Development of polarization-sensitive optical coherence tomography imaging platform and metrics to quantify electrostimulation-induced peripheral nerve injury in vivo in a small animal model.

Significance: Neuromodulation devices are rapidly evolving for the treatment of neurological diseases and conditions. Injury from implantation or long-term use without obvious functional losses is often only detectable through terminal histology. New technologies are needed that assess the peripheral nervous system (PNS) under normal and diseased or injured conditions. Aim: We aim to demonstrate an imaging and stimulation platform that can elucidate the biological mechanisms and impacts of neurostimulation in the PNS and apply it to the sciatic nerve to extract imaging metrics indicating electrical overstimulation. Approach: A sciatic nerve injury model in a 15-rat cohort was observed using a newly developed imaging and stimulation platform that can detect electrical overstimulation effects with polarization-sensitive optical coherence tomography. The sciatic nerve was electrically stimulated using a custom-developed nerve holder with embedded electrodes for 1 h, followed by a 1-h recovery period, delivered at above-threshold Shannon model k -values in experimental groups: sham control (SC, n = 5 , 0.0 mA / 0 Hz ), stimulation level 1 (SL1, n = 5 , 3.4 mA / 50 Hz , and k = 2.57 ), and stimulation level 2 (SL2, n = 5 , 6.8 mA / 100 Hz , and k = 3.17 ). Results: The stimulation and imaging system successfully captured study data across the cohort. When compared to a SC after a 1-week recovery, the fascicle closest to the stimulation lead showed an average change of + 4 % / - 309 % (SL1/SL2) in phase retardation and - 79 % / - 148 % in optical attenuation relative to SC. Analysis of immunohistochemistry (IHC) shows a + 1 % / - 36 % difference in myelin pixel counts and - 13 % / + 29 % difference in axon pixel counts, and an overall increase in cell nuclei pixel count of + 20 % / + 35 % . These metrics were consistent with IHC and hematoxylin/eosin tissue section analysis. Conclusions: The poststimulation changes observed in our study are manifestations of nerve injury and repair, specifically degeneration and angiogenesis. Optical imaging metrics quantify these processes and may help evaluate the safety and efficacy of neuromodulation devices.

Convolutional Neural Networks for Spectroscopic Analysis in Retinal Oximetry.

Retinal oximetry is a non-invasive technique to investigate the hemodynamics, vasculature and health of the eye. Current techniques for retinal oximetry have been plagued by quantitatively inconsistent measurements and this has greatly limited their adoption in clinical environments. To become clinically relevant oximetry measurements must become reliable and reproducible across studies and locations. To this end, we have developed a convolutional neural network algorithm for multi-wavelength oximetry, showing a greatly improved calculation performance in comparison to previously reported techniques. The algorithm is calibration free, performs sensing of the four main hemoglobin conformations with no prior knowledge of their characteristic absorption spectra and, due to the convolution-based calculation, is invariable to spectral shifting. We show, herein, the dramatic performance improvements in using this algorithm to deduce effective oxygenation (SO2), as well as the added functionality to accurately measure fractional oxygenation ([Formula: see text]). Furthermore, this report compares, for the first time, the relative performance of several previously reported multi-wavelength oximetry algorithms in the face of controlled spectral variations. The improved ability of the algorithm to accurately and independently measure hemoglobin concentrations offers a high potential tool for disease diagnosis and monitoring when applied to retinal spectroscopy.

Intact primate brain tissue identification using a completely fibered coherent Raman spectroscopy system.

Coherent Raman fiber probes have not yet found their way into the clinic despite their immense potential for label-free sensing and imaging. This is mainly due to the traditional bulky laser systems required to create the high peak power laser pulses needed for coherent Raman, as well as the complications that arise from the propagation of this type of energy through silica. Specifically, a coherent anti-Stokes Raman scattering (CARS) probe that could select its integration volume at high resolution, away from the tip of the fiber, is particularly interesting in the case of electrode implantation neurosurgeries, wherein it is possible to place optical fibers on-board the chronic electrode and provide optical guidance during its implantation, through the semi-transparent tip. To this clinical end, we have created an all fiber CARS system, consisting of small, rapidly tunable, turn-key fiber-lasers, capable of creating high wavenumber CARS spectra on the order of tens-of-milliseconds. The use of traditional silica fibers is made possible by the use of the laser's long pulse-widths (25 ps). The probe itself has an outer diameter of 250 µm allowing it to fit within commercially available metal tubes that can replace deep brain stimulation (DBS) stylets. Using this system, we identified brain tissue types in intact nonhuman primates' brains and showed the ability to delineate white and gray matters with high resolution. Its advantages over spontaneous Raman stem from the orders of magnitude improvement in spatial resolution, its inherent translatability to three-dimensional (3-D) imaging, as well as the theoretical ability to remove parasitic Raman signal from probe encasements, such as a DBS electrode. The system is planned to have clinical implications in neurosurgical guidance as well as diseased tissue detection.