Evidence map›Paper›PMID 39108672›Full record

ArticleFrontiers in cardiovascular medicine2024

Improving image quality and in-stent restenosis diagnosis with high-resolution "double-low" coronary CT angiography in patients after percutaneous coronary intervention.

Wenjie Wu, Hefeng Zhan, Yiran Wang, Xueyan Ma, Jiameng Hou, Lichen Ren, Jie Liu, Luotong Wang, Yonggao Zhang

Abstract read
In one paragraph

Article in Frontiers in cardiovascular medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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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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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Wenjie WuDepartment of Radiology, First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Hefeng ZhanDepartment of Radiology, First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Yiran WangDepartment of Radiology, First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Xueyan MaDepartment of Radiology, First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Jiameng HouDepartment of Radiology, First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Lichen RenDepartment of Radiology, First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Jie LiuDepartment of Radiology, First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Luotong WangCT Imaging Research Center, GE Healthcare China, Beijing, China.
Yonggao ZhangDepartment of Radiology, First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aims to investigate the image quality of a high-resolution, low-dose coronary CT angiography (CCTA) with deep learning image reconstruction (DLIR) and second-generation motion correction algorithms, namely, SnapShot Freeze 2 (SSF2) algorithm, and its diagnostic accuracy for in-stent restenosis (ISR) in patients after percutaneous coronary intervention (PCI), in comparison with standard-dose CCTA with high-definition mode reconstructed by adaptive statistical iterative reconstruction Veo algorithm (ASIR-V) and the first-generation motion correction algorithm, namely, SnapShot Freeze 1 (SSF1). Methods: Patients after PCI and suspected of having ISR scheduled for high-resolution CCTA (randomly for 100 kVp low-dose CCTA or 120 kVp standard-dose) and invasive coronary angiography (ICA) were prospectively enrolled in this study. After the basic information pairing, a total of 105 patients were divided into the LD group (60 patients underwent 100 kVp low-dose CCTA reconstructed with DLIR and SSF2) and the SD group (45 patients underwent 120 kVp standard-dose CCTA reconstructed with ASIR-V and SSF1). Radiation and contrast medium doses, objective image quality including CT value, image noise (standard deviation), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) for the aorta, left main artery (LMA), left ascending artery (LAD), left circumflex artery (LCX), and right coronary artery (RCA) of the two groups were compared. A five-point scoring system was used for the overall image quality and stent appearance evaluation. Binary ISR was defined as an in-stent neointimal proliferation with diameter stenosis ≥50% to assess the diagnostic performance between the LD group and SD group with ICA as the standard reference. Results: The LD group achieved better objective and subjective image quality than that of the SD group even with 39.1% radiation dose reduction and 28.0% contrast media reduction. The LD group improved the diagnostic accuracy for coronary ISR to 94.2% from the 83.8% of the SD group on the stent level and decreased the ratio of false-positive cases by 19.2%. Conclusion: Compared with standard-dose CCTA with ASIR-V and SSF1, the high-resolution, low-dose CCTA with DLIR and SSF2 reconstruction algorithms further improves the image quality and diagnostic performance for coronary ISR at 39.1% radiation dose reduction and 28.0% contrast dose reduction.

Indexed as

coronary CT angiographydeep learning image reconstruction algorithmin-stent restenosispercutaneous coronary interventionSnapShot Freeze 2

Identifiers

PMID39108672
PMCPMC11300262

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