Evidence map›Paper›PMID 36672124›Full record

ReviewBrain sciences2023

Imaging and Hemodynamic Characteristics of Vulnerable Carotid Plaques and Artificial Intelligence Applications in Plaque Classification and Segmentation.

Na Han, Yurong Ma, Yan Li, Yu Zheng, Chuang Wu, Tiejun Gan, Min Li, Laiyang Ma, Jing Zhang

Open access · goldAbstract readReview
In one paragraph

Review in Brain sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
4.1field-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

14 citing papers in PubMed, 16 citations in OpenAlex.

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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

9 authors at 2 institutions in 1 country.

Na HanDepartment of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou 730030, China.ORCID 0000-0003-2322-4405
Yurong MaDepartment of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou 730030, China.
Yan LiSchool of Mathematics and Statistics, Lanzhou University, Lanzhou 730030, China.
Yu ZhengDepartment of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou 730030, China.
Chuang WuDepartment of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou 730030, China.
Tiejun GanDepartment of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou 730030, China.
Min LiDepartment of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou 730030, China.
Laiyang MaDepartment of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou 730030, China.
Jing ZhangDepartment of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou 730030, China.
Lanzhou University Second Hospital · CNLanzhou University · CN

Funding

Gansu Province Clinical Research Center for Functional and Molecular Imaging 21JR7RA438Health Industry Research Program Funding Project of Gansu Province GSWSKY-2019-09Lanzhou University Second Hospital ‟Cuiying Technology Innovation Plan" Applied Basic Research Project CY2018-MS02National Natural Science Foundation of China 81960309Scientific Research Cultivation Plan of Cuiying Students in Lanzhou University Second Hospital CYXZ2021-33Special Fund for the Cultivation of Doctoral Candidate in Lanzhou University Second Hospital YJS-BD-28
6 · The paper itself

Abstract

Stroke is a massive public health problem. The rupture of vulnerable carotid atherosclerotic plaques is the most common cause of acute ischemic stroke (AIS) across the world. Currently, vessel wall high-resolution magnetic resonance imaging (VW-HRMRI) is the most appropriate and cost-effective imaging technique to characterize carotid plaque vulnerability and plays an important role in promoting early diagnosis and guiding aggressive clinical therapy to reduce the risk of plaque rupture and AIS. In recent years, great progress has been made in imaging research on vulnerable carotid plaques. This review summarizes developments in the imaging and hemodynamic characteristics of vulnerable carotid plaques on the basis of VW-HRMRI and four-dimensional (4D) flow MRI, and it discusses the relationship between these characteristics and ischemic stroke. In addition, the applications of artificial intelligence in plaque classification and segmentation are reviewed.

Indexed as

4D flowartificial intelligencestrokevulnerable plaqueVW-HRMRI

Identifiers

PMID36672124
PMCPMC9856903
OpenAlexW4316371406

What Socratic 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 Socratic graph.