Evidence map›Paper›PMID 29028189›Full record

ArticleIEEE transactions on medical imaging2018

Non-Rigid Event-by-Event Continuous Respiratory Motion Compensated List-Mode Reconstruction for PET.

Chung Chan, John Onofrey, Yiqiang Jian, Mary Germino, Xenophon Papademetris, Richard E Carson, Chi Liu

Abstract read
In one paragraph

Article in IEEE transactions on medical imaging, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
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  3. Review
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  11. Article
  12. Respiratory Motion Compensation for PET/CT with Motion Information Derived from Matched Attenuation-Corrected Gated PET Data.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2018
    Article
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

7 authors.

Chung Chan
John Onofrey
Yiqiang Jian
Mary Germino
Xenophon Papademetris
Richard E Carson
Chi Liu

Funding

Yale University Clinical and Translational Science Award ProgramUL1TR000142 · NCATS · YALE UNIVERSITY · PI SHERWIN, ROBERT S · 2012 to 2015
$31.8M
State-of-the-Art PET/CT InstrumentationS10RR029245 · NCRR · YALE UNIVERSITY · PI CARSON, RICHARD E. · 2010 to 2010
$2.3M
NCATS NIH HHS UL1 TR000142NCRR NIH HHS S10 RR029245
6 · The paper itself

Abstract

Respiratory motion during positron emission tomography (PET)/computed tomography (CT) imaging can cause significant image blurring and underestimation of tracer concentration for both static and dynamic studies. In this paper, with the aim to eliminate both intra-cycle and inter-cycle motions, and apply to dynamic imaging, we developed a non-rigid event-by-event (NR-EBE) respiratory motion-compensated list-mode reconstruction algorithm. The proposed method consists of two components: the first component estimates a continuous non-rigid motion field of the internal organs using the internal-external motion correlation. This continuous motion field is then incorporated into the second component, non-rigid MOLAR (NR-MOLAR) reconstruction algorithm to deform the system matrix to the reference location where the attenuation CT is acquired. The point spread function (PSF) and time-of-flight (TOF) kernels in NR-MOLAR are incorporated in the system matrix calculation, and therefore are also deformed according to motion. We first validated NR-MOLAR using a XCAT phantom with a simulated respiratory motion. NR-EBE motion-compensated image reconstruction using both the components was then validated on three human studies injected with

Indexed as

AlgorithmsFluorodeoxyglucose F18HumansImage Processing, Computer-AssistedPhantoms, ImagingPositron Emission Tomography Computed TomographyRespiratory MechanicsFluorodeoxyglucose F18

Identifiers

PMID29028189
PMCPMC7304524

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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.