In vivo analysis of burns in a mouse model using spectroscopic optical coherence tomography

Deep learning classification of ex vivo human colon tissues using spectroscopic optical coherence tomography

Screening for colorectal cancer (CRC) with colonoscopy has improved patient outcomes; however, it remains the third leading cause of cancer-related mortality, novel strategies to improve screening are needed. Here, we propose an optical biopsy technique based on spectroscopic optical coherence tomography (OCT). Depth resolved OCT images are analyzed as a function of wavelength to measure optical tissue properties and used as input to machine learning algorithms. Previously, we used this approach to analyze mouse colon polyps. Here, we extend the approach to examine human biopsied colonic epithelial tissue samples ex vivo. Optical properties are used as input to a novel deep learning architecture, producing accuracy of up to 97.9% in discriminating tissue type. SOCT parameters are used to create false colored en face OCT images and deep learning classifications are used to enable visual classification by tissue type. This study advances SOCT toward clinical utility for analysis of colonic epithelium.

Deep learning classification of ex vivo human colon tissues using spectroscopic OCT

Screening programs for colorectal cancer (CRC) have had a profound impact on the morbidity and mortality of this disease by detecting and removing early cancers and precancerous adenomas with colonoscopy. However, CRC continues to be the third leading cause of cancer-related mortality in both men and woman, partly because of limitations in colonoscopy-based screening. Thus, novel strategies to improve the efficiency and effectiveness of screening colonoscopy are urgently needed. Here, we propose to address this need using an optical biopsy technique based on spectroscopic optical coherence tomography (OCT). The depth resolved images obtained with OCT are analyzed as a function of wavelength to measure optical tissue properties. The optical properties can be used as input to machine learning algorithms as a means to classify adenomatous tissue in the colon. In this study, biopsied tissue samples from the colonic epithelium are analyzed ex vivo using spectroscopic OCT and tissue classifications are generated using a novel deep learning architecture, informed by machine learning methods including LSTM and KNN. The overall classification accuracy obtained was 88.9%, 76.0% and 97.9% in discriminating tissue type for these methods. Further, we apply an approach using false coloring of en face OCT images based on SOCT parameters and deep learning predictions to enable visual identification of tissue type. This study advances the spectroscopic OCT towards clinical utility for analyzing colonic epithelium for signs of adenoma.

Geometry-Dependent Spectroscopic Contrast in Deep Tissues

Nano-structures of biological systems can produce diverse spectroscopic effects through interactions with broadband light. Although structured coloration at the surface has been extensively studied, natural spectroscopic contrasts in deep tissues are poorly understood, which may carry valuable information for evaluating the anatomy and function of biological systems. Here we investigated the spectroscopic characteristics of an important geometry in deep tissues at the nanometer scale: packed nano-cylinders, in the near-infrared window, numerically predicted and experimentally proved that transversely oriented and regularly arranged nano-cylinders could selectively backscatter light of the long wavelengths. Notably, we found that the spectroscopic contrast of nanoscale fibrous structures was sensitive to the pressure load, possibly owing to the changes in the orientation, the degree of alignment, and the spacing. To explore the underlying physical basis, we further developed an analytical model based on the radial distribution function in terms of their radius, refractive index, and spatial distribution.

Fiber-based visible and near infrared optical coherence tomography (vnOCT) enables quantitative elastic light scattering spectroscopy in human retina

Elastic light scattering spectroscopy (ELSS) has been proven a powerful method in measuring tissue structures with exquisite nanoscale sensitivity. However, ELSS contrast in the living human retina has been relatively underexplored, primarily due to the lack of imaging tools with a large spectral bandwidth. Here, we report a simple all fiber-based setup to implement dual-channel visible and near infrared (NIR) optical coherence tomography (vnOCT) for human retinal imaging, bridging over a 300nm spectral gap. Remarkably, the fiber components in our vnOCT system support single-mode propagation for both visible and NIR light, both of which maintain excellent interference efficiencies with fringe visibility of 97% and 90%, respectively. The longitudinal chromatic aberration from the eye is corrected by a custom-designed achromatizing lens. The elegant fiber-based design enables simultaneous imaging for both channels and allows comprehensive ELSS analysis on several important anatomical layers, including nerve fiber layer, outer segment of the photoreceptors and retinal pigment epithelium. This vnOCT platform and method of ELSS analysis open new opportunities in understanding structure-function relationship in the human retina and in exploring new biomarkers for retinal diseases.

A systematic review on the quality of measurement techniques for the assessment of burn wound depth or healing potential

PURPOSE

Reliable and valid assessment of burn wound depth or healing potential is essential to treatment decision-making, to provide a prognosis, and to compare studies evaluating different treatment modalities. The aim of this review was to critically appraise, compare and summarize the quality of relevant measurement properties of techniques that aim to assess burn wound depth or healing potential.

METHODS

A systematic literature search was performed using PubMed, EMBASE and Cochrane Library. Two reviewers independently evaluated the methodological quality of included articles using an adapted version of the Consensus-based Standards for the selection of health Measurement INstruments (COSMIN) checklist. A synthesis of evidence was performed to rate the measurement properties for each technique and to draw an overall conclusion on quality of the techniques.

RESULTS

Thirty-six articles were included, evaluating various techniques, classified as (1) laser Doppler techniques; (2) thermography or thermal imaging; (3) other measurement techniques. Strong evidence was found for adequate construct validity of laser Doppler imaging (LDI). Moderate evidence was found for adequate construct validity of thermography, videomicroscopy, and spatial frequency domain imaging (SFDI). Only two studies reported on the measurement property reliability. Furthermore, considerable variation was observed among comparator instruments.

CONCLUSIONS

Considering the evidence available, it appears that LDI is currently the most favorable technique; thereby assessing burn wound healing potential. Additional research is needed into thermography, videomicroscopy, and SFDI to evaluate their full potential. Future studies should focus on reliability and measurement error, and provide a precise description of which construct is aimed to measure.

Visible-light optical coherence tomography: a review

Visible-light optical coherence tomography (vis-OCT) is an emerging imaging modality, providing new capabilities in both anatomical and functional imaging of biological tissue. It relies on visible light illumination, whereas most commercial and investigational OCTs use near-infrared light. As a result, vis-OCT requires different considerations in engineering design and implementation but brings unique potential benefits to both fundamental research and clinical care of several diseases. Here, we intend to provide a summary of the development of vis-OCT and its demonstrated applications. We also provide perspectives on future technology improvement and applications.

Thermal injury of skin and subcutaneous tissues: A review of experimental approaches and numerical models

Thermal injury to skin and subcutaneous tissue is common in both civilian and combat scenarios. Understanding the change in tissue morphologies and properties and the underlying mechanisms of thermal injury are of vital importance to clinical determination of the degree of burn and treatment approach. This review aims at summarizing the research involving experimental and numerical studies of skin and subcutaneous tissue subjected to thermal injury. The review consists of two parts. The first part deals with experimental studies including burn protocols and prevailing imaging approaches. The second part deals with existing numerical models for burns of tissue and related computational simulations. Based on this review, we conclude that though there is literature contributing to the knowledge of the pathology and pathogenesis of tissue burn, there is scant quantitative information regarding changes in tissue properties including mechanical, thermal, electrical and optical properties as a result of burns that are linked to altered tissue morphology.

Dual-axis optical coherence tomography for deep tissue imaging

We have developed dual-axis optical coherence tomography (DA-OCT) which enables deep tissue imaging by using a novel off-axis illumination/detection configuration. DA-OCT offers a 100-fold speed increase compared with its predecessor, multispectral multiple-scattering low coherence interferometry (ms2/LCI), by using a new beam scanning mechanism based on a microelectro-mechanical system (MEMS) mirror. The data acquisition scheme was altered to take advantage of this scanning speed, producing tomographic images at a rate of 4 frames (B-scans) per second. DA-OCT differs from ms2/LCI in that the dual axes intersect at a shallower depth (∼1  mm). This difference, coupled with the faster scanning speed, shifts the detection priority from multiply scattered to ballistic light. The utility of this approach was demonstrated by imaging both ex vivo porcine ear skin and in vivo rat skin from a McFarlane flap model. The enhanced penetration depth provided by the DA-OCT system will be beneficial to various clinical applications in dermatology and surgery.

Deep imaging of absorption and scattering features by multispectral multiple scattering low coherence interferometry

We have developed frequency domain multispectral multiple scattering low coherence interferometry (ms2/LCI) for deep imaging of absorption and scattering contrast. Using tissue-mimicking phantoms that match the full scattering phase function of human dermal tissue, we demonstrate that ms2/LCI can provide a signal/noise ratio (SNR) improvement of 15.4 dB over conventional OCT at an imaging depth of 1 mm. The enhanced SNR and penetration depth provided by ms2/LCI could be leveraged for a variety of clinical applications including the assessment of burn injuries where current clinical classification of severity only provides limited accuracy. The utility of the approach was demonstrated by imaging a tissue phantom simulating a partial-thickness burn revealing good spectroscopic contrast between healthy and injured tissue regions deep below the sample surface. Finally, healthy rat skin was imaged in vivo with both a commercial OCT instrument and our custom ms2/LCI system. The results demonstrate that ms2/LCI is capable of obtaining spectroscopic information far beyond the penetration depth provided by conventional OCT.

Characterization of lipid-rich plaques using spectroscopic optical coherence tomography

Intravascular optical coherence tomography (IV-OCT) is a high-resolution imaging method used to visualize the internal structures of walls of coronary arteries in vivo. However, accurate characterization of atherosclerotic plaques with gray-scale IV-OCT images is often limited by various intrinsic artifacts. In this study, we present an algorithm for characterizing lipid-rich plaques with a spectroscopic OCT technique based on a Gaussian center of mass (GCOM) metric. The GCOM metric, which reflects the absorbance properties of lipids, was validated using a lipid phantom. In addition, the proposed characterization method was successfully demonstrated in vivo using an atherosclerotic rabbit model and was found to have a sensitivity and specificity of 94.3% and 76.7% for lipid classification, respectively.

Burn depth assessments by photoacoustic imaging and laser Doppler imaging

Diagnosis of burn depths is crucial to determine the treatment plan for severe burn patients. However, an objective method for burn depth assessment has yet to be established, although a commercial laser Doppler imaging (LDI) system is used limitedly. We previously proposed burn depth assessment based on photoacoustic imaging (PAI), in which thermoelastic waves originating from blood under the burned tissue are detected, and we showed the validity of the method by experiments using rat models with three different burn depths: superficial dermal burn, deep dermal burn and deep burn. On the basis of those results, we recently developed a real-time PAI system for clinical burn diagnosis. Before starting a clinical trial, however, there is a need to reveal more detailed diagnostic characteristics, such as linearity and error, of the PAI system as well as to compare its characteristics with those of an LDI system. In this study, we prepared rat models with burns induced at six different temperatures from 70 to 98 °C, which showed a linear dependence of injury depth on the temperature. Using these models, we examined correlations of signals obtained by PAI and LDI with histologically determined injury depths and burn induction temperatures at 48 hours postburn. We found that the burn depths indicated by PAI were highly correlative with histologically determined injury depths (depths of viable vessels) as well as with burn induction temperatures. Perfusion values measured by LDI were less correlative with these parameters, especially for burns induced at higher temperatures, being attributable to the limited detectable depth for light involving a Doppler shift in tissue. In addition, the measurement errors in PAI were smaller than those in LDI. On the basis of these results, we will be able to start clinical studies using the present PAI system.

Evaluation of burn severity in vivo in a mouse model using spectroscopic optical coherence tomography

Clinical management of burn injuries depends upon an accurate assessment of the depth of the wound. Current diagnostic methods rely primarily on subjective visual inspection, which can produce variable results. In this study, spectroscopic optical coherence tomography was used to objectively evaluate burn injuries in vivo in a mouse model. Significant spectral differences were observed and correlated with the depth of the injury as determined by histopathology. The relevance of these results to clinical burn management in human tissues is discussed.

Co-localized confocal Raman spectroscopy and optical coherence tomography (CRS-OCT) for depth-resolved analyte detection in tissue

We report the development of a combined confocal Raman spectroscopy (CRS) and optical coherence tomography (OCT) instrument (CRS-OCT) capable of measuring analytes in targeted biological tissues with sub-100-micron spatial resolution. The OCT subsystem was used to measure depth-resolved tissue morphology and guide the acquisition of chemically-specific Raman spectra. To demonstrate its utility, the instrument was used to accurately measure depth-resolved, physiologically-relevant concentrations of Tenofovir, a microbicide drug used to prevent the sexual transmission of HIV, in ex vivo tissue samples.

Functional optical coherence tomography: principles and progress

In the past decade, several functional extensions of optical coherence tomography (OCT) have emerged, and this review highlights key advances in instrumentation, theoretical analysis, signal processing and clinical application of these extensions. We review five principal extensions: Doppler OCT (DOCT), polarization-sensitive OCT (PS-OCT), optical coherence elastography (OCE), spectroscopic OCT (SOCT), and molecular imaging OCT. The former three have been further developed with studies in both ex vivo and in vivo human tissues. This review emphasizes the newer techniques of SOCT and molecular imaging OCT, which show excellent potential for clinical application but have yet to be well reviewed in the literature. SOCT elucidates tissue characteristics, such as oxygenation and carcinogenesis, by detecting wavelength-dependent absorption and scattering of light in tissues. While SOCT measures endogenous biochemical distributions, molecular imaging OCT detects exogenous molecular contrast agents. These newer advances in functional OCT broaden the potential clinical application of OCT by providing novel ways to understand tissue activity that cannot be accomplished by other current imaging methodologies.

Tri-band spectroscopic optical coherence tomography based on optical parametric amplification for lipid and vessel visualization

A tri-band spectroscopic optical coherence tomography (SOCT) system has been implemented for visualization of lipid and blood vessel distribution. The tri-band swept source, which covers output spectrum in 1.3, 1.5, and 1.6  μm wavelength windows, is based on a dual-band Fourier domain mode-locked laser and a fiber optical parametric amplifier. This tri-band SOCT can further differentiate materials, e.g., lipid and artery, qualitatively by contrasting attenuation coefficients difference within any two of these bands. Furthermore, ex vivo imaging of both porcine artery with artificial lipid plaque phantom and mice with coronary artery disease were demonstrated to showcase the capability of our SOCT.