{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T22:31:01Z","timestamp":1777501861261,"version":"3.51.4"},"reference-count":35,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2023,6,2]],"date-time":"2023-06-02T00:00:00Z","timestamp":1685664000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Cardiovasc. Med."],"abstract":"<jats:sec><jats:title>Purpose<\/jats:title><jats:p>To explore the potential of perivascular fat attenuation index (FAI) and coronary computed tomography angiography (CCTA) derived fractional flow reserve (CT-FFR) in the identification of culprit lesion leading to subsequent acute coronary syndrome (ACS).<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Thirty patients with documented ACS event who underwent invasive coronary angiography (ICA) from February 2019 to February 2021 and had received CCTA in the previous 6 months were collected retrospectively. 40 patients with stable angina pectoris (SAP) were matched as control group according to sex, age and risk factors. The study population has a mean age of 59.3\u2009\u00b1\u200912.3 years, with a male prevalence of 81.4%. The plaque characteristics, perivascular fat attenuation index (FAI), and coronary computed tomography angiography-derived fractional flow reserve (CT-FFR) of 32 culprit lesions and 30 non-culprit lesions in ACS patients and 40 highest-grade stenosis lesions in SAP patients were statistically analyzed.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>FAI around culprit lesions was increased significantly (\u221272.4\u2009\u00b1\u20093.2 HU vs. \u221279.0\u2009\u00b1\u20097.7 HU, vs. \u221280.4\u2009\u00b1\u20097.0HU, all <jats:italic>p<\/jats:italic>\u2009&amp;lt;\u20090.001) and CT-FFR was decreased for culprit lesions of ACS patients [0.7(0.1) vs. 0.8(0.1), vs.0.8(0.1), <jats:italic>p\u2009<\/jats:italic>&amp;lt;\u20090.001] compared to other lesions. According to multivariate analysis, diameter stenosis (DS), FAI, and CT-FFR were significant predictors for identification of the culprit lesion. The integration model of DS, FAI, and CT-FFR showed the significantly highest area under the curve (AUC) of 0.917, compared with other single predictors (all <jats:italic>p<\/jats:italic>\u2009&amp;lt;\u20090.05).<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>This study proposes a novel integrated prediction model of DS, FAI, and CT-FFR that enhances the diagnostic accuracy of traditional CCTA for identifying culprit lesions that trigger ACS. Furthermore, this model also provides improved risk stratification for patients and offers valuable insights for predicting future cardiovascular events.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fcvm.2023.1090397","type":"journal-article","created":{"date-parts":[[2023,6,2]],"date-time":"2023-06-02T14:34:11Z","timestamp":1685716451000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["Clinical value of perivascular fat attenuation index and computed tomography derived fractional flow reserve in identification of culprit lesion of subsequent acute coronary syndrome"],"prefix":"10.3389","volume":"10","author":[{"given":"Minggang","family":"Huang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tingting","family":"Han","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuan","family":"Nie","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shunming","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Di","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yue","family":"Mu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yan","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2023,6,2]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"144","DOI":"10.1001\/jamacardio.2017.4973","article-title":"Use of high-risk coronary atherosclerotic plaque detection for risk stratification of patients with stable chest pain: a secondary analysis of the PROMISE randomized clinical trial","volume":"3","author":"Ferencik","year":"2018","journal-title":"JAMA Cardiol"},{"key":"B2","doi-asserted-by":"publisher","first-page":"e007657","DOI":"10.1161\/circimaging.118.007657","article-title":"Coronary computed tomography angiography- specific definitions of high-risk plaque features improve detection of acute coronary syndrome","volume":"11","author":"Bittner","year":"2018","journal-title":"Circ Cardiovasc Imaging"},{"key":"B3","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1056\/NEJM199901143400207","article-title":"Atherosclerosis\u2013an inflammatory disease","volume":"340","author":"Ross","year":"1999","journal-title":"N Engl J Med"},{"key":"B4","doi-asserted-by":"publisher","first-page":"eaal2658","DOI":"10.1126\/scitranslmed.aal2658","article-title":"Detecting human coronary inflammation by imaging perivascular fat","volume":"9","author":"Antonopoulos","year":"2017","journal-title":"Sci Transl Med"},{"key":"B5","doi-asserted-by":"publisher","first-page":"929","DOI":"10.1016\/s0140-6736(18)31114-0","article-title":"Non-invasive detection of coronary inflammation using computed tomography and prediction of residual cardiovascular risk (the CRISP CT study): a posthoc analysis of prospective outcome data","volume":"392","author":"Oikonomou","year":"2018","journal-title":"Lancet"},{"key":"B6","doi-asserted-by":"publisher","first-page":"881","DOI":"10.1161\/circimaging.113.000297","article-title":"Noninvasive fractional flow reserve derived from computed tomography angiography for coronary lesions of intermediate stenosis severity: results from the DeFACTO study","volume":"6","author":"Nakazato","year":"2013","journal-title":"Circ Cardiovasc Imaging"},{"key":"B7","doi-asserted-by":"publisher","first-page":"1145","DOI":"10.1016\/j.jacc.2013.11.043","article-title":"Diagnostic performance of noninvasive fractional flow reserve derived from coronary computed tomography angiography in suspected coronary artery disease: the NXT trial (analysis of coronary blood flow using CT angiography: next steps)","volume":"63","author":"N\u00f8rgaard","year":"2014","journal-title":"J Am Coll Cardiol"},{"key":"B8","doi-asserted-by":"publisher","first-page":"1989","DOI":"10.1016\/j.jacc.2011.06.066","article-title":"Diagnosis of ischemia-causing coronary stenoses by noninvasive fractional flow reserve computed from coronary computed tomographic angiograms. 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