Improved Accuracy of NIRS-based Skeletal Muscle Oxygen Saturation Measurement through Model Creation and Advanced Signal Processing Techniques

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DESCRIPTION (provided by applicant): Near infrared spectroscopy (NIRS) oximeters have the potential to measure tissue oxygenation in brain, muscle, and other organs to improve management of blood transfusion, shock, hypoxia-ischemia, and vascular disease. However, currently available NIRS tissue oximeters have either been calibrated primarily for cerebral oxygenation measurements or for other tissues at a limited depth, limiting accuracy or applicability to these clinical conditions. The aim of this proposal is to develop LED-based NIRS tissue oximetry sensors capable of measuring skeletal muscle oxygenation several centimeters deep to the surface. The sensor design will decrease inter-subject variability of the measurement and improve accuracy of the measurement. This depth of measurement will allow for application to monitor peripheral artery disease, shock detection, and blood cell transfusion. Key milestones include: • Determine optical light characteristics of skeletal muscle tissue which impact accuracy of NIRS tissue oximetry through a vascular occlusion study • Determine if an improved ex vivo blood-tissue model utilizing lipid mixing techniques can adequately represent blood tissue optical characteristics • Determine effectiveness of dynamic path-length adjustment signal processing to reduce inter-subject variability and improve skeletal muscle tissue oximetry accuracy Ex vivo models allow for known and controllable reference values, but fail to model the appropriate tissue scattering properties. Severed limb models have been tested, but also do not necessarily represent the scattering properties of living human tissue measured by NIRS. Human vascular occlusion models allow for appropriate light scattering properties to be assessed, but fail to have controlled or known reference saturations. A combined approach of an improved ex vivo model and a vascular occlusion study with advanced signal processing techniques will be incorporated, altering the ex vivo modeling to better represent optical characteristics of tissue. The end result will be a robust model of skeletal muscle tissue and a tissue oximetry sensor with improved accuracy for skeletal muscle measurement and reduced inter-subject variability. Phase II work will focus on expanding into lower limb occlusion studies and validation in peripheral arterial disease (PAD) patients to document characterization of the optical properties of skeletal muscle in the presence of plaque and possible light path adjustment techniques for correcting alterations in optics. Eventual commercialization includes a hand held portable device that will support spot check of muscle oxygenation in multiple clinical settings with possible extension to a wearable, mobile device.