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Decision Criteria for Large Vessel Occlusion Using Transcranial Doppler Waveform Morphology

Background: The current lack of effective tools for prehospital identification of Large Vessel Occlusion (LVO) represents a significant barrier to efficient triage of stroke patients and detriment to treatment efficacy. The validation of objective Transcranial Doppler (TCD) metrics for LVO detection...

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Autores principales: Thorpe, Samuel G., Thibeault, Corey M., Canac, Nicolas, Wilk, Seth J., Devlin, Thomas, Hamilton, Robert B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6199366/
https://www.ncbi.nlm.nih.gov/pubmed/30386287
http://dx.doi.org/10.3389/fneur.2018.00847
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author Thorpe, Samuel G.
Thibeault, Corey M.
Canac, Nicolas
Wilk, Seth J.
Devlin, Thomas
Hamilton, Robert B.
author_facet Thorpe, Samuel G.
Thibeault, Corey M.
Canac, Nicolas
Wilk, Seth J.
Devlin, Thomas
Hamilton, Robert B.
author_sort Thorpe, Samuel G.
collection PubMed
description Background: The current lack of effective tools for prehospital identification of Large Vessel Occlusion (LVO) represents a significant barrier to efficient triage of stroke patients and detriment to treatment efficacy. The validation of objective Transcranial Doppler (TCD) metrics for LVO detection could provide first responders with requisite tools for informing stroke transfer decisions, dramatically improving patient care. Objective: To compare the diagnostic efficacy of two such candidate metrics: Velocity Asymmetry Index (VAI), which quantifies disparity of blood flow velocity across the cerebral hemispheres, and Velocity Curvature Index (VCI), a recently proposed TCD morphological biomarker. Additionally, we investigate a simple decision tree combining both metrics. Methods: We retrospectively compare accuracy/sensitivity/specificity (ACC/SEN/SPE) of each method (relative to standard CT-Angiography) in detecting LVO in a population of 66 subjects presenting with stroke symptoms (33 with CTA-confirmed LVO), enrolled consecutively at Erlanger Southeast Regional Stroke Center in Chattanooga, TN. Results: Individual VCI and VAI metrics demonstrated robust performance, with area under receiver operating characteristic curve (ROC-AUC) of 94% and 88%, respectively. Additionally, leave-one-out cross-validation at optimal identified thresholds resulted in 88% ACC (88% SEN) for VCI, vs. 79% ACC (76% SEN) for VAI. When combined, the resultant decision tree achieved 91% ACC (94% SEN). Discussion: We conclude VCI to be superior to VAI for LVO detection, and provide evidence that simple decision criteria incorporating both metrics may further optimize. Performance: Our results suggest that machine-learning approaches to TCD morphological analysis may soon enable robust prehospital LVO identification. Registration: Was not required for this feasibility study.
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spelling pubmed-61993662018-11-01 Decision Criteria for Large Vessel Occlusion Using Transcranial Doppler Waveform Morphology Thorpe, Samuel G. Thibeault, Corey M. Canac, Nicolas Wilk, Seth J. Devlin, Thomas Hamilton, Robert B. Front Neurol Neurology Background: The current lack of effective tools for prehospital identification of Large Vessel Occlusion (LVO) represents a significant barrier to efficient triage of stroke patients and detriment to treatment efficacy. The validation of objective Transcranial Doppler (TCD) metrics for LVO detection could provide first responders with requisite tools for informing stroke transfer decisions, dramatically improving patient care. Objective: To compare the diagnostic efficacy of two such candidate metrics: Velocity Asymmetry Index (VAI), which quantifies disparity of blood flow velocity across the cerebral hemispheres, and Velocity Curvature Index (VCI), a recently proposed TCD morphological biomarker. Additionally, we investigate a simple decision tree combining both metrics. Methods: We retrospectively compare accuracy/sensitivity/specificity (ACC/SEN/SPE) of each method (relative to standard CT-Angiography) in detecting LVO in a population of 66 subjects presenting with stroke symptoms (33 with CTA-confirmed LVO), enrolled consecutively at Erlanger Southeast Regional Stroke Center in Chattanooga, TN. Results: Individual VCI and VAI metrics demonstrated robust performance, with area under receiver operating characteristic curve (ROC-AUC) of 94% and 88%, respectively. Additionally, leave-one-out cross-validation at optimal identified thresholds resulted in 88% ACC (88% SEN) for VCI, vs. 79% ACC (76% SEN) for VAI. When combined, the resultant decision tree achieved 91% ACC (94% SEN). Discussion: We conclude VCI to be superior to VAI for LVO detection, and provide evidence that simple decision criteria incorporating both metrics may further optimize. Performance: Our results suggest that machine-learning approaches to TCD morphological analysis may soon enable robust prehospital LVO identification. Registration: Was not required for this feasibility study. Frontiers Media S.A. 2018-10-17 /pmc/articles/PMC6199366/ /pubmed/30386287 http://dx.doi.org/10.3389/fneur.2018.00847 Text en Copyright © 2018 Thorpe, Thibeault, Canac, Wilk, Devlin and Hamilton. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neurology
Thorpe, Samuel G.
Thibeault, Corey M.
Canac, Nicolas
Wilk, Seth J.
Devlin, Thomas
Hamilton, Robert B.
Decision Criteria for Large Vessel Occlusion Using Transcranial Doppler Waveform Morphology
title Decision Criteria for Large Vessel Occlusion Using Transcranial Doppler Waveform Morphology
title_full Decision Criteria for Large Vessel Occlusion Using Transcranial Doppler Waveform Morphology
title_fullStr Decision Criteria for Large Vessel Occlusion Using Transcranial Doppler Waveform Morphology
title_full_unstemmed Decision Criteria for Large Vessel Occlusion Using Transcranial Doppler Waveform Morphology
title_short Decision Criteria for Large Vessel Occlusion Using Transcranial Doppler Waveform Morphology
title_sort decision criteria for large vessel occlusion using transcranial doppler waveform morphology
topic Neurology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6199366/
https://www.ncbi.nlm.nih.gov/pubmed/30386287
http://dx.doi.org/10.3389/fneur.2018.00847
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