Novel aspects of spinal cord evoked potentials (SCEPs) in the evaluation of dorso-ventral and lateral mechanical impacts on the spinal cord.

OBJECTIVES

The aim of the current study was to mimic mechanical impacts on the spinal cord by manifesting the effects of dorsoventral (DVMP) and lateral (LMP) mechanical pressure on neural activity to address points to be considered during surgery for different purposes, including spinal cord decompression.

APPROACHES

Spinal cords of anesthetized rats were compressed at T13. Different characteristics of axons, including vulnerability, excitability, and conduction velocity (CV), in response to promptness, severity, and duration of pressure were assessed by spinal cord evoked potentials (SCEPs). Real-time SCEPs recorded at L4-5 revealed N1, N2, and N3 peaks that were used to represent the activity of injured sensory afferents, interneurons, and MN fibers. The averaged SCEP recordings were fitted by trust-region algorithm to find the equivalent Gaussian and polynomial equations.

MAIN RESULTS

The pyramidal and extrapyramidal pathways possessed CVs of 3-11 and 16-80 m s(-1), respectively. DVMP decreased the excitability of myelinated neural fibers in antidromic and orthodromic pathways. The excitability of fibers in extrapyramidal and pyramidal pathways of lateral corticospinal (LCS) and anterior corticospinal (ACS) tracts decreased following LMP. A significant drop in the amplitude of N3 and its conduction velocity (CV) revealed higher susceptibility of less-myelinated fibers to both DVMP and LMP. The best parametric fitting model for triplet healthy spinal cord CAP was a six-term Gaussian equation (G6) that fell into a five-term equation (G5) at the complete compression stage.

SIGNIFICANCE

The spinal cord is more susceptible to dorsoventral than lateral mechanical pressures, and this should be considered in spinal cord operations. SCEPs have shown promising capabilities for evaluating the severity of SCI and thus can be applied for diagnostic or prognostic intraoperative monitoring (IOM).