Evidence map›Paper›PMID 42865857›Full record

ArticleTranslational pediatrics2026

Application of AI-assisted compressed sensing cine sequence in the assessment of cardiac function in children with Kawasaki disease.

Xin Zhao, Xihong Hu, Yipu Li, Quanli Shen, Yan Zheng, Chengxiang Lin, Kai Lu, Junpu Hu, Lan He, Chenxi Hu and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Translational pediatrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

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4 · The record

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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

12 authors.

Xin ZhaoDepartment of Radiology, Children's Hospital of Fudan University, Shanghai, China.
Xihong HuDepartment of Radiology, Children's Hospital of Fudan University, Shanghai, China.
Yipu LiScience Park, University of Amsterdam, Amsterdam, Netherlands.
Quanli ShenDepartment of Radiology, Children's Hospital of Fudan University, Shanghai, China.
Yan ZhengDepartment of Radiology, Children's Hospital of Fudan University, Shanghai, China.
Chengxiang LinDepartment of Radiology, Children's Hospital of Fudan University, Shanghai, China.
Kai LuUnited Imaging Research, United Imaging Healthcare, Shanghai, China.
Junpu HuUnited Imaging Research, United Imaging Healthcare, Shanghai, China.
Lan HeHeart Center, Children's Hospital of Fudan University, Shanghai, China.
Chenxi HuSchool of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
Guanke CaiDepartment of Radiology, Children's Hospital of Fudan University, Shanghai, China.
Qiong YaoDepartment of Radiology, Children's Hospital of Fudan University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Cardiac magnetic resonance (CMR) imaging is an important tool for assessing the cardiac structure and function in Kawasaki disease. To perform a prospective analysis comparing the newly developed temporal artificial intelligence (AI)-assisted compressed sensing cine (ACS-cine) and conventional cine (Conv-cine) in the assessment of cardiac function in Kawasaki disease patients. Methods: This study included 45 patients (35 males), who were scanned using both ACS-cine and Conv-cine sequences. Left and right ventricular ejection fractions (LVEF and RVEF), left and right ventricular end-systolic volumes (LVESV and RVESV), and left and right ventricular end-diastolic volumes (LVEDV and RVEDV) were measured. The image quality and intraclass correlation coefficient (ICC) of the two methods were also assessed. Results: The mean acquisition time of ACS-cine was significantly shorter than that of Conv-cine (17.18±2.45 Conclusions: ACS-cine technology demonstrates significant time efficiency advantages in CMR with satisfactory image quality, although there are statistically significant differences in the measurement of certain cardiac function parameters (LVEF and LVESV) compared to Conv-cine.

Indexed as

Cardiac magnetic resonance imaging (CMR imaging)childrencine sequencecompressed sensing (CS)Kawasaki disease

Identifiers

PMID42865857
PMCPMC13655866

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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.