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Ischemic stroke
Original research
Automated assessment of ischemic core on non-contrast computed tomography: a multicenter comparative analysis with CT perfusion
  1. Puja Shahrouki1,
  2. Shingo Kihira1,
  3. Elham Tavakkol1,
  4. Joe X Qiao1,
  5. Achala Vagal2,
  6. Pooja Khatri3,
  7. Mersedeh Bahr-Hosseini4,
  8. Geoffrey P Colby1,5,
  9. Reza Jahan1,
  10. Gary Duckwiler1,
  11. Viktor Szeder1,4,
  12. Luke Ledbetter1,
  13. Stephen Cai1,
  14. Banafsheh Salehi1,
  15. Amish H. Doshi6,
  16. Puneet Belani6,
  17. Johanna T Fifi7,
  18. Reade De Leacy7,
  19. J Mocco7,
  20. Jeffrey L Saver4,
  21. David S Liebeskind4,
  22. Kambiz Nael1
  1. 1Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
  2. 2Department of Radiology, University of Cincinnati Medical Center, Cincinnati, Ohio, USA
  3. 3Department of Neurology, University of Cincinnati, Cincinnati, Ohio, USA
  4. 4Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
  5. 5Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
  6. 6Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
  7. 7Department of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, New York, USA
  1. Correspondence to Dr Kambiz Nael, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA; kambiznael{at}gmail.com

Abstract

Background Application of machine learning (ML) algorithms has shown promising results in estimating ischemic core volumes using non-contrast CT (NCCT).

Objective To assess the performance of the e-Stroke Suite software (Brainomix) in assessing ischemic core volumes on NCCT compared with CT perfusion (CTP) in patients with acute ischemic stroke.

Methods In this retrospective multicenter study, patients with anterior circulation large vessel occlusions who underwent pretreatment NCCT and CTP, successful reperfusion (modified Thrombolysis in Cerbral Infarction ≥2b), and post-treatment MRI, were included from three stroke centers. Automated calculation of ischemic core volumes was obtained on NCCT scans using ML algorithm deployed by e-Stroke Suite and from CTP using Olea software (Olea Medical). Comparative analysis was performed between estimated core volumes on NCCT and CTP and against MRI calculated final infarct volume (FIV).

Results A total of 111 patients were included. Estimated ischemic core volumes (mean±SD, mL) were 20.4±19.0 on NCCT and 19.9±18.6 on CTP, not significantly different (P=0.82). There was moderate (r=0.40) and significant (P<0.001) correlation between estimated core on NCCT and CTP. The mean difference between FIV and estimated core volume on NCCT and CTP was 29.9±34.6 mL and 29.6±35.0 mL, respectively (P=0.94). Correlations between FIV and estimated core volume were similar for NCCT (r=0.30, P=0.001) and CTP (r=0.36, P<0.001).

Conclusions Results show that ML-based estimated ischemic core volumes on NCCT are comparable to those obtained from concurrent CTP in magnitude and in degree of correlation with MR-assessed FIV.

  • stroke
  • CT perfusion
  • CT

Data availability statement

Data are available upon reasonable request.

http://dx.doi.org/10.1136/jnis-2023-020954

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    Data availability statement

    Data are available upon reasonable request.

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    Footnotes

    • Twitter @rdeleacymd, @kambiznael

    • Presented at The results of this paper were presented at the ASNR 61st Annual Meeting, Chicago, Ilinois, USA. Abstract#473. April 29-May 3, 2023.

    • Contributors Study design: AV, JM, KN. Data collection: PS, SK, ET, JXQ, AV, PB, AD, JTF. Data analysis and interpretation: PS, PK, MB-H, GPC, RJ, GD, VS, LL, SC, BS, JTF, RDL, JM, JLS, DSL, KN. Clinical input: PK, MB-H, GPC, JLS, DSL, KN. Writing manuscript: PS, KN. Revising the manuscript for important intellectual content: All authors. Approved the final version to be published: All authors. Guarantor: KN.

    • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

    • Competing interests GPC: Stryker Neurovascular, MicroVention, Medtronic, Rapid Medical; JLS: Medtronic Cerenovus, Boehringer Ingelheim, NeuroVasc, Rapid Medical; DSL: Cerenovus, Genentech, Medtronic, Stryker, Olea; KN: Olea Medical, Brainomix; Achala Vagal: Viz AI.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.