Design and testing of a novel circumesophageal cuff for chronic bilateral subdiaphragmatic vagal nerve stimulation (sVNS)

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Rationale: Obesity affects ≥30% of the U.S. population, including Veterans, with related costs estimated at $190B/yr. Researchers use vagus nerve stimulation (VNS) to treat a number of conditions, including obesity. Sensory afferents in the vagus nerves innervate the stomach and relay information about the state of the stomach, particularly the degree of stomach wall stretch associated with increased stomach volume. Desired outcomes are maximized when VNS is applied bilaterally and off-target effects are minimized when VNS is applied at the subdiaphragmatic level. However, VNS parameters vary widely and it is unknown how changes in stimulus parameters alter outcomes. Until the parameter-to-outcome relationship is mapped, developing optimal stimulus waveforms is impossible. Experiments in rats could facilitate development of these maps, but bilateral subdiaphragmatic VNS (sVNS) is difficult/impossible in rats with currently available cuffs, which carry an inherent risk of esophageal stenosis. Objective: The primary objective of this study is to map the relationship between sVNS parameters, nerve recruitment, and brain activation with a novel helical cuff that eliminates the risk of esophageal stenosis. The secondary objective of this study is to demonstrate that the novel helical cuff is effective and safe for use in both acute and survival experiments, including experiments that use strong magnetic fields for MRI. Hypotheses will be tested through a series of animal experiments over a period of 2 years. Research Plan and Methodology: During Aim 1, the relationship between sVNS parameters and axon recruitment will be mapped to generate recruitment surfaces. Comparisons will include unilateral vs. bilateral sVNS; sVNS delivered through a traditional cuff vs. sVNS delivered through the novel helical cuff; sVNS at the time of surgery vs. sVNS at long-term follow-up. The effect of a chronic high glucose diet will be determined. During Aim 2, the relationship between sVNS parameters and brain activation/inhibition in key regions of the brain associated with satiety and food-based reward will be mapped using an 11.1 T fMRI. During Aim 3, the mechanical effects of a chronically-implanted novel cuff will be determined by examining the pressure required to distend the esophagus and through microscopic analysis of the subdiaphragmatic vagus nerves. Expected Outcomes: This proof-of-concept study is a critical first step in developing a new interface that addresses several limitations with currently-available technology. We expect that the novel cuff will 1) be easy to implant; 2) bilaterally recruit most of the target axons innervating the stomach without apparent off-target effects; 3) cause no or minimal damage to the subdiaphragmatic vagus nerves; 4) cause no or minimal risk of esophageal stenosis; 5) show no signs of heating during fMRI; 6) not introduce artefacts into the fMRI data. This study will generate data to facilitate understanding how unilateral and bilateral sVNS effects the system at two levels by generating a map that links sVNS parameters to: 1) axon recruitment and 2) brain activation. These maps, which are currently unknown, are critical for sVNS parameter optimization, which, itself, is critical for successful clinical deployment. We anticipate that this SPiRE will generate one publication and one patent. It is our long-term goal to translate optimal stimulus parameters and possibly the novel interface to individuals who have failed to lose weight under traditional weight loss regimens. Benefit to Veterans: With regard to obesity, 72% of Veterans are overweight or obese. Obesity has several comorbidities including hypertension, heart disease, and diabetes. There is a strong link between obesity and depression. Although this study is entirely preclinical, it is a critical first step in developing optimal stimulus waveforms. If the study is successful, then the chance of successful optimization of sVNS parameters is dramatically increased and, as such, the chance of translating this technology to the clinic.