Evidence mapPaperPMID 41809772Full record

ArticleInternational journal of cardiology. Heart & vasculature2026

Vessel-specific perivascular fat attenuation index derived from AI-CCTA and its association with impaired coronary flow reserve in patients with INOCA.

Jing Ni, Ting Wang, Haoran Guo, Ajay Kumar Chaudhary, Zekun Pang, Fukai Zhao, Yue Chen, Jiao Wang, Jianming Li

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Article in International journal of cardiology. Heart & vasculature, 2026. 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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5 · Who and what money

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9 authors.

Jing NiClinical College of Cardiovascular Diseases, Tianjin Medical University, China.
Ting WangClinical College of Cardiovascular Diseases, Tianjin Medical University, China.
Haoran GuoClinical College of Cardiovascular Diseases, Tianjin Medical University, China.
Ajay Kumar ChaudharyClinical College of Cardiovascular Diseases, Tianjin Medical University, China.
Zekun PangDepartment of Nuclear Medicine, TEDA International Cardiovascular Hospital, Tianjin 300457, China.
Fukai ZhaoDepartment of Nuclear Medicine, TEDA International Cardiovascular Hospital, Tianjin 300457, China.
Yue ChenDepartment of Nuclear Medicine, TEDA International Cardiovascular Hospital, Tianjin 300457, China.
Jiao WangDepartment of Nuclear Medicine, TEDA International Cardiovascular Hospital, Tianjin 300457, China.
Jianming LiClinical College of Cardiovascular Diseases, Tianjin Medical University, China.

Funding

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6 · The paper itself

Abstract

Objectives: To investigate the association between artificial intelligence (AI)-derived coronary computed tomography angiography (CCTA) features and impaired coronary flow reserve (CFR) in patients with ischemia and non-obstructive coronary arteries (INOCA). Methods: Retrospective analysis of 101 suspected coronary artery disease (CAD) patients with non-obstructive stenosis (<50%) on CCTA who underwent cadmium-zinc-telluride single photon emission computed tomography (CZT-SPECT). Stratified by coronary flow reserve (CFR) into CFR < 2.0 and CFR ≥ 2.0 groups at patient and vessel levels. Compared AI-CCTA parameters between groups; identified predictors via logistic regression; diagnostic performance was evaluated using receiver operating characteristic (ROC) analysis with Bootstrap internal validation. Results: At the vessel-level, the CFR < 2.0 group had lower coronary artery calcium score (CACS) (62.12 vs. 142.40 AU, P = 0.021) and higher perivascular fat attenuation index (FAI) (-78.69 ± 8.34 vs. -82.03 ± 8.56 HU, P = 0.009). FAI was independently predictor of CFR < 2.0 (OR = 1.043, 95%CI: 1.005 ∼ 1.084, P = 0.028). A combined model integrating AI-CCTA and clinical features showed an apparent AUC of 0.807, but Bootstrap validation yielded a corrected AUC of 0.648. Inverse spatial distributions of CACS (RCA > LAD > LCX) and FAI (LCX > LAD > RCA). Vessels with CFR < 2.0 were characterized by lower calcification and higher FAI. Conclusions: FAI is independently associated with vessel-level CFR impairment in INOCA. The combined model demonstrates potential but requires external validation. The observed inverse spatial and functional relationship between CACS and FAI may reflect different stages or patterns of coronary atherosclerosis in non-obstructive CAD, warranting further investigation.

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PMID41809772
PMCPMC12969458

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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.