Evidence map›Paper›PMID 26952727›Full record

ReviewPET clinics2016

MR Imaging-Guided Attenuation Correction of PET Data in PET/MR Imaging.

David Izquierdo-Garcia, Ciprian Catana

Abstract readReview
In one paragraph

Review in PET clinics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing 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

26 citing papers in PubMed.

  1. Article
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  11. Diagnostic efficiency of whole-bodyCancer imaging : the official publication of the International Cancer Imaging Society · 2021
    Article
  12. Article
  13. Article
  14. Article
  15. Advances in simultaneous PET/MR for imaging neuroreceptor function.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2020
    Review
  16. Metal artifact reduction inEuropean journal of hybrid imaging · 2020
    Article
  17. Intrascanner Reproducibility of an SPM-based Head MR-based Attenuation Correction Method.IEEE transactions on radiation and plasma medical sciences · 2019
    Article
  18. Dixon-VIBE Deep Learning (DIVIDE) Pseudo-CT Synthesis for Pelvis PET/MR Attenuation Correction.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2019
    Article
  19. Review
  20. 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

2 authors.

David Izquierdo-GarciaDepartment of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, 149 13th Street, Charlestown 02129, MA, USA. Electronic address: davidizq@nmr.mgh.harvard.edu.
Ciprian CatanaDepartment of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, 149 13th Street, Charlestown 02129, MA, USA.

Funding

MR-assisted PET data optimization for neuroimaging studiesR01EB014894 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI CATANA, CIPRIAN · 2013 to 2016
$2.6M
NIBIB NIH HHS R01 EB014894
6 · The paper itself

Abstract

Attenuation correction (AC) is one of the most important challenges in the recently introduced combined PET/magnetic resonance (MR) scanners. PET/MR AC (MR-AC) approaches aim to develop methods that allow accurate estimation of the linear attenuation coefficients of the tissues and other components located in the PET field of view. MR-AC methods can be divided into 3 categories: segmentation, atlas, and PET based. This review provides a comprehensive list of the state-of-the-art MR-AC approaches and their pros and cons. The main sources of artifacts are presented. Finally, this review discusses the current status of MR-AC approaches for clinical applications.

Indexed as

ArtifactsHumansImage EnhancementMagnetic Resonance ImagingMultimodal ImagingPositron-Emission TomographyArtifactsAtlasAttenuation correctionBody truncationMR-ACPET/MR imagingSegmentationTemplate

Identifiers

PMID26952727
PMCPMC5798860

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.