Near InfraRed Layered Imaging of Tissue Hemodynamics (NIR-LITH)

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Project Summary/Abstract Diabetic foot ulcers (DFU) are associated with significant morbidity and mortality, with a 2.5x higher risk of 5-year mortality compared to diabetic patients without DFUs [3, 4]. The reason behind these dramatic statistics is tied to the lack of objective metrics for monitoring wound progress or deteriorating conditions. Assessment of functional perfusion is one of the biggest unmet needs for predicting wound healing. Current clinical practices still rely heavily on visual observation and clinical examination of the wound, an approach in which successful prediction of healing or amputation level survival is poor even among very experienced clinicians. The proposed innovative solution will complement the current standards of care for the characterization of DFUs by providing objective metrics and will provide details that can be missed during routine visual inspections and clinical assessments only. This solution will allow the clinician to select an appropriate management strategy for the specific case by providing clear images relative to potentially compromised circulation. The aim of the herein proposed work is to provide a three-dimensional hemodynamic map of the imaged DFU and surrounding tissue, with a controllable ≈1 mm depth resolution over a depth from 0 to 0.5 cm to assess different degrees of microcirculatory perfusion and hemodynamics. This approach will provide objective and immediate assessment of DFU and surgical wound healing potential and will help clinicians make more accurate and faster treatment decisions. In complex cases, it will help surgeons select a level amputation that will still be able to heal, reducing the number of surgeries and the length of hospitalizations. We call this system NIR-LITH (Near InfraRed Layered Imaging of Tissue Hemodynamics). The system herein proposed leverages a non-contact optical- based system for tissue viability assessment, previously developed at Vivonics, to provide objective metrics about tissue viability to surgeons during debridement procedures. In order to achieve this overarching goal, the following specific aims have been proposed:  Aim 1: Enhance first generation prototype to improve depth discrimination capabilities. Controllable depth imaging capabilities (0-0.5cm) for tissue layers discrimination (≈1 mm) is the goal of this task.  Aim 2: Develop algorithm for depth discrimination and phantom testing and characterization.  Aim 3: System evaluation: thirty DFU patients in collaboration with Dr. L. Lavery at the University of Texas Southwestern Medical Center (UTSW) will be recruited for this task and gold standard analysis will comparted against the NIR-LITH results.