{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T15:13:44Z","timestamp":1775056424602,"version":"3.50.1"},"reference-count":39,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2022,10,14]],"date-time":"2022-10-14T00:00:00Z","timestamp":1665705600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2022,10,14]],"date-time":"2022-10-14T00:00:00Z","timestamp":1665705600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Med Imaging"],"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Background<\/jats:title>\n                <jats:p>This study aimed to evaluate the artificial intelligence (AI)-based coronary artery calcium (CAC) quantification and regional distribution of CAC on non-gated chest CT, using standard electrocardiograph (ECG)-gated CAC scoring as the reference.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Methods<\/jats:title>\n                <jats:p>In this retrospective study, a total of 405 patients underwent non-gated chest CT and standard ECG-gated cardiac CT. An AI-based algorithm was used for automated CAC scoring on chest CT, and Agatston score on cardiac CT was manually quantified. Bland-Altman plots were used to evaluate the agreement of absolute Agatston score between the two scans at the patient and vessel levels. Linearly weighted kappa (\u03ba) was calculated to assess the reliability of AI-based CAC risk categorization and the number of involved vessels on chest CT.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>The AI-based algorithm showed moderate reliability for the number of involved vessels in comparison to measures on cardiac CT (\u03ba\u2009=\u20090.75, 95% CI 0.70\u20130.79, <jats:italic>P<\/jats:italic>\u2009&lt;\u20090.001) and an assignment agreement of 76%. Considerable coronary arteries with CAC were not identified with a per-vessel false-negative rate of 59.3%, 17.8%, 34.9%, and 34.7% for LM, LAD, CX, and RCA on chest CT. The leading causes for false negatives of LM were motion artifact (56.3%, 18\/32) and segmentation error (43.8%, 14\/32). The motion artifact was almost the only cause for false negatives of LAD (96.6%, 28\/29), CX (96.7%, 29\/30), and RCA (100%, 34\/34). Absolute Agatston scores on chest CT were underestimated either for the patient and individual vessels except for LAD (median difference: \u2212\u200912.5, \u2212\u200911.3, \u2212\u20095.6, \u2212\u200918.6 for total, LM, CX, and RCA, all <jats:italic>P<\/jats:italic>\u2009&lt;\u20090.01; \u2212\u20092.5 for LAD, <jats:italic>P<\/jats:italic>\u2009=\u20090.18). AI-based total Agatston score yielded good reliability for risk categorization (weighted \u03ba 0.86, <jats:italic>P<\/jats:italic>\u2009&lt;\u20090.001) and an assignment agreement of 86.7% on chest CT, with a per-patient false-negative rate of 15.2% (28\/184) and false-positive rate of 0.5% (1\/221) respectively.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>AI-based per-patient CAC quantification on non-gated chest CT achieved a good agreement with dedicated ECG-gated CAC scoring overall and highly reliable CVD risk categorization, despite a slight but significant underestimation. However, it is challenging to evaluate the regional distribution of CAC without ECG-synchronization.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s12880-022-00907-1","type":"journal-article","created":{"date-parts":[[2022,10,14]],"date-time":"2022-10-14T04:02:50Z","timestamp":1665720170000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Automated total and vessel-specific coronary artery calcium (CAC) quantification on chest CT: direct comparison with CAC scoring on non-contrast cardiac CT"],"prefix":"10.1186","volume":"22","author":[{"given":"Jie","family":"Yu","sequence":"first","affiliation":[]},{"given":"Lijuan","family":"Qian","sequence":"additional","affiliation":[]},{"given":"Wengang","family":"Sun","sequence":"additional","affiliation":[]},{"given":"Zhuang","family":"Nie","sequence":"additional","affiliation":[]},{"given":"DanDan","family":"Zheng","sequence":"additional","affiliation":[]},{"given":"Ping","family":"Han","sequence":"additional","affiliation":[]},{"given":"Heshui","family":"Shi","sequence":"additional","affiliation":[]},{"given":"Chuansheng","family":"Zheng","sequence":"additional","affiliation":[]},{"given":"Fan","family":"Yang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,10,14]]},"reference":[{"key":"907_CR1","doi-asserted-by":"publisher","first-page":"1643","DOI":"10.1016\/j.jacc.2015.08.035","volume":"66","author":"RL McClelland","year":"2015","unstructured":"McClelland RL, Jorgensen NW, Budoff M, Blaha MJ, Post WS, Kronmal RA, et al. 10-Year coronary heart disease risk prediction using coronary artery calcium and traditional risk factors: derivation in the MESA (multi-ethnic study of atherosclerosis) with validation in the HNR (Heinz nixdorf recall) study and the DHS (Dallas heart study). J Am Coll Cardiol. 2015;66:1643\u201353.","journal-title":"J Am Coll Cardiol"},{"key":"907_CR2","doi-asserted-by":"publisher","first-page":"e197440","DOI":"10.1001\/jamanetworkopen.2019.7440","volume":"2","author":"MD Miedema","year":"2019","unstructured":"Miedema MD, Dardari ZA, Nasir K, Blankstein R, Knickelbine T, Oberembt S, et al. Association of coronary artery calcium with long-term, cause-specific mortality among young adults. JAMA Netw Open. 2019;2:e197440.","journal-title":"JAMA Netw Open"},{"key":"907_CR3","doi-asserted-by":"publisher","first-page":"411","DOI":"10.1016\/j.jcmg.2019.12.010","volume":"14","author":"MJ Blaha","year":"2021","unstructured":"Blaha MJ, Whelton SP, Al Rifai M, Dardari Z, Shaw LJ, Al-Mallah MH, et al. Comparing risk scores in the prediction of coronary and cardiovascular deaths. JACC Cardiovasc Imaging. 2021;14:411\u201321.","journal-title":"JACC Cardiovasc Imaging"},{"key":"907_CR4","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1016\/j.jcct.2018.03.008","volume":"12","author":"HS Hecht","year":"2018","unstructured":"Hecht HS, Blaha MJ, Kazerooni EA, Cury RC, Budoff M, Leipsic J, et al. CAC-DRS: coronary artery calcium data and reporting system. An expert consensus document of the Society of cardiovascular computed tomography (SCCT). J Cardiovasc Comput Tomogr. 2018;12:185\u201391.","journal-title":"J Cardiovasc Comput Tomogr"},{"key":"907_CR5","doi-asserted-by":"publisher","first-page":"1229","DOI":"10.1016\/j.amjcard.2015.01.555","volume":"115","author":"R Tota-Maharaj","year":"2015","unstructured":"Tota-Maharaj R, Joshi PH, Budoff MJ, Whelton S, Zeb I, Rumberger J, et al. Usefulness of regional distribution of coronary artery calcium to improve the prediction of all-cause mortality. Am J Cardiol. 2015;115:1229\u201334.","journal-title":"Am J Cardiol"},{"key":"907_CR6","doi-asserted-by":"publisher","first-page":"172","DOI":"10.1016\/j.atherosclerosis.2019.03.015","volume":"286","author":"SJ Lahti","year":"2019","unstructured":"Lahti SJ, Feldman DI, Dardari Z, Mirbolouk M, Orimoloye OA, Osei AD, et al. The association between left main coronary artery calcium and cardiovascular-specific and total mortality: the Coronary Artery Calcium Consortium. Atherosclerosis. 2019;286:172\u20138.","journal-title":"Atherosclerosis"},{"key":"907_CR7","doi-asserted-by":"publisher","first-page":"1407","DOI":"10.1016\/j.jcmg.2016.03.001","volume":"9","author":"MJ Blaha","year":"2016","unstructured":"Blaha MJ, Budoff MJ, Tota-Maharaj R, Dardari ZA, Wong ND, Kronmal RA, et al. Improving the CAC score by addition of regional measures of calcium distribution: multi-ethnic study of atherosclerosis. JACC Cardiovasc Imaging. 2016;9:1407\u201316.","journal-title":"JACC Cardiovasc Imaging"},{"key":"907_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1161\/CIRCIMAGING.117.006592","volume":"10","author":"M Ferencik","year":"2017","unstructured":"Ferencik M, Pencina KM, Liu T, Ghemigian K, Baltrusaitis K, Massaro JM, et al. Coronary artery calcium distribution is an independent predictor of incident major coronary heart disease events: results from the framingham heart study. Circ Cardiovasc Imaging. 2017;10:1\u20139.","journal-title":"Circ Cardiovasc Imaging"},{"key":"907_CR9","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1016\/j.jcct.2019.03.011","volume":"14","author":"O Dzaye","year":"2020","unstructured":"Dzaye O, Dudum R, Mirbolouk M, Orimoloye OA, Osei AD, Dardari ZA, et al. Validation of the coronary artery calcium data and reporting system (CAC-DRS): dual importance of CAC score and CAC distribution from the Coronary artery calcium (CAC) consortium. J Cardiovasc Comput Tomogr. 2020;14:12\u20137.","journal-title":"J Cardiovasc Comput Tomogr"},{"key":"907_CR10","doi-asserted-by":"publisher","first-page":"152","DOI":"10.1016\/j.jcmg.2015.06.030","volume":"9","author":"JM Hughes-Austin","year":"2016","unstructured":"Hughes-Austin JM, Dominguez A, Allison MA, Wassel CL, Rifkin DE, Morgan CG, et al. Relationship of coronary calcium on standard chest CT scans with mortality. JACC Cardiovasc Imaging. 2016;9:152\u20139.","journal-title":"JACC Cardiovasc Imaging"},{"key":"907_CR11","doi-asserted-by":"publisher","first-page":"715","DOI":"10.1038\/s41467-021-20966-2","volume":"12","author":"R Zeleznik","year":"2021","unstructured":"Zeleznik R, Foldyna B, Eslami P, Weiss J, Alexander I, Taron J, et al. Deep convolutional neural networks to predict cardiovascular risk from computed tomography. Nat Commun. 2021;12:715.","journal-title":"Nat Commun"},{"key":"907_CR12","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1016\/j.jcct.2014.11.006","volume":"9","author":"RAP Takx","year":"2015","unstructured":"Takx RAP, I\u0161gum I, Willemink MJ, van der Graaf Y, de Koning HJ, Vliegenthart R, et al. Quantification of coronary artery calcium in nongated CT to predict cardiovascular events in male lung cancer screening participants: results of the NELSON study. J Cardiovasc Comput Tomogr. 2015;9:50\u20137.","journal-title":"J Cardiovasc Comput Tomogr"},{"key":"907_CR13","doi-asserted-by":"publisher","first-page":"568","DOI":"10.1016\/j.jcmg.2015.09.020","volume":"9","author":"CE Handy","year":"2016","unstructured":"Handy CE, Desai CS, Dardari ZA, Al-Mallah MH, Miedema MD, Ouyang P, et al. The association of coronary artery calcium with noncardiovascular disease the multi-ethnic study of atherosclerosis. JACC Cardiovasc Imaging. 2016;9:568\u201376.","journal-title":"JACC Cardiovasc Imaging"},{"key":"907_CR14","doi-asserted-by":"publisher","first-page":"846","DOI":"10.1093\/ehjci\/jeab119","volume":"23","author":"DJ Winkel","year":"2022","unstructured":"Winkel DJ, Suryanarayana VR, Ali AM, G\u00f6rich J, Bu\u00df SJ, Mendoza A, et al. Deep learning for vessel-specific coronary artery calcium scoring: validation on a multi-centre dataset. Eur Hear J - Cardiovasc Imaging. 2022;23:846\u201354.","journal-title":"Eur Hear J - Cardiovasc Imaging"},{"key":"907_CR15","doi-asserted-by":"publisher","first-page":"e91239","DOI":"10.1371\/journal.pone.0091239","volume":"9","author":"RAP Takx","year":"2014","unstructured":"Takx RAP, De Jong PA, Leiner T, Oudkerk M, De Koning HJ, Mol CP, et al. Automated coronary artery calcification scoring in non-gated chest CT: Agreement and reliability. PLoS One. 2014;9:e91239.","journal-title":"PLoS One"},{"key":"907_CR16","doi-asserted-by":"publisher","first-page":"2127","DOI":"10.1109\/TMI.2019.2899534","volume":"38","author":"BD de Vos","year":"2019","unstructured":"de Vos BD, Wolterink JM, Leiner T, de Jong PA, Lessmann N, Isgum I. Direct automatic coronary calcium scoring in cardiac and chest CT. IEEE Trans Med Imaging. 2019;38:2127\u201338.","journal-title":"IEEE Trans Med Imaging"},{"key":"907_CR17","doi-asserted-by":"publisher","first-page":"66","DOI":"10.1148\/radiol.2020191621","volume":"295","author":"SGM van Velzen","year":"2020","unstructured":"van Velzen SGM, Lessmann N, Velthuis BK, Bank IEM, van den Bongard DHJG, Leiner T, et al. Deep learning for automatic calcium scoring in CT: validation using multiple cardiac CT and chest CT protocols. Radiology. 2020;295:66\u201379.","journal-title":"Radiology"},{"key":"907_CR18","doi-asserted-by":"publisher","first-page":"109428","DOI":"10.1016\/j.ejrad.2020.109428","volume":"134","author":"M van Assen","year":"2021","unstructured":"van Assen M, Martin SS, Varga-Szemes A, Rapaka S, Cimen S, Sharma P, et al. Automatic coronary calcium scoring in chest CT using a deep neural network in direct comparison with non-contrast cardiac CT: a validation study. Eur J Radiol. 2021;134:109428.","journal-title":"Eur J Radiol"},{"key":"907_CR19","doi-asserted-by":"publisher","first-page":"1764","DOI":"10.3348\/kjr.2021.0148","volume":"22","author":"JG Lee","year":"2021","unstructured":"Lee JG, Kim H, Kang H, Koo HJ, Kang JW, Kim YH, et al. Fully automatic coronary calcium score software empowered by artificial intelligence technology: validation study using three CT cohorts. Korean J Radiol. 2021;22:1764\u201376.","journal-title":"Korean J Radiol"},{"issue":"134","key":"907_CR20","first-page":"109420","volume":"2021","author":"N Zhang","year":"2020","unstructured":"Zhang N, Yang G, Zhang W, Wang W, Zhou Z, Zhang H, et al. Fully automatic framework for comprehensive coronary artery calcium scores analysis on non-contrast cardiac-gated CT scan: total and vessel-specific quantifications. Eur J Radiol. 2020;2021(134):109420.","journal-title":"Eur J Radiol"},{"key":"907_CR21","doi-asserted-by":"publisher","first-page":"358","DOI":"10.1093\/ehjci\/jeu218","volume":"16","author":"HS Hecht","year":"2015","unstructured":"Hecht HS, De Siqueira MEM, Cham M, Yip R, Narula J, Henschke C, et al. Low- vs. Standard-dose coronary artery calcium scanning. Eur Heart J Cardiovasc Imaging. 2015;16:358\u201363.","journal-title":"Eur Heart J Cardiovasc Imaging"},{"key":"907_CR22","doi-asserted-by":"publisher","first-page":"1165","DOI":"10.2214\/AJR.11.6533","volume":"197","author":"FJ Larke","year":"2011","unstructured":"Larke FJ, Kruger RL, Cagnon CH, Flynn MJ, McNitt-Gray MM, Wu X, et al. Estimated radiation dose associated with low-dose chest CT of average-size participants in the national lung screening trial. Am J Roentgenol. 2011;197:1165\u20139.","journal-title":"Am J Roentgenol"},{"key":"907_CR23","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, Detrano R. Quantification of coronary artery calcium using ultrafast computed tomography. J Am Coll Cardiol. 1990;15:827\u201332.","journal-title":"J Am Coll Cardiol"},{"key":"907_CR24","doi-asserted-by":"publisher","first-page":"96","DOI":"10.1016\/j.jclinepi.2010.03.002","volume":"64","author":"J Kottner","year":"2011","unstructured":"Kottner J, Audig\u00e9 L, Brorson S, Donner A, Gajewski BJ, Hr\u00f3bjartsson A, et al. Guidelines for reporting reliability and agreement studies (GRRAS) were proposed. J Clin Epidemiol. 2011;64:96\u2013106.","journal-title":"J Clin Epidemiol"},{"key":"907_CR25","doi-asserted-by":"publisher","first-page":"1546","DOI":"10.2214\/AJR.04.1589","volume":"185","author":"AB Sevrukov","year":"2005","unstructured":"Sevrukov AB, Bland JM, Kondos GT. Serial electron beam CT measurements of coronary artery calcium: has your patient\u2019s calcium score actually changed? Am J Roentgenol. 2005;185:1546\u201353.","journal-title":"Am J Roentgenol"},{"key":"907_CR26","doi-asserted-by":"publisher","first-page":"276","DOI":"10.11613\/BM.2012.031","volume":"22","author":"ML McHugh","year":"2012","unstructured":"McHugh ML. Lessons in biostatistics interrater reliability: the kappa statistic. Biochem Medica. 2012;22:276\u201382.","journal-title":"Biochem Medica"},{"key":"907_CR27","doi-asserted-by":"publisher","first-page":"567","DOI":"10.1148\/radiol.2451061791","volume":"245","author":"L Husmann","year":"2007","unstructured":"Husmann L, Leschka S, Desbiolles L, Schepis T, Gaemperli O, Seifert B, et al. Coronary artery motion and cardiac phases: dependency on heart rate - implications for CT image reconstruction. Radiology. 2007;245:567\u201376.","journal-title":"Radiology"},{"key":"907_CR28","doi-asserted-by":"publisher","first-page":"081915","DOI":"10.1118\/1.4813904","volume":"40","author":"X Xie","year":"2013","unstructured":"Xie X, Greuter MJW, Groen JM, de Bock GH, Oudkerk M, de Jong PA, et al. Can nontriggered thoracic CT be used for coronary artery calcium scoring? A phantom study. Med Phys. 2013;40:081915.","journal-title":"Med Phys"},{"key":"907_CR29","doi-asserted-by":"publisher","first-page":"1407","DOI":"10.1016\/j.jcmg.2016.03.001","volume":"9","author":"MJ Blaha","year":"2016","unstructured":"Blaha MJ, Budoff MJ, Tota-Maharaj R, Dardari ZA, Wong ND, Kronmal RA, et al. Improving the CAC Score by addition of regional measures of calcium distribution. JACC Cardiovasc Imaging. 2016;9:1407\u201316.","journal-title":"JACC Cardiovasc Imaging"},{"key":"907_CR30","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1016\/j.jcct.2020.04.013","volume":"15","author":"C Xia","year":"2021","unstructured":"Xia C, Vonder M, Pelgrim GJ, Rook M, Xie X, Alsurayhi A, et al. High-pitch dual-source CT for coronary artery calcium scoring: a head-to-head comparison of non-triggered chest versus triggered cardiac acquisition. J Cardiovasc Comput Tomogr. 2021;15:65\u201372.","journal-title":"J Cardiovasc Comput Tomogr"},{"key":"907_CR31","doi-asserted-by":"publisher","first-page":"1521","DOI":"10.1007\/s00330-015-3978-7","volume":"26","author":"A Hutt","year":"2016","unstructured":"Hutt A, Duhamel A, Deken V, Faivre JB, Molinari F, Remy J, et al. Coronary calcium screening with dual-source CT: reliability of ungated, high-pitch chest CT in comparison with dedicated calcium-scoring CT. Eur Radiol. 2016;26:1521\u20138.","journal-title":"Eur Radiol"},{"key":"907_CR32","doi-asserted-by":"publisher","first-page":"74","DOI":"10.1016\/j.jcct.2016.11.003","volume":"11","author":"HS Hecht","year":"2017","unstructured":"Hecht HS, Cronin P, Blaha MJ, Budoff MJ, Kazerooni EA, Narula J, et al. 2016 SCCT\/STR guidelines for coronary artery calcium scoring of noncontrast noncardiac chest CT scans: a report of the society of cardiovascular computed tomography and society of thoracic radiology. J Cardiovasc Comput Tomogr. 2017;11:74\u201384.","journal-title":"J Cardiovasc Comput Tomogr"},{"key":"907_CR33","doi-asserted-by":"publisher","first-page":"514","DOI":"10.1161\/CIRCIMAGING.113.000092","volume":"6","author":"X Xie","year":"2013","unstructured":"Xie X, Zhao Y, De Bock GH, De Jong PA, Mali WP, Oudkerk M, et al. Validation and prognosis of coronary artery calcium scoring in nontriggered thoracic computed tomography: systematic review and meta-analysis. Circ Cardiovasc Imaging. 2013;6:514\u201321.","journal-title":"Circ Cardiovasc Imaging"},{"key":"907_CR34","doi-asserted-by":"publisher","first-page":"849","DOI":"10.1161\/CIRCULATIONAHA.115.018524","volume":"133","author":"MJ Blaha","year":"2016","unstructured":"Blaha MJ, Cainzos-Achirica M, Greenland P, McEvoy JW, Blankstein R, Budoff MJ, et al. Role of coronary artery calcium score of zero and other negative risk markers for cardiovascular disease\u202f: the multi-ethnic study of atherosclerosis (MESA). Circulation. 2016;133:849\u201358.","journal-title":"Circulation"},{"key":"907_CR35","doi-asserted-by":"publisher","first-page":"957","DOI":"10.1016\/j.jcmg.2017.04.016","volume":"10","author":"PH Joshi","year":"2017","unstructured":"Joshi PH, Blaha MJ, Budoff MJ, Miedema MD, McClelland RL, Lima JAC, et al. The 10-year prognostic value of zero and minimal CAC. JACC Cardiovasc Imaging. 2017;10:957\u20138.","journal-title":"JACC Cardiovasc Imaging"},{"key":"907_CR36","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1007\/s10654-007-9123-4","volume":"22","author":"S Sabour","year":"2007","unstructured":"Sabour S, Rutten A, Van Der Schouw YT, Atsma F, Grobbee DE, Mali WP, et al. Inter-scan reproducibility of coronary calcium measurement using multi detector-row computed tomography (MDCT). Eur J Epidemiol. 2007;22:235\u201343.","journal-title":"Eur J Epidemiol"},{"key":"907_CR37","doi-asserted-by":"publisher","first-page":"2684","DOI":"10.21037\/qims-21-1017","volume":"12","author":"C Xu","year":"2022","unstructured":"Xu C, Guo H, Xu M, Duan M, Wang M, Liu P, et al. Automatic coronary artery calcium scoring on routine chest computed tomography (CT): comparison of a deep learning algorithm and a dedicated calcium scoring CT. Quant Imaging Med Surg. 2022;12:2684\u201395.","journal-title":"Quant Imaging Med Surg"},{"key":"907_CR38","doi-asserted-by":"publisher","first-page":"412","DOI":"10.6004\/jnccn.2018.0020","volume":"16","author":"DE Wood","year":"2018","unstructured":"Wood DE, Kazerooni EA, Baum SL, Eapen GA, Ettinger DS, Hou L, et al. Lung cancer screening, version 3.2018, NCCN clinical practice guidelines in oncology. J Natl Compr Cancer Netw. 2018;16:412\u201341.","journal-title":"J Natl Compr Cancer Netw"},{"key":"907_CR39","first-page":"67","volume":"21","author":"Q Zhou","year":"2018","unstructured":"Zhou Q, Fan Y, Wang Y, Qiao Y, Wang G, Huang Y, et al. China national lung cancer screening guideline with low-dose computed tomography (2018 version). Chin J Lung Cancer. 2018;21:67\u201375.","journal-title":"Chin J Lung Cancer"}],"container-title":["BMC Medical Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12880-022-00907-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12880-022-00907-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12880-022-00907-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,4,21]],"date-time":"2023-04-21T16:50:51Z","timestamp":1682095851000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcmedimaging.biomedcentral.com\/articles\/10.1186\/s12880-022-00907-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,14]]},"references-count":39,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2022,12]]}},"alternative-id":["907"],"URL":"https:\/\/doi.org\/10.1186\/s12880-022-00907-1","relation":{},"ISSN":["1471-2342"],"issn-type":[{"value":"1471-2342","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,10,14]]},"assertion":[{"value":"22 June 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 October 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 October 2022","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 study was conducted in accordance with the Declaration of Helsinki. Institutional Review Board approval was obtained (No. [2019] S878, Tongji Medical College, Huazhong University of Science and Technology). The requirement for informed patient consent was waived by the ethics committee of Tongji Medical College, Huazhong University of Science and Technology for this retrospective study.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare that they have no conflict of interest.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"177"}}