3D patient-specific spinal cord computational model for SCS management: potential clinical applications

Abstract

Objective.Although spinal cord stimulation (SCS) is an established therapy for treating neuropathic chronic pain, in tonic stimulation, postural changes, electrode migration or badly-positioned electrodes can produce annoying stimulation (intercostal neuralgia) in about 35% of the patients. SCS models are used to study the effect of electrical stimulation to better manage the stimulation parameters and electrode position. The goal of this work was to develop a realistic 3D patient-specific spinal cord model from a real patient and develop a future clinical application that would help physicians to optimize paresthesia coverage in SCS therapy.Approach.We developed two 3D patient-specific models from a high-resolution MRI of two patients undergoing SCS treatment. The model consisted of a finite element model of the spinal cord and a sensory myelinated nerve fiber model. The same simulations were performed with a generalized spinal cord model and we compared the results with the clinical data to evaluate the advantages of a patient-specific model. To identify the geometrical parameters that most influence the stimulation predictions, a sensitivity analysis was conducted. We used the patient-specific model to perform a clinical application involving the pre-implantation selection of electrode polarity and study the effect of electrode offset.Main results.The patient-specific model correlated better with clinical data than the generalized model. Electrode-dura mater distance, dorsal cerebrospinal fluid (CSF) thickness, and CSF diameter are the geometrical parameters that caused significant changes in the stimulation predictions. Electrode polarity could be planned and optimized to stimulate the patient's painful dermatomes. The addition of offset in parallel electrodes would not have been beneficial for one of the patients of this study because they reduce neural activation displacement.Significance.This is the first study to relate the activation area model prediction in dorsal columns with the clinical effect on paresthesia coverage. The outcomes show that 3D patient-specific models would help physicians to choose the best stimulation parameters to optimize neural activation and SCS therapy in tonic stimulation.

Keywords: 3D patient-specific model; clinical applications; computational model; paresthesia coverage; spinal cord stimulation therapy.