Estimation of ischemic core volume using computed tomographic perfusion Bayesian versus singular value deconvolution postprocessing

Yu Sakai, Bradley N. Delman, Johanna T. Fifi, Stanley Tuhrim, Danielle Wheelwright, Amish H. Doshi, J. Mocco, Kambiz Nael

Research output: Contribution to journalArticlepeer-review

25 Scopus citations


Background and Purpose: Estimation of infarction based on computed tomographic perfusion (CTP) has been challenging, mainly because of noise associated with CTP data. The Bayesian method is a robust probabilistic method that minimizes effects of oscillation, tracer delay, and noise during residue function estimation compared with other deconvolution methods. This study compares CTP-estimated ischemic core volume calculated by the Bayesian method and by the commonly used block-circulant singular value deconvolution technique. Methods: Patients were included if they had (1) anterior circulation ischemic stroke, (2) baseline CTP, (3) successful recanalization defined by thrombolysis in cerebral infarction ≥IIb, and (4) minimum infarction volume of >5 mL on follow-up magnetic resonance imaging (MRI). CTP data were processed with circulant singular value deconvolution and Bayesian methods. Two established CTP methods for estimation of ischemic core volume were applied: cerebral blood flow (CBF) method (relative CBF, <30% within the region of delay >2 seconds) and cerebral blood volume method (<2 mL per 100 g within the region of relative mean transit time >145%). Final infarct volume was determined on MRI (fluid-attenuated inversion recovery images). CTP and MRI-derived ischemic core volumes were compared by univariate and Bland-Altman analysis. Results: Among 35 patients included, the mean/median (mL) difference for CTP-estimated ischemic core volume against MRI was −4/−7 for Bayesian CBF (P=0.770), 20/12 for Bayesian cerebral blood volume (P=0.041), 21/10 for circulant singular value deconvolution CBF (P=0.006), and 35/18 for circulant singular value deconvolution cerebral blood volume (P<0.001). Among all methods, Bayesian CBF provided the narrowest limits of agreement (−28 to 19 mL) in comparison with MRI. Conclusions: Despite existing variabilities between CTP postprocessing methods, Bayesian postprocessing increases accuracy and limits variability in CTP estimation of ischemic core.

Original languageEnglish
Pages (from-to)2345-2352
Number of pages8
Issue number10
StatePublished - 2018


  • Computed tomography
  • Follow-up studies
  • Humans
  • Infarction
  • Magnetic resonance imaging
  • Perfusion imaging


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