Optical brain imaging has several advantages over other imaging techniques and was used to visualize both the structural and functional aspects of the brain, providing a more complete picture of brain activity. One of the promising techniques is optical coherence tomography (OCT), which uses low-coherence interferometry to obtain three-dimensional depth-resolved imaging of structures. In this research, we proposed a micro-electro-mechanical (MEMS) based miniature OCT probe and conducted brain imaging at the hippocampus area. The designed probe has great potential applied to freely moving mice that can observe the changes in brain structure and vascular, thus aimed at early detection of Alzheimer's disease.
We present an early release of our study utilizing a fiber-based Optical Coherence Tomography (OCT) probe to acquire 3D images of the airway in sleep apnea patients. The probe, with a 1.3mm diameter, navigates from the nasal cavity to the vocal cords while rotating within a transparent protective sheath. Long-range OCT imaging (2-30mm) enables comprehensive airway visualization. Our approach facilitates airflow dynamic analysis, aiding in the identification of critical regions prone to collapse during sleep. This non-invasive technique promises to revolutionize sleep apnea diagnostics and personalized treatment planning, offering substantial benefits to patient care.
Proper ciliary dynamics is vital for effective mucociliary transport, the primary defense mechanism for the upper respiratory tract. Abnormal cilia behavior could lead to chronic respiratory disease, making it essential to conduct more detailed studies. In this study we present a multimodality system, specifically using optical coherence tomography (OCT) and phase-resolved spectrally encoded interferometric microscopy (PR-SEIM). We have already shown that PR-SEIM is capable of measuring cilia beat frequency ex vivo. Although we were able to visually identify the ciliary motion in the nasal cavity of rabbits in vivo, due to its sensitivity to motion artifacts, it has been difficult to quantitatively analyze ciliary dynamics. To overcome this obstacle, we incorporated OCT along with a high-speed laser source to compensate for bulk motion. Ultimately, this system will provide a way to study ciliary dynamics in its natural environment, thus allowing more in-depth understanding of ciliary functions.
Acute Respiratory Distress Syndrome (ARDS) is a life-threatening condition in critically ill patients, characterized by severe acute hypoxemia and lung injuries. The complexity of ARDS and its high mortality rates warrant innovative approaches for accurate assessment and early intervention. In this scientific study, we present an advanced methodology to evaluate proximal airway volume (PAV) in a porcine model using optical coherence tomography (OCT) and deep learning techniques. We developed an OCT system capable of capturing changes in mucosa thickness (MT) and proximal airway volume in response to smoke inhalation injury in the porcine model. OCT images were acquired at various time points, including baseline, post-injury, and 24, 48, and 72 hours after injury. A comprehensive dataset was compiled for training and validating the deep learning models. The deep learning approach, employing U-Net, DeepLabv3, and SegNet architectures, demonstrated remarkable efficiency in automated PAV calculation when compared to manual segmentation. The Intersection over Union and Dice similarity coefficient metrics validated the accuracy of the models in delineating proximal airway structures.
Past studies used the VCSEL OCTs to image neonatal upper airways. However, due to manufacturing difficulties, the optimal focal length of the probe for VCSEL OCTs has yet to be determined. To determine this, both animal tracheas (duck and rabbit) and in vivo intubated neonates' upper airways were imaged with different probe focal lengths. In this study, the optimal VCSEL OCT probe focal lengths were provided for better image quality.
Acute Respiratory Distress Syndrome (ARDS) is a heterogenic clinical condition that affects critically-ill patients and is associated with high mortality rates and treatment costs. It is characterized by severe acute hypoxemia and alveolar lung injuries. We previously designed an optical coherence tomography (OCT) system to evaluate the changes in mucosa thickness (MT) and proximal airway volume in a swine model after a smoke inhalation injury. However, the analysis relied on manual segmentation of OCT images. Since the manual segmentation of large amounts of OCT data is time-consuming, tedious, and prone to error, this study aims to assess proximal airway volume (PAV) using an automated method based on deep learning. We use convolutional neural networks (CNN) to calculate PAV in a swine model affected by ARDS. We compare the PAV of the swine affected by ARDS with non-ARDS swine. We evaluate OCT images obtained at baseline (BL), post-injury (PI), 24 hours, 48 hours, and 72 hours after smoke inhalation injury. The neural network is modeled utilizing the U-net architecture. The accuracy is evaluated by computing the Sørensen-Dice similarity coefficient. We also demonstrate the correlation between PAV and MT, PFR values obtained from our previous study.
Mucociliary clearance is an important physiological mechanism for clearing the upper airways. Previously, it has been shown that different disease processes and drugs affect ciliary beat frequency (CBF). Namely, epinephrine has been shown to accelerate CBF in various animal models. Additionally, phase contrast microscopy (PCM) and spectrally encoded interferometric microscopy (SEIM) have been used to image dynamic tissue of the upper airway. Herein, we explore the effects of epinephrine on human sinonasal mucosa through PCM and SEIM. Sinonasal mucosa was harvested from patients undergoing endoscopic sinus surgery (ESS). Tissue was imaged using PCM and SEIM, maintaining physiological temperature through the use of warmed HBSS and a heating plate. Videos were taken before addition of any drugs as baseline. Epinephrine was diluted to 1 mg/mL (1:1000) and 1mL of solution was introduced to the sinonasal mucosa. PCM and SEIM was performed after to determine effects of epinephrine on CBF. Data analysis was performed using MATLAB (Mathworks, Natick, Massachusetts). Human sinonasal mucosa, taken from various anatomic locations, showed CBF values on PCM and SEIM consistent with what has been shown in previous literature. Upon addition of epinephrine to sinonasal mucosa, a marked increase in CBF was observed in both PCM and SEIM. In conclusion, the addition of epinephrine to sinonasal mucosa increased ciliary beat frequency. This validates the use of SEIM for determining CBF in sinonasal tissues. Further studies include adding to our sample size to determine a more accurate magnitude of increase of CBF.
Mucociliary clearance is vital for preventing any foreign substances from entering the upper airway that can later develop into acute and/or chronic respiratory diseases. Therefore, it is essential to further advance our understanding of the mucociliary functions. Our lab has been able to make key developments in imaging cilia, specifically measuring cilia beat frequency, with phase-resolved Doppler optical coherence tomography. In this system, we have further developed the system by incorporating phase-resolved spectrally encoded interferometric microscopy (SIEM) system with an FDML laser with MHz sweep rate to image cilia with higher accuracy and to minimize motion artifacts. In addition, we have designed a compact handheld probe system with a GRIN lens for easier in vivo imaging. The development of this system will allow us to further investigate cilia dynamics and ultimately utilize the system for clinical applications.
Hereditary Hemorrhagic Telangiectasia (HHT) is an inherited, autosomal dominant, vascular disorder that affects an estimated 1 in 5,000 individuals (approximately 1.5M globally and 62,000 in the USA. It is characterized by the presence of multiple arteriovenous malformations (AVMs). An arteriovenous malformation (AVM) is an abnormal tangle of blood vessels connecting arteries and veins, disrupting normal blood flow and oxygen circulation. This study proposes a high-resolution, non-invasive multifunctional imaging system that combines 1.7um D-OCT/OCTA to accurately interrogate HHT skin lesions, including hands, chest, and tongue. Integrated OCTA and Doppler OCT imaging can provide information on lesion architecture and microvasculature. We use this methodology to interrogate individual lesion morphology, compare mucosal and skin lesions, and ultimately, evaluate the vascular effects of anti-VEGF treatment.
Mucociliary clearance facilitated by healthy cilia beating is crucial to normal upper airway function. Phase-contrast microscopy (PCM) is the current golden standard for measuring ciliary beat frequency (CBF) and has limitations. With PCM, one cannot appreciate how CBF varies across the complex landscape of the nasal vault and sinus tissues. With Spectrally encoded interferometric microscopy (SEIM), en face imaging of cilia can be achieved, providing insight into the changes in CBF across tissue surfaces. This study aims to validate the use of SEIM to quantify ciliary beat frequency across ex vivo upper airway tissue.
Acute respiratory distress syndrome (ARDS) is a form of lung injury that is associated with inflammation and increased permeability in the lung. It is characterized by acute arterial hypoxemia. The accurate assessment of the airway damage due to smoke inhalation injury (SII) plays a vital role in facilitating appropriate treatment strategies and improved clinical outcomes. This study evaluates the efficiency and accuracy of a trained neural network in segmenting the pig airway images which is used in the assessment of ARDS caused by smoke inhalation injury (SII). The neural network is modeled after the U-net convolutional neural network and the segmentation accuracy is calculated.
Acute Respiratory Distress Syndrome (ARDS) is a severe form of lung injury characterized by hypoxemia. ARDS is estimated to affect at least 190,000 patients per year in the United States. The median time for ARDS onset is 48 hours after hospital admission. The early assessment of the ARDS due to smoke inhalation injury (SII) plays a vital role in facilitating appropriate treatment strategies and improved clinical outcomes. Optical coherence tomography (OCT) may be used as an effective diagnostic tool in quantifying the physiological changes in the airway after smoke inhalation injury. The objective of this study is to develop and evaluate a deep-learning technique to predict and early uncover (within 24 hours) ARDS in a pig model based on the information obtained from the OCT images. A convolutional neural network (CNN) is modeled to train and classify the pig airway images. The early prediction would help clinicians in the accurate diagnosis of ARDS which is of great clinical value.
In human airway, the ciliated cells and mucus are the first line of defense against inhaled pathogens and particulates, preventing them from invading the rest of the respiratory system. Ciliary dysfunction can quickly develop into a vulnerability for patients with acute and/or chronic diseases, including cystic fibrosis, asthma, chronic obstructive pulmonary disease, and primary cilia dyskinesia. Ciliary beating frequency (CBF) can provide a good standard for determining cilia functionality. In this study, we developed a homemade prototype front-facing endoscope based on a spectrally encoded interferometric microscopy (SEIM) system using a phase-resolved Doppler (PRD) algorithm to measure and map the ciliary beating frequency within an en face region. We evaluated the capability of assessing the CBF ex vivo. This study is the steppingstone to in-vivo studies and the translation of mapping spatial CBF in clinics.
Significance: The human vocal fold (VF) oscillates in multiple vectors and consists of distinct layers with varying viscoelastic properties that contribute to the mucosal wave. Office-based and operative laryngeal endoscopy are limited to diagnostic evaluation of the VF epithelial surface only and are restricted to axial-plane characterization of the horizontal mucosal wave. As such, understanding of the biomechanics of human VF motion remains limited.
Aim: Optical coherence tomography (OCT) is a micrometer-resolution, high-speed endoscopic imaging modality which acquires cross-sectional images of tissue. Our study aimed to leverage OCT technology and develop quantitative methods for analyzing the anatomy and kinematics of in vivo VF motion in the coronal plane.
Approach: A custom handheld laryngeal stage was used to capture OCT images with 800 A-lines at 250 Hz. Automated image postprocessing and analytical methods were developed.
Results: Novel kinematic analysis of in vivo, long-range OCT imaging of the vibrating VF in awake human subjects is reported. Cross-sectional, coronal-plane panoramic videos of the larynx during phonation are presented with three-dimensional videokymographic and space-time velocity analysis of VF motion.
Conclusions: Long-range OCT with automated computational methods allows for cross-sectional dynamic laryngeal imaging and has the potential to broaden our understanding of human VF biomechanics and sound production.
KEYWORDS: Optical coherence tomography, Imaging systems, Vertical cavity surface emitting lasers, Real time imaging, Range imaging, Medical imaging, Laser development, GRIN lenses, Image resolution, In vivo imaging
Fourier domain optical coherence tomography (FD-OCT) is a noninvasive imaging modality that has previously been used to image the human larynx. However, differences in anatomical geometry and short imaging range of conventional OCT limits its application in a clinical setting. In order to address this issue, we have developed a gradient-index (GRIN) lens rod-based hand-held probe in conjunction with a long imaging range 200 kHz Vertical-Cavity Surface Emitting Lasers (VCSEL) swept-source optical coherence tomography (SS-OCT) system for high speed real-time imaging of the human larynx in an office setting. This hand-held probe is designed to have a long and dynamically tunable working distance to accommodate the differences in anatomical geometry of human test subjects. A nominal working distance (~6 cm) of the probe is selected to have a lateral resolution <100 um within a depth of focus of 6.4 mm, which covers more than half of the 12 mm imaging range of the VCSEL laser. The maximum lateral scanning range of the probe at 6 cm working distance is approximately 8.4 mm, and imaging an area of 8.5 mm by 8.5 mm is accomplished within a second. Using the above system, we will demonstrate real-time cross-sectional OCT imaging of larynx during phonation in vivo in human and ex-vivo in pig vocal folds.
Evaluation of neurodegenerative disease often requires examination of brain morphology. Volumetric analysis of brain regions and structures can be used to track developmental changes, progression of disease, and the presence of transgenic phenotypes. Current standards for microscopic investigation of brain morphology are limited to detection of superficial structures at a maximum depth of 300μm. While histological techniques can provide detailed cross-sections of brain structures, they require complicated tissue preparation and the ultimate destruction of the sample. A non-invasive, label-free imaging modality known as Optical Coherence Tomography (OCT) can produce 3-dimensional reconstructions through high-speed, cross-sectional scans of biological tissue. Although OCT allows for the preservation of intact samples, the highly scattering and absorbing properties of biological tissue limit imaging depth to 1-2mm. Optical clearing agents have been utilized to increase imaging depth by index matching and lipid digestion, however, these contemporary techniques are expensive and harsh on tissues, often irreversibly denaturing proteins. Here we present an ideal optical clearing agent that offers ease-of-use and reversibility. Similar to how SeeDB has been effective for microscopy, our fructose-based, reversible optical clearing technique provides improved OCT imaging and functional immunohistochemical mapping of disease. Fructose is a natural, non-toxic sugar with excellent water solubility, capable of increasing tissue transparency and reducing light scattering. We will demonstrate the improved depth-resolving performance of OCT for enhanced whole-brain imaging of normal and diseased murine brains following a fructose clearing treatment. This technique potentially enables rapid, 3-dimensional evaluation of biological tissues at axial and lateral resolutions comparable to histopathology.
Biofilm formation has been linked to ventilator-associated pneumonia, which is a prevalent infection in hospital intensive care units. Currently, there is no rapid diagnostic tool to assess the degree of biofilm formation or cellular biofilm composition. Optical coherence tomography (OCT) is a minimally invasive, nonionizing imaging modality that can be used to provide high-resolution cross-sectional images. Biofilm deposited in critical care patients’ endotracheal tubes was analyzed in vitro. This study demonstrates that OCT could potentially be used as a diagnostic tool to analyze and assess the degree of biofilm formation and extent of airway obstruction caused by biofilm in endotracheal tubes.
KEYWORDS: Optical coherence tomography, Imaging systems, Injuries, Range imaging, 3D image processing, In vivo imaging, 3D image reconstruction, Tissues, Bragg cells, Cartilage
We report on the feasibility of using long-range swept-source optical coherence tomography (OCT) to detect airway changes following smoke inhalation in a sheep model. The long-range OCT system (with axial imaging range of 25 mm) and probe are capable of rapidly obtaining a series of high-resolution full cross-sectional images and three-dimensional reconstructions covering 20-cm length of tracheal and bronchial airways with airway diameter up to 25 mm, regardless of the position of the probe within the airway lumen. Measurements of airway thickness were performed at baseline and postinjury to show mucosal thickness changes following smoke inhalation.
A novel two-frequency dynamic light scattering system (TF-DLS) and differential heterodyne en face laser Doppler velocimeter (LDV) are proposed and setup. The power spectrum of the heterodyne beat signal is detected whereas the width of power spectrum and shift of central frequency are measured simultaneously. These are able to provide the particle sizing and its tangential velocity in suspension. Finally, the localization ability of TF-DLS/LDV system on en face velocity measurement was discussed.
Long range optical coherence tomography (OCT), with its high speed, high resolution, non-ionized properties and cross-sectional imaging capability, is suitable for upper airway lumen imaging. To render 2D OCT datasets to true 3D anatomy, additional tools are usually applied, such as X-ray guidance or a magnetic sensor. X-ray increases ionizing radiation. A magnetic sensor either increases probe size or requires an additional pull-back of the tracking sensor through the body cavity. In order to overcome these limitations, we present a novel tracking method using a 1.5 mm×1.5mm, 90/10-ratio micro-beamsplitter: 10% light through the beam-splitter is used for motion tracking and 90% light is used for regular OCT imaging and motion tracking. Two signals corresponding to these two split-beams that pass through different optical path length delays are obtained by the detector simultaneously. Using the two split beams’ returned signals from the same marker line, the 2D inclination angle of each step is computed. By calculating the 2D inclination angle of each step and then connecting the translational displacements of each step, we can obtain the 2D motion trajectory of the probe. With two marker lines on the probe sheath, 3D inclination angles can be determined and then used for 3D trajectory reconstruction. We tested the accuracy of trajectory reconstruction using the probe and demonstrated the feasibility of the design for structure reconstruction of a biological sample using a porcine trachea specimen. This optical-tracking probe has the potential to be made as small as an outer diameter of 1.0mm, which is ideal for upper airway imaging.
Many diseases involve changes in the biomechanical properties of tissue, and there is a close correlation between tissue elasticity and pathology. We report on the development of a phase-resolved acoustic radiation force optical coherence elastography method (ARF-OCE) to evaluate the elastic properties of tissue. This method utilizes chirped acoustic radiation force to produce excitation along the sample's axial direction, and it uses phase-resolved optical coherence tomography (OCT) to measure the vibration of the sample. Under 500-Hz square wave modulated ARF signal excitation, phase change maps of tissue mimicking phantoms are generated by the ARF-OCE method, and the resulting Young's modulus ratio is correlated with a standard compression test. The results verify that this technique could efficiently measure sample elastic properties accurately and quantitatively. Furthermore, a three-dimensional ARF-OCE image of the human atherosclerotic coronary artery is obtained. The result indicates that our dynamic phase-resolved ARF-OCE method can delineate tissues with different mechanical properties.
Traditional phase-resolve Doppler method demonstrates great success for in-vivo imaging of blood flow and blood vessel. However,
the phase-resolved methods always require high phase stability of the system. During phase instable situations, the performance of the phase-resolved
methods will be degraded. We propose a modified Doppler variance algorithm that is based on the intensity or amplitude value.
Performances of the proposed algorithm are compared with traditional phase-resolved Doppler variance and color Doppler methods for two
phase instability systems. The proposed algorithm demonstrates good performances without phase instability induced artifacts.
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