Mitigating Neuropathic Pain: From Theory to Practice

Inhibiting Neuroma Pain <i>In­-silico</i> and Measuring Neural Activity <i>In­-vivo</i>

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Neuropathic pain (NP) affects approximately seven to ten percent of the general population. Seventeen percent of NP patients scored their life as “worse than death”. A myriad of causes may underlie NP, such as stroke or spinal cord injury. Also, damage or disease of the peripheral nervous system (PNS) may result in NP. One of the main issues of NP caused by a peripheral nerve injury (PNI) is the development of a neuroma, which is a tumor-like mass at the proximal end of a severed nerve that can become very painful. Neuromas show unique neurophysiological characteristics. Cell membrane alternations lead to different ion channel distributions, which in turn result in subthreshold oscillations (SO) and ectopic discharges (ED). It is assumed that this behavior could lead to NP generation.

Electrical neurostimulation (ENS) is used to treat patients, thereby applying pre-programmed stimulation patterns to the affected nerves. However, the pain-provoking signals which run through the nerves are not detected and analyzed before ENS is provided. Furthermore, it is questionable whether (the currently applied) pre-programmed ENS defuses these signals anyway. In addition, pre-programmed ENS is not effective at all moments of the pain experience caused by fluctuations in signal intensity. As the clinical results are discouraging, and in view of the high costs, the popularity of this technology is currently waning. Optimization of this potentially powerful technique is needed to improve the outcome and make this technology useful to implement in the treatment strategy of patients with intractable otherwise difficult to treat pain syndromes. Theoretically, optimization of stimulation technology is possible by actually neutralizing SO and ED, which should lead to mitigating the generation of NP.

We propose an approach to neutralize SO and ED consisting of several steps. Firstly, the nerve activity is real-time monitored. Secondly,
a decision mechanism (called a ‘controller’) is developed that constructs electrical neurostimulation (ENS) patterns to neutralize SO and ED. Finally, these patterns are actually applied to the nerve by an electrical stimulator...