Abstract
Background
Cranial accelerometry is used to detect cerebral vasospasm and concussion. We explored this technique in a cohort of code stroke patients to see whether a signature could be identified to aid in the diagnosis of large vessel occlusion (LVO) stroke.
Methods
A military-grade three-axis accelerometer was affixed to a headset. Accelerometer and electrocardiogram (ECG) outputs were digitized at 1.6 kHz. We call the resulting digitized signals the “headpulse.” Three-minute recordings were performed immediately after computed tomography (CT) angiography (CTA) and/or immediately before and after attempted mechanical thrombectomy in patents with suspected stroke. The resulting waveforms were inspected by eye and then subjected to supervised machine learning (MATLAB Classification Learner R2018a) to train a model using fivefold cross-validation.
Results
Of 42 code stroke subjects with recordings, 19 (45%) had LVO and 23 (55%) had normal CTAs. In patients without LVO, ECG-triggered waveforms followed a self-similar time course revealing that the headpulse is highly coupled to the cardiac contraction. However, in most patients with LVO, headpulses showed little cardiac contraction correlation. We term this abnormality “chaos” and parameterized it with 156 measures of trace-by-trace variation from the ECG-signal-averaged mean for machine learning model training. Selecting the best model, using biometric data only, we properly classified 15/19 LVOs and 20/23 non-LVO patients, with receiver operating characteristic curve area = 0.79, sensitivity of 73%, and specificity of 87%, P < 0.0001. Headpulse waveforms following thrombectomy showed return of cardiac contraction correlation.
Conclusions
Headpulse recordings performed on patients with suspected acute stroke significantly identify those with LVO. The lack of temporal correlation of the headpulse with cardiac contraction and resolution to normal may reflect changes in cerebral blood flow and may provide a useful technique to triage stroke patients for thrombectomy using a noninvasive device.
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Acknowledgements
We thank Dominica Randazzo, Tina Rothschild, and Jeany Duncan for their expert clinical coordination skills in this research.
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All authors made subsubstantial contributions to conception and design, acquisition of data, and analysis and interpretation of data, contibuted to drafting the article, and provided final approval of the version to be published.
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Funding was provided by internal UCSF Department of Neurology sources. Dr. Keenan was supported by NIH StrokeNet Fellowship: U24NS107229
Conflict of interest
Kevin Keenan has no disclosures. Wade Smith and Paul Lovoi have a provisional patent filed by UCSF naming them as inventors in this technology and both have ownership interest in MindRhythm, Inc. Dr. Lovoi holds stock in Jan Medical.
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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
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Smith, W.S., Keenan, K.J. & Lovoi, P.A. A Unique Signature of Cardiac-Induced Cranial Forces During Acute Large Vessel Stroke and Development of a Predictive Model. Neurocrit Care 33, 58–63 (2020). https://doi.org/10.1007/s12028-019-00845-x
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DOI: https://doi.org/10.1007/s12028-019-00845-x