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Effect of computed tomography perfusion post-processing algorithms on optimal threshold selection for final infarct

Ryan A Rava1,2, Kenneth V Snyder2,3, Maxim Mokin4

  • 1Department of Biomedical Engineering, University at Buffalo, USA.

The Neuroradiology Journal
|June 24, 2020
PubMed
Summary

This study identifies optimal computed tomography perfusion (CTP) thresholds for acute ischemic stroke (AIS) patients, improving infarct volume accuracy. Different thresholds are needed for intervention vs. non-intervention cases and between CTP analysis algorithms.

Keywords:
BayesianCT perfusionfluid-attenuation inversion recovery MRIischemic strokesingular value decomposition plus

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Area of Science:

  • Neurology
  • Radiology
  • Medical Imaging

Background:

  • Computed tomography perfusion (CTP) is crucial for assessing acute ischemic stroke (AIS) and guiding endovascular intervention eligibility.
  • Current CTP analysis methods lack uniform perfusion parameter thresholds, leading to variability in infarct and penumbra volume quantification.
  • This variability stems from differences in patient demographics and computational algorithms used in post-processing.

Purpose of the Study:

  • To determine optimal perfusion thresholds for infarct and penumbra volume quantification in AIS patients.
  • To compare the performance of two CTP post-processing algorithms: Vitrea Bayesian and singular value decomposition plus (SVD+).
  • To investigate if optimal thresholds differ between intervention and non-intervention patient groups and between the two algorithms.

Main Methods:

  • Utilized data from 107 AIS patients (67 non-intervention, 40 intervention with successful reperfusion).
  • Predicted infarct volumes using absolute time-to-peak (TTP) and relative regional cerebral blood volume (rCBV) thresholds for both algorithms.
  • Determined optimal thresholds by minimizing discrepancies between CTP-predicted and 24-hour FLAIR MRI infarct volumes, validated on 60 additional patients.

Main Results:

  • Identified distinct optimal thresholds for TTP and rCBV for both Bayesian and SVD+ algorithms across intervention and non-intervention groups.
  • Optimal TTP thresholds varied significantly between intervention and non-intervention patients for both algorithms.
  • Optimal rCBV thresholds were consistent for intervention patients but differed significantly for non-intervention patients between algorithms.

Conclusions:

  • Optimal CTP perfusion thresholds for infarct quantification in AIS are algorithm- and patient-dependent.
  • The findings provide specific optimal thresholds for Bayesian and SVD+ algorithms, aiding in more accurate infarct volume assessment.
  • The study suggests that tailored threshold selection is necessary for precise CTP analysis in acute ischemic stroke management.