PET/MR focusing on brain imaging. Phantom data were acquired to determine recovery coefficients (RCs), % background variability (%BG), and image voxel noise (%). Cross-validation studies were performed with six healthy volunteers using [

resultsPhantom data showed that the PET/MR images reconstructed with an ordered subset expectation maximization (OSEM) algorithm with time-of-flight (TOF) and TOF + point spread function (PSF) + filter revealed similar RCs for the hot spheres compared to those obtained on the HRRT reconstructed with an ordinary Poisson-OSEM algorithm with PSF and PSF + filter. The PET/MR TOF + PSF reconstruction revealed the highest RCs for all hot spheres. Image voxel noise of the PET/MR system was significantly lower. Line profiles revealed excellent spatial agreement between the two systems. BP

conclusionsThese results demonstrated comparable performances of the two systems in terms of RCs with lower voxel-level noise (%) present in the PET/MR system. Comparison of in vivo human data confirmed the comparability of the two systems. The whole-body GE SIGNA PET/MR system is well suited for high-resolution brain imaging as no significant performance degradation was found compared to that of the reference standard HRRT.

Indexed as

Binding potentialsCross-validation studyHRRTPET/MRRecovery coefficients

Identifiers

PMID33635449
PMCPMC7910400
OpenAlexW3132169697

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.