Evidence map›Paper›PMID 40785922›Full record

ArticleQuantitative imaging in medicine and surgery2025

Predicting chronic stenosis progression of stable coronary artery disease using peri-coronary fat attenuation index derived from coronary computed tomography angiography.

Wanyue Huang, Junzhe Wen, Yuefei Guo, Yani Duan, Yanqiu Zhu, Mingming Liu, Chao Li, Zongzheng Yang, Zhiping Lin, Jie Qin and 1 more

Abstract read
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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. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Wanyue Huang *Department of Radiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.ORCID https://orcid.org/0000-0002-6348-2882
Junzhe Wen *Department of Radiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.ORCID https://orcid.org/0009-0009-8735-7531
Yuefei GuoDepartment of Radiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Yani DuanDepartment of Radiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Yanqiu ZhuDepartment of Radiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Mingming LiuDepartment of Radiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Chao LiDepartment of Radiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Zongzheng YangDepartment of Radiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Zhiping LinGE Healthcare, Guangzhou, China.
Jie QinDepartment of Radiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.ORCID https://orcid.org/0000-0002-0550-457X
Mingsheng HuangDepartment of Interventional Radiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.ORCID https://orcid.org/0000-0003-4749-4231

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Stable coronary artery disease (CAD), a common condition in CAD, often requires monitoring and treatment. However, predicting its chronic stenosis progression remains challenging. Peri-coronary fat attenuation index (FAI), a quantitative parameter derived from coronary computed tomography angiography (CCTA), may provide valuable information for predicting the chronic stenosis progression of CAD. By examining the relationship between peri-coronary FAI and chronic stenosis progression in three different coronary arteries, we aimed to address a critical knowledge gap in the field of cardiovascular disease prevention and treatment. Methods: A retrospective analysis of 145 stable CAD patients' CCTA images revealed stenosis degree, plaque properties, and quantitative parameters. Patients were divided into progression and no progression groups at three coronary artery levels. Intergroup comparison, univariate and multivariate logistic regression analyses were applied to identify predictors of stenosis progression in each coronary artery. Additionally, subgroup analyses of FAI based on different study intervals were performed. Results: Stenosis progression was most commonly seen in the left anterior descending artery (LAD), especially in its proximal and middle segments. Peri-coronary FAI was significantly higher in the progression group than it was in the no progression group [-72.2±7.8 Conclusions: Baseline peri-coronary FAI is valuable in predicting chronic coronary stenosis progression that occurs within a short period (within 1 year) in RCA, and, potentially, in LM + CX. Stenosis progression in LAD might be mainly driven by factors other than coronary inflammation.

Indexed as

coronary computed tomography angiography (CCTA)maximal area stenosisperi-coronary fat attenuation index (FAI)Stable coronary artery disease (stable CAD)stenosis progression

Identifiers

PMID40785922
PMCPMC12332561

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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.