Derivation and evaluation of thresholds for core and tissue at risk of infarction using CT perfusion

Ferghal McVerry, Krishna Ashok Dani, Niall J J MacDougall, Mary Joan MacLeod, Joanna Wardlaw, Keith W Muir

Research output: Contribution to journalArticlepeer-review

23 Citations (Scopus)

Abstract

BACKGROUND AND PURPOSE: Computed tomography perfusion provides information on tissue viability according to proposed thresholds. We evaluated thresholds for ischemic core and tissue at risk and subsequently tested their accuracy in independent datasets.

MATERIALS AND METHODS: Tissue at risk was evaluated in patients with persistent arterial occlusions, and ischemic core thresholds in patients with recanalization and major clinical improvement. Scans were randomly allocated to derivation or validation groups for tissue at risk and core analysis. Optimum thresholds using mean transit time (MTT), cerebral blood flow (CBF), cerebral blood volume, and delay time (DT) were assessed.

RESULTS: Absolute MTT, relative MTT and DT were best derived predictors of tissue at risk with thresholds of ≥ 7 seconds, ≥ 125%, and ≥ 2 seconds respectively. DT ≥ 2 seconds was the best predictor in the validation dataset (95% agreement levels = -44 to +30 mL, Bias = -6.9). Absolute and relative MTT were the best derived predictors of infarct volume in the core group (8 seconds and 125% respectively) but relative CBF of ≤ 45% performed best in the core validation dataset.

CONCLUSIONS: Time-based perfusion thresholds perform well as predictors of tissue at risk of infarction with DT the best predictor. Relative CBF was the best predictor of ischemic core. Evaluation in larger populations is needed to confirm the performance of tissue viability thresholds.

Original languageEnglish
Pages (from-to)562-568
Number of pages7
JournalJournal of neuroimaging : official journal of the American Society of Neuroimaging
Volume24
Issue number6
Early online date4 Jul 2014
DOIs
Publication statusPublished - 22 Jul 2014

Bibliographical note

Copyright © 2014 by the American Society of Neuroimaging.

Accepted for publication March 31, 2014

Funded by
Translational Medicine Research Collaboration

Keywords

  • stroke
  • computed tomography
  • imaging
  • perfusion

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