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Automated estimation of ischemic core prior to thrombectomy: comparison of two current algorithms

  • Diagnostic Neuroradiology
  • Published:
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Abstract

Purpose

Endovascular thrombectomy (EVT) improves clinical outcomes in ischemic stroke with large vessel occlusion. Clinical benefits are inversely proportional to size of the pre-treatment ischemic core. This study compared estimated ischemic core volumes by two different CT perfusion (CTP) automated algorithms to the gold standard follow-up infarct volume using diffusion-weighted imaging (DWI) to assess for congruence, and thus eligibility for EVT.

Methods

Retrospective, single-center cohort study of 102 patients presenting to a comprehensive stroke center between 2012 and 2018. Inclusion criteria were CT perfusion prior to EVT, successful EVT with mTIBI 2b-3 reperfusion, and DWI post-EVT. CTP data were retrospectively processed by two algorithms: “delay and dispersion insensitive deconvolution” (DISD, RAPID software) versus “delay and dispersion corrected single value decomposition” (ddSVD, Mistar software), using commercially available software. Core volumes were compared to follow up DWI using independent software (MRIcron). Agreement between each algorithm and DWI was estimated using Lin’s concordance coefficient and analyzed using reduced major axis regression.

Results

We included 102 patients. Both algorithms had excellent agreement with DWI (Lin’s concordance coefficients: DISD 0.8 (95% CI: 0.73; 0.87), ddSVD 0.92 (95% CI: 0.89; 0.95). Compared to ddSVD (reduced major axis slope = 0.95), DISD exhibited a larger extent of proportional bias (slope = 1.12).

Conclusion

The ddSVD algorithm better correlates with DWI follow-up infarct volume than DISD processing. The DISD algorithm overestimated larger ischemic cores which may lead to patient exclusion from thrombectomy based on selection by core volume.

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Data availability

Available upon request

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Materials availability

Available upon request

Code availability

RAPID (Version 4.6.1, iSchemaView, MountainView, California) and Mistar (Version 3.2.63, Apollo Medical Imaging Technology, Melbourne, Australia) were used (see “Methods” section).

Funding

No funding was received for this study.

Author information

Authors and Affiliations

  1. Melbourne Brain Centre at Royal Melbourne Hospital, University of Melbourne, Grattan St, Parkville, Victoria, 3050, Australia

    Lakshini Gunasekera, Andrew Bivard, Gagan Sharma, Mark W. Parsons & Bernard Yan

  2. Melbourne Medical School, University of Melbourne, Melbourne, Australia

    Leonid Churilov

  3. Neurointervention Service, Department of Radiology, Royal Melbourne Hospital, Melbourne, Australia

    Peter Mitchell

Authors
  1. Lakshini Gunasekera
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  2. Leonid Churilov
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  3. Peter Mitchell
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  4. Andrew Bivard
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  5. Gagan Sharma
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  6. Mark W. Parsons
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  7. Bernard Yan
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Contributions

BY and MP conceived the study. LG performed data collection. LG, BY, MP, and AB analyzed data. LG drafted the manuscript and all authors contributed equally to its revision. LC, BY, MP, and AB were involved in the statistical analysis. LG and BY take responsibility for the paper as a whole.

Corresponding author

Correspondence to Lakshini Gunasekera.

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Ethics approval

Royal Melbourne Hospital Institutional Review Board approval (HREC QA 2013-072).

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Not applicable

Conflicts of interest

MP and AB have research partnerships with Apollo, Siemens, and Canon.

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Supplementary information

Supplementary Figure 1

Sample outcome from anonymised patient (PNG 3945 kb)

High resulotion image (TIF 1060 kb)

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Gunasekera, L., Churilov, L., Mitchell, P. et al. Automated estimation of ischemic core prior to thrombectomy: comparison of two current algorithms. Neuroradiology 63, 1645–1649 (2021). https://doi.org/10.1007/s00234-021-02651-9

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  • DOI: https://doi.org/10.1007/s00234-021-02651-9

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