Investigation of water diffusion dynamics in corneal phantoms using terahertz time-domain spectroscopy

Countermeasure to cell dehydration caused terahertz near-field scanning image deterioration

Most biomedical applications of terahertz (THz) imaging are based on distinguishing the dielectric differences of tissues or cells in the THz band. But changes in bio-sample dehydration during the point-scanning process can lead to time-varying deviations in the imaging results. To eliminate the deviations, we proposed a time-varying dehydration kinetic model by analyzing the water diffusion process. The model is verified by experiments and applied to restore each point close to the initial imaging starting state of fresh cellular samples, compensating for the impact of slow speed point-scanning on image deterioration. This methodology has significantly improved the THz super-resolution imaging quality of fresh cellular samples, and successfully restored the cell contours that had been obscured by the cell dehydration over time. Although the dehydration model is developed in THz near-filed imaging, it also pertains to other spectral systems that operate in the raster-scan mode on fresh bio-samples.

Design and characterization of a hyperbolic-elliptical lens pair in a rapid beam steering system for single-pixel terahertz spectral imaging of the cornea

Terahertz (THz) time-domain spectroscopy has been investigated for assessment of the hydration levels in the cornea, intraocular pressure, and changes in corneal topography. Previous efforts at THz imaging of the cornea have employed off-axis parabolic mirrors to achieve normal incidence along the spherical surface. However, this comes at the cost of an asymmetric field-of-view (FOV) and a long scan time because it requires raster-scanning of the collimated beam across the large mirror diameter. This paper proposes a solution by designing a pair of aspheric lenses that can provide a larger symmetric spherical FOV (9.6 mm) and reduce the scan time by two orders of magnitude using a novel beam-steering approach. A hyperbolic-elliptical lens was designed and optimized to achieve normal incidence and phase-front matching between the focused THz beam and the target curvature. The lenses were machined from a slab of high-density polyethylene and characterized in comparison to ray-tracing simulations by imaging several targets of similar sizes to the cornea. Our experimental results showed excellent agreement in the increased symmetric FOV and confirmed the reduction in scan time to about 3-4 seconds. In the future, this lens design process can be extended for imaging the sclera of the eye and other curved biological surfaces, such as the nose and fingers.

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.

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

The accuracy of clinical assessment techniques in diagnosing partial-thickness burn injuries has remained as low as 50-76%. Depending on the burn depth and environmental factors in the wound, such as reactive oxygen species, inflammation, and autophagy, partial-thickness burns can heal spontaneously or require surgical intervention. Herein, it is demonstrated that terahertz time-domain spectral imaging (THz-TDSI) is a promising tool for in vivo quantitative assessment and monitoring of partial-thickness burn injuries in large animals. We used a novel handheld THz-TDSI scanner to characterize burn injuries in a porcine scald model with histopathological controls. Statistical analysis (n= 40) indicates that the THz-TDSI modality can accurately differentiate between partial-thickness and full-thickness burn injuries (1-way ANOVA, p< 0.05). THz-TDSI has the potential to improve burn care outcomes by helping surgeons in making objective decisions for early excision of the wound.

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.

Terahertz scattering microscopy for dermatology diagnostics

We explore the possibility of detecting anomalous structures buried under the skin surface by studying the deviations from the ideal Airy pattern of the point-spread function (PSF) of a terahertz microscope that includes the skin as one of the reflecting surfaces of the optical system. Using a custom terahertz microscope with a monochromatic point source emitting at 0.611 THz, we record the PSF images with a microbolometer camera. Skin simulants based on collagen gel, with and without artificial buried structures, have been analyzed. The geometrical features characterizing the PSF deformations have been extracted automatically from the PSF images. A machine learning algorithm applied to these geometrical features produces a reliable classification of targets with or without buried structures with error below 5%. It can even classify targets with anisotropic buried structures according to their different orientation.

Non-contact terahertz spectroscopic measurement of the intraocular pressure through corneal hydration mapping

Elevated intraocular pressure (IOP) results in endothelial layer damage that can induce corneal hydration perturbations. We investigated the potential of terahertz spectroscopy in measuring the IOP levels through mapping corneal water content. We controlled the IOP levels in ex vivo rabbit and porcine eye samples while monitoring the change in corneal hydration using a terahertz time-domain spectroscopy (THz-TDS) scanner. Our results showed a statistically significant increase in the THz reflectivity between 0.4 and 0.6 THz corresponding to the increase in the IOP. Endothelial layer damage was confirmed using scanning electron microscopy (SEM) of the corneal biopsy samples. Our empirical results indicate that the THz-TDS can be used to track IOP levels through the changes in corneal hydration.

Development of a terahertz time-domain scanner for topographic imaging of spherical targets

Topographical abnormality in corneal tissue is a common diagnostic marker for many eye diseases and injuries. Using an asynchronous optical sampling terahertz time-domain spectroscopy setup, we developed a non-contact and normal-incidence imaging system to measure topographic changes along the surface of spherical samples. We obtained orthogonal 1D scans of calibration spheres to evaluate the minimum axial resolution of our system. We determined the axial and spatial resolution of the scanner using 3D-printed spherical cross and Boehler star targets. Furthermore, we characterized the asymmetrical performance of the scanner due to the use of an off-axis parabolic mirror. Finally, we developed an edge-detection filter to aid with improving the topographic scans. We showed that when imaging samples were comparable in size to the human cornea, the axial and spherical spatial resolutions were limited to about 15 µm (∼λ/67) and 1 mm, respectively.

Effective Debye relaxation models for binary solutions of polar liquids at terahertz frequencies

There are many effective medium models that accurately describe the dielectric properties of mixtures. However, these models assume that the components are non-interacting. This assumption is not valid for solutions of polar liquids, resulting in significant deviations between the measured and theoretically predicted values of the complex index of refraction of the mixtures. We present three effective medium theories by expanding the well-known Debye relaxation model for solutions of polar liquids in the terahertz (THz) regime. The new effective medium models proposed in this paper predict the individual relaxation Debye parameters based on the cooperative motion dynamics and self-associative properties of each mixture, and therefore explain the deviation of the dielectric functions of the solutions from the traditional effective medium models. These models are verified through reflection measurements of four alcohol-water solutions acquired through THz time-domain spectroscopy (THz-TDS). Compared to the current mixed medium models, the new effective Debye theorem predicts the dielectric properties of polar solutions more accurately and has the potential to explain inter-species mixing schemes and interactions.