{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T20:29:46Z","timestamp":1772828986193,"version":"3.50.1"},"reference-count":27,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2021,10,11]],"date-time":"2021-10-11T00:00:00Z","timestamp":1633910400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2021,10,11]],"date-time":"2021-10-11T00:00:00Z","timestamp":1633910400000},"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"],"published-print":{"date-parts":[[2021,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Background<\/jats:title>\n                <jats:p>Radiomics analysis is a newly emerging quantitative image analysis technique. The aim of this study was to extract a radiomics signature from the computed tomography (CT) imaging to determine the infarction onset time in patients with acute middle cerebral artery occlusion (MCAO).<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Methods<\/jats:title>\n                <jats:p>A total of 123 patients with acute MCAO in the M1 segment (85 patients in the development cohort and 38 patients in the validation cohort) were enrolled in the present study. Clinicoradiological profiles, including head CT without contrast enhancement and computed tomographic angiography (CTA), were collected. The time from stroke onset (TFS) was classified into two subcategories: \u2264\u00a04.5\u00a0h, and &gt;\u20094.5\u00a0h. The middle cerebral artery (MCA) territory on CT images was segmented to extract and score the radiomics features associated with the TFS. In addition, the clinicoradiological factors related to the TFS were identified. Subsequently, a combined model of the radiomics signature and clinicoradiological factors was constructed to distinguish the TFS\u2009\u2264\u20094.5\u00a0h. Finally, we evaluated the overall performance of our constructed model in an external validation sample of ischemic stroke patients with acute MCAO in the M1 segment.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>The area under the curve (AUC) of the radiomics signature for discriminating the TFS in the development and validation cohorts was 0.770 (95% confidence interval (CI): 0.665\u20130.875) and 0.792 (95% CI: 0.633\u20130.950), respectively. The AUC of the combined model comprised of the radiomics signature, age and ASPECTS on CT in the development and validation cohorts was 0.808 (95% CI: 0.701\u20130.916) and 0.833 (95% CI: 0.702\u20130.965), respectively. In the external validation cohort, the AUC of the radiomics signature was 0.755 (95% CI: 0.614\u20130.897), and the AUC of the combined model was 0.820 (95% CI: 0.712\u20130.928).<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>The CT-based radiomics signature is a valuable tool for discriminating the TFS in patients with acute MCAO in the M1 segment, which may guide the use of thrombolysis therapy in patients with indeterminate stroke onset time.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s12880-021-00678-1","type":"journal-article","created":{"date-parts":[[2021,10,11]],"date-time":"2021-10-11T18:06:19Z","timestamp":1633975579000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Developing a model for estimating infarction onset time based on computed tomography radiomics in patients with acute middle cerebral artery occlusion"],"prefix":"10.1186","volume":"21","author":[{"given":"Xuehua","family":"Wen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhenyu","family":"Shu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yumei","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xingfei","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiangyang","family":"Gong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,10,11]]},"reference":[{"key":"678_CR1","doi-asserted-by":"publisher","first-page":"1612","DOI":"10.1016\/S0140-6736(08)60694-7","volume":"371","author":"GA Donnan","year":"2008","unstructured":"Donnan GA, Fisher M, Macleod M, Davis SM, Stroke. Lancet. 2008;371:1612\u201323.","journal-title":"Lancet"},{"key":"678_CR2","doi-asserted-by":"publisher","first-page":"215","DOI":"10.3389\/fneur.2014.00215","volume":"5","author":"G Tsivgoulis","year":"2014","unstructured":"Tsivgoulis G, Katsanos AH, Alexandrov AV. Reperfusion therapies of acute ischemic stroke: potentials and failures. Front Neurol. 2014;5:215.","journal-title":"Front Neurol"},{"key":"678_CR3","doi-asserted-by":"publisher","first-page":"299","DOI":"10.1016\/S1474-4422(08)70044-9","volume":"7","author":"SM Davis","year":"2008","unstructured":"Davis SM, Donnan GA, Parsons MW, Levi C, Butcher KS, Peeters A, et al. Effects of alteplase beyond 3\u00a0h after stroke in the Echoplanar Imaging Thrombolytic Evaluation Trial (EPITHET): a placebo-controlled randomised trial. Lancet Neurol. 2008;7:299\u2013309.","journal-title":"Lancet Neurol"},{"key":"678_CR4","doi-asserted-by":"publisher","first-page":"250","DOI":"10.1161\/STROKEAHA.109.568410","volume":"41","author":"M Ebinger","year":"2010","unstructured":"Ebinger M, Galinovic I, Rozanski M, Brunecker P, Endres M, Fiebach JB. Fluid-attenuated inversion recovery evolution within 12 hours from stroke onset: a reliable tissue clock? Stroke. 2010;41:250\u20135.","journal-title":"Stroke"},{"key":"678_CR5","doi-asserted-by":"publisher","first-page":"724","DOI":"10.1002\/ana.21651","volume":"65","author":"G Thomalla","year":"2009","unstructured":"Thomalla G, Rossbach P, Rosenkranz M, Siemonsen S, Krutzelmann A, Fiehler J, et al. Negative fluid-attenuated inversion recovery imaging identifies acute ischemic stroke at 3 hours or less. Ann Neurol. 2009;65:724\u201332.","journal-title":"Ann Neurol"},{"key":"678_CR6","doi-asserted-by":"publisher","first-page":"131","DOI":"10.5853\/jos.2014.16.3.131","volume":"16","author":"BJ Kim","year":"2014","unstructured":"Kim BJ, Kang HG, Kim HJ, Ahn SH, Kim NY, Warach S, et al. Magnetic resonance imaging in acute ischemic stroke treatment. J Stroke. 2014;16:131\u201345.","journal-title":"J Stroke"},{"key":"678_CR7","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1159\/000505807","volume":"49","author":"J Lin","year":"2020","unstructured":"Lin J, Li X, Wu G, Chen X, Weng Y, Wang H, et al. White matter high signals interfere with noncontrast computed tomography in the early identification of cerebral infarction. Cerebrovasc Dis. 2020;49:135\u201343.","journal-title":"Cerebrovasc Dis"},{"key":"678_CR8","doi-asserted-by":"publisher","first-page":"720","DOI":"10.1148\/radiol.2432060137","volume":"243","author":"I Dzialowski","year":"2007","unstructured":"Dzialowski I, Klotz E, Goericke S, Doerfler A, Forsting M, von Kummer R. Ischemic brain tissue water content: CT monitoring during middle cerebral artery occlusion and reperfusion in rats. Radiology. 2007;243:720\u20136.","journal-title":"Radiology"},{"key":"678_CR9","doi-asserted-by":"publisher","first-page":"1117","DOI":"10.1111\/ijs.12360","volume":"9","author":"M Koga","year":"2014","unstructured":"Koga M, Toyoda K, Kimura K, Yamamoto H, Sasaki M, Hamasaki T, et al. THrombolysis for acute wake-up and unclear-onset Strokes with alteplase at 0.6\u00a0mg\/kg (THAWS) Trial. Int J Stroke. 2014;9:1117\u201324.","journal-title":"Int J Stroke"},{"key":"678_CR10","doi-asserted-by":"publisher","first-page":"3912","DOI":"10.1007\/s00330-018-5395-1","volume":"28","author":"Z Shi","year":"2018","unstructured":"Shi Z, Zhu C, Degnan AJ, Tian X, Li J, Chen L, et al. Identification of high-risk plaque features in intracranial atherosclerosis: initial experience using a radiomic approach. Eur Radiol. 2018; 28: 3912\u201321.","journal-title":"Eur Radiol"},{"key":"678_CR11","doi-asserted-by":"publisher","first-page":"708","DOI":"10.3389\/fnins.2020.00708","volume":"14","author":"X Wen","year":"2020","unstructured":"Wen X, Li Y, He X, Xu Y, Shu Z, Hu X, et al. Prediction of malignant acute middle cerebral artery infarction via computed tomography radiomics. Front Neurosci. 2020;14:708.","journal-title":"Front Neurosci"},{"key":"678_CR12","doi-asserted-by":"publisher","first-page":"3374","DOI":"10.1038\/s41598-019-39651-y","volume":"9","author":"Z Shu","year":"2019","unstructured":"Shu Z, Fang S, Ding Z, Mao D, Cai R, Chen Y, et al. MRI-based Radiomics nomogram to detect primary rectal cancer with synchronous liver metastases. Sci Rep. 2019;9:3374.","journal-title":"Sci Rep"},{"key":"678_CR13","doi-asserted-by":"publisher","first-page":"1574","DOI":"10.1161\/STROKEAHA.117.016745","volume":"48","author":"M Mokin","year":"2017","unstructured":"Mokin M, Primiani C, Siddiqui AH, Turk AS. ASPECTS (Alberta Stroke Program Early CT Score) measurement using hounsfield unit values when selecting patients for stroke thrombectomy. Stroke. 2017;48:1574\u20139.","journal-title":"Stroke"},{"key":"678_CR14","doi-asserted-by":"publisher","first-page":"992","DOI":"10.1111\/j.1747-4949.2012.00922.x","volume":"9","author":"F Brunner","year":"2014","unstructured":"Brunner F, Tomandl B, Hanken K, Hildebrandt H, Kastrup A. Impact of collateral circulation on early outcome and risk of hemorrhagic complications after systemic thrombolysis. Int J Stroke. 2014;9:992\u20138.","journal-title":"Int J Stroke"},{"key":"678_CR15","doi-asserted-by":"publisher","first-page":"525","DOI":"10.3174\/ajnr.A1408","volume":"30","author":"IY Tan","year":"2009","unstructured":"Tan IY, Demchuk AM, Hopyan J, Zhang L, Gladstone D, Wong K, et al. CT angiography clot burden score and collateral score: correlation with clinical and radiologic outcomes in acute middle cerebral artery infarct. Am J Neuroradiol. 2009;30:525\u201331.","journal-title":"Am J Neuroradiol"},{"key":"678_CR16","doi-asserted-by":"publisher","first-page":"144","DOI":"10.1016\/j.ejrad.2019.05.006","volume":"116","author":"R Cuocolo","year":"2019","unstructured":"Cuocolo R, Stanzione A, Ponsiglione A, Romeo V, Verde F, Creta M, et al. Clinically significant prostate cancer detection on MRI: a radiomic shape features study. Eur J Radiol. 2019;116:144\u20139.","journal-title":"Eur J Radiol"},{"key":"678_CR17","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. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics. 1988;44:837\u201345.","journal-title":"Biometrics"},{"key":"678_CR18","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1097\/01.NT.0000349810.48689.50","volume":"9","author":"MARTHA KERR","year":"2009","unstructured":"KERR MARTHA. MRI reported to show duration of ischemic stroke symptoms. Neurology Today. 2009;9:13\u20134.","journal-title":"Neurology Today"},{"key":"678_CR19","doi-asserted-by":"publisher","first-page":"903","DOI":"10.1161\/STROKEAHA.113.003701","volume":"45","author":"F Macellari","year":"2014","unstructured":"Macellari F, Paciaroni M, Agnelli G, Caso V. Neuroimaging in intracerebral hemorrhage. Stroke. 2014;45:903\u20138.","journal-title":"Stroke"},{"key":"678_CR20","doi-asserted-by":"publisher","first-page":"2005","DOI":"10.21037\/cdt-20-156","volume":"10","author":"A Murgia","year":"2020","unstructured":"Murgia A, Balestrieri A, Crivelli P, Suri JS, Conti M, Cademartiri F, et al. Cardiac computed tomography radiomics: an emerging tool for the non-invasive assessment of coronary atherosclerosis. Cardiovasc Diagn Ther. 2020;10:2005\u201317.","journal-title":"Cardiovasc Diagn Ther"},{"key":"678_CR21","doi-asserted-by":"publisher","first-page":"192","DOI":"10.1002\/mp.12015","volume":"44","author":"R Peter","year":"2017","unstructured":"Peter R, Korfiatis P, Blezek D, Oscar Beitia A, Stepan-Buksakowska I, Horinek D, et al. A quantitative symmetry-based analysis of hyperacute ischemic stroke lesions in noncontrast computed tomography. Med Phys. 2017;44:192\u20139.","journal-title":"Med Phys"},{"key":"678_CR22","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1016\/j.compmedimag.2019.02.006","volume":"74","author":"R Ortiz-Ramon","year":"2019","unstructured":"Ortiz-Ramon R, Valdes Hernandez MDC, Gonzalez-Castro V, Makin S, Armitage PA, Aribisala BS, et al. Identification of the presence of ischaemic stroke lesions by means of texture analysis on brain magnetic resonance images. Comput Med Imaging Graph. 2019;74:12\u201324.","journal-title":"Comput Med Imaging Graph"},{"key":"678_CR23","doi-asserted-by":"publisher","first-page":"643","DOI":"10.1007\/s12975-019-00746-3","volume":"11","author":"N Betrouni","year":"2020","unstructured":"Betrouni N, Yasmina M, Bombois S, Petrault M, Dondaine T, Lachaud C, et al. Texture features of magnetic resonance images: an early marker of post-stroke cognitive impairment. Transl Stroke Res. 2020;11:643\u201352.","journal-title":"Transl Stroke Res"},{"key":"678_CR24","doi-asserted-by":"publisher","first-page":"116730","DOI":"10.1016\/j.jns.2020.116730","volume":"412","author":"X Yao","year":"2020","unstructured":"Yao X, Mao L, Lv S, Ren Z, Li W, Ren K. CT radiomics features as a diagnostic tool for classifying basal ganglia infarction onset time. J Neurol Sci. 2020;412:116730.","journal-title":"J Neurol Sci"},{"key":"678_CR25","doi-asserted-by":"publisher","first-page":"953","DOI":"10.1161\/STROKEAHA.109.571943","volume":"41","author":"ZS Shi","year":"2010","unstructured":"Shi ZS, Loh Y, Walker G, Duckwiler GR, MERCI and Multi-MERCI Investigators. Clinical outcomes in middle cerebral artery trunk occlusions versus secondary division occlusions after mechanical thrombectomy: pooled analysis of the Mechanical Embolus Removal in Cerebral Ischemia (MERCI) and Multi MERCI trials. Stroke. 2010;41:953\u201360.","journal-title":"Stroke"},{"key":"678_CR26","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1016\/j.compbiomed.2016.09.011","volume":"78","author":"D Molina","year":"2016","unstructured":"Molina D, P\u00e9rez-Beteta J, Mart\u00ednez-Gonz\u00e1lez A, Martino J, Vel\u00e1squez C, Arana E, et al. Influence of gray level and space discretization on brain tumor heterogeneity measures obtained from magnetic resonance images. Comput Biol Med. 2016;78:49\u201357.","journal-title":"Comput Biol Med"},{"key":"678_CR27","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1159\/000338778","volume":"34","author":"P Garcia-Bermejo","year":"2012","unstructured":"Garcia-Bermejo P, Calleja AI, Perez-Fernandez S, Cortijo E, del Monte JM, Garcia-Porrero M, et al. Perfusion computed tomography-guided intravenous thrombolysis for acute ischemic stroke beyond 4.5 hours: a case-control study. Cerebrovasc Dis. 2012;34:31\u20137.","journal-title":"Cerebrovasc Dis"}],"container-title":["BMC Medical Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12880-021-00678-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12880-021-00678-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12880-021-00678-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,10,11]],"date-time":"2021-10-11T18:08:51Z","timestamp":1633975731000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcmedimaging.biomedcentral.com\/articles\/10.1186\/s12880-021-00678-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,10,11]]},"references-count":27,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,12]]}},"alternative-id":["678"],"URL":"https:\/\/doi.org\/10.1186\/s12880-021-00678-1","relation":{},"ISSN":["1471-2342"],"issn-type":[{"value":"1471-2342","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,10,11]]},"assertion":[{"value":"20 May 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 September 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 October 2021","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 present retrospective study was approved by the Ethics Committee and Institutional Review Board of Zhejiang Provincial People\u2019s Hospital, and the need for informed consent from patients was waived. All methods were carried out in accordance with institutional guidelines and regulations.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare that they have no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"147"}}