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Hypoperfusion intensity ratio and CBV index as predictive parameters to identify underlying intracranial atherosclerotic stenosis in endovascular thrombectomy.
Imaoka, Yukihiro; Shindo, Seigo; Miura, Masatomo; Terasaki, Tadashi; Mukasa, Akitake; Todaka, Tatemi.
Afiliação
  • Imaoka Y; Department of Neurosurgery, Kumamoto Red Cross Hospital, 2-1-1 Nagamineminami, Higashiku, Kumamoto City, Kumamoto 861-8520, Japan; Department of Neurosurgery, Graduate School of Medical Sciences, Kumamoto University, 1-1-1 Honjo, Kumamoto City, Kumamoto 860-8556, Japan. Electronic address: yukihiro.
  • Shindo S; Department of Neurology, Kumamoto Red Cross Hospital, 2-1-1 Nagamineminami, Higashiku, Kumamoto City, Kumamoto 861-8520, Japan.
  • Miura M; Department of Neurology, Kumamoto Red Cross Hospital, 2-1-1 Nagamineminami, Higashiku, Kumamoto City, Kumamoto 861-8520, Japan.
  • Terasaki T; Department of Neurology, Kumamoto Red Cross Hospital, 2-1-1 Nagamineminami, Higashiku, Kumamoto City, Kumamoto 861-8520, Japan.
  • Mukasa A; Department of Neurosurgery, Graduate School of Medical Sciences, Kumamoto University, 1-1-1 Honjo, Kumamoto City, Kumamoto 860-8556, Japan.
  • Todaka T; Department of Neurosurgery, Kumamoto Red Cross Hospital, 2-1-1 Nagamineminami, Higashiku, Kumamoto City, Kumamoto 861-8520, Japan.
J Neuroradiol ; 50(4): 424-430, 2023 Jun.
Article em En | MEDLINE | ID: mdl-36270500
ABSTRACT
BACKGROUND AND

PURPOSE:

Intracranial atherosclerotic stenosis (ICAS)-related large vessel occlusion (LVO) is difficult to diagnose before endovascular thrombectomy (EVT) in an emergency. We hypothesized that hypoperfusion intensity ratio (HIR) and cerebral blood volume (CBV) index reflect collateral flow and would be useful parameters to predict underlying ICAS. MATERIALS AND

METHODS:

Clinical and perfusion imaging parameters of patients receiving EVT for LVO were reviewed retrospectively. Patients were divided into ICAS and embolism groups with angiographical findings. The association between prespecified parameters and underlying ICAS were assessed using multivariable logistic regression analyses. Discriminative ability was assessed using receiver operating characteristic analysis.

RESULTS:

Among 238 consecutive patients, 47 satisfied the inclusion criteria, including 10 with ICAS-related LVO. In ROC analyses, HIR showed good discrimination with a cutoff value of 0.22 (area under the curve, 0.85; 95%CI, 0.75-0.96; sensitivity, 0.84; specificity, 0.80) for underlying ICAS. CBV index showed excellent discrimination with a cutoff value of 0.90 (area under the curve, 0.92; 95%CI, 0.81-0.98; sensitivity, 0.92; specificity, 0.79). Multivariable logistic regression analysis revealed that HIR ≤ 0.22 (OR, 22.5; 95%CI, 2.9-177.0; P = 0.003) and CBV index ≥ 0.9 (OR, 75.7; 95%CI, 5.8-994.0; P < 0.001) were significantly associated with underlying ICAS.

CONCLUSION:

HIR ≤ 0.22 and CBV index ≥ 0.9 were associated with underlying ICAS and may predict underlying ICAS before EVT.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Arteriosclerose Intracraniana / Acidente Vascular Cerebral Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Arteriosclerose Intracraniana / Acidente Vascular Cerebral Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article