Velocity Curvature Index: a Novel Diagnostic Biomarker for Large Vessel Occlusion.


Journal

Translational stroke research
ISSN: 1868-601X
Titre abrégé: Transl Stroke Res
Pays: United States
ID NLM: 101517297

Informations de publication

Date de publication:
10 2019
Historique:
received: 07 06 2018
accepted: 24 09 2018
revised: 06 08 2018
pubmed: 8 10 2018
medline: 31 3 2020
entrez: 8 10 2018
Statut: ppublish

Résumé

Despite being a conveniently portable technology for stroke assessment, Transcranial Doppler ultrasound (TCD) remains widely underutilized due to complex training requirements necessary to reliably obtain and interpret cerebral blood flow velocity (CBFV) waveforms. The validation of objective TCD metrics for large vessel occlusion (LVO) represents a first critical step toward enabling use by less formally trained personnel. In this work, we assess the diagnostic utility, relative to current standard CT angiography (CTA), of a novel TCD-derived biomarker for detecting LVO. Patients admitted to the hospital with stroke symptoms underwent TCD screening and were grouped into LVO and control groups based on the presence of CTA confirmed occlusion. Velocity curvature index (VCI) was computed from CBFV waveforms recorded at multiple depths from the middle cerebral arteries (MCA) of both cerebral hemispheres. VCI was assessed for 66 patients, 33 of which had occlusions of the MCA or internal carotid artery. Our results show that VCI was more informative when measured from the cerebral hemisphere ipsilateral to the site of occlusion relative to contralateral. Moreover, given any pair of bilateral recordings, VCI separated LVO patients from controls with average area under receiver operating characteristic curve of 92%, which improved to greater than 94% when pairs were selected by maximal velocity. We conclude that VCI is an analytically valid candidate biomarker for LVO diagnosis, possessing comparable accuracy, and several important advantages, relative to current TCD diagnostic methodologies.

Identifiants

pubmed: 30293170
doi: 10.1007/s12975-018-0667-2
pii: 10.1007/s12975-018-0667-2
pmc: PMC6733810
doi:

Substances chimiques

Biomarkers 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

475-484

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Auteurs

Samuel G Thorpe (SG)

Neural Analytics, Inc., 2440 S. Sepulveda Blvd. Suite 115, Los Angeles, CA, 90064, USA. samuel.thorpe@neuralanalytics.com.

Corey M Thibeault (CM)

Neural Analytics, Inc., 2440 S. Sepulveda Blvd. Suite 115, Los Angeles, CA, 90064, USA.

Seth J Wilk (SJ)

Neural Analytics, Inc., 2440 S. Sepulveda Blvd. Suite 115, Los Angeles, CA, 90064, USA.

Michael O'Brien (M)

Neural Analytics, Inc., 2440 S. Sepulveda Blvd. Suite 115, Los Angeles, CA, 90064, USA.

Nicolas Canac (N)

Neural Analytics, Inc., 2440 S. Sepulveda Blvd. Suite 115, Los Angeles, CA, 90064, USA.

Mina Ranjbaran (M)

Neural Analytics, Inc., 2440 S. Sepulveda Blvd. Suite 115, Los Angeles, CA, 90064, USA.

Christian Devlin (C)

Cardiac Biomechanics Group, University of Virginia, Charlottesville, VA, USA.

Thomas Devlin (T)

Department of Neurology, Erlanger Medical Center, Chattanooga, TN, USA.

Robert B Hamilton (RB)

Neural Analytics, Inc., 2440 S. Sepulveda Blvd. Suite 115, Los Angeles, CA, 90064, USA.

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