First evidence of a biomarker-based dose-response relationship in chronic pain using physiological closed-loop spinal cord stimulation.

BACKGROUND AND OBJECTIVES: In spinal cord stimulation (SCS) therapy, electricity is the medication delivered to the spinal cord for pain relief. In contrast to conventional medication where dose is determined by desired therapeutic plasma concentration, there is lack of equivalent means of determining dose delivery in SCS. In open-loop (OL) SCS, due to the dynamic nature of the epidural space, the activating electric field delivered is inconsistent at the level of the dorsal columns. Recent Food and Drug Administration guidance suggests accurate and consistent therapy delivered using physiologic closed-loop control (PCLC) devices can minimize underdosage or overdosage and enhance medical care. PCLC-based evoked compound action potential (ECAP)-controlled technology provides the ability to prescribe a precise stimulation dose unique to each patient, continuously measure neural activation, and objectively inform SCS therapy optimization. METHODS: Neurophysiological indicator metrics of therapy dose, usage above neural activation threshold, and accuracy of SCS therapy were assessed for relationship with pain reduction in over 600 SCS patients. RESULTS: Significant relationships between objective metrics and pain relief across the patient population are shown, including first evidence for a dose-response relationship in SCS. CONCLUSIONS: Higher dose, more time over ECAP threshold, and higher accuracy are associated with better outcomes across patients. There is potential to optimize individual patient outcomes based on unique objective measurable electrophysiological inputs.

ECAP-controlled closed-loop versus open-loop SCS for the treatment of chronic pain: 36-month results of the EVOKE blinded randomized clinical trial.

INTRODUCTION: The evidence for spinal cord stimulation (SCS) has been criticized for the absence of blinded, parallel randomized controlled trials (RCTs) and limited evaluations of the long-term effects of SCS in RCTs. The aim of this study was to determine whether evoked compound action potential (ECAP)-controlled, closed-loop SCS (CL-SCS) is associated with better outcomes when compared with fixed-output, open-loop SCS (OL-SCS) 36 months following implant. METHODS: The EVOKE study was a multicenter, participant-blinded, investigator-blinded, and outcome assessor-blinded, randomized, controlled, parallel-arm clinical trial that compared ECAP-controlled CL-SCS with fixed-output OL-SCS. Participants with chronic, intractable back and leg pain refractory to conservative therapy were enrolled between January 2017 and February 2018, with follow-up through 36 months. The primary outcome was a reduction of at least 50% in overall back and leg pain. Holistic treatment response, a composite outcome including pain intensity, physical and emotional functioning, sleep, and health-related quality of life, and objective neural activation was also assessed. RESULTS: At 36 months, more CL-SCS than OL-SCS participants reported ≥50% reduction (CL-SCS=77.6%, OL-SCS=49.3%; difference: 28.4%, 95% CI 12.8% to 43.9%, p<0.001) and ≥80% reduction (CL-SCS=49.3%, OL-SCS=31.3%; difference: 17.9, 95% CI 1.6% to 34.2%, p=0.032) in overall back and leg pain intensity. Clinically meaningful improvements from baseline were observed at 36 months in both CL-SCS and OL-SCS groups in all other patient-reported outcomes with greater levels of improvement with CL-SCS. A greater proportion of patients with CL-SCS were holistic treatment responders at 36-month follow-up (44.8% vs 28.4%), with a greater cumulative responder score for CL-SCS patients. Greater neural activation and accuracy were observed with CL-SCS. There were no differences between CL-SCS and OL-SCS groups in adverse events. No explants due to loss of efficacy were observed in the CL-SCS group. CONCLUSION: This long-term evaluation with objective measurement of SCS therapy demonstrated that ECAP-controlled CL-SCS resulted in sustained, durable pain relief and superior holistic treatment response through 36 months. Greater neural activation and increased accuracy of therapy delivery were observed with ECAP-controlled CL-SCS than OL-SCS. TRIAL REGISTRATION NUMBER: NCT02924129.

Durability of Clinical and Quality-of-Life Outcomes of Closed-Loop Spinal Cord Stimulation for Chronic Back and Leg Pain: A Secondary Analysis of the Evoke Randomized Clinical Trial.

Importance: Chronic pain is debilitating and profoundly affects health-related quality of life. Spinal cord stimulation (SCS) is a well-established therapy for chronic pain; however, SCS has been limited by the inability to directly measure the elicited neural response, precluding confirmation of neural activation and continuous therapy. A novel SCS system measures the evoked compound action potentials (ECAPs) to produce a real-time physiological closed-loop control system. Objective: To determine whether ECAP-controlled, closed-loop SCS is associated with better outcomes compared with fixed-output, open-loop SCS at 24 months following implant. Design, Setting, and Participants: The Evoke study was a double-blind, randomized, controlled, parallel arm clinical trial with 36 months of follow-up. Participants were enrolled from February 2017 to 2018, and the study was conducted at 13 US investigation sites. SCS candidates with chronic, intractable back and leg pain refractory to conservative therapy, who consented, were screened. Key eligibility criteria included overall, back, and leg pain visual analog scale score of 60 mm or more; Oswestry Disability Index score of 41 to 80; stable pain medications; and no previous SCS. Analysis took place from October 2020 to April 2021. Interventions: ECAP-controlled, closed-loop SCS was compared with fixed-output, open-loop SCS. Main Outcomes and Measures: Reported here are the 24-month outcomes of the trial, which include all randomized patients in the primary and safety analyses. The primary outcome was a reduction of 50% or more in overall back and leg pain assessed at 3 and 12 months (previously published). Results: Of 134 randomized patients, 65 (48.5%) were female and the mean (SD) age was 55.2 (10.6) years. At 24 months, significantly more closed-loop than open-loop patients were responders (≥50% reduction) in overall pain (53 of 67 [79.1%] in the closed-loop group; 36 of 67 [53.7%] in the open-loop group; difference, 25.4% [95% CI, 10.0%-40.8%]; P = .001). There was no difference in safety profiles between groups (difference in rate of study-related adverse events: 6.0 [95% CI, -7.8 to 19.7]). Improvements were also observed in health-related quality of life, physical and emotional functioning, and sleep, in parallel with opioid reduction or elimination. Objective neurophysiological measurements substantiated the clinical outcomes and provided evidence of activation of inhibitory pain mechanisms. Conclusions and Relevance: ECAP-controlled, closed-loop SCS, which elicited a more consistent neural response, was associated with sustained superior pain relief at 24 months, consistent with the 3- and 12-month outcomes.

Evoked Compound Action Potentials Reveal Spinal Cord Dorsal Column Neuroanatomy.

INTRODUCTION: The electrically evoked compound action potential (ECAP) is a measure of the response from a population of fibers to an electrical stimulus. ECAPs can be assessed during spinal cord stimulation (SCS) to elucidate the relationship between stimulation, electrophysiological response, and neuromodulation. This has consequences for the design and programming of SCS devices. METHODS: Sheep were implanted with linear epidural SCS leads. After a stimulating pulse, electrodes recorded ECAPs sequentially as they propagated orthodromically or antidromically. After filtering, amplification, and signal processing, ECAP amplitude and dispersion (width) was measured, and conduction velocity was calculated. Similar clinical data was also collected. A single-neuron computer model that simulated large-diameter sensory axons was used to explore and explain the observations. RESULTS: ECAPs, both animal and human, have a triphasic structure, with P1, N1, and P2 peaks. Conduction velocity in sheep was 109 ms-1 , which indicates that the underlying neural population includes fibers of up to 20 µm in diameter. For travel in both directions, propagation distance was associated with decrease in amplitude and increase in dispersion. Importantly, characteristics of these changes shifted abruptly at various positions along the cord. DISCUSSION: ECAP dispersion increases with propagation distance due to the contribution of slow-conducting small-diameter fibers as the signal propagates away from the source. An analysis of the discontinuities in ECAP dispersion changes with propagation revealed that these are due to the termination of smaller-diameter, slower-conducting fibers at corresponding segmental levels. The implications regarding SCS lead placement, toward the goal of maximizing clinical benefit while minimizing side-effects, are discussed. CONFLICT OF INTEREST: John Parker is the founder and CEO of Saluda Medical and holds stock options. Milan Obradovic, Nastaran Hesam Shariati, Dean M. Karantonis, Peter Single, James Laird-Wah, Robert Gorman and Mark Bickerstaff are employees of Saluda Medical with stock options. At the time the data was collected for the study, Prof. Cousins was a paid consultant for Saluda Medical. John Parker, Milan Obradovic, Dean Karantonis, James Laird-Wah, Robert Gorman and Peter Single are co-inventors in one or more patents related to the topics discussed in this work.

Electrically evoked compound action potentials recorded from the sheep spinal cord.

OBJECTIVES: The study aims to characterize the electrical response of dorsal column axons to depolarizing stimuli to help understand the mechanisms of spinal cord stimulation (SCS) for the relief of chronic pain. MATERIALS AND METHODS: We recorded electrically evoked compound action potentials (ECAPs) during SCS in 10 anesthetized sheep using stimulating and recording electrodes on the same epidural SCS leads. A novel stimulating and recording system allowed artifact contamination of the ECAP to be minimized. RESULTS: The ECAP in the sheep spinal cord demonstrates a triphasic morphology, with P1, N1, and P2 peaks. The amplitude of the ECAP varies along the length of the spinal cord, with minimum amplitudes recorded from electrodes positioned over each intervertebral disc, and maximum amplitudes recorded in the midvertebral positions. This anatomically correlated depression of ECAP also correlates with the areas of the spinal cord with the highest thresholds for stimulation; thus regions of weakest response invariably had least sensitivity to stimulation by as much as a factor of two. The choice of stimulating electrode location can therefore have a profound effect on the power consumption for an implanted stimulator for SCS. There may be optimal positions for stimulation in the sheep, and this observation may translate to humans. Almost no change in conduction velocity (∼100 ms) was observed with increasing currents from threshold to twice threshold, despite increased Aß fiber recruitment. CONCLUSIONS: Amplitude of sheep Aß fiber potentials during SCS exhibit dependence on electrode location, highlighting potential optimization of Aß recruitment and power consumption in SCS devices.

Compound action potentials recorded in the human spinal cord during neurostimulation for pain relief.

Electrical stimulation of the spinal cord provides effective pain relief to hundreds of thousands of chronic neuropathic pain sufferers. The therapy involves implantation of an electrode array into the epidural space of the subject and then stimulation of the dorsal column with electrical pulses. The stimulation depolarises axons and generates propagating action potentials that interfere with the perception of pain. Despite the long-term clinical experience with spinal cord stimulation, the mechanism of action is not understood, and no direct evidence of the properties of neurons being stimulated has been presented. Here we report novel measurements of evoked compound action potentials from the spinal cords of patients undergoing stimulation for pain relief. The results reveal that Aß sensory nerve fibres are recruited at therapeutic stimulation levels and the Aß potential amplitude correlates with the degree of coverage of the painful area. Aß-evoked responses are not measurable below a threshold stimulation level, and their amplitude increases with increasing stimulation current. At high currents, additional late responses are observed. Our results contribute towards efforts to define the mechanism of spinal cord stimulation. The minimally invasive recording technique we have developed provides data previously obtained only through microelectrode techniques in spinal cords of animals. Our observations also allow the development of systems that use neuronal recording in a feedback loop to control neurostimulation on a continuous basis and deliver more effective pain relief. This is one of numerous benefits that in vivo electrophysiological recording can bring to a broad range of neuromodulation therapies.

Noninvasive activity-based control of an implantable rotary blood pump: comparative software simulation study.

A control algorithm for an implantable centrifugal rotary blood pump (RBP) based on a noninvasive indicator of the implant recipient's activity level has been proposed and evaluated in a software simulation environment. An activity level index (ALI)-derived from a noninvasive estimate of heart rate and the output of a triaxial accelerometer-forms the noninvasive indicator of metabolic energy expenditure. Pump speed is then varied linearly according to the ALI within a defined range. This ALI-based control module operates within a hierarchical multiobjective framework, which imposes several constraints on the operating region, such as minimum flow and minimum speed amplitude thresholds. Three class IV heart failure (HF) cases of varying severity were simulated under rest and exercise conditions, and a comparison with other popular RBP control strategies was performed. Pump flow increases of 2.54, 1.94, and 1.15 L/min were achieved for the three HF cases, from rest to exercise. Compared with constant speed control, this represents a relative flow change of 30.3, 19.8, and -15.4%, respectively. Simulations of the proposed control algorithm exhibited the effective intervention of each constraint, resulting in an improved flow response and the maintenance of a safe operating condition, compared with other control modes.

Noninvasive average flow and differential pressure estimation for an implantable rotary blood pump using dimensional analysis.

Accurate noninvasive average flow and differential pressure estimation of implantable rotary blood pumps (IRBPs) is an important practical element for their physiological control. While most attempts at developing flow and differential pressure estimate models have involved purely empirical techniques, dimensional analysis utilizes theoretical principles of fluid mechanics that provides valuable insights into parameter relationships. Based on data obtained from a steady flow mock loop under a wide range of pump operating points and fluid viscosities, flow and differential pressure estimate models were thus obtained using dimensional analysis. The algorithm was then validated using data from two other VentrAssist IRBPs. Linear correlations between estimated and measured pump flow over a flow range of 0.5 to 8.0 L/min resulted in a slope of 0.98 ( R(2) = 0.9848). The average flow error was 0.20 +/- 0.14 L/min (mean +/- standard deviation) and the average percentage error was 5.79%. Similarly, linear correlations between estimated and measured pump differential pressure resulted in a slope of 1.027 ( R(2) = 0.997) over a pressure range of 60 to 180 mmHg. The average differential pressure error was 1.84 +/- 1.54 mmHg and the average percentage error was 1.51%.

Noninvasive pulsatile flow estimation for an implantable rotary blood pump.

A noninvasive approach to the task of pulsatile flow estimation in an implantable rotary blood pump (iRBP) has been proposed. Employing six fluid solutions representing a range of viscosities equivalent to 20-50% blood hematocrit (HCT), pulsatile flow data was acquired from an in vitro mock circulatory loop. The entire operating range of the pump was examined, including flows from -2 to 12 L/min. Taking the pump feedback signals of speed and power, together with the HCT level, as input parameters, several flow estimate models were developed via system identification methods. Three autoregressive with exogenous input (ARX) model structures were evaluated: structures I and II used the input parameters directly; structure II incorporated additional terms for HCT; and the third structure employed as input a non-pulsatile flow estimate equation. Optimal model orders were determined, and the associated models yielded minimum mean flow errors of 5.49% and 0.258 L/min for structure II, and 5.77% and 0.270 L/min for structure III, when validated on unseen data. The models developed in this study present a practical method of accurately estimating iRBP flow in a pulsatile environment.

A dynamic lumped parameter model of the left ventricular assisted circulation.

A lumped parameter model of the cardiovascular system (CVS) and its interaction with an implantable rotary blood pump (iRBP) is presented. The CVS model consists of the heart, the systemic and the pulmonary circulations. The pump model is made up of three differential equations, i.e. the motor equation, the torque equation and the hydraulic equation. Qualitative comparison with data from ex vivo porcine experiments suggests that the model is able to simulate different physiologically significant pumping states with varying pump speed set points. The combined CVS-iRBP model is suitable for use as a tool for investigating changes in the circulatory system parameters in the presence of the pump, and for testing control algorithms.

Classification of physiologically significant pumping states in an implantable rotary blood pump: patient trial results.

An integral component in the development of a control strategy for implantable rotary blood pumps is the task of reliably detecting the occurrence of left ventricular collapse due to overpumping of the native heart. Using the noninvasive pump feedback signal of impeller speed, an approach to distinguish between overpumping (or ventricular collapse) and the normal pumping state has been developed. Noninvasive pump signals from 10 human pump recipients were collected, and the pumping state was categorized as either normal or suction, based on expert opinion aided by transesophageal echocardiographic images. A number of indices derived from the pump speed waveform were incorporated into a classification and regression tree model, which acted as the pumping state classifier. When validating the model on 12,990 segments of unseen data, this methodology yielded a peak sensitivity/specificity for detecting suction of 99.11%/98.76%. After performing a 10-fold cross-validation on all of the available data, a minimum estimated error of 0.53% was achieved. The results presented suggest that techniques for pumping state detection, previously investigated in preliminary in vivo studies, are applicable and sufficient for use in the clinical environment.

Classification of physiologically significant pumping states in an implantable rotary blood pump: effects of cardiac rhythm disturbances.

Methods of speed control for implantable rotary blood pumps (iRBPs) are vital for providing implant recipients with sufficient blood flow to cater for their physiological requirements. The detection of pumping states that reflect the physiological state of the native heart forms a major component of such a control method. Employing data from a number of acute animal experiments, five such pumping states have been previously identified: regurgitant pump flow, ventricular ejection (VE), nonopening of the aortic valve (ANO), and partial collapse (intermittent [PVC-I] and continuous [PVC-C]) of the ventricle wall. An automated approach that noninvasively detects such pumping states, employing a classification and regression tree (CART), has also been developed. An extension to this technique, involving an investigation into the effects of cardiac rhythm disturbances on the state detection process, is discussed. When incorporating animal data containing arrhythmic events into the CART model, the strategy showed a marked improvement in detecting pumping states as compared to the model devoid of arrhythmic data: state VE--57.4/91.7% (sensitivity/specificity) improved to 97.1/100.0%; state PVC-I--66.7/83.1% improved to 100.0/88.3%, and state PVC-C--11.1/66.2% changed to 0.0/100%. With a simplified binary scheme differentiating suction (PVC-I, PVC-C) and nonsuction (VE, ANO) states, suction was initially detected with 100/98.5% sensitivity/specificity, whereas with the subsequent improved model, both these states were detected with 100% sensitivity. The accuracy achieved demonstrates the robustness of the technique presented, and substantiates its inclusion into any iRBP control methodology.

Noninvasive average flow estimation for an implantable rotary blood pump: a new algorithm incorporating the role of blood viscosity.

The effect of blood hematocrit (HCT) on a noninvasive flow estimation algorithm was examined in a centrifugal implantable rotary blood pump (iRBP) used for ventricular assistance. An average flow estimator, based on three parameters, input electrical power, pump speed, and HCT, was developed. Data were collected in a mock loop under steady flow conditions for a variety of pump operating points and for various HCT levels. Analysis was performed using three-dimensional polynomial surfaces to fit the collected data for each different HCT level. The polynomial coefficients of the surfaces were then analyzed as a function of HCT. Linear correlations between estimated and measured pump flow over a flow range from 1.0 to 7.5 L/min resulted in a slope of 1.024 L/min (R2=0.9805). Early patient data tested against the estimator have shown promising consistency, suggesting that consideration of HCT can improve the accuracy of existing flow estimation algorithms.

Identification and classification of physiologically significant pumping states in an implantable rotary blood pump.

In a clinical setting it is necessary to control the speed of rotary blood pumps used as left ventricular assist devices to prevent possible severe complications associated with over- or underpumping. The hypothesis is that by using only the noninvasive measure of instantaneous pump impeller speed to assess flow dynamics, it is possible to detect physiologically significant pumping states (without the need for additional implantable sensors). By varying pump speed in an animal model, five such states were identified: regurgitant pump flow, ventricular ejection (VE), nonopening of the aortic valve over the cardiac cycle (ANO), and partial collapse (intermittent and continuous) of the ventricle wall (PVC-I and PVC-C). These states are described in detail and a strategy for their noninvasive detection has been developed and validated using (n = 6) ex vivo porcine experiments. Employing a classification and regression tree, the strategy was able to detect pumping states with a high degree of sensitivity and specificity: state VE-99.2/100.0% (sensitivity/specificity); state ANO-100.0/100.0%; state PVC-I- 95.7/91.2%; state PVC-C-69.7/98.7%. With a simplified binary scheme differentiating suction (PVC-I, PVC-C) and nonsuction (VE, ANO) states, both such states were detected with 100% sensitivity.

Implementation of a real-time human movement classifier using a triaxial accelerometer for ambulatory monitoring.

The real-time monitoring of human movement can provide valuable information regarding an individual's degree of functional ability and general level of activity. This paper presents the implementation of a real-time classification system for the types of human movement associated with the data acquired from a single, waist-mounted triaxial accelerometer unit. The major advance proposed by the system is to perform the vast majority of signal processing onboard the wearable unit using embedded intelligence. In this way, the system distinguishes between periods of activity and rest, recognizes the postural orientation of the wearer, detects events such as walking and falls, and provides an estimation of metabolic energy expenditure. A laboratory-based trial involving six subjects was undertaken, with results indicating an overall accuracy of 90.8% across a series of 12 tasks (283 tests) involving a variety of movements related to normal daily activities. Distinction between activity and rest was performed without error; recognition of postural orientation was carried out with 94.1% accuracy, classification of walking was achieved with less certainty (83.3% accuracy), and detection of possible falls was made with 95.6% accuracy. Results demonstrate the feasibility of implementing an accelerometry-based, real-time movement classifier using embedded intelligence.

Automated non-invasive detection of pumping states in an implantable rotary blood pump.

With respect to rotary blood pumps used as left ventricular assist devices (LVADs), it is clinically important to control pump flow to avoid complications associated with over-or under-pumping of the native heart. By employing only the non-invasive observer of instantaneous pump impeller speed to assess flow dynamics, a number of physiologically significant pumping states may be detected. Based on a number of acute animal experiments, five such states were identified: regurgitant pump flow (PR), ventricular ejection (VE), non-opening of the aortic valve (ANO), and partial collapse (intermittent and continuous) of the ventricle wall (PVC-I and PVC-C). Two broader states, normal (corresponding to VE, ANO) and suction (corresponding to PVC-I, PVC-C) were readily discernable in clinical data from human patients implanted with LVADs. Based on data from both the animal experiments (N=6) and the human patients (N=10), a strategy for the automated non-invasive detection of significant pumping states has been developed and validated. Employing a classification and regression tree (CART), this system detects pumping states with a high degree of accuracy: state VE -87.5/100.0% (sensitivity/specificity); state ANO - 98.1/92.5%; state PVC-I - 90.0/90.2%; state PVC-C - 61.2/98.0%. With a simplified binary scheme differentiating suction and normal states, both states were detected without error in data from the animal experiments, and with a sensitivity/specificity, for detecting suction, of 99.2/98.3% in the human patient data.