Evidence map›Paper›PMID 29754007›Full record

ReviewCurrent opinion in chemical biology2018

Magnetic particle imaging for radiation-free, sensitive and high-contrast vascular imaging and cell tracking.

Xinyi Y Zhou, Zhi Wei Tay, Prashant Chandrasekharan, Elaine Y Yu, Daniel W Hensley, Ryan Orendorff, Kenneth E Jeffris, David Mai, Bo Zheng, Patrick W Goodwill and 1 more

Abstract readReview
In one paragraph

Review in Current opinion in chemical biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing 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

38 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
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  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Machine Learning and Deep Learning Applications in Magnetic Particle Imaging.Journal of magnetic resonance imaging : JMRI · 2025
    Review
  11. Review
  12. Theranostics · 2024
    Article
  13. Article
  14. International journal of stem cells · 2023
    Review
  15. Review
  16. Article
  17. Article
  18. Article
  19. Multimodality imaging of nanoparticle-based vaccines: Shedding light on immunology.Wiley interdisciplinary reviews. Nanomedicine and nanobiotechnology · 2022
    Review
  20. Direct Cell Radiolabeling forChemical reviews · 2022
    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

11 authors.

Xinyi Y ZhouDepartment of Bioengineering, University of California Berkeley, Berkeley, CA 94720, United States; UC Berkeley - UCSF Graduate Program in Bioengineering, United States. Electronic address: xizhou@berkeley.edu.
Zhi Wei TayDepartment of Bioengineering, University of California Berkeley, Berkeley, CA 94720, United States; UC Berkeley - UCSF Graduate Program in Bioengineering, United States.
Prashant ChandrasekharanDepartment of Bioengineering, University of California Berkeley, Berkeley, CA 94720, United States.
Elaine Y YuDepartment of Bioengineering, University of California Berkeley, Berkeley, CA 94720, United States; UC Berkeley - UCSF Graduate Program in Bioengineering, United States.
Daniel W HensleyDepartment of Bioengineering, University of California Berkeley, Berkeley, CA 94720, United States; UC Berkeley - UCSF Graduate Program in Bioengineering, United States.
Ryan OrendorffDepartment of Bioengineering, University of California Berkeley, Berkeley, CA 94720, United States; UC Berkeley - UCSF Graduate Program in Bioengineering, United States.
Kenneth E JeffrisDepartment of Bioengineering, University of California Berkeley, Berkeley, CA 94720, United States.
David MaiDepartment of Bioengineering, University of California Berkeley, Berkeley, CA 94720, United States.
Bo ZhengDepartment of Bioengineering, University of California Berkeley, Berkeley, CA 94720, United States.
Patrick W GoodwillMagnetic Insight, Inc., Alameda, CA 94501, United States.
Steven M ConollyDepartment of Bioengineering, University of California Berkeley, Berkeley, CA 94720, United States; Department of Electrical Engineering and Computer Sciences, University of California Berkeley, Berkeley, CA 94720, United States.

Funding

In Vivo Therapeutic Cell Tracking by Advanced Magnetic Particle ImagingR01EB024578 · NIBIB · UNIVERSITY OF CALIFORNIA BERKELEY · PI CONOLLY, STEVEN M · 2017 to 2020
$2.2M
Pre-clinical quantitation of ovarian cancer tumor burden using Magnetic Particle Imaging and non-dilutive cell labelingR01EB019458 · NIBIB · UNIVERSITY OF CALIFORNIA BERKELEY · PI BELL, CALEB B., CONOLLY, STEVEN M · 2015 to 2018
$1.9M
NIBIB NIH HHS R01 EB019458NIBIB NIH HHS R01 EB024578
6 · The paper itself

Abstract

Magnetic particle imaging (MPI) is an emerging ionizing radiation-free biomedical tracer imaging technique that directly images the intense magnetization of superparamagnetic iron oxide nanoparticles (SPIOs). MPI offers ideal image contrast because MPI shows zero signal from background tissues. Moreover, there is zero attenuation of the signal with depth in tissue, allowing for imaging deep inside the body quantitatively at any location. Recent work has demonstrated the potential of MPI for robust, sensitive vascular imaging and cell tracking with high contrast and dose-limited sensitivity comparable to nuclear medicine. To foster future applications in MPI, this new biomedical imaging field is welcoming researchers with expertise in imaging physics, magnetic nanoparticle synthesis and functionalization, nanoscale physics, and small animal imaging applications.

Indexed as

AnimalsBlood VesselsCell TrackingContrast MediaDiagnostic Techniques, CardiovascularEquipment DesignHumansMagneticsMagnetite NanoparticlesContrast MediaMagnetite Nanoparticles

Identifiers

PMID29754007
PMCPMC6500458

What OpenQuestion holds

Textmetadata
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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.