Evidence map›Paper›PMID 28534848›Full record

ArticleSensors (Basel, Switzerland)2017

Development and Design of Next-Generation Head-Mounted Ambulatory Microdose Positron-Emission Tomography (AM-PET) System.

Samantha Melroy, Christopher Bauer, Matthew McHugh, Garret Carden, Alexander Stolin, Stan Majewski, Julie Brefczynski-Lewis, Thorsten Wuest

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
3.9field-weighted citation impact, top 6% 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

17 citing papers in PubMed, 32 citations in OpenAlex.

  1. Article
  2. Article
  3. NRM 2021 Abstract Booklet.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2021
    Article
  4. Review
  5. Article
  6. Review
  7. Applications of artificial intelligence in nuclear medicine image generation.Quantitative imaging in medicine and surgery · 2021
    Review
  8. Application-specific nuclear medicalPhysics in medicine and biology · 2021
    Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Development of Dedicated Brain PET Imaging Devices: Recent Advances and Future Perspectives.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2019
    Review
  15. Article
  16. Review
  17. 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

8 authors at 2 institutions in 1 country.

Samantha MelroyIndustrial and Management Systems Engineering, West Virginia University, Morgantown, WV 26506, USA. smelroy@mix.wvu.edu.
Christopher BauerMontgomery-Downs Lab, Blanchette Rockefeller Neuroscience Institute, West Virginia University, Morgantown, WV 26506, USA. cbauer5@mix.wvu.edu.
Matthew McHughMechanical and Aerospace Engineering, West Virginia University, Morgantown, WV 26506, USA. mmchugh4@mix.wvu.edu.
Garret CardenIndustrial and Management Systems Engineering, West Virginia University, Morgantown, WV 26506, USA. gtcarden@mix.wvu.edu.
Alexander StolinDepartment of Radiology, Center for Advanced Imaging, West Virginia University, Morgantown, WV 26506, USA. astolin@hsc.wvu.edu.
Stan MajewskiDepartment of Radiology & Medical Imaging, University of Virginia, Charlottesville, VA 22903, USA. sm4aa@virginia.edu.
Julie Brefczynski-LewisPhysiology & Pharmacology & Blanchette Rockefeller Neuroscience Institute, West Virginia University, Morgantown, WV 26506, USA. jblewis@hsc.wvu.edu.
Thorsten WuestIndustrial and Management Systems Engineering, West Virginia University, Morgantown, WV 26506, USA. thwuest@mail.wvu.edu.
West Virginia University · USUniversity of Virginia · US

Funding

West Virginia IDEA-CTRU54GM104942 · NIGMS · WEST VIRGINIA UNIVERSITY · PI Anne Courtney DeVries · 2012 to 2026
$81.0M
Imaging the Brain in Motion: The Ambulatory Micro-Dose, Wearable PET Brain ImagerR24MH106057 · NIMH · WEST VIRGINIA UNIVERSITY · PI BREFCZYNSKI-LEWIS, JULIE ANN · 2014 to 2016
$1.6M
NIGMS NIH HHS U54 GM104942NIMH NIH HHS R24 MH106057
6 · The paper itself

Abstract

Several applications exist for a whole brain positron-emission tomography (PET) brain imager designed as a portable unit that can be worn on a patient's head. Enabled by improvements in detector technology, a lightweight, high performance device would allow PET brain imaging in different environments and during behavioral tasks. Such a wearable system that allows the subjects to move their heads and walk-the Ambulatory Microdose PET (AM-PET)-is currently under development. This imager will be helpful for testing subjects performing selected activities such as gestures, virtual reality activities and walking. The need for this type of lightweight mobile device has led to the construction of a proof of concept portable head-worn unit that uses twelve silicon photomultiplier (SiPM) PET module sensors built into a small ring which fits around the head. This paper is focused on the engineering design of mechanical support aspects of the AM-PET project, both of the current device as well as of the coming next-generation devices. The goal of this work is to optimize design of the scanner and its mechanics to improve comfort for the subject by reducing the effect of weight, and to enable diversification of its applications amongst different research activities.

Indexed as

Positron-Emission TomographyBrainEquipment DesignHumansMagnetic Resonance ImagingPhantoms, ImagingSiliconSiliconautismbrainbrain disordersbrain injuriesdementiasmicrodosepositron emission tomographystrokewearable

Identifiers

PMID28534848
PMCPMC5470909
OpenAlexW2615543798

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.