Evidence map›Paper›PMID 41312544›Full record

ReviewInternational journal of cardiology. Cardiovascular risk and prevention2025

Noninvasive coronary imaging: Technological breakthroughs and the integrated application of coronary magnetic resonance angiography.

Yiming Sang, Shuang Li, Hui Wang, Hongkai Zhang, Baiyan Zhuang, Lei Xu

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in International journal of cardiology. Cardiovascular risk and prevention, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

6 authors.

Yiming SangDepartment of Radiology, Beijing Anzhen Hospital, Beijing Institute of Heart, Lung, and Blood Vessel Diseases, Capital Medical University, China.
Shuang LiDepartment of Radiology, Beijing Anzhen Hospital, Beijing Institute of Heart, Lung, and Blood Vessel Diseases, Capital Medical University, China.
Hui WangDepartment of Radiology, Beijing Anzhen Hospital, Beijing Institute of Heart, Lung, and Blood Vessel Diseases, Capital Medical University, China.
Hongkai ZhangDepartment of Radiology, Beijing Anzhen Hospital, Beijing Institute of Heart, Lung, and Blood Vessel Diseases, Capital Medical University, China.
Baiyan ZhuangDepartment of Radiology, Beijing Anzhen Hospital, Beijing Institute of Heart, Lung, and Blood Vessel Diseases, Capital Medical University, China.
Lei XuDepartment of Radiology, Beijing Anzhen Hospital, Beijing Institute of Heart, Lung, and Blood Vessel Diseases, Capital Medical University, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the growing demand for coronary artery visualization and the diagnosis of coronary artery disease, noninvasive coronary imaging modalities have gained significance. Coronary magnetic resonance angiography (CMRA) is a promising technique as it is noninvasive and does not involve ionizing radiation or iodinated contrast agents. Although certain limitations in this technology have prevented its application as a first-line clinical imaging modality, its immense developmental potential has positioned it as a focal point of research. This review discusses the advancements in CMRA across multiple technical domains-including motion correction, imaging acceleration, and integration with artificial intelligence-as well as its current clinical status and future prospects.

Indexed as

5.0TCompressed sensingCoronary magnetic resonance angiographyFat suppressionNavigator

Identifiers

PMID41312544
PMCPMC12650774

What OpenQuestion holds

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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.