Evidence map›Paper›PMID 25841276›Full record

ReviewSeminars in nuclear medicine2015

Motion correction options in PET/MRI.

Ciprian Catana

Open access · greenAbstract readReview
In one paragraph

Review in Seminars in nuclear medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed, 1 pooled it
14.9field-weighted citation impact, top 1% 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

44 citing papers in PubMed, 1 synthesis or guideline pooled it, 108 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Review
  4. (Hybrid) SPECT and PET Technologies.Recent results in cancer research. Fortschritte der Krebsforschung. Progres dans les recherches sur le cancer · 2026
    Review
  5. Article
  6. Review
  7. Article
  8. PET/MRI imaging in neuroendocrine neoplasm.Abdominal radiology (New York) · 2023
    Review
  9. Inter-pass motion correction for whole-body dynamic PET and parametric imaging.IEEE transactions on radiation and plasma medical sciences · 2023
    Article
  10. Article
  11. Article
  12. Advances in Preclinical PET.Seminars in nuclear medicine · 2022
    Review
  13. Review
  14. Review
  15. Article
  16. Attenuation correction for human PET/MRI studies.Physics in medicine and biology · 2020
    Article
  17. PET/MRI of atherosclerosis.Cardiovascular diagnosis and therapy · 2020
    Review
  18. Dose Reduction in Brain [Molecular imaging and biology · 2020
    Article
  19. Quantitative Rodent Brain Receptor Imaging.Molecular imaging and biology · 2020
    Review
  20. 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

1 author at 1 institution in 1 country.

Ciprian CatanaAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA. Electronic address: ccatana@nmr.mgh.harvard.edu.
Athinoula A. Martinos Center for Biomedical Imaging · US

Funding

MR-assisted PET data optimization for neuroimaging studiesR01EB014894 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI CATANA, CIPRIAN · 2013 to 2016
$2.6M
Quantitative MR-PET for Therapy Assessment in Glioma PatientsR01CA137254 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI CATANA, CIPRIAN, SCHMAND, MATTHIAS · 2009 to 2012
$2.5M
NCI NIH HHS R01 CA137254NIBIB NIH HHS R01 EB014894
6 · The paper itself

Abstract

Subject motion is unavoidable in clinical and research imaging studies. Breathing is the most important source of motion in whole-body PET and MRI studies, affecting not only thoracic organs but also those in the upper and even lower abdomen. The motion related to the pumping action of the heart is obviously relevant in high-resolution cardiac studies. These two sources of motion are periodic and predictable, at least to a first approximation, which means certain techniques can be used to control the motion (eg, by acquiring the data when the organ of interest is relatively at rest). Additionally, nonperiodic and unpredictable motion can also occur during the scan. One obvious limitation of methods relying on external devices (eg, respiratory bellows or the electrocardiogram signal to monitor the respiratory or cardiac cycle, respectively) to trigger or gate the data acquisition is that the complex motion of internal organs cannot be fully characterized. However, detailed information can be obtained using either the PET or MRI data (or both) allowing the more complete characterization of the motion field so that a motion model can be built. Such a model and the information derived from simple external devices can be used to minimize the effects of motion on the collected data. In the ideal case, all the events recorded during the PET scan would be used to generate a motion-free or corrected PET image. The detailed motion field can be used for this purpose by applying it to the PET data before, during, or after the image reconstruction. Integrating all these methods for motion control, characterization, and correction into a workflow that can be used for routine clinical studies is challenging but could potentially be extremely valuable given the improvement in image quality and reduction of motion-related image artifacts.

Indexed as

MovementAnimalsArtifactsHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingPositron-Emission Tomography

Identifiers

PMID25841276
PMCPMC4487884
OpenAlexW2085885731

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.