Integration of multiple prognostic predictors in a porcine spinal cord injury model: A further step closer to reality

Abstract

IntroductionSpinal cord injury (SCI) is a devastating neurological disorder with an enormous impact on individual's life and society. A reliable and reproducible animal model of SCI is crucial to have a deeper understanding of SCI. We have developed a large-animal model of spinal cord compression injury (SCI) with integration of multiple prognostic factors that would have applications in humans.MethodsFourteen human-like sized pigs underwent compression at T8 by implantation of an inflatable balloon catheter. In addition to basic neurophysiological recording of somatosensory and motor evoked potentials, we introduced spine-to-spine evoked spinal cord potentials (SP-EPs) by direct stimulation and measured them just above and below the affected segment. A novel intraspinal pressure monitoring technique was utilized to measure the actual pressure on the cord. The gait and spinal MRI findings were assessed in each animal postoperatively to quantify the severity of injury.ResultsWe found a strong negative correlation between the intensity of pressure applied to the spinal cord and the functional outcome (P < 0.0001). SP-EPs showed high sensitivity for real time monitoring of intraoperative cord damage. On MRI, the ratio of the high-intensity area to the cross-sectional of the cord was a good predictor of recovery (P < 0.0001).ConclusionOur balloon compression SCI model is reliable, predictable, and easy to implement. By integrating SP-EPs, cord pressure, and findings on MRI, we can build a real-time warning and prediction system for early detection of impending or iatrogenic SCI and improve outcomes.