Visibility Graph Analysis of Intraspinal Pressure Signal Predicts Functional Outcome in Spinal Cord Injured Patients

Abstract

To guide management of patients with acute spinal cord injuries, we developed intraspinal pressure monitoring from the injury site. Here, we examine the complex fluctuations in the intraspinal pressure signal using network theory. We analyzed 7097 h of intraspinal pressure data from 58 patients with severe cord injuries. Intraspinal pressure signals were split into hourly windows. Each window was mapped into a visibility graph as follows. Vertical bars were drawn at 0.1 Hz representing signal amplitudes. Each bar produced a node, thus totalling 360 nodes per graph. Two nodes were linked with an edge if the straight line through the nodes did not intersect a bar. We computed several topological metrics for each graph including diameter, modularity, eccentricity, and small-worldness. Patients were followed up for 20 months on average. Our data show that the topological structure of intraspinal pressure visibility graphs is highly sensitive to pathological events at the injury site, including cord compression (high intraspinal pressure), ischemia (low spinal cord perfusion pressure), and deranged autoregulation (high spinal pressure reactivity index). These pathological changes correlate with long graph diameter, high modularity, high eccentricity and reduced small-worldness. In a multivariate logistic regression model, age, neurological status on admission, and average node eccentricity were independent predictors of neurological improvement. We conclude that analysis of intraspinal pressure fluctuations after spinal cord injury as graphs, rather than as time series, captures clinically important information. Our novel technique may be applied to other signals recorded from injured central nervous system (CNS); for example, intracranial pressure, tissue metabolite, and oxygen levels.

Efficacy of Ultra-Early (< 12 h), Early (12–24 h), and Late (>24–138.5 h) Surgery with Magnetic Resonance Imaging-Confirmed Decompression in American Spinal Injury Association Impairment Scale Grades A, B, and C Cervical Spinal Cord Injury

“…35 Additional studies incorporating post-operative MRI indicate that up to 25% of patients may need expansive duraplasty for adequate spinal cord decompression, along with reduction of intraspinal pressure, in order to improve functional outcome. 14,15,42,44,45 As a result, studies on the effect of timing of surgical intervention have likely been confounded by incomplete spinal cord decompression, and, therefore, the effect of timing on outcome remains uncertain. 28,30,[46][47][48] The null hypothesis was that in patients with subaxial cervical TSCI and post-operative MRI confirmation of decompression, the timing of surgery has no effect on long-term improvement in American Spinal Injury Association (ASIA) Impairment Scale (AIS) grade conversion.…”

Medical Communication Services after Traumatic Spinal Cord Injury

“…Most sufferers of complete SCI are paralyzed, with no bladder, bowel, or sexual function [ 1 ]. The swollen spinal cord is compressed by the dura mater, leading to raised intraspinal pressure (ISP).…”

Individual-specific networks for prediction modelling – A scoping review of methods

“…A time series with n sequentially ordered data points, { x t } t = 1, …, n is transformed into a network in which each time point t represents a node connected to time point s if the visibility criterion holds true for an additional data point x u placed between them. Applications of visibility graphs were mostly found in context of EEG data [ 43 – 45 ] but also in a cardiologic study dealing with human heart rate variability time series to differentiate between wake/sleep stages [ 46 ] and patients of spinal cord injury [ 47 ]. A more thorough overview of concepts and algorithms to map time series data into networks can be found in Silva et al [ 48 ].…”