Quantitative Sensory Testing of Spinal Cord and Dorsal Root Ganglion Stimulation in Chronic Pain Patients.

BACKGROUND/OBJECTIVES: The physiological mechanisms underlying the pain-modulatory effects of clinical neurostimulation therapies, such as spinal cord stimulation (SCS) and dorsal root ganglion stimulation (DRGS), are only partially understood. In this pilot prospective study, we used patient-reported outcomes (PROs) and quantitative sensory testing (QST) to investigate the physiological effects and possible mechanisms of action of SCS and DRGS therapies. MATERIALS AND METHODS: We tested 16 chronic pain patients selected for SCS and DRGS therapy, before and after treatment. PROs included pain intensity, pain-related symptoms (e.g., pain interference, pain coping, sleep interference) and disability, and general health status. QST included assessments of vibration detection theshold (VDT), pressure pain threshold (PPT) and tolerance (PPToL), temporal summation (TS), and conditioned pain modulation (CPM), at the most painful site. RESULTS: Following treatment, all participants reported significant improvements in PROs (e.g., reduced pain intensity [p < 0.001], pain-related functional impairment [or pain interference] and disability [p = 0.001 for both]; better pain coping [p = 0.03], sleep [p = 0.002]), and overall health [p = 0.005]). QST showed a significant treatment-induced increase in PPT (p = 0.002) and PPToL (p = 0.011), and a significant reduction in TS (p = 0.033) at the most painful site, but showed no effects on VDT and CPM. We detected possible associations between a few QST measures and a few PROs. Notably, higher TS was associated with increased pain interference scores at pre-treatment (r = 0.772, p = 0.009), and a reduction in TS was associated with the reduction in pain interference (r = 0.669, p = 0.034) and pain disability (r = 0.690, p = 0.027) scores with treatment. CONCLUSIONS: Our preliminary findings suggest significant clinical and therapeutic benefits associated with SCS and DRGS therapies, and the possible ability of these therapies to modulate pain processing within the central nervous system. Replication of our pilot findings in future, larger studies is necessary to characterize the physiological mechanisms of SCS and DRGS therapies.

Anatomical and technical factors affecting the neural response to epidural spinal cord stimulation.

OBJECTIVE: Spinal cord stimulation (SCS) is a common neurostimulation therapy to treat chronic pain. Computational models represent a valuable tool to study the potential mechanisms of action of SCS and to optimize the design and implementation of SCS technologies. However, it is imperative that these computational models include the appropriate level of detail to accurately predict the neural response to SCS and to correlate model predictions with clinical outcomes. Therefore, the goal of this study was to investigate several anatomic and technical factors that may affect model-based predictions of neural activation during thoracic SCS. APPROACH: We developed computational models that consisted of detailed finite element models of the lower thoracic spinal cord, surrounding tissues, and implanted SCS electrode arrays. We positioned multicompartment models of sensory axons within the spinal cord to calculate the activation threshold for each sensory axon. We then investigated how activation thresholds changed as a function of several anatomical variables (e.g. spine geometry, dorsal rootlet anatomy), stimulation type (i.e. voltage-controlled vs. current-controlled), electrode impedance, lead position, lead type, and electrical properties of surrounding tissues (e.g. dura conductivity, frequency-dependent conductivity). MAIN RESULTS: Several anatomic and modeling factors produced significant percent differences or errors in activation thresholds. Rostrocaudal positioning of the cathode with respect to the vertebrae had a large effect (up to 32%) on activation thresholds. Variability in electrode impedance produced significant changes in activation thresholds for voltage-controlled stimulation (38% to 51%), but had little effect on activation thresholds for current-controlled stimulation (less than 13%). Changing the dura conductivity also produced significant differences in activation thresholds. SIGNIFICANCE: This study demonstrates several anatomic and technical factors that can affect the neural response to SCS. These factors should be considered in clinical implementation and in future computational modeling studies of thoracic SCS.

Evoked Potentials Recorded From the Spinal Cord During Neurostimulation for Pain: A Computational Modeling Study.

OBJECTIVES: Spinal cord stimulation (SCS) for pain is typically implemented in an open-loop manner using parameters that remain largely unchanged. To improve the overall efficacy and consistency of SCS, one closed-loop approach proposes to use evoked compound action potentials (ECAPs) recorded from the SCS lead(s) as a feedback control signal to guide parameter selection. The goal of this study was to use a computational modeling approach to investigate the source of these ECAP recordings and technical and physiological factors that affect their composition. METHODS: We developed a computational model that coupled a finite element model of lower thoracic SCS with multicompartment models of sensory axons within the spinal cord. We used a reciprocity-based approach to calculate SCS-induced ECAPs recorded from the SCS lead. RESULTS: Our model ECAPs contained a triphasic, P1, N1, P2 morphology. The model P2-N1 amplitudes and conduction velocities agreed with previous experimental data from human subjects. Model results suggested that the ECAPs are dominated by the activation of axons with diameters 8.7-10.0 µm located in the dorsal aspect of the spinal cord. We also observed changes in the ECAP amplitude and shape due to the electrode location relative to the vertebrae and spinal cord. CONCLUSION: Our modeling results suggest that clinically effective SCS relies on the activation of numerous axons within a narrow fiber diameter range and that several factors affect the composition of the ECAP recordings. These results can improve how we interpret and implement these recordings in a potential closed-loop approach to SCS.

Patient-Specific Analysis of Neural Activation During Spinal Cord Stimulation for Pain.

OBJECTIVE: Despite the widespread use of spinal cord stimulation (SCS) for chronic pain management, its neuromodulatory effects remain poorly understood. Computational models provide a valuable tool to study SCS and its effects on axonal pathways within the spinal cord. However, these models must include sufficient detail to correlate model predictions with clinical effects, including patient-specific data. Therefore, the goal of this study was to investigate axonal activation at clinically relevant SCS parameters using a computer model that incorporated patient-specific anatomy and electrode locations. METHODS: We developed a patient-specific computer model for a patient undergoing SCS to treat chronic pain. This computer model consisted of two main components: 1) finite element model of the extracellular voltages generated by SCS and 2) multicompartment cable models of axons in the spinal cord. To determine the potential significance of a patient-specific approach, we also performed simulations with standard canonical models of SCS. We used the computer models to estimate axonal activation at clinically measured sensory, comfort, and discomfort thresholds. RESULTS: The patient-specific and canonical models predicted significantly different axonal activation. Relative to the canonical models, the patient-specific model predicted sensory threshold estimates that were more consistent with the corresponding clinical measurements. These results suggest that it is important to account for sources of interpatient variability (e.g., anatomy, electrode locations) in model-based analysis of SCS. CONCLUSIONS: This study demonstrates the potential for patient-specific computer models to quantitatively describe the axonal response to SCS and to address scientific questions related to clinical SCS.

Murine model and mechanisms of treatment-induced painful diabetic neuropathy.

Diabetes mellitus represents a group of metabolic diseases that are characterized by hyperglycemia caused by either lack of insulin production or a reduced ability to respond to insulin. It is estimated that there were 347 million people worldwide who suffered from diabetes in 2008 and incidence is predicted to double by 2050. Neuropathy is the most common complication of long-term diabetes and approximately 30% of these subjects develop chronic neuropathic pain. A distinct acute, severe form of neuropathic pain, called insulin neuritis or treatment-induced painful neuropathy of diabetes (TIND), may also occur shortly after initiation of intensive glycemic control, with an incidence rate of up to 10.9%. The pathological mechanisms leading to TIND, which is mostly unresponsive to analgesics, are not yet understood, impeding the development of therapies. Studies to date have been clinical and with limited cohorts of patients. In the current study, we developed chronic and acute insulin-induced neuropathic pain in mice with type 2 insulin-resistant diabetes. Furthermore, we determined that insulin-induced acute allodynia is independent of glycemia levels, can also be induced with Insulin-like Growth Factor 1 (IGF1) and be prevented by inhibition of AKT, providing evidence of an insulin/IGF1 signaling pathway-based mechanism for TIND. This mouse model is useful for the elucidation of mechanisms contributing to TIND and for the testing of new therapeutic approaches to treat TIND.