Evidence map›Paper›PMID 34778395›Full record

ReviewFrontiers in cardiovascular medicine2021

Magnetic Resonance Texture Analysis in Myocardial Infarction.

Fei Peng, Tian Zheng, Xiaoping Tang, Qiao Liu, Zijing Sun, Zhaofeng Feng, Heng Zhao, Lianggeng Gong

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in cardiovascular medicine, 2021. 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
0.4field-weighted citation impact, top 37% 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

4 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Advances in using biomaterials for repairing thin endometrium.Frontiers in bioengineering and biotechnology · 2025
    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 3 institutions in 1 country.

Fei PengDepartment of Medical Imaging Center, Second Affiliated Hospital of Nanchang University, Nanchang, China.
Tian ZhengDepartment of Medical Imaging Center, Second Affiliated Hospital of Nanchang University, Nanchang, China.
Xiaoping TangDepartment of Medical Imaging Center, Second Affiliated Hospital of Nanchang University, Nanchang, China.
Qiao LiuDepartment of Medical Imaging Center, Second Affiliated Hospital of Nanchang University, Nanchang, China.
Zijing SunDepartment of Medical Imaging Center, Second Affiliated Hospital of Nanchang University, Nanchang, China.
Zhaofeng FengDepartment of Medical Imaging Center, Second Affiliated Hospital of Nanchang University, Nanchang, China.
Heng ZhaoDepartment of Radiology, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, China.
Lianggeng GongDepartment of Medical Imaging Center, Second Affiliated Hospital of Nanchang University, Nanchang, China.
Nanchang University · CNSecond Affiliated Hospital of Nanchang University · CNUniversity of South China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Texture analysis (TA) is a newly arisen field that can detect the invisible MRI signal changes among image pixels. Myocardial infarction (MI) is cardiomyocyte necrosis caused by myocardial ischemia and hypoxia, becoming the primary cause of death and disability worldwide. In recent years, various TA studies have been performed in patients with MI and show a good clinical application prospect. This review briefly presents the main pathogenesis and pathophysiology of MI, introduces the overview and workflow of TA, and summarizes multiple magnetic resonance TA (MRTA) clinical applications in MI. We also discuss the facing challenges currently for clinical utilization and propose the prospect.

Indexed as

machine learningmagnetic resonance imagingmyocardial infarctionstratifying risktexture analysis (TA)

Identifiers

PMID34778395
PMCPMC8581163
OpenAlexW3208558634

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.