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Hypoperfusion Intensity Ratio as an Independent Predictor of Functional Outcome After Mechanical Thrombectomy for Large Vessel Occlusion Stroke

  • Dagnija Grabovska
  • , Arturs Balodis*
  • , Arvīds Bušs
  • , Madara Ratniece
  • , Roberts Šamanskis
  • , Evija Miglāne
  • , Kārlis Kupčs
  • , Kristaps Jurjāns
  • , Arta Grosmane
  • , Sigita Zālīte
  • , Maija Radziņa
  • *Corresponding author for this work
  • Paula Stradina Clinical University Hospital
  • University of Latvia
  • Pauls Stradiņš Clinical University Hospital
  • Riga Stradins University

Research output: Contribution to journalArticlepeer-review

Abstract

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 > 3 at 90 days). Results: Lower HIR (<0.5) and good collaterals were associated with favourable outcomes (p < 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.

Original languageEnglish
Article number731
JournalMedicina (Lithuania)
Volume62
Issue number4
DOIs
Publication statusPublished - Apr 2026

Keywords

  • CT perfusion
  • artificial intelligence
  • collateral circulation
  • hypoperfusion intensity ratio
  • mechanical thrombectomy
  • stroke

OECD Field of Science

  • 3.2 Clinical Medicine

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