A novel predictive spinal cord stimulation (SCS) algorithm for chronic pain, presented at the 2016 Neural Interfaces Conference in Baltimore, was inspired by biological evolution.
Akin to the neck of a giraffe becoming longer in order to reach leaves higher on a tree for eating, the algorithm relies on computational evolution to refine sets of stimulation parameters. “These stimulation parameters are optimized or evolve over time to become the most fit,” said Warren M. Grill, PhD, professor of biomedical engineering at Duke University, in Durham, N.C. “In this case, fitness is a computer-based prediction of how well those parameters will relieve pain in a particular patient.”
The investigators recognize the significant clinical challenge in programming the parameters of SCS. “This is a time-consuming process,” Dr. Grill said. “Also, it is highly likely that many patients are walking around with suboptimal programs.”
One reason for inferior programming is that the parameter space of potential choices “is very, very large,” Dr. Grill said. “You have to select a stimulation voltage for each contact on the electrode array—in some instances, as many as 25 electrode contacts. You also have to pick stimulation pulse duration and a stimulation frequency.”
All these required choices occur within a short period of time, during which the only elements available to the programmer “are qualitative descriptions provided by the patient,” Dr. Grill said. “As a result, we were motivated to develop a systematic way to select stimulation parameters in hopes of making that process more rapid and leading to optimal parameters, in other words, doing a better job in relieving pain in the patient.”
For the new algorithm, the intent of the fitness function is to maximize the activation of the dorsal column fibers while minimizing activation of the nearby dorsal root fibers. “You want to stimulate most of the pain-relieving elements and lessen stimulation of the elements that produce side effects,” Dr. Grill said.
To date, the algorithm has been validated retrospectively in 12 patients with either low back or leg pain. “Results are extremely encouraging,” Dr. Grill said. However, in the retrospective study, there was no assessment of pain using the chosen parameters, but rather a comparison of the model-generated parameters with factors selected by an expert programmer. “We wanted to see if our algorithm achieves somewhere in the neighborhood of the current state of the art, which it does,” Dr. Grill said.
Timothy Deer, MD, president of the International Neuromodulation Society, noted that the use of computer modeling for neuromodulation “is not a new concept.” However, the work being conducted by Dr. Grill and his associates “could be the next great step forward.”
The translation from the computer model to the patient “is the critical piece that we must explore,” Dr. Deer said. “This work shows the importance of the bench researcher, scientist and clinician all working together to create the next great advances.”
Dr. Deer said the last model that proved to be clinically effective was the feedback loop model. “This new model could have equal impact in the field,” Dr. Deer said. “The SCS algorithm needs to be tested initially as a pilot in a small patient group and then expanded, if results show promise.”
In the future, the ability to apply new computer modeling “will be very efficient, since most stimulation systems will be upgradable and the access to new algorithms will be almost instantaneous, once safety is established,” Dr. Deer said.
Dr. Grill affirmed that the algorithm represents a successful collaboration between Duke neurosurgeon Shivanand Lad, MD, PhD, and engineers. “It is through these partnerships that we can truly advance SCS therapies,” said Dr. Grill, who is an inventor on pending patents related to the algorithm. “We are convinced that our algorithm is a viable approach to select optimal parameters. But the ultimate efficacy will be determined in a prospective study, for which we have secured both financing through a grant and regulatory approval to pursue a roughly 30-patient study, starting this fall.”
The prospective study will assess pain and pain interference, comparing conventional programming with programming with the optimization algorithm. The investigators eventually hope to partner with an existing commercial manufacturer of SCS. In turn, the manufacturer would offer the algorithm software to physicians who use its system.