Evidence map›Paper›PMID 40384682›Full record

ArticleQuantitative imaging in medicine and surgery2025

Free-breathing pediatric cardiac dark-blood imaging with reverse double inversion-recovery and single-shot deep learning reconstruction.

Yixin Emu, Quanli Shen, Qiong Yao, Guanke Cai, Zhuo Chen, Junpu Hu, Chenxi Hu, Xihong Hu

Abstract read
In one paragraph

Article in Quantitative imaging in medicine and surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Yixin Emu *National Engineering Research Center of Advanced Magnetic Resonance Technologies for Diagnosis and Therapy, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.ORCID https://orcid.org/0009-0000-9420-9208
Quanli Shen *Department of Radiology, Children's Hospital of Fudan University, Shanghai, China.
Qiong YaoDepartment of Radiology, Children's Hospital of Fudan University, Shanghai, China.
Guanke CaiDepartment of Radiology, Children's Hospital of Fudan University, Shanghai, China.
Zhuo ChenNational Engineering Research Center of Advanced Magnetic Resonance Technologies for Diagnosis and Therapy, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
Junpu HuUnited Imaging Healthcare Co. Ltd., Shanghai, China.
Chenxi HuNational Engineering Research Center of Advanced Magnetic Resonance Technologies for Diagnosis and Therapy, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
Xihong HuDepartment 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: Dark-blood T2-weighted fast spin-echo (DB-FSE) is sensitive to motion, leading to signal dropout artifacts and ghosting artifacts in free-breathing pediatric cardiac imaging, which severely impairs its diagnostic quality. Here, we aimed to fulfill high-resolution motion-robust edema assessment during free-breathing by combining reverse double inversion recovery (RDIR) and single-shot DB-FSE based on artificial intelligence (AI)-assisted compressed sensing (ACS) reconstruction. Methods: This prospective study included 20 healthy children and 47 pediatric patients. Three imaging techniques were compared: routine multi-shot DB-FSE based on double inversion recovery (MS-DIR), multi-shot DB-FSE based on RDIR (MS-RDIR), and single-shot DB-FSE based on RDIR (SS-RDIR) with ACS reconstruction. These methods were compared via quantitative metrics, including total acquisition time, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR), and qualitative metrics, including myocardial visibility, ghosting artifacts, and overall quality. Results: In healthy children, the total acquisition time (seconds) of SS-RDIR (64.8±21.8) was significantly less than those of MS-DIR (222.5±69.3, P<0.001) and MS-RDIR (234.0±64.1, P<0.001). The SNR and CNR were comparable (P=0.094 for SNR and P=0.054 for CNR). Ghosting artifacts were significantly reduced in SS-RDIR (4.70±0.18) compared to MS-DIR (3.95±0.28, P<0.001) and MS-RDIR (3.97±0.31, P<0.001), whereas overall quality was improved in SS-RDIR (4.42±0.19) compared to MS-DIR (3.87±0.27, P=0.004) and MS-RDIR (3.95±0.34, P=0.010). In patients, SS-RDIR significantly reduced the total acquisition time compared to MS-DIR (62.1±24.0 Conclusions: SS-RDIR with ACS reconstruction offers substantially shorter scan time and superior image quality than traditional multi-shot techniques. This approach enhances clinical workflow and patient comfort, facilitating a broader application of DB-FSE in pediatric cardiac imaging.

Indexed as

artificial intelligence (AI)Dark bloodfree-breathingpediatric imagingT2-weighted imaging

Identifiers

PMID40384682
PMCPMC12082608

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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.