In Vivo Assessment and Monitoring of Burn Wounds Using a Handheld Terahertz Hyperspectral Scanner

Terahertz polarimetric imaging of biological tissue: Monte Carlo modeling of signal contrast mechanisms due to Mie scattering

Many promising biomedical applications have been proposed for terahertz (THz) spectroscopy and diagnostic imaging techniques. Polarimetric imaging systems are generally useful for enhancing imaging contrasts, yet the interplay between THz polarization changes and the random discrete structures in biological samples is not well understood. In this work, we performed Monte Carlo simulations of the propagation of polarized THz waves in skin and adipose tissues based on the Mie scattering from intrinsic structures, such as hair follicles or sweat glands. We show that the polarimetric contrasts are distinctly affected by concentration, size and dielectric properties of the scatterers, as well as the frequency and polarization of the incident THz waves. We describe the experimental requirements for observing and extracting these polarimetric signals due to the low energy and small angular spread of the back-scattered THz radiation. We analyzed the spatially integrated Mueller matrices of samples in the normal-incidence back-scattering geometry. We show that the frequency-dependent degree of polarization (DOP) can be used to infer the concentrations and dielectric contents of the scattering structures. Our modeling approach can be used to inform the design of the imaging modalities and the interpretation of the spectroscopic data in future terahertz biomedical imaging applications.

Terahertz polarimetric imaging of biological tissues: Monte Carlo modeling of signal contrast mechanisms due to Mie scattering

Many promising biomedical applications have been proposed for terahertz (THz) spectroscopy and diagnostic imaging techniques. Polarimetric imaging systems are generally useful for enhancing imaging contrasts, yet the interplay between THz polarization changes and the random discrete structures in biological samples are not well understood. In this work, we performed Monte Carlo simulations of the propagation of polarized THz waves in skin and adipose tissues based on the Mie scattering from intrinsic structures, such as hair follicles or sweat glands. We show that the polarimetric contrasts are distinctly affected by concentration, size and dielectric properties of the scatterers, as well as the frequency and polarization of the incident THz waves. We describe the experimental requirements for observing and extracting these polarimetric signals due to the low energy and small angular spread of the back-scattered THz radiation. We analyzed the spatially integrated Mueller matrices of samples in the normal-incidence back-scattering geometry. We show that the frequency-dependent degree of polarization (DOP) can be used to infer the concentrations and dielectric contents of the scattering structures. Our modeling approach can be used to inform the design of the imaging modalities and the interpretation of the spectroscopic data in future terahertz biomedical imaging applications.

Polarimetric imaging of back-scattered terahertz speckle fields using a portable scanner

Speckle patterns observed in coherent optical imaging reflect important characteristic information of the scattering object. To capture speckle patterns, angular resolved or oblique illumination geometries are usually employed in combination with Rayleigh statistical models. We present a portable and handheld 2-channel polarization-sensitive imaging instrument to directly resolve terahertz (THz) speckle fields in a collocated telecentric back-scattering geometry. The polarization state of the THz light is measured using two orthogonal photoconductive antennas and can be presented in the form of the Stokes vectors of the THz beam upon interaction with the sample. We report on the validation of the method in surface scattering from gold-coated sandpapers, demonstrating a strong dependence of the polarization state on the surface roughness and the frequency of the broadband THz illumination. We also demonstrate non-Rayleigh first-order and second-order statistical parameters, such as degree of polarization uniformity (DOPU) and phase difference, for quantifying the randomness of polarization. This technique provides a fast method for broadband THz polarimetric measurement in the field and has the potential for detecting light depolarization in applications ranging from biomedical imaging to non-destructive testing.

Triage of in vivo burn injuries and prediction of wound healing outcome using neural networks and modeling of the terahertz permittivity based on the double Debye dielectric parameters

The initial assessment of the depth of a burn injury during triage forms the basis for determination of the course of the clinical treatment plan. However, severe skin burns are highly dynamic and hard to predict. This results in a low accuracy rate of about 60 - 75% in the diagnosis of partial-thickness burns in the acute post-burn period. Terahertz time-domain spectroscopy (THz-TDS) has demonstrated a significant potential for non-invasive and timely estimation of the burn severity. Here, we describe a methodology for the measurement and numerical modeling of the dielectric permittivity of the in vivo porcine skin burns. We use the double Debye dielectric relaxation theory to model the permittivity of the burned tissue. We further investigate the origins of dielectric contrast between the burns of various severity, as determined histologically based on the percentage of the burned dermis, using the empirical Debye parameters. We demonstrate that the five parameters of the double Debye model can form an artificial neural network classification algorithm capable of automatic diagnosis of the severity of the burn injuries, and predicting its ultimate wound healing outcome by forecasting its re-epithelialization status in 28 days. Our results demonstrate that the Debye dielectric parameters provide a physics-based approach for the extraction of the biomedical diagnostic markers from the broadband THz pulses. This method can significantly boost dimensionality reduction of THz training data in artificial intelligence models and streamline machine learning algorithms.

Assessing Corneal Endothelial Damage Using Terahertz Time-Domain Spectroscopy and Support Vector Machines

The endothelial layer of the cornea plays a critical role in regulating its hydration by actively controlling fluid intake in the tissue via transporting the excess fluid out to the aqueous humor. A damaged corneal endothelial layer leads to perturbations in tissue hydration and edema, which can impact corneal transparency and visual acuity. We utilized a non-contact terahertz (THz) scanner designed for imaging spherical targets to discriminate between ex vivo corneal samples with intact and damaged endothelial layers. To create varying grades of corneal edema, the intraocular pressures of the whole porcine eye globe samples (n = 19) were increased to either 25, 35 or 45 mmHg for 4 h before returning to normal pressure levels at 15 mmHg for the remaining 4 h. Changes in tissue hydration were assessed by differences in spectral slopes between 0.4 and 0.8 THz. Our results indicate that the THz response of the corneal samples can vary according to the differences in the endothelial cell density, as determined by SEM imaging. We show that this spectroscopic difference is statistically significant and can be used to assess the intactness of the endothelial layer. These results demonstrate that THz can noninvasively assess the corneal endothelium and provide valuable complimentary information for the study and diagnosis of corneal diseases that perturb the tissue hydration.

Accurate and early prediction of the wound healing outcome of burn injuries using the wavelet Shannon entropy of terahertz time-domain waveforms

Significance

Severe 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.

Aim

We 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.

Approach

We 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.

Results

We 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.

Conclusions

The THz PHASR scanner promises a robust, high-speed, and accurate diagnostic modality to improve the clinical triage of burns and their management.

Terahertz PHASR Scanner with 2 kHz, 100 picosecond Time-Domain Trace Acquisition Rate and an Extended Field-of-View Based on a Heliostat Design

Recently, we introduced a Portable HAndheld Spectral Reflection (PHASR) Scanner to allow THz Time-Domain Spectroscopic (THz-TDS) imaging in clinical and industrial settings using a fiber-coupled and alignment-free telecentric beam steering design. The key limitations of the version 1.0 of the PHASR Scanner were its field-of-view and speed of time-domain trace acquisition. In this paper, we address these limitations by introducing a heliostat geometry for beam scanning to achieve an extended field-of-view, and by reconfiguring the Asynchronous OPtical Sampling (ASOPS) system to perform Electronically Controlled OPtical Sampling (ECOPS) measurements. The former change improved the deflection range of the beam, while also drastically reducing the coupling of the two scanning axes, the combination of which resulted in a larger than four-fold increase in the FOV area. The latter change significantly improves the acquisition speed and frequency domain performance simultaneously by improving measurement efficiency. To accomplish this, we characterized the non-linear time-axis sampling behavior of the electro-mechanical system in the ECOPS mode. We proposed methods to model and correct the non-linear time-axis distortions and tested the performance of the high-speed ECOPS trace acquisition. Therefore, here we introduce the PHASR Scanner version 2.0, which is capable of imaging a 40×27 mm2 FOV with 2000 traces per second over a 100 picosecond TDS range. This new scanner represents a significant leap towards translating the THz-TDS technology from the lab bench to the bedside for real-time clinical imaging applications.

Multiresolution spectrally-encoded terahertz reflection imaging through a highly diffusive cloak

Turbid media, made of wavelength-scale inhomogeneous particles, can give rise to many significant imaging and spectroscopy challenges. The random variation of the refractive index within such media distorts the spherical wavefronts, resulting in smeared and speckly images. The scattering-induced artifacts can obscure the characteristic spectral fingerprints of the chemicals in a sample. This in turn prevents accurate chemical imaging and characterization of the materials cloaked with a diffusive medium. In this work, we present a novel computational technique for creating spatially- and spectrally-resolved chemical maps through a diffusive cloak using terahertz time-domain spectroscopy. We use the maximal overlap discrete wavelet transform to obtain a multiresolution spectral decomposition of THz extinction coefficients. We define a new spectroscopic concept dubbed the "bimodality coefficient spectrum" using the skewness and kurtosis of the spectral images. We demonstrate that broadband wavelet-based reconstruction of the bimodality coefficient spectrum can resolve the signature resonant frequencies through the scattering layers. Additionally, we show that our approach can achieve spectral images with diffraction-limited resolution. This technique can be used for stand-off characterization of materials and spectral imaging in nondestructive testing and biological applications.

Deep neural network classification of in vivo burn injuries with different etiologies using terahertz time-domain spectral imaging

Thermal injuries can occur due to direct exposure to hot objects or liquids, flames, electricity, solar energy and several other sources. If the resulting injury is a deep partial thickness burn, the accuracy of a physician's clinical assessment is as low as 50-76% in determining the healing outcome. In this study, we show that the Terahertz Portable Handheld Spectral Reflection (THz-PHASR) Scanner combined with a deep neural network classification algorithm can accurately differentiate between partial-, deep partial-, and full-thickness burns 1-hour post injury, regardless of the etiology, scanner geometry, or THz spectroscopy sampling method (ROC-AUC = 91%, 88%, and 86%, respectively). The neural network diagnostic method simplifies the classification process by directly using the pre-processed THz spectra and removing the need for any hyperspectral feature extraction. Our results show that deep learning methods based on THz time-domain spectroscopy (THz-TDS) measurements can be used to guide clinical treatment plans based on objective and accurate classification of burn injuries.

Supervised machine learning for automatic classification of in vivo scald and contact burn injuries using the terahertz Portable Handheld Spectral Reflection (PHASR) Scanner

We present an automatic classification strategy for early and accurate assessment of burn injuries using terahertz (THz) time-domain spectroscopic imaging. Burn injuries of different severity grades, representing superficial partial-thickness (SPT), deep partial-thickness (DPT), and full-thickness (FT) wounds, were created by a standardized porcine scald model. THz spectroscopic imaging was performed using our new fiber-coupled Portable HAndheld Spectral Reflection Scanner, incorporating a telecentric beam steering configuration and an f-[Formula: see text] scanning lens. ASynchronous Optical Sampling in a dual-fiber-laser THz spectrometer with 100 MHz repetition rate enabled high-speed spectroscopic measurements. Given twenty-four different samples composed of ten scald and ten contact burns and four healthy samples, supervised machine learning algorithms using THz-TDS spectra achieved areas under the receiver operating characteristic curves of 0.88, 0.93, and 0.93 when differentiating between SPT, DPT, and FT burns, respectively, as determined by independent histological assessments. These results show the potential utility of our new broadband THz PHASR Scanner for early and accurate triage of burn injuries.

Translation-Invariant Zero-Phase Wavelet Methods for Feature Extraction in Terahertz Time-Domain Spectroscopy

Wavelet transform is an important tool in the computational signal processing of terahertz time-domain spectroscopy (THz-TDS) measurements. Despite its prevalence, the effects of using different forms of wavelet transforms in THz-TDS studies have not been investigated. In this paper, we explore the implications of using the maximal overlap discrete wavelet transform (MODWT) versus the well-known discrete wavelet transform (DWT). We demonstrate that the spectroscopic features extracted using DWT can vary over different overlapping frequency ranges. On the contrary, MODWT is translation-invariant and results in identical features, regardless of the spectral range used for its implementation.We also demonstrate that the details coefficients obtained by the multiresolution analysis (MRA) using MODWT are associated with zero-phase filters. In contrast, DWT details coefficients suffer from misalignments originated from the down- and upsampling operations in DWT pyramid algorithm. Such misalignments have adverse effects when it is critical to retain the exact location of the absorption lines. We study the differences of DWT and MODWT both analytically and experimentally, using reflection THz-TDS measurements of α-lactose monohydrate. This manuscript can guide the researchers to select the right wavelet analysis tool for their specific application of the THz spectroscopy.