Evaluation of Efficiency and Selectivity of a Novel Computational Model of Spinal Cord Stimulation for Chronic Pain



 DESCRIPTION (provided by applicant): Chronic pain is an important, prevalent, and expensive condition that is difficult to treat. Modern innovations in the field have dramatically increased the survival of combatants, but also increased the number of those surviving with chronic pain. Pain issues among active-duty military and Veterans have many unique features. In addition to battlefield injuries, greater exposure to trauma and psychological stress than the general public compounds the likelihood of developing chronic pain. Management of injury-related chronic pain may require a combination of approaches including local and systemic analgesic drugs, pain-directed physical therapy, behavior modification, biofeedback, and other interventions. An increasingly employed therapy in the management of Veterans with chronic pain is spinal cord stimulation (SCS). It has been shown in clinical studies to be safe and effective for properly selected patients and approved by the FDA to treat chronic pain of the trunk and limbs. SCS remains significantly under-utilized compared to either chronic opiates or surgical re- operation. The VHA has adopted routine screening and assessment of pain as well as planning for pain reduction as a national policy throughout the VHA health care system. SCS involves epidural implantation of a stimulation electrode connected to a small internal pacemaker. Activation of dorsal column (DC) fibers in the dermatomes associated with pain is often limited by the onset of discomfort associated with activation of nearby dorsal roots (DR). Successful SCS is thought to depend on activation of DC fibers without activation of DR fibers, which is termed selectivity. Predicting selectivity, and which patients will respond to the therapy, is currently only possible by doing an invasive "trial" procedure, where an electrode is temporarily inserted and the patient is allowed to experience the neurostimulation and state whether it is helpful. Furthermore, due to the millions of possible stimulation parameters and varying patient anatomy, SCS programming can be time consuming, expensive, and result in aberrant stimulation. The objective of this proposal is to validate a patient-specific model that reliably predicts %DC/DR selective activation, by tailoring the dynamic range based on patient anatomy. This project is a collaboration with experts from VA Neurosurgery and the Bioengineering and Neurosurgery Departments at Duke University. It will focus on validating a patient-specific SCS model that reliably predicts activaton of neural elements responsible for pain relief, utilizing settings tailored to patient anatomy. A pilot clinical study demonstrating proof of concept has already been completed. This CSR&D Merit Award will expand upon this in a larger, mechanistic study in Veterans with existing SCS therapy. In Aim 1, each patient's existing preoperative MRI and postoperative X-ray images will be combined to construct a personalized, computational model based on patient-specific anatomy. Aim 2 will further demonstrate feasibility of models in maximizing selectivity, while reducing SCS programming times and improving clinical outcomes, by providing >50% reduction in pain from baseline. Successful completion of this proposal is expected based on the strength of the team and extensive preliminary data. This project will provide the data to justify broader clinical studies and development of a customized SCS software platform for the evaluation and treatment of chronic pain. The long-term goal of the project is to develop a novel platform that will lead to significant advances in the treatment of chronic pain for Veterans worldwide.