Joint time-frequency analysis of dynamic cerebral autoregulation using generalized harmonic wavelets.
Physiol Meas
; 41(2): 024002, 2020 03 06.
Article
em En
| MEDLINE
| ID: mdl-32000149
OBJECTIVE: To develop a joint time-frequency analysis technique based on generalized harmonic wavelets (GHWs) for dynamic cerebral autoregulation (DCA) performance quantification. APPROACH: We considered two groups of human subjects to develop and validate the method: 55 healthy volunteers and 35 stroke-free subjects with unilateral internal carotid artery stenosis (CAS). We determined the mean and coherence-weighted average of the phase shift (PS) of appropriately defined GHW-based transfer functions, based on data points over the joint time-frequency domain. We compared agreement of standard transfer function analysis (TFA) and GHW analyses in healthy subjects using Bland-Altman plots. We assessed sensitivity of each metric to detect the presumed side-to-side difference in DCA function in CAS subjects (with decreased PS on the occluded side), using McNemar's chi square test to compare each metric to the standard TFA approach. An alternative Morlet wavelet-based approach was also considered. MAIN RESULTS: The GHW and TFA methods exhibited strong agreement in healthy subjects. Among CAS subjects, GHW metrics outperformed TFA and Morlet wavelet-based approaches in identifying expected side-to-side differences: TFA sensitivity was 40.0% (95%CI 23.9-57.9), Morlet 60.0% (95%CI 42.1-76.1), and GHW >70% for both metrics (GHW mean PS sensitivity 74.3, 95%CI 56.7-87.5, pâ = 0.0027 versus TFA; GHW coherence-weighted PS sensitivity 71.4, 95%CI 53.7-85.4, pâ = 0.0009 versus TFA). SIGNIFICANCE: In comparison to the widely used stationary Fourier transform-based TFA and to Morlet wavelet-based analysis, our data suggest that the GHW-based analysis performs better in identifying DCA asymmetry between the two cerebral hemispheres in patients with high grade unilateral carotid stenosis. Our method may provide enhanced confidence in employing DCA metrics as a sensitive diagnostic tool for detecting impaired DCA function in a variety of pathological settings.
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Base de dados:
MEDLINE
Assunto principal:
Circulação Cerebrovascular
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Análise de Ondaletas
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Homeostase
Tipo de estudo:
Observational_studies
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Prognostic_studies
Limite:
Adult
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Female
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Humans
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Male
Idioma:
En
Ano de publicação:
2020
Tipo de documento:
Article