{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T15:25:48Z","timestamp":1772119548152,"version":"3.50.1"},"reference-count":27,"publisher":"Springer Science and Business Media LLC","issue":"7","license":[{"start":{"date-parts":[[2023,3,24]],"date-time":"2023-03-24T00:00:00Z","timestamp":1679616000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,3,24]],"date-time":"2023-03-24T00:00:00Z","timestamp":1679616000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82070328"],"award-info":[{"award-number":["82070328"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Medical Big Data Program of PLAGH","award":["2019MBD-035"],"award-info":[{"award-number":["2019MBD-035"]}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2016YFC1300304"],"award-info":[{"award-number":["2016YFC1300304"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int J Cardiovasc Imaging"],"DOI":"10.1007\/s10554-023-02831-z","type":"journal-article","created":{"date-parts":[[2023,3,24]],"date-time":"2023-03-24T01:02:32Z","timestamp":1679619752000},"page":"1323-1332","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Incremental diagnostic value of perivascular fat attenuation index for identifying hemodynamically significant ischemia with severe calcification"],"prefix":"10.1007","volume":"39","author":[{"given":"Dongkai","family":"Shan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yipu","family":"Ding","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xi","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zinuan","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guanhua","family":"Dou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kai","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jing","family":"Jing","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bai","family":"He","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yang","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junjie","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yundai","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,3,24]]},"reference":[{"issue":"1","key":"2831_CR1","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1016\/j.jcmg.2013.07.013","volume":"7","author":"M Kruk","year":"2014","unstructured":"Kruk M, Noll D, Achenbach S et al (2014) Impact of coronary artery calcium characteristics on accuracy of CT angiography. JACC Cardiovasc Imaging 7(1):49\u201358","journal-title":"JACC Cardiovasc Imaging"},{"issue":"4","key":"2831_CR2","doi-asserted-by":"publisher","first-page":"943","DOI":"10.1007\/s10554-011-9902-6","volume":"28","author":"J Abdulla","year":"2012","unstructured":"Abdulla J, Pedersen KS, Budoff M, Kofoed KF (2012) Influence of coronary calcification on the diagnostic accuracy of 64-slice computed tomography coronary angiography: a systematic review and meta-analysis. Int J Cardiovasc Imaging 28(4):943\u2013953","journal-title":"Int J Cardiovasc Imaging"},{"issue":"2","key":"2831_CR3","doi-asserted-by":"publisher","first-page":"300","DOI":"10.1161\/CIRCRESAHA.116.307914","volume":"119","author":"HS Hecht","year":"2016","unstructured":"Hecht HS, Narula J, Fearon WF (2016) Fractional Flow Reserve and Coronary Computed Tomographic Angiography: a review and critical analysis. Circ Res 119(2):300\u2013316","journal-title":"Circ Res"},{"issue":"11","key":"2831_CR4","doi-asserted-by":"publisher","first-page":"1621","DOI":"10.1016\/j.hlc.2020.05.099","volume":"29","author":"N Khav","year":"2020","unstructured":"Khav N, Ihdayhid AR, Ko B (2020) CT-Derived fractional Flow Reserve (CT-FFR) in the evaluation of coronary artery disease. Heart Lung Circ 29(11):1621\u20131632","journal-title":"Heart Lung Circ"},{"issue":"5","key":"2831_CR5","doi-asserted-by":"publisher","first-page":"435","DOI":"10.1016\/j.jacc.2016.05.057","volume":"68","author":"PS Douglas","year":"2016","unstructured":"Douglas PS, De Bruyne B, Pontone G et al (2016) 1-Year outcomes of FFRCT-Guided care in patients with suspected coronary disease: the PLATFORM Study. J Am Coll Cardiol 68(5):435\u2013445","journal-title":"J Am Coll Cardiol"},{"issue":"19","key":"2831_CR6","doi-asserted-by":"publisher","first-page":"1989","DOI":"10.1016\/j.jacc.2011.06.066","volume":"58","author":"BK Koo","year":"2011","unstructured":"Koo BK, Erglis A, Doh JH et al (2011) Diagnosis of ischemia-causing coronary stenoses by noninvasive fractional flow reserve computed from coronary computed tomographic angiograms. Results from the prospective multicenter DISCOVER-FLOW (diagnosis of ischemia-causing Stenoses Obtained Via Noninvasive Fractional Flow Reserve) study. J Am Coll Cardiol 58(19):1989\u20131997","journal-title":"J Am Coll Cardiol"},{"issue":"12","key":"2831_CR7","doi-asserted-by":"publisher","first-page":"1237","DOI":"10.1001\/2012.jama.11274","volume":"308","author":"JK Min","year":"2012","unstructured":"Min JK, Leipsic J, Pencina MJ et al (2012) Diagnostic accuracy of fractional flow reserve from anatomic CT angiography. JAMA 308(12):1237\u20131245","journal-title":"JAMA"},{"issue":"12","key":"2831_CR8","doi-asserted-by":"publisher","first-page":"1145","DOI":"10.1016\/j.jacc.2013.11.043","volume":"63","author":"BL Norgaard","year":"2014","unstructured":"Norgaard BL, Leipsic J, Gaur S et al (2014) 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). J Am Coll Cardiol 63(12):1145\u20131155","journal-title":"J Am Coll Cardiol"},{"issue":"5","key":"2831_CR9","doi-asserted-by":"publisher","first-page":"989","DOI":"10.2214\/AJR.13.11441","volume":"202","author":"J Leipsic","year":"2014","unstructured":"Leipsic J, Yang TH, Thompson A et al (2014) CT angiography (CTA) and diagnostic performance of noninvasive fractional flow reserve: results from the determination of fractional Flow Reserve by anatomic CTA (DeFACTO) study. AJR Am J Roentgenol 202(5):989\u2013994","journal-title":"AJR Am J Roentgenol"},{"key":"2831_CR10","doi-asserted-by":"crossref","unstructured":"Antonopoulos AS, Sanna F, Sabharwal N et al (2017) Detecting human coronary inflammation by imaging perivascular fat.Sci Transl Med9(398)","DOI":"10.1126\/scitranslmed.aal2658"},{"issue":"2","key":"2831_CR11","doi-asserted-by":"publisher","first-page":"673","DOI":"10.1007\/s00330-019-06400-8","volume":"30","author":"M Yu","year":"2020","unstructured":"Yu M, Dai X, Deng J, Lu Z, Shen C, Zhang J (2020) Diagnostic performance of perivascular fat attenuation index to predict hemodynamic significance of coronary stenosis: a preliminary coronary computed tomography angiography study. Eur Radiol 30(2):673\u2013681","journal-title":"Eur Radiol"},{"issue":"10151","key":"2831_CR12","doi-asserted-by":"publisher","first-page":"929","DOI":"10.1016\/S0140-6736(18)31114-0","volume":"392","author":"EK Oikonomou","year":"2018","unstructured":"Oikonomou EK, Marwan M, Desai MY et al (2018) Non-invasive detection of coronary inflammation using computed tomography and prediction of residual cardiovascular risk (the CRISP CT study): a post-hoc analysis of prospective outcome data. Lancet 392(10151):929\u2013939","journal-title":"Lancet"},{"issue":"4 Suppl","key":"2831_CR13","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1161\/01.CIR.51.4.5","volume":"51","author":"WG Austen","year":"1975","unstructured":"Austen WG, Edwards JE, Frye RL et al (1975) A reporting system on patients evaluated for coronary artery disease. Report of the ad Hoc Committee for Grading of Coronary Artery Disease, Council on Cardiovascular surgery, American Heart Association. Circulation 51(4 Suppl):5\u201340","journal-title":"Circulation"},{"key":"2831_CR14","doi-asserted-by":"crossref","unstructured":"Cury RC, Abbara S, Achenbach S et al (2016) An expert consensus document of the Society of Cardiovascular Computed Tomography (SCCT), the American College of Radiology (ACR) and the North American Society for Cardiovascular Imaging (NASCI). Endorsed by the American College of Cardiology. J Cardiovasc Comput Tomogr 10(4):269\u2013281CAD-RADS(TM) Coronary Artery Disease - Reporting and Data System","DOI":"10.1016\/j.jcct.2016.04.005"},{"issue":"4","key":"2831_CR15","doi-asserted-by":"publisher","first-page":"827","DOI":"10.1016\/0735-1097(90)90282-T","volume":"15","author":"AS Agatston","year":"1990","unstructured":"Agatston AS, Janowitz WR, Hildner FJ, Zusmer NR, Viamonte M Jr, Detrano R (1990) Quantification of coronary artery calcium using ultrafast computed tomography. J Am Coll Cardiol 15(4):827\u2013832","journal-title":"J Am Coll Cardiol"},{"issue":"1","key":"2831_CR16","doi-asserted-by":"publisher","first-page":"728","DOI":"10.1186\/s13063-020-04649-9","volume":"21","author":"J Yang","year":"2020","unstructured":"Yang J, Shan D, Dong M et al (2020) The effect of on-site CT-derived fractional flow reserve on the management of decision making for patients with stable chest pain (TARGET trial): objective, rationale, and design. Trials 21(1):728","journal-title":"Trials"},{"issue":"6","key":"2831_CR17","doi-asserted-by":"publisher","first-page":"e007217","DOI":"10.1161\/CIRCIMAGING.117.007217","volume":"11","author":"A Coenen","year":"2018","unstructured":"Coenen A, Kim YH, Kruk M et al (2018) Diagnostic accuracy of a machine-learning Approach to Coronary computed Tomographic Angiography-Based fractional Flow Reserve: result from the MACHINE Consortium. Circ Cardiovasc Imaging 11(6):e007217","journal-title":"Circ Cardiovasc Imaging"},{"issue":"7","key":"2831_CR18","doi-asserted-by":"publisher","first-page":"1563","DOI":"10.1253\/circj.CJ-19-0163","volume":"83","author":"A Kurata","year":"2019","unstructured":"Kurata A, Fukuyama N, Hirai K et al (2019) On-Site computed tomography-derived fractional Flow Reserve using a machine-learning algorithm- clinical effectiveness in a Retrospective Multicenter Cohort. Circ J 83(7):1563\u20131571","journal-title":"Circ J"},{"issue":"3","key":"2831_CR19","doi-asserted-by":"publisher","first-page":"837","DOI":"10.2307\/2531595","volume":"44","author":"ER DeLong","year":"1988","unstructured":"DeLong ER, DeLong DM, Clarke-Pearson DL (1988) Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 44(3):837\u2013845","journal-title":"Biometrics"},{"issue":"6","key":"2831_CR20","doi-asserted-by":"publisher","first-page":"1046","DOI":"10.1016\/j.jcmg.2021.12.010","volume":"15","author":"H Mickley","year":"2022","unstructured":"Mickley H, Veien KT, Gerke O et al (2022) Diagnostic and clinical value of FFR(CT) in stable chest Pain patients with extensive coronary calcification: the FACC study. JACC Cardiovasc Imaging 15(6):1046\u20131058","journal-title":"JACC Cardiovasc Imaging"},{"issue":"9","key":"2831_CR21","doi-asserted-by":"publisher","first-page":"1045","DOI":"10.1016\/j.jcmg.2015.06.003","volume":"8","author":"BL Norgaard","year":"2015","unstructured":"Norgaard BL, Gaur S, Leipsic J et al (2015) Influence of coronary calcification on the diagnostic performance of CT angiography derived FFR in Coronary Artery Disease: a Substudy of the NXT Trial. JACC Cardiovasc Imaging 8(9):1045\u20131055","journal-title":"JACC Cardiovasc Imaging"},{"issue":"3","key":"2831_CR22","doi-asserted-by":"publisher","first-page":"760","DOI":"10.1016\/j.jcmg.2019.06.027","volume":"13","author":"C Tesche","year":"2020","unstructured":"Tesche C, Otani K, De Cecco CN et al (2020) Influence of coronary calcium on diagnostic performance of machine learning CT-FFR: results from MACHINE Registry. JACC Cardiovasc Imaging 13(3):760\u2013770","journal-title":"JACC Cardiovasc Imaging"},{"issue":"15","key":"2831_CR23","doi-asserted-by":"publisher","first-page":"1220","DOI":"10.1093\/eurheartj\/ehv690","volume":"37","author":"S Gaur","year":"2016","unstructured":"Gaur S, Ovrehus KA, Dey D et al (2016) Coronary plaque quantification and fractional flow reserve by coronary computed tomography angiography identify ischaemia-causing lesions. Eur Heart J 37(15):1220\u20131227","journal-title":"Eur Heart J"},{"key":"2831_CR24","doi-asserted-by":"crossref","unstructured":"Brandt V, Decker J, Schoepf UJ et al (2022) Additive value of epicardial adipose tissue quantification to coronary CT angiography-derived plaque characterization and CT fractional flow reserve for the prediction of lesion-specific ischemia. Eur Radiol","DOI":"10.1007\/s00330-021-08481-w"},{"issue":"20","key":"2831_CR25","doi-asserted-by":"publisher","first-page":"1654","DOI":"10.1136\/heartjnl-2017-312324","volume":"104","author":"J Mancio","year":"2018","unstructured":"Mancio J, Oikonomou EK, Antoniades C (2018) Perivascular adipose tissue and coronary atherosclerosis. Heart 104(20):1654\u20131662","journal-title":"Heart"},{"issue":"43","key":"2831_CR26","doi-asserted-by":"publisher","first-page":"3529","DOI":"10.1093\/eurheartj\/ehz592","volume":"40","author":"EK Oikonomou","year":"2019","unstructured":"Oikonomou EK, Williams MC, Kotanidis CP et al (2019) A novel machine learning-derived radiotranscriptomic signature of perivascular fat improves cardiac risk prediction using coronary CT angiography. Eur Heart J 40(43):3529\u20133543","journal-title":"Eur Heart J"},{"issue":"9","key":"2831_CR27","doi-asserted-by":"publisher","first-page":"885","DOI":"10.1001\/jamacardio.2019.2589","volume":"4","author":"YA Elnabawi","year":"2019","unstructured":"Elnabawi YA, Oikonomou EK, Dey AK et al (2019) Association of Biologic Therapy with coronary inflammation in patients with psoriasis as assessed by Perivascular Fat Attenuation Index. JAMA Cardiol 4(9):885\u2013891","journal-title":"JAMA Cardiol"}],"container-title":["The International Journal of Cardiovascular Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10554-023-02831-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10554-023-02831-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10554-023-02831-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,8]],"date-time":"2023-06-08T05:20:27Z","timestamp":1686201627000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10554-023-02831-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,3,24]]},"references-count":27,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2023,7]]}},"alternative-id":["2831"],"URL":"https:\/\/doi.org\/10.1007\/s10554-023-02831-z","relation":{"has-preprint":[{"id-type":"doi","id":"10.21203\/rs.3.rs-1833625\/v1","asserted-by":"object"}]},"ISSN":["1875-8312"],"issn-type":[{"value":"1875-8312","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,3,24]]},"assertion":[{"value":"7 July 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 March 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 March 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of Interest"}},{"value":"This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Chinese PLA General Hospital.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"Informed consent was not required because we only assessed retrospective data without personal identifying information.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}}]}}