Evidence map›Paper›PMID 37145148›Full record

ArticleEuropean radiology2023

Fully automated pixel-wise quantitative CMR-myocardial perfusion with CMR-coronary angiography to detect hemodynamically significant coronary artery disease.

Shi-Hai Zhao, Wei-Feng Guo, Zhi-Feng Yao, Shan Yang, Hong Yun, Yin-Yin Chen, Tong-Tong Han, Xiao-Yue Zhou, Cai-Xia Fu, Meng-Su Zeng and 3 more

Abstract read
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Article in European radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.8field-weighted citation impact, top 10% 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

6 citing papers in PubMed, 12 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

13 authors at 5 institutions in 2 countries.

Shi-Hai Zhao *Department of Radiology, Zhongshan Hospital, Fudan University and Shanghai Institute of Medical Imaging, Shanghai, China.
Wei-Feng Guo *Department of Radiology, Zhongshan Hospital, Fudan University and Shanghai Institute of Medical Imaging, Shanghai, China.
Zhi-Feng YaoDepartment of Cardiology, Zhongshan Hospital, Fudan University and Shanghai Institute of Cardiovascular Diseases, Shanghai, China.
Shan YangDepartment of Radiology, Zhongshan Hospital, Fudan University and Shanghai Institute of Medical Imaging, Shanghai, China.
Hong YunDepartment of Radiology, Zhongshan Hospital, Fudan University and Shanghai Institute of Medical Imaging, Shanghai, China.
Yin-Yin ChenDepartment of Radiology, Zhongshan Hospital, Fudan University and Shanghai Institute of Medical Imaging, Shanghai, China.
Tong-Tong HanCircle Cardiovascular Imaging, Calgary, Alberta, Canada.
Xiao-Yue ZhouMR Collaboration, Siemens Healthineers Ltd., Shanghai, China.
Cai-Xia FuSiemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China.
Meng-Su ZengDepartment of Radiology, Zhongshan Hospital, Fudan University and Shanghai Institute of Medical Imaging, Shanghai, China. mengsuzeng@sina.com.
Chen-Guang LiDepartment of Cardiology, Zhongshan Hospital, Fudan University and Shanghai Institute of Cardiovascular Diseases, Shanghai, China. lichenguangzs@163.com.
Cui-Zhen PanDepartment of Echocardiography, Zhongshan Hospital, Fudan University, Shanghai, China.
Hang JinDepartment of Radiology, Zhongshan Hospital, Fudan University and Shanghai Institute of Medical Imaging, Shanghai, China. ZS_jinhang@163.com.
Shanghai Medical College of Fudan University · CNFudan University · CNZhongshan Hospital · CNSiemens (China) · CNCircle Cardiovascular Imaging · CA

Funding

Science Foundation of Shanghai Municipal Health Commission 202040349Science Foundation of Shanghai Municipal Health Commission 202140291Shanghai Municipal Key Clinical Specialty shslczdzk03202Shanghai Pujiang Program 21PJD012Shanghai Science and Technology Committee 18DZ1930102
6 · The paper itself

Abstract

objectivesWe applied a fully automated pixel-wise post-processing framework to evaluate fully quantitative cardiovascular magnetic resonance myocardial perfusion imaging (CMR-MPI). In addition, we aimed to evaluate the additive value of coronary magnetic resonance angiography (CMRA) to the diagnostic performance of fully automated pixel-wise quantitative CMR-MPI for detecting hemodynamically significant coronary artery disease (CAD).

methodsA total of 109 patients with suspected CAD were prospectively enrolled and underwent stress and rest CMR-MPI, CMRA, invasive coronary angiography (ICA), and fractional flow reserve (FFR). CMRA was acquired between stress and rest CMR-MPI acquisition, without any additional contrast agent. Finally, CMR-MPI quantification was analyzed by a fully automated pixel-wise post-processing framework.

resultsOf the 109 patients, 42 patients had hemodynamically significant CAD (FFR ≤ 0.80 or luminal stenosis ≥ 90% on ICA) and 67 patients had hemodynamically non-significant CAD (FFR ˃ 0.80 or luminal stenosis < 30% on ICA) were enrolled. On the per-territory analysis, patients with hemodynamically significant CAD had higher myocardial blood flow (MBF) at rest, lower MBF under stress, and lower myocardial perfusion reserve (MPR) than patients with hemodynamically non-significant CAD (p < 0.001). The area under the receiver operating characteristic curve of MPR (0.93) was significantly larger than those of stress and rest MBF, visual assessment of CMR-MPI, and CMRA (p < 0.05), but similar to that of the integration of CMR-MPI with CMRA (0.90).

conclusionsFully automated pixel-wise quantitative CMR-MPI can accurately detect hemodynamically significant CAD, but the integration of CMRA obtained between stress and rest CMR-MPI acquisition did not provide significantly additive value. KEY POINTS: • Full quantification of stress and rest cardiovascular magnetic resonance myocardial perfusion imaging can be postprocessed fully automatically, generating pixel-wise myocardial blood flow (MBF) and myocardial perfusion reserve (MPR) maps. • Fully quantitative MPR provided higher diagnostic performance for detecting hemodynamically significant coronary artery disease, compared with stress and rest MBF, qualitative assessment, and coronary magnetic resonance angiography (CMRA). • The integration of CMRA and MPR did not significantly improve the diagnostic performance of MPR alone.

Indexed as

Coronary Artery DiseaseCoronary StenosisFractional Flow Reserve, MyocardialMyocardial Perfusion ImagingConstriction, PathologicCoronary AngiographyHumansPerfusionPredictive Value of TestsCoronary angiographyCoronary artery diseaseFractional flow reserve, myocardialMagnetic resonance angiographyMyocardial perfusion imaging

Identifiers

PMID37145148
OpenAlexW4372317432

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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 OpenQuestion graph.