Burn IQ: Predicting Burn Wound Depth to Improve Care for Burn Patients

Project Summary Up tomillion Americans per year suffer from burn injuries that require medical careThe foundation of burn wound care is determining whether a patient has a deep burn that will require excision and skin grafting or a partial thickness burn that is expected to heal without surgery and without scarringAccurate determination of burn wound depth is critical because over estimation results in unnecessary surgery and under estimation results in prolonged treatmentincreased costincreased scarringdisfigurement and loss of functionClinical assessment is most commonly used to determine burn wound depthbut is not very reliableand even with the most experienced surgeons is only accurateof the timeA variety of imaging modalities have been used to try and estimate burn wound depthThe current gold standard is laser Doppler imagingLDIthat correlates blood flow with burn wound depthIt has not been widely adopted in the USBarriers include difficulty interpreting the imagesand multiple variables that interfere with light based detection of blood flow including residual pigments from silver dressings or tattoosand patient conditions that affect blood flow such as infectionedema and use of vasoactive medicinesWe propose to detect burn induced changes in the mechanical properties of the subcutaneous tissue using FDA approved tissue Doppler elastography imagingTDIThe premise is that changes caused by burn injury that have propagated beyond the skin will change the stiffness of the subcutaneous tissueThose changes can be detected by changes in colorredsoftbluehardin the imageUsing sound waves to detect tissue changes avoids the limitations of light based imaging technologies such as LDITo promote adoption of this technologyMed Compliance IQ will develop a software platform called Burn IQ that uses neural networks to analyze the TDI imagesIt will provide clinical decision support by providing a probability that a burn injury is deepi erequires excision and graftingvspartial thicknessMed Compliance IQ has partnered with a team at Ohio State University that established model of pig burn injury that has been characterized with TDIFor phaseof the SBIR proposal the pig model will be used for software planning and development by obtaining TDI images from known partial thickness burnsknown full thickness burns and burns of indeterminate thicknessInitial testing and refinement of the software technology will also be done with human subject that also have known partial thicknessknown full thickness and indeterminate depth burns based on healing outcomesThis information will be used to yield a software product ready for testing on a large scale in human subjects during Phaseof the SBIRDevelopment of this product will improve diagnostic accuracy to achieve better outcomes for burn patients Project Narrative Optimal outcomes for people with burn wound injuries depends on accurate determination of burn wound depthTissue Doppler elastography imaging can detect burn induced changes in tissue stiffness to aid in assessing burn wound depthBurn IQ software technology will use neural networks to interpret tissue Doppler elastography images to improve diagnostic accuracy and achieve better clinical outcomes