Neurostimulation in the patient with chronic pain: forecasting the future with data from the present – data-driven analysis or just dreams?

Abstract

Chronic pain involves a structured and individualized development of neurophysiological and biological responses. The final expression in each patient correlates with diverse expressions of mediators and activations of different transmission and modulation pathways, as well as alterations in the structure and function of the brain, all of which develop according to the pain phenotype. Still today, the selection process for the ideal candidate for spinal cord stimulation (SCS) is based on results from test and functional variables analysis as well as pain evaluation. In addition to the difficulties in the initial selection of patients and the predictive analysis of the test phase, which undoubtedly impact on the results in the middle and long term, the rate of explants is one of the most important concerns, in the analysis of suitability of implanted candidates. A potential for useful integration of genome analysis and lymphocyte expression in the daily practice of neurostimulation, for pain management is presented. Structural and functional quantitative information provided by imaging biomarkers will allow establishing a clinical decision support system that improve the effectiveness of the SCS implantation, optimizing human, economic and psychological resources. A correct programming of the neurostimulator, as well as other factors associated with the choice of leads and their position in the epidural space, are the critical factors for the effectiveness of the therapy. Using a model of SCS based on mathematical methods and computational simulation, the effect of different factors of influence on clinical practice studied, as several configurations of electrodes, position of these, and programming of polarities, in order to draw conclusions of clinical utility in neuroestimulation therapy.