Traditional diagnostic methods for burn wounds have remained inaccurate.We have recently demonstrated that terahertz (THz) spectroscopic imaging can assess wound severity and predict healing outcome with high accuracy using our Portable HAndheld Spectral Reflection (PHASR) Scanners, which provide fast full-spectroscopic imaging. We will describe recent work exploring different physics-based machine learning methods to classify wounds using THz spectral data. THz images captured 1-hour post-burn achieve an accuracy of 94.7% in predicting the wound healing outcome by 28 days. A reduced-dimensionality double-Debye model describes the refractive index of the tissue over the entire spectra using only five empirical parameters. A neural network based on this model still achieved 88% healing outcome prediction accuracy. Finally, we will discuss plans to translate this technology to clinical trials.
We report on the development and application of terahertz spectral imaging in burn diagnosis, using our new Portable HAndheld Spectral Reflection (PHASR) Scanner. The PHASR Scanner features a fiber-coupled housing, which provides an alignment-free strategy for the placement and operation of the THz optics. Image formation is achieved through telecentric beam steering over a planar surface through a custom f-θ scanning lens. Electronically Controlled Optical Sampling can be implemented for high THz trace acquisition rates and a simultaneously recorded error signal can be used to calibrate the signals for accurate measurement. This scanner allows for a constant spatial resolution over a wide field of view and rapid acquisition of full THz-TDS spectra in clinical and operating room settings.
SignificanceSevere burn injuries cause significant hypermetabolic alterations that are highly dynamic, hard to predict, and require acute and critical care. The clinical assessments of the severity of burn injuries are highly subjective and have consistently been reported to be inaccurate. Therefore, the utilization of other imaging modalities is crucial to reaching an objective and accurate burn assessment modality.AimWe describe a non-invasive technique using terahertz time-domain spectroscopy (THz-TDS) and the wavelet packet Shannon entropy to automatically estimate the burn depth and predict the wound healing outcome of thermal burn injuries.ApproachWe created 40 burn injuries of different severity grades in two porcine models using scald and contact methods of infliction. We used our THz portable handheld spectral reflection (PHASR) scanner to obtain the in vivo THz-TDS images. We used the energy to Shannon entropy ratio of the wavelet packet coefficients of the THz-TDS waveforms on day 0 to create supervised support vector machine (SVM) classification models. Histological assessments of the burn biopsies serve as the ground truth.ResultsWe achieved an accuracy rate of 94.7% in predicting the wound healing outcome, as determined by histological measurement of the re-epithelialization rate on day 28 post-burn induction, using the THz-TDS measurements obtained on day 0. Furthermore, we report the accuracy rates of 89%, 87.1%, and 87.6% in automatic diagnosis of the superficial partial-thickness, deep partial-thickness, and full-thickness burns, respectively, using a multiclass SVM model.ConclusionsThe THz PHASR scanner promises a robust, high-speed, and accurate diagnostic modality to improve the clinical triage of burns and their management.
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