Evidence map›Paper›PMID 34422087›Full record

ArticleJournal of instrumentation : an IOP and SISSA journal2021

Tomographic imaging with Compton PET modules: ideal case and first implementation.

P Peng, M Zhang, N Zeraatkar, J Qi, S R Cherry

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of instrumentation : an IOP and SISSA journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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

1 citing paper in PubMed.

  1. Review
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

5 authors.

P PengDepartment of Biomedical Engineering, University of California-Davis One Shields Avenue, Davis, CA 95616, USA.
M ZhangDepartment of Biomedical Engineering, University of California-Davis One Shields Avenue, Davis, CA 95616, USA.
N ZeraatkarDepartment of Biomedical Engineering, University of California-Davis One Shields Avenue, Davis, CA 95616, USA.
J QiDepartment of Biomedical Engineering, University of California-Davis One Shields Avenue, Davis, CA 95616, USA.
S R CherryDepartment of Biomedical Engineering, University of California-Davis One Shields Avenue, Davis, CA 95616, USA.

Funding

Optimization of PET ImagingR01EB000194 · NIBIB · UNIVERSITY OF CALIFORNIA DAVIS · PI QI, JINYI · 2003 to 2018
$3.7M
Innovative Silicon Photomultiplier Technologies for Small-Animal PETR01EB019439 · NIBIB · UNIVERSITY OF CALIFORNIA AT DAVIS · PI CHERRY, SIMON R · 2015 to 2018
$1.4M
High performance PET Detector Module for Human Brain ImagingR01EB028337 · NIBIB · CANON MEDICAL RESEARCH USA, INC. · PI PENG, PENG · 2019 to 2021
$775k
NIBIB NIH HHS R01 EB000194NIBIB NIH HHS R01 EB019439NIBIB NIH HHS R01 EB028337
6 · The paper itself

Abstract

In our previous studies, we demonstrated that the Compton PET module, a layer structure PET detector with side readout, can provide high performance in terms of spatial/energy/timing resolution, as well as high gamma ray detection efficiency. In this study, we investigate how to translate the high performance of the detector module into good quality reconstructed tomographic images. This study is performed using GATE simulation, as well as with physical experiments. Similar detector geometry is used in the simulation and experiment: two identical 4-layer detector modules are placed with face to face distance of 56 mm. In the simulation study, each layer consists of a 1-mm-pitch pixelated crystal array. In the experimental study, each layer is a monolithic crystal, which is virtually binned into 1 mm

Indexed as

Compton PETDerenzo phantomGATEMonte CarloReconstruction

Identifiers

PMID34422087
PMCPMC8372193

What OpenQuestion holds

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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.