Evidence map›Paper›PMID 37775372›Full record

ReviewPET clinics2024

High-resolution Imaging Using Virtual-Pinhole PET Concept.

Yuan-Chuan Tai

Abstract readReview
In one paragraph

Review in PET clinics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Development of a Prototype AWSM-PET Device for Augmented Whole-Body PET Imaging and Initial Human Study.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2026
    Article
  2. Article
  3. Review
  4. 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

1 author.

Yuan-Chuan TaiDepartment of Radiology, Washington University in St. Louis, St Louis, MO, USA; Department of Biomedical Engineering, Washington University in St. Louis, St Louis, MO, USA; Department of Electrical and System Engineering, Washington University in St. Louis, St Louis, MO, USA. Electronic address: taiy@wustl.edu.

Funding

Translation of virtual-pinhole magnifying PET technology to clinical whole-body cancer imagingR01CA233912 · NCI · WASHINGTON UNIVERSITY · PI TAI, YUAN-CHUAN · 2019 to 2023
$2.6M
A Sub-Millimeter Resolution add-on for Animal PET scannersR01CA136554 · NCI · WASHINGTON UNIVERSITY · PI SIEGEL, STEFAN, TAI, YUAN-CHUAN · 2009 to 2013
$2.1M
A Novel Device to Allow Zoom-In Imaging for PET ScannersR33CA110011 · NCI · WASHINGTON UNIVERSITY · PI TAI, YUAN-CHUAN · 2005 to 2007
$1.2M
A Novel Device to Allow Zoom-In Imaging for PET ScannersR21CA110011 · NCI · WASHINGTON UNIVERSITY · PI TAI, YUAN-CHUAN · 2004 to 2004
$172k
NCI NIH HHS R01 CA136554NCI NIH HHS R01 CA233912NCI NIH HHS R21 CA110011NCI NIH HHS R33 CA110011
6 · The paper itself

Abstract

Organ-specific PET scanners continues to draw interest for their high-resolution imaging capability that is unmatched by whole-body PET/computed tomography (CT) scanners. The virtual-pinhole PET concept offers new opportunities in PET system design, allowing one to mix and match detectors of different characteristics to achieve the highest performance such as high image resolution, high system sensitivity, and large imaging field-of-view. This novel approach delivers high-resolution PET images previously available only through organ-specific PET scanner while maintaining the imaging field-of-view of a clinical PET/CT scanner to see the entire body.

Indexed as

Positron-Emission TomographyPositron Emission Tomography Computed TomographyHumansPhantoms, ImagingOrgan-specific PET imagingPETPositron emission tomographyVirtual-pinhole PETZoom-in PET imaging

Identifiers

PMID37775372
PMCPMC10840911

What OpenQuestion holds

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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.