{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T13:06:25Z","timestamp":1776085585623,"version":"3.50.1"},"reference-count":30,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2026,4,11]],"date-time":"2026-04-11T00:00:00Z","timestamp":1775865600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Medicina"],"abstract":"<jats:p>Background and Objectives: Acute ischemic stroke (AIS) caused by large vessel occlusion (LVO) remains a major cause of disability and mortality. Mechanical thrombectomy (MT) improves outcomes, but recovery varies. This study assessed the prognostic value of hypoperfusion intensity ratio (HIR), collateral circulation, and other clinical\/imaging factors. Materials and Methods: This retrospective cohort study included 96 LVO patients treated with MT with or without intravenous thrombolysis (IVT) between 2020 and 2024 at a tertiary hospital. Inclusion required multimodal CT (CT, CTA, CTP) and clinical data (NIHSS, mRS). HIR, core volume, CBV index, mismatch ratio, and collateral status were evaluated using artificial intelligence (AI)-based software. Univariate\/multivariate logistic regression identified predictors of poor outcome (mRS &gt; 3 at 90 days). Results: Lower HIR (&lt;0.5) and good collaterals were associated with favourable outcomes (p &lt; 0.001). Multivariate analysis identified HIR, initial NIHSS, and procedure duration as independent predictors of poor outcome. CTP-derived core volume, cerebral blood volume index, and mismatch ratio were also significant predictors. ROC analysis showed the highest AUC for core volume (0.810). Diabetes mellitus was associated with a worse prognosis compared to other clinical factors. Conclusions: HIR and collateral status are independent predictors of functional recovery after MT. CTP-derived core volume and CBV index have strong prognostic value. AI-based perfusion analysis supports patient selection and risk stratification.<\/jats:p>","DOI":"10.3390\/medicina62040731","type":"journal-article","created":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T11:38:26Z","timestamp":1776080306000},"page":"731","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Hypoperfusion Intensity Ratio as an Independent Predictor of Functional Outcome After Mechanical Thrombectomy for Large Vessel Occlusion Stroke"],"prefix":"10.3390","volume":"62","author":[{"given":"Dagnija","family":"Grabovska","sequence":"first","affiliation":[{"name":"Institute of Diagnostic Radiology, Pauls Stradins Clinical University Hospital, LV-1002 Riga, Latvia"},{"name":"Faculty of Medicine and Life Sciences, University of Latvia, LV-1586 Riga, Latvia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7457-1901","authenticated-orcid":false,"given":"Arturs","family":"Balodis","sequence":"additional","affiliation":[{"name":"Institute of Diagnostic Radiology, Pauls Stradins Clinical University Hospital, LV-1002 Riga, Latvia"},{"name":"Faculty of Medicine and Life Sciences, University of Latvia, LV-1586 Riga, Latvia"},{"name":"Department of Radiology, Riga Stradi\u0146\u0161 University, LV-1007 Riga, Latvia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1646-9853","authenticated-orcid":false,"given":"Arv\u012bds","family":"Bu\u0161s","sequence":"additional","affiliation":[{"name":"Institute of Diagnostic Radiology, Pauls Stradins Clinical University Hospital, LV-1002 Riga, Latvia"},{"name":"Faculty of Medicine, Riga Stradins University, LV-1007 Riga, Latvia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5674-7240","authenticated-orcid":false,"given":"Madara","family":"Ratniece","sequence":"additional","affiliation":[{"name":"Institute of Diagnostic Radiology, Pauls Stradins Clinical University Hospital, LV-1002 Riga, Latvia"},{"name":"Faculty of Medicine and Life Sciences, University of Latvia, LV-1586 Riga, Latvia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-3731-6493","authenticated-orcid":false,"given":"Roberts","family":"\u0160amanskis","sequence":"additional","affiliation":[{"name":"Faculty of Medicine and Life Sciences, University of Latvia, LV-1586 Riga, Latvia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4862-6726","authenticated-orcid":false,"given":"Evija","family":"Migl\u0101ne","sequence":"additional","affiliation":[{"name":"Department of Neurology, Pauls Stradins Clinical University Hospital, LV-1002 Riga, Latvia"},{"name":"Department of Neurology and Neurosurgery, Riga Stradi\u0146\u0161 University, LV-1007 Riga, Latvia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"K\u0101rlis","family":"Kup\u010ds","sequence":"additional","affiliation":[{"name":"Institute of Diagnostic Radiology, Pauls Stradins Clinical University Hospital, LV-1002 Riga, Latvia"},{"name":"Department of Radiology, Riga Stradi\u0146\u0161 University, LV-1007 Riga, Latvia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1730-8354","authenticated-orcid":false,"given":"Kristaps","family":"Jurj\u0101ns","sequence":"additional","affiliation":[{"name":"Department of Neurology, Pauls Stradins Clinical University Hospital, LV-1002 Riga, Latvia"},{"name":"Department of Neurology and Neurosurgery, Riga Stradi\u0146\u0161 University, LV-1007 Riga, Latvia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Arta","family":"Grosmane","sequence":"additional","affiliation":[{"name":"Department of Neurology, Pauls Stradins Clinical University Hospital, LV-1002 Riga, Latvia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-0119-1352","authenticated-orcid":false,"given":"Sigita","family":"Z\u0101l\u012bte","sequence":"additional","affiliation":[{"name":"Faculty of Medicine, Riga Stradins University, LV-1007 Riga, Latvia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9518-4855","authenticated-orcid":false,"given":"Maija","family":"Radzi\u0146a","sequence":"additional","affiliation":[{"name":"Institute of Diagnostic Radiology, Pauls Stradins Clinical University Hospital, LV-1002 Riga, Latvia"},{"name":"Faculty of Medicine and Life Sciences, University of Latvia, LV-1586 Riga, Latvia"},{"name":"Department of Radiology, Riga Stradi\u0146\u0161 University, LV-1007 Riga, Latvia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,4,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"132","DOI":"10.1177\/17474930241308142","article-title":"World Stroke Organization: Global Stroke Fact Sheet 2025","volume":"20","author":"Feigin","year":"2025","journal-title":"Int. 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