Evidence map›Paper›PMID 39698647›Full record

ArticleQuantitative imaging in medicine and surgery2024

Diffusion-derived vessel density (DDVD) for penumbra delineation in brain acute ischemic stroke: initial proof-of-concept results using single NEX DWI.

Jian-Qiang Chen, Cai-Ying Li, Wen Wang, Dian-Qi Yao, Ri-Feng Jiang, Yì Xiáng J Wáng

Abstract read
In one paragraph

Article in Quantitative imaging in medicine and surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

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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

11 citing papers in PubMed.

  1. Article
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  8. MRI signal simulation of liverQuantitative imaging in medicine and surgery · 2025
    Article
  9. Article
  10. Influences of the second motion probing gradientQuantitative imaging in medicine and surgery · 2025
    Article
  11. 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.

Jian-Qiang Chen *Department of Radiology, The First Affiliated Hospital of Hainan Medical University, Haikou, China.
Cai-Ying Li *Department of Imaging and Interventional Radiology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China.
Wen WangDepartment of Radiology, The First Affiliated Hospital of Hainan Medical University, Haikou, China.
Dian-Qi YaoDepartment of Imaging and Interventional Radiology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China.
Ri-Feng JiangDepartment of Radiology, Fujian Medical University Union Hospital, Fuzhou, China.
Yì Xiáng J WángDepartment of Imaging and Interventional Radiology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China.ORCID https://orcid.org/0000-0001-5697-0717

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Neuroimaging is a cornerstone in the diagnosis and treatment decision-making for brain acute ischemic stroke. A rapid and accurate diagnosis is the key, specifically for time-critical reperfusion therapies. Successful reperfusion of salvageable penumbra can reduce the extent of ischemic stroke and thus improve clinical outcomes, whereas reperfusion of irreversibly affected brain tissue is thought to be futile and may result in harm due to the risk of hemorrhagic transformation. For neuroimaging work-up of acute stroke, computed tomography (CT) is more commonly applied than magnetic resonance imaging (MRI), due to the wider availability of CT scanners in emergency settings. However, the CT perfusion readout thresholds to define infarct area remain controversial. Diffusion-weighted (DW) MRI remains the best imaging modality to define the infarct area. Low-cost portable MRI scanners are available in recent years. MRI diffusion-derived vessel density (DDVD) reflects

Indexed as

acute ischemic strokeCerebral blood perfusiondiffusion-weighted imaging (DWI)ischemic penumbra

Identifiers

PMID39698647
PMCPMC11651923

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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.