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New devices and techniques
Original research
Portable cerebral blood flow monitor to detect large vessel occlusion in patients with suspected stroke
  1. Christopher G Favilla1,
  2. Grayson L Baird2,
  3. Kedar Grama3,
  4. Soren Konecky3,
  5. Sarah Carter1,
  6. Wendy Smith4,
  7. Rebecca Gitlevich1,
  8. Alexa Lebron-Cruz1,
  9. Arjun G Yodh5,
  10. Ryan A McTaggart2
  1. 1Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
  2. 2Department of Interventional Radiology, Brown University, Providence, Rhode Island, USA
  3. 3Openwater, San Francisco, California, USA
  4. 4Department of Diagnostic Imaging, Lifespan Health System, Providence, Rhode Island, USA
  5. 5Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, Pennsylvania, USA
  1. Correspondence to Dr Christopher G Favilla, Department of Neurology, University of Pennsylvania, Philadelphia, USA; Christopher.favilla{at}pennmedicine.upenn.edu

Abstract

Background Early detection of large vessel occlusion (LVO) facilitates triage to an appropriate stroke center to reduce treatment times and improve outcomes. Prehospital stroke scales are not sufficiently sensitive, so we investigated the ability of the portable Openwater optical blood flow monitor to detect LVO.

Methods Patients were prospectively enrolled at two comprehensive stroke centers during stroke alert evaluation within 24 hours of onset with National Institutes of Health Stroke Scale (NIHSS) score ≥2. A 70 s bedside optical blood flow scan generated cerebral blood flow waveforms based on relative changes in speckle contrast. Anterior circulation LVO was determined by CT angiography. A deep learning model trained on all patient data using fivefold cross-validation and learned discriminative representations from the raw speckle contrast waveform data. Receiver operating characteristic (ROC) analysis compared the Openwater diagnostic performance (ie, LVO detection) with prehospital stroke scales.

Results Among 135 patients, 52 (39%) had an anterior circulation LVO. The median NIHSS score was 8 (IQR 4–14). The Openwater instrument had 79% sensitivity and 84% specificity for the detection of LVO. The rapid arterial occlusion evaluation (RACE) scale had 60% sensitivity and 81% specificity and the Los Angeles motor scale (LAMS) had 50% sensitivity and 81% specificity. The binary Openwater classification (high-likelihood vs low-likelihood) had an area under the ROC (AUROC) of 0.82 (95% CI 0.75 to 0.88), which outperformed RACE (AUC 0.70; 95% CI 0.62 to 0.78; P=0.04) and LAMS (AUC 0.65; 95% CI 0.57 to 0.73; P=0.002).

Conclusions The Openwater optical blood flow monitor outperformed prehospital stroke scales for the detection of LVO in patients undergoing acute stroke evaluation in the emergency department. These encouraging findings need to be validated in an independent test set and the prehospital environment.

  • Stroke
  • Blood Flow
  • Device
  • Technology
  • Thrombectomy

Data availability statement

Data are available upon reasonable request. The de-identified data that support the reported findings are available from the corresponding author upon reasonable request.

https://doi.org/10.1136/jnis-2024-021536

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    Data availability statement

    Data are available upon reasonable request. The de-identified data that support the reported findings are available from the corresponding author upon reasonable request.

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    Footnotes

    • CGF and GLB contributed equally.

    • Contributors CGF: study design, data collection, data analysis, data interpretation, manuscript preparation, manuscript revision. CGF is also responsible for the overall content as the guarantor. GB: study design, data analysis, data interpretation, manuscript preparation, manuscript revision. KG: study design, data analysis, database management, data interpretation, manuscript edits. SK: study design, data analysis, data interpretation, manuscript edits. SC: data collection, database management, manuscript edits. WS: data collection, database management, data interpretation, manuscript edits. RG: data collection, database management, manuscript edits. ALC: data collection, database management, manuscript edits. AGY: study design, data interpretation, manuscript preparation, manuscript edits. RAM: study design, data interpretation, manuscript preparation, manuscript edits.

    • Funding This work was supported by National Institutes of Health (K23-NS110993, CGF) and an investigator-initiated grant from Openwater (CGF & RAM).

    • Competing interests CGF and RAM received an investigator-initiated grant from Openwater. AGY has patents related to biomedical optical imaging but not directly relevant to this work (US patents 10,342,488; 10,827,976; 8,082,015; and 6,076,010) that do not currently generate income. SK and KG are employees of Openwater.

    • 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.