{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T03:24:04Z","timestamp":1773977044164,"version":"3.50.1"},"reference-count":33,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,12,11]],"date-time":"2025-12-11T00:00:00Z","timestamp":1765411200000},"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. Neuroinform."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Timely and accurate assessment of acute ischemic stroke is crucial for determining eligibility for mechanical thrombectomy. The Alberta Stroke Program Early CT Score (ASPECTS) is a widely used tool for evaluating early ischemic changes on non-contrast CT (NCCT), but its interpretation is subject to interobserver variability. Brainomix e-ASPECTS is an automated software designed to standardize and expedite this assessment. We aimed to evaluate the clinical utility and diagnostic performance of the Brainomix e-ASPECTS software in an unselected, real-world cohort of patients undergoing NCCT for suspected acute ischemic stroke.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We retrospectively analyzed 1,029 NCCT studies from 954 patients between March 2020 and December 2024. e-ASPECTS scores were compared to radiologist-assigned ASPECTS, which served as the reference standard. Diagnostic accuracy, sensitivity, specificity, and correlation between scoring methods were assessed.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      There was a strong correlation between e-ASPECTS and radiologist ASPECTS (\n                      <jats:italic>\u03c1<\/jats:italic>\n                      \u202f=\u202f0.953,\n                      <jats:italic>p<\/jats:italic>\n                      \u202f&amp;lt;\u202f0.001). For detecting acute ischemia, sensitivity was 95.8% (95% CI, 93.6\u201397.3%), specificity 96.9% (95% CI, 94.7\u201398.2%), and overall accuracy 96.3% (95% CI, 95.1\u201397.5%). The positive predictive value was 97.2% (95% CI, 95.3\u201398.4%), and the negative predictive value was 95.3% (95% CI, 92.8\u201396.9%). Score concordance was high, with exact matches in 92.3% of cases and a\u202f\u2264\u202f1-point difference in 97.7%. Misclassification for thrombectomy eligibility (ASPECTS &amp;lt; 6) occurred in four cases (0.4%). The software achieved a processing success rate of 91.9%.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>E-ASPECTS demonstrates high diagnostic accuracy and strong agreement with expert radiological assessment, supporting its role as a valuable decision support tool in acute stroke imaging. However, its use should complement, not replace, expert interpretation, particularly in patients with low ASPECTS scores, where treatment decisions are most sensitive.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fninf.2025.1668395","type":"journal-article","created":{"date-parts":[[2025,12,11]],"date-time":"2025-12-11T06:30:25Z","timestamp":1765434625000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Assessing the eligibility of Brainomix e-ASPECTS for acute stroke imaging"],"prefix":"10.3389","volume":"19","author":[{"given":"Mateusz","family":"Dorochowicz","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Arkadiusz","family":"Kaca\u0142a","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Micha\u0142","family":"Pu\u0142a","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Adrian","family":"Korbecki","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aleksandra","family":"Kosikowska","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aleksandra","family":"To\u0142kacz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anna","family":"Zimny","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maciej","family":"Guzi\u0144ski","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2025,12,11]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"e298","DOI":"10.1136\/jnis-2022-019447","article-title":"Artificial intelligence-driven ASPECTS for the detection of early stroke changes in non-contrast CT: a systematic review and meta-analysis","volume":"15","author":"Adamou","year":"2023","journal-title":"J. Neurointerv. Surg."},{"key":"ref2","doi-asserted-by":"publisher","first-page":"879","DOI":"10.1016\/j.jacc.2018.11.052","article-title":"Impact of procedure time on outcomes of thrombectomy for stroke","volume":"73","author":"Alawieh","year":"2019","journal-title":"J. Am. Coll. Cardiol."},{"key":"ref3","doi-asserted-by":"publisher","first-page":"6285","DOI":"10.1007\/s00330-019-06252-2","article-title":"Automated versus manual imaging assessment of early ischemic changes in acute stroke: comparison of two software packages and expert consensus","volume":"29","author":"Austein","year":"2019","journal-title":"Eur. Radiol."},{"key":"ref4","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1111\/j.1747-4949.2012.00859.x","article-title":"Time dependence of reliability of noncontrast computed tomography in comparison to computed tomography angiography source image in acute ischemic stroke","volume":"10","author":"Bal","year":"2015","journal-title":"Int. J. Stroke"},{"key":"ref5","doi-asserted-by":"publisher","first-page":"1670","DOI":"10.1016\/S0140-6736(00)02237-6","article-title":"Validity and reliability of a quantitative computed tomography score in predicting outcome of hyperacute stroke before thrombolytic therapy. ASPECTS Study Group. Alberta Stroke Programme Early CT Score","volume":"355","author":"Barber","year":"2000","journal-title":"Lancet"},{"key":"ref6","doi-asserted-by":"publisher","first-page":"781","DOI":"10.1177\/15910199211011861","article-title":"E-ASPECTS software improves interobserver agreement and accuracy of interpretation of aspects score","volume":"27","author":"Brinjikji","year":"2021","journal-title":"Interv. Neuroradiol."},{"key":"ref7","doi-asserted-by":"publisher","first-page":"249","DOI":"10.1212\/WNL.0000000000002860","article-title":"Early CT changes in patients admitted for thrombectomy: intrarater and interrater agreement","volume":"87","author":"Farzin","year":"2016","journal-title":"Neurology"},{"key":"ref8","doi-asserted-by":"publisher","first-page":"1267","DOI":"10.1007\/s00234-018-2098-x","article-title":"Automated ASPECT rating: comparison between the frontier ASPECT score software and the Brainomix software","volume":"60","author":"Goebel","year":"2018","journal-title":"Neuroradiology"},{"key":"ref9","doi-asserted-by":"publisher","first-page":"1019","DOI":"10.1056\/NEJMoa1414905","article-title":"Randomized assessment of rapid endovascular treatment of ischemic stroke","volume":"372","author":"Goyal","year":"2015","journal-title":"N. Engl. J. Med."},{"key":"ref10","doi-asserted-by":"publisher","first-page":"889","DOI":"10.1007\/s00234-018-2066-5","article-title":"Detection of early infarction signs with machine learning-based diagnosis by means of the Alberta Stroke Program Early CT Score (ASPECTS) in the clinical routine","volume":"60","author":"Guberina","year":"2018","journal-title":"Neuroradiology"},{"key":"ref11","doi-asserted-by":"publisher","first-page":"421","DOI":"10.1136\/neurintsurg-2020-016125","article-title":"What predicts poor outcome after successful thrombectomy in late time windows?","volume":"13","author":"Heit","year":"2021","journal-title":"J Neurointerv Surg."},{"key":"ref12","doi-asserted-by":"publisher","first-page":"1231","DOI":"10.1007\/s00234-020-02439-3","article-title":"Automated ASPECT scoring in acute ischemic stroke: comparison of three software tools","volume":"62","author":"Hoelter","year":"2020","journal-title":"Neuroradiology"},{"key":"ref13","doi-asserted-by":"publisher","first-page":"1272","DOI":"10.1056\/NEJMoa2213379","article-title":"Trial of endovascular therapy for acute ischemic stroke with large infarct","volume":"388","author":"Huo","year":"2023","journal-title":"N. Engl. J. Med."},{"key":"ref14","doi-asserted-by":"publisher","first-page":"2296","DOI":"10.1056\/NEJMoa1503780","article-title":"Thrombectomy within 8 hours after symptom onset in ischemic stroke","volume":"372","author":"Jovin","year":"2015","journal-title":"N. Engl. J. Med."},{"key":"ref15","doi-asserted-by":"publisher","first-page":"2986","DOI":"10.1161\/STROKEAHA.112.661009","article-title":"Diffusion lesion reversal after thrombolysis: a MR correlate of early neurological improvement","volume":"43","author":"Labeyrie","year":"2012","journal-title":"Stroke"},{"key":"ref16","doi-asserted-by":"publisher","first-page":"654980","DOI":"10.1155\/2014\/654980","article-title":"Detection of early ischemic changes in noncontrast CT head improved with \u201cstroke windows\u201d","volume":"2014","author":"Mainali","year":"2014","journal-title":"ISRN Neurosci."},{"key":"ref17","doi-asserted-by":"publisher","first-page":"943","DOI":"10.1002\/ana.26495","article-title":"External validation of e-ASPECTS software for interpreting brain CT in stroke","volume":"92","author":"Mair","year":"2022","journal-title":"Ann. Neurol."},{"key":"ref18","doi-asserted-by":"publisher","first-page":"1072","DOI":"10.1002\/acn3.51790","article-title":"Accuracy of artificial intelligence software for CT angiography in stroke","volume":"10","author":"Mair","year":"2023","journal-title":"Ann. Clin. Transl. Neurol."},{"key":"ref19","doi-asserted-by":"publisher","first-page":"497","DOI":"10.1136\/svn-2023-002859","article-title":"Real-world evaluation of Brainomix e-stroke software","volume":"9","author":"Mallon","year":"2024","journal-title":"Stroke Vasc. Neurol."},{"key":"ref20","doi-asserted-by":"publisher","first-page":"1574","DOI":"10.1161\/STROKEAHA.117.016745","article-title":"ASPECTS (Alberta stroke program early CT score) measurement using Hounsfield unit values when selecting patients for stroke thrombectomy","volume":"48","author":"Mokin","year":"2017","journal-title":"Stroke"},{"key":"ref21","doi-asserted-by":"publisher","first-page":"1023147","DOI":"10.3389\/fneur.2022.1023147","article-title":"CT after interhospital transfer in acute ischemic stroke: imaging findings and impact of prior intravenous contrast administration","volume":"13","author":"Mueller","year":"2022","journal-title":"Front. Neurol."},{"key":"ref22","doi-asserted-by":"publisher","first-page":"615","DOI":"10.1177\/1747493016681020","article-title":"E-ASPECTS software is non-inferior to neuroradiologists in applying the ASPECT score to computed tomography scans of acute ischemic stroke patients","volume":"12","author":"Nagel","year":"2017","journal-title":"Int. J. Stroke"},{"key":"ref23","doi-asserted-by":"publisher","first-page":"1407","DOI":"10.1161\/STROKEAHA.117.019863","article-title":"Clinical utility of electronic Alberta stroke program early computed tomography score software in the ENCHANTED trial database","volume":"49","author":"Nagel","year":"2018","journal-title":"Stroke"},{"key":"ref24","doi-asserted-by":"publisher","first-page":"2547","DOI":"10.1016\/j.jstrokecerebrovasdis.2017.05.042","article-title":"Reliability and utility of the Alberta stroke program early computed tomography score in hyperacute stroke","volume":"26","author":"Naylor","year":"2017","journal-title":"J. Stroke Cerebrovasc. Dis."},{"key":"ref25","doi-asserted-by":"publisher","first-page":"720","DOI":"10.1136\/neurintsurg-2019-015442","article-title":"Region-specific agreement in ASPECTS estimation between neuroradiologists and e-ASPECTS software","volume":"12","author":"Neuhaus","year":"2020","journal-title":"J. Neurointerv. Surg."},{"key":"ref26","doi-asserted-by":"publisher","first-page":"1069","DOI":"10.1136\/neurintsurg-2019-015473","article-title":"Per-region interobserver agreement of Alberta stroke program early CT scores (ASPECTS)","volume":"12","author":"Nicholson","year":"2020","journal-title":"J. Neurointerv. Surg."},{"key":"ref27","doi-asserted-by":"publisher","first-page":"1594","DOI":"10.3174\/ajnr.A5236","article-title":"E-ASPECTS correlates with and is predictive of outcome after mechanical thrombectomy","volume":"38","author":"Pfaff","year":"2017","journal-title":"AJNR Am. J. Neuroradiol."},{"key":"ref30","volume-title":"R: A language and environment for statistical computing","year":"2021"},{"key":"ref28","doi-asserted-by":"publisher","first-page":"3190","DOI":"10.1161\/STROKEAHA.123.044985","article-title":"Priorities for advancements in neuroimaging in the diagnostic workup of acute stroke","volume":"54","author":"Samaniego","year":"2023","journal-title":"Stroke"},{"key":"ref29","doi-asserted-by":"publisher","first-page":"1259","DOI":"10.1056\/NEJMoa2214403","article-title":"Trial of endovascular thrombectomy for large ischemic strokes","volume":"388","author":"Sarraj","year":"2023","journal-title":"N. Engl. J. Med."},{"key":"ref31","doi-asserted-by":"publisher","first-page":"136","DOI":"10.1186\/s12873-022-00692-8","article-title":"Shortening door-to-puncture time and improving patient outcome with workflow optimization in patients with acute ischemic stroke associated with large vessel occlusion","volume":"22","author":"Yang","year":"2022","journal-title":"BMC Emerg. Med."},{"key":"ref32","doi-asserted-by":"publisher","first-page":"1303","DOI":"10.1056\/NEJMoa2118191","article-title":"Endovascular therapy for acute stroke with a large ischemic region","volume":"386","author":"Yoshimura","year":"2022","journal-title":"N. Engl. J. Med."},{"key":"ref33","doi-asserted-by":"publisher","first-page":"e210064","DOI":"10.1148\/ryai.210064","article-title":"External validation of deep learning algorithms for radiologic diagnosis: a systematic review","volume":"4","author":"Yu","year":"2022","journal-title":"Radiol. Artif. Intell."}],"container-title":["Frontiers in Neuroinformatics"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fninf.2025.1668395\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,11]],"date-time":"2025-12-11T06:30:25Z","timestamp":1765434625000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fninf.2025.1668395\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,11]]},"references-count":33,"alternative-id":["10.3389\/fninf.2025.1668395"],"URL":"https:\/\/doi.org\/10.3389\/fninf.2025.1668395","relation":{},"ISSN":["1662-5196"],"issn-type":[{"value":"1662-5196","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,11]]},"article-number":"1668395"}}