Evidence mapPaperPMID 42250883Full record

ArticleJournal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance2026

Fully automated free-breathing cardiac magnetic resonance imaging at 3T: A prospective randomized study of image quality, efficiency, and workflow burden.

Keyi Li, Wenli Zhou, Xinling Yang, Lin Chen, Xuan Qin, Chen Cui, Kai Yang, Weipeng Yan, Wenhao Dong, Lele Liu and 7 more

Abstract read
In one paragraph

Article in Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

17 authors.

Keyi LiDepartment of Radiology, Imaging Center, Fuwai Hospital and National Center for Cardiovascular Diseases, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China; Department of Radiology, The First Hospital of Jiaxing & The Affiliated Hospital of Jiaxing University, Jiaxing, China.
Wenli ZhouDepartment of Radiology, Imaging Center, Fuwai Hospital and National Center for Cardiovascular Diseases, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China.
Xinling YangDepartment of Radiology, Imaging Center, Fuwai Hospital and National Center for Cardiovascular Diseases, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China.
Lin ChenDepartment of Radiology, Imaging Center, Fuwai Hospital and National Center for Cardiovascular Diseases, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China.
Xuan QinDepartment of Radiology, Imaging Center, Fuwai Hospital and National Center for Cardiovascular Diseases, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China; Department of Radiology, The First Hospital of Jiaxing & The Affiliated Hospital of Jiaxing University, Jiaxing, China.
Chen CuiDepartment of Radiology, Imaging Center, Fuwai Hospital and National Center for Cardiovascular Diseases, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China.
Kai YangDepartment of Radiology, Imaging Center, Fuwai Hospital and National Center for Cardiovascular Diseases, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China.
Weipeng YanDepartment of Radiology, Imaging Center, Fuwai Hospital and National Center for Cardiovascular Diseases, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China.
Wenhao DongDepartment of Radiology, Imaging Center, Fuwai Hospital and National Center for Cardiovascular Diseases, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China.
Lele LiuDepartment of Radiology, Imaging Center, Fuwai Hospital and National Center for Cardiovascular Diseases, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China.
Jialin SongDepartment of Radiology, Imaging Center, Fuwai Hospital and National Center for Cardiovascular Diseases, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China.
Jing AnDL Department, Siemens Shenzhen Magnetic Resonance Ltd., Guangdong, China.
Jens WetzlMR Application Predevelopment, Siemens Healthineers AG, Forchheim, Germany.
Michaela SchmidtMR Application Predevelopment, Siemens Healthineers AG, Forchheim, Germany.
Shihua ZhaoDepartment of Radiology, Imaging Center, Fuwai Hospital and National Center for Cardiovascular Diseases, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China.
Gang YinDepartment of Radiology, Imaging Center, Fuwai Hospital and National Center for Cardiovascular Diseases, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China. Electronic address: cardiacbmeyg@163.com.
Minjie LuDepartment of Radiology, Imaging Center, Fuwai Hospital and National Center for Cardiovascular Diseases, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China. Electronic address: coolkan@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAutomation in cardiovascular magnetic resonance (CMR) scans holds the potential to improve examination efficiency and workflow consistency. Prospective clinical evidence validating automated scan workflows in routine CMR practice remains limited.

methodsIn this prospective randomized study, consecutive patients referred for non-stress CMR were assigned to either an automated or a manual free-breathing scanning workflow. The fully automated workflow integrated automated plane prescription of multiple steps required for successful image acquisition. The primary endpoint was total examination time; secondary endpoints included plane prescription accuracy, image quality scores, scanner idle time, and technologist workload.

resultsOf 255 screened patients, 221 were included (automated, n = 109; manual, n = 112). All examinations were diagnostically adequate. The automated and manual workflows showed a similarly low incidence of plane prescription misalignment, corresponding to 19.3% (21/109) and 17.9% (20/112) misalignment events per examination, respectively, with no significant difference between groups (0.19 vs. 0.18 events per examination, P = 0.780). No significant differences were observed across imaging planes or technologist experience levels, and image quality scores were comparable between workflows (2.74 ± 0.67 vs. 2.69 ± 0.70, P = 0.547). However, the automated scanning workflow significantly reduced total examination time (19.16 ± 2.32 vs. 21.25 ± 2.25 min, P < 0.001) and scanner idle time (7.80 ± 1.80 vs. 10.12 ± 2.03 min, P < 0.001), with consistent savings across all experience levels. Operator workload was also substantially lower with automated scanning, evidenced by fewer mouse clicks and keystrokes (both P < 0.01).

conclusionsAn automated CMR scanning workflow improves examination efficiency and reduces operator workload without compromising image quality or plane prescription accuracy, supporting its integration in routine clinical CMR practice.

Indexed as

artificial intelligenceautomated workflowcardiac magnetic resonance

Identifiers

PMID42250883
PMCPMC13292677

What Socratic holds

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LicenceCC BY-NC-ND
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Registered trials

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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 Socratic graph.