In a paper published by Khani et al in Biomedical Optics Express, researchers described the use of a neural network model that uses terahertz time-domain spectroscopy (THz-TDS) data for noninvasive burn assessment. Current methods to evaluate burns quickly use visual and tactile examination, and have been found to be only 60% to 75% effective. According to the recently published findings, the THz-TDS method showed 93% efficacy in predicting the healing of in vivo burns in a porcine model; it also showed an 84.5% average accuracy rate in predicting the severity of the burns. In a companion press release, senior study author M. Hassan Arbab, PhD, Assistant Professor of Biomedical Engineering at SUNY Stony Brook, commented, “In 2018, approximately 416,000 patients were treated for burn injuries in emergency departments in the United States alone…. Our research has the potential to significantly improve burn healing outcomes by guiding surgical treatment plans, which could have a major impact on reducing the length of hospital stays and number of surgical procedures for skin grafting while also improving rehabilitation after injury.”
April 30, 2023