Continuous wavelet transform in the study of the time-scale properties of intracranial pressure in hydrocephalus. (9th July 2018)

• Record Type: Journal Article
• Authors: García, María; Poza, Jesús; Santamarta, David; Romero-Oraá, Roberto; Hornero, Roberto
• Is Part Of: Philosophical transactions. Volume 376:Number 2126(2018)
• Publication Date: 2018-07-09
• Subjects: hydrocephalus -- infusion test -- intracranial pressure -- continuous wavelet transform; Physical sciences -- Periodicals; Engineering -- Periodicals; Mathematics -- Periodicals; 500
• DOI: 10.1098/rsta.2017.0251
• Languages: English
• ISSNs: 1364-503X

Abstract

Abstract : Normal pressure hydrocephalus (NPH) encompasses a heterogeneous group of disorders generally characterized by clinical symptoms, ventriculomegaly and anomalous cerebrospinal fluid (CSF) dynamics. Lumbar infusion tests (ITs) are frequently performed in the preoperatory evaluation of patients who show NPH features. The analysis of intracranial pressure (ICP) signals recorded during ITs could be useful to better understand the pathophysiology underlying NPH and to assist treatment decisions. In this study, 131 ICP signals recorded during ITs were analysed using two continuous wavelet transform (CWT)-derived parameters: Jensen divergence (JD) and spectral flux (SF). These parameters were studied in two frequency bands, associated with different components of the signal: B 1 (0.15–0.3 Hz), related to respiratory blood pressure oscillations; and B 2 (0.67–2.5 Hz), related to ICP pulse waves. Statistically significant differences ( p < 1.70 × 10 −3, Bonferroni-corrected Wilcoxon signed-rank tests) in pairwise comparisons between phases of ITs were found using the mean and standard deviation of JD and SF. These differences were mainly found in B 2, where a lower irregularity and variability, together with less prominent time-frequency fluctuations, were found in the hypertension phase of ITs. Our results suggest that wavelet analysis could be useful for understanding CSF dynamics in NPH. This article is part of the theme issue 'Redundancy rules: the continuous wavelet transform comes of age'.