Evidence map›Paper›PMID 35510241›Full record

ReviewJournal of clinical imaging science2022

Practice enhancements with FastStroke ColorViz analysis in acute ischemic stroke.

Vivek Pai, Joanna Pearly Ti, Leanne Qiaojing Tan, Thye Sin Ho, Carol Tham, Yih Yian Sitoh

Open access · hybridAbstract readReview
In one paragraph

Review in Journal of clinical imaging science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.8field-weighted citation impact, top 30% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. AI and Neurology.Neurological research and practice · 2025
    Review
  2. 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

6 authors at 2 institutions in 2 countries.

Vivek PaiDivision of Neuroradiology, Joint Department of Medical Imaging, University of Toronto, Toronto, Canada.ORCID https://orcid.org/0000-0001-7933-5994
Joanna Pearly TiDepartment of Neuroradiology, National Neuroscience Institute, Singapore.
Leanne Qiaojing TanDepartment of Neurosurgery, National Neuroscience Institute, Singapore.
Thye Sin HoDepartment of Neuroradiology, National Neuroscience Institute, Singapore.
Carol ThamDepartment of Neurology, National Neuroscience Institute, Singapore.
Yih Yian SitohDepartment of Neuroradiology, National Neuroscience Institute, Singapore.ORCID https://orcid.org/0000-0001-9693-7559
National Neuroscience Institute · SGUniversity of Toronto · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In acute ischemic stroke (AIS), large vessel occlusion (LVO) and the status of pial collaterals are important factors in decision-making for further treatment such as endovascular therapy. Multiphasic CT Angiogram (mCTA) is the mainstay of AIS imaging, allowing detection of LVO, evaluation of intracranial arterial dynamics, and quantification of pial collaterals. However, thorough mCTA evaluation entails scrutiny of multiple image datasets, individually and then simultaneously, which can be time-consuming, causing a potential delay in treatment. ColorViz (FastStroke, GE Healthcare, Milwaukee, Wisconsin) is a novel CT application which combines mCTA information into a single color-coded dataset for quick, unequivocal evaluation of pial collaterals. In our practice, ColorViz is both time-saving and increases the diagnostic accuracy of LVO and pial collaterals as well as medium vessel, multivessel and posterior circulation occlusions. In this article, we discuss the practical aspects of ColorViz in patients presenting with AIS.

Indexed as

ColorVizPial CollateralsStroke

Identifiers

PMID35510241
PMCPMC9062937
OpenAlexW4224433772

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.