A New Direction for Closed-Loop Spinal Cord Stimulation: Combining Contemporary Therapy Paradigms with Evoked Compound Action Potential Sensing.

Abstract

Spinal cord stimulation (SCS) utilizes the delivery of mild electrical pulses via epidural electrodes placed on the dorsal side of the spinal cord, typically to treat chronic pain. The first clinical use of SCS involved the delivery of paresthesia inducing, low-frequency waveforms to the neural targets corresponding to the painful areas. Contemporary SCS therapies now leverage novel therapeutic pathways to limit paresthesia and deliver superior clinical outcomes. Historically, SCS has largely been delivered with fixed stimulation parameters. This approach, referred to as open-loop (OL) SCS, does not account for the fluctuations in spacing—driven by postural changes and activity—between the electrodes and the cord. These fluctuations result in variability in the delivered dose and the volume of tissue activation (VTA) that manifests with each stimulation pulse. Inconsistent dosing may lead to suboptimal therapeutic efficacy and durability. To address this clinical need, closed-loop (CL) SCS systems have been developed to automatically adjust stimulation parameters to compensate for this variability. The evoked compound action potential (ECAP), a biopotential generated by the synchronous activation of dorsal column fibers, is indicative of the VTA resulting from the stimulation pulse. The ECAP may be utilized as a control signal in CL SCS systems to adjust stimulation parameters to reduce variability in the ECAP, and in turn, variability in the VTA. While investigational CL SCS systems with ECAP sensing have so far focused solely on managing paresthesia-based SCS, such systems must also incorporate the stimulation approaches that now define the contemporary clinical practice of SCS. Accordingly, we describe here a flexible, next-generation framework for neural responsive SCS that blends science-based methodologies for pain management with real-time CL control for biophysical variation. We conclude with a clinical example of such a system and the associated performance characteristics.