A Programmable Multi-biomarker Neural Sensor for Closed-loop DBS

Open-source 3D printable frameless stereotaxic system for young and adult pigs

BACKGROUND

Here we present an open-source solution, comprising several 3D-printable mechanical pieces and software tools, for frameless stereotaxic targeting in young and adult pigs of varying weights.

NEW METHOD

Localization was achieved using an IR camera and CT imaging. The positions of the tools were followed, after registration of the pig stereotaxic space, with a CT scan and open-source brain atlas. The system was used to target the lateral ventricle and the subthalamic nucleus (STN) in one piglet and two adult Yucatan miniature pigs, which were either normal weight or obese.

RESULTS AND CONCLUSIONS

Positive targeting was confirmed in the first trial for all subjects, either by radiopaque CT enhancement of the ventricle or actual recording of the STN electrophysiological signature. We conclude that open-source freely available models, easily built with low-end 3D printers, and their associated software can be effectively used for brain surgery in pigs, at a minimal cost, irrespective of the weight of the animal.

Multi-disease Deep Brain Stimulation

Current closed-loop deep brain stimulation (DBS) devices can generally tackle one disorder. This paper presents the design and evaluation of a multi-disease closed-loop DBS device that can sense multiple brain biomarkers, detect a disorder, and adaptively deliver electrical stimulation pulses based on the disease state. The device consists of: (i) a neural sensor, (ii) a controller involving a feature extractor, a disease classifier, and a control strategy, and (iii) neural stimulator. The neural sensor records and processes local field potentials and spikes from within the brain using two low-frequency and high-frequency channels. The feature extractor digitally processes the output of the neural sensor, and extracts five potential biomarkers: alpha, beta, slow gamma, high-frequency oscillations, and spikes. The disease classifier identifies the type of the neurological disorder through an analysis of the biomarkers' amplitude features. The control strategy considers the disease state and supplies the stimulation settings to the neural stimulator. Both the disease classifier and control strategy are based on fuzzy algorithms. The neural stimulator generates electrical stimulation pulses according to the control commands, and delivers them to the target area of the brain. The device can generate current stimulation pulses with specific amplitude, frequency, and duration. The fabricated device has the maximum radius of 15 mm. Its total weight including the circuit board, battery and battery holder is 5.1 g. The performance of the integrated device has been evaluated through six bench and in-vitro experiments. The experimental results are presented, analyzed, and discussed. Six bench and in-vitro experiments were conducted using sinusoidal, normal pre-recorded, and diseased neural signals representing normal, epilepsy, depression and PD conditions. The results obtained through these tests indicate the successful neural sensing, classification, control, and neural stimulating performance.

Biomarker Optimization of Spinal Cord Stimulation Therapies

OBJECTIVES

We are in the process of designing and testing an intradural stimulation device that will shorten the distance between the location of the electrode array and the targeted neural tissue, thus improving the efficacy of electrical current delivery. Identifying a biomarker that accurately reflects the response to this intervention is highly valued because of the potential to optimize interventional parameters or predict a response before it is clinically measurable. In this report, we summarize the findings pertaining to the study of biomarkers so that we and others will have an up-to-date reference that critically evaluates the current approaches and select one or several for testing during the development of our device.

MATERIALS AND METHODS

We have conducted a broad survey of the existing literature to catalogue the biomarkers that could be coupled to intradural spinal cord stimulation. We describe in detail some of the most promising biomarkers, existing limitations, and suitability to managing chronic pain.

RESULTS

Chronic, intractable pain is an all-encompassing condition that is incurable. Many treatments for managing chronic pain are nonspecific in action and intermittently administered; therefore, patients are particularly susceptible to large fluctuations in pain control over the course of a day. The absence of a reliable biomarker challenges assessment of therapeutic efficacy and contributes to either incomplete and inconsistent pain relief or, alternatively, intolerable side effects. Fluctuations in metabolites or inflammatory markers, signals captured during dynamic imaging, and genomics will likely have a role in governing how a device is modulated.

CONCLUSIONS

Efforts to identify one or more biomarkers are well underway with some preliminary evidence supporting their efficacy. This has far-reaching implications, including improved outcomes, fewer adverse events, harmonization of treatment and individuals, performance gains, and cost savings. We anticipate that novel biomarkers will be used widely to manage chronic pain.