State-of-the art of acousto-optic sensing and imaging of turbid media

Acousto-optic (AO) is an emerging hybrid technique for measuring optical contrast in turbid media using coherent light and ultrasound (US). A turbid object is illuminated with a coherent light source leading to speckle formation in the remitted light. With the use of US, a small volume is selected,which is commonly referred to as the “tagging” volume. This volume acts as a source of modulated light, where modulation might involve phase and intensity change. The tagging volume is created by focusing ultrasound for good lateral resolution; the axial resolution is accomplished by making either the US frequency, amplitude, or phase time-dependent. Typical resolutions are in the order of 1 mm. We will concentrate on the progress in the field since 2003. Different schemes will be discussed to detect the modulated photons based on speckle detection, heterodyne detection, photorefractive crystal (PRC) assisted detection, and spectral hole burning (SHB) as well as Fabry-Perot interferometers. The SHB and Fabry-Perot interferometer techniques are insensitive to speckle decorrelation and therefore suitable for in vivo imaging. However, heterodyne and PRC methods also have potential for in vivo measurements. Besides measuring optical properties such as scattering and absorption, AO can be applied in fluorescence and elastography applications

Multiple Scattering Of Light In Inhomogeneous Media And Applications

Light scattering-based techniques are being developed for non-invasive diagnostics of inhomogeneous media in various fields, such as medicine, biology, and material characterization. However, as most media of interest are highly scattering and have a complex structure, it is difficult to obtain a full analytical solution of the scattering problem without introducing approximations and assumptions about the properties of the system under consideration. Moreover, most of the previous studies deal with idealized scattering situations, rarely encountered in practice. This dissertation provides new analytical, numerical, and experimental solutions to describe subtle effects introduced by the properties of the light sources, and by the boundaries, absorption and morphology of the investigated media. A novel Monte Carlo simulation was developed to describe the statistics of partially coherent beams after propagation through inhomogeneous media. The Monte Carlo approach also enabled us to study the influence of the refractive index contrast on the diffusive processes, to discern between different effects of absorption in multiple scattering, and to support experimental results on inhomogeneous media with complex morphology. A detailed description of chromatic effects in scattering was used to develop new models that explain the spectral dependence of the detected signal in applications such as imaging and diffuse reflectance measurements. The quantitative and non-invasive characterization of inhomogeneous media with complex structures, such as porous membranes, diffusive coatings, and incipient lesions in natural teeth was then demonstrated

Design and development of optical reflectance spectroscopy and optical coherence tomography catheters for myocardial tissue characterization

Catheter ablation therapy attempts to restore sinus rhythm in arrhythmia patients by producing site-specific tissue modification along regions which cause abnormal electrical activity. This treatment, though widely used, often requires repeat procedures to observe long-term therapeutic benefits. This limitation is driven in part by challenges faced by conventional schemes in validating lesion adequacy at the time of the procedure. Optical techniques are well-suited for the interrogation and characterization of biological tissues. In particular, optical coherence tomography (OCT) relies on coherence gating of singly-scattered light to enable high-resolution structural imaging for tissue diagnostics and procedural guidance. Alternatively, optical reflectance spectroscopy (ORS) is a point measurement technique which makes use of incoherent, multiply-scattered light to probe tissue volumes and derive important data from its optical signature. ORS relies on the fact that light-tissue interactions are regulated by absorption and scattering, which directly relate to the intrinsic tissue biochemistry and cellular organization. In this thesis, we explore the integration of these modalities into ablation catheters for obtaining procedural metrics which could be utilized to guide catheter ablation therapy. We first present the development of an accelerated computational light transport model and its application for guiding ORS catheter design. A custom ORS-integrated ablation catheter is then implemented and tested within porcine specimens in vitro. A model is proposed for real-time estimation of lesion size based on changes in spectral morphology acquired during ablation. We then fabricated custom integrated OCT M-mode RF catheters and present a model for detecting contact status based on deep convolutional neural networks trained on endomyocardial images. Additionally, we demonstrate for the first time, tracking of RF-induced lesion formation employing OCT Doppler micro-velocimetry; this response is shown to be commensurate with the degree of treatment. We further demonstrate for the first time spectroscopic tracking of kinetics related to the heme oxidation cascade during thermal treatment, which are linked to tissue denaturation. The pairing of these modalities into a single RF catheter was also validated for guiding lesion delivery in vitro and within live pigs. Finally, we conclude with a proof-of-concept demonstration of ORS as a mapping tool to guide epicardial ablation in human donor hearts. These results showcase the vast potential of ORS and OCT empowered RF catheters for aiding intraprocedural guidance of catheter ablation procedures which could be utilized alongside current practices

Infrared attenuated total reflection spectroscopy for monitoring biological systems

Mid-infrared (MIR) spectroscopy has been recognized as an important analytical technique, and is widely applied for qualitative and quantitative analysis of materials with an increasing interest in addressing complex organic or biologic constituents. In the presented thesis, (a) the fundamental principles for IR spectroscopic applications via in vivo catheters in combination with multivariate data analysis technique were developed, and (b) the combination with a second analytical technique ¨C scanning electrochemical microscopy (SECM) - for enhancing the information obtained at complex or frequently changing matrices was demonstrated. The first part of this thesis focused on the combination of different MIR measurment techniques with specific focus on evanescent field absorption spectroscopy along with multivariate data analysis methods, for the discrimination of atherosclerotic and normal rabbit aorta tissues. Atherosclerotic and normal rabbit aorta tissues are characterized by marked differences in chemical composition governed by their water, lipid, and protein content. Strongly overlapping infrared absorption features of the different constituents and the complexity of the tissue matrix render the direct evaluation of molecular spectroscopic characteristics obtained from IR measurements challenging for classification. We have successfully applied multivariate data analysis and classification techniques based on principal component analysis (PCA), partial least squares regression (PLS), and linear discriminant analysis (LDA) to IR spectroscopic data obtained by infrared attenuated total reflectance (IR-ATR) measurements, reflection IR microscopy, and a recently developed IR-ATR catheter prototype for future in vivo diagnostic applications. Training and test data were collected ex vivo at atherosclerotic and normal rabbit aorta samples. The successful classification results at atherosclerotic and normal aorta samples utilizing the developed data evaluation routines reveals the potential of IR spectroscopy combined with multivariate classification strategies for in vitro, and ¨C in future - in vivo applications. The second part of this thesis aimed at the development of a novel multifunctional analytical platform by combining SECM with single-bounce IR-ATR spectroscopy for in situ studies of electrochemically active or electrochemically induced processes at the IR waveguide surface via simultaneous evanescent field absorption spectroscopy. The utility of the developed SECM-IR-ATR platform was demonstrated by spectroscopically monitoring microstructured polymer depositions induced via feedback mode SECM experiments using a 25μm Pt disk ultramicroelectrode (UME). The surface of a ZnSe ATR crystal was coated with a thin layer of 2,5-di-(2-thienyl)-pyrrole (SNS), which was then polymerized in a Ru(bpy) ₃ ² ⁺-mediated feedback mode SECM experiment. The polymerization reaction was simultaneously spectroscopically monitored by recording the absorption intensity changes of specific IR bands characteristic for SNS, thereby providing information on the polymerization progress, mechanism, and level of surface modification. Furthermore, a novel current-independent approach mechanism for positioning the UME in aqueous electrolyte solution was demonstrated by monitoring IR absorption changes of borosilicate glass (BSG) shielding the UME, and of water within the penetration depth of the evanescent field.Ph.D.Committee Chair: Mizaikoff, Boris; Committee Member: Fernandez, Facundo; Committee Member: Orlando, Thomas; Committee Member: Palmer. Richard; Committee Member: Whetten, Rober

Causal connectivity of evolved neural networks during behavior

To show how causal interactions in neural dynamics are modulated by behavior, it is valuable to analyze these interactions without perturbing or lesioning the neural mechanism. This paper proposes a method, based on a graph-theoretic extension of vector autoregressive modeling and 'Granger causality,' for characterizing causal interactions generated within intact neural mechanisms. This method, called 'causal connectivity analysis' is illustrated via model neural networks optimized for controlling target fixation in a simulated head-eye system, in which the structure of the environment can be experimentally varied. Causal connectivity analysis of this model yields novel insights into neural mechanisms underlying sensorimotor coordination. In contrast to networks supporting comparatively simple behavior, networks supporting rich adaptive behavior show a higher density of causal interactions, as well as a stronger causal flow from sensory inputs to motor outputs. They also show different arrangements of 'causal sources' and 'causal sinks': nodes that differentially affect, or are affected by, the remainder of the network. Finally, analysis of causal connectivity can predict the functional consequences of network lesions. These results suggest that causal connectivity analysis may have useful applications in the analysis of neural dynamics

Multi-spectral light interaction modeling and imaging of skin lesions

Nevoscope as a diagnostic tool for melanoma was evaluated using a white light source with promising results. Information about the lesion depth and its structure will further improve the sensitivity and specificity of melanoma diagnosis. Wavelength-dependent variable penetration power of monochromatic light in the trans-illumination imaging using the Nevoscope can be used to obtain this information. Optimal selection of wavelengths for multi-spectral imaging requires light-tissue interaction modeling. For this, three-dimensional wavelength dependent voxel-based models of skin lesions with different depths are proposed. A Monte Carlo simulation algorithm (MCSVL) is developed in MATLAB and the tissue models are simulated using the Nevoscope optical geometry. 350-700nm optical wavelengths with an interval of 5nm are used in the study. A correlation analysis between the lesion depth and the diffuse reflectance is then used to obtain wavelengths that will produce diffuse reflectance suitable for imaging and give information related to the nevus depth and structure. Using the selected wavelengths, multi-spectral trans-illumination images of the skin lesions are collected and analyzed. An adaptive wavelet transform based tree-structure classification method (ADWAT) is proposed to classify epi-illuminance images of the skin lesions obtained using a white light source into melanoma and dysplastic nevus images classes. In this method, tree-structure models of melanoma and dysplastic nevus are developed and semantically compared with the tree-structure of the unknown image for classification. Development of the tree-structure is dependent on threshold selections obtained from a statistical analysis of the feature set. This makes the classification method adaptive. The true positive value obtained for this classifier is 90% with a false positive of 10%. The Extended ADWAT method and Fuzzy Membership Functions method using combined features from the epi-illuminance and multi-spectral images further improve the sensitivity and specificity of melanoma diagnosis. The combined feature set with the Extended-ADWAT method gives a true positive of 93.33% with a false positive of 8.88%. The Gaussian Membership Functions give a true positive of 100% with a false positive of 17.77% while the Bell Membership Functions give a true positive of 100% with a false positive of 4.44%

Characterization and modeling of the human left atrium using optical coherence tomography

With current needs to better understand the interaction between atrial tissue microstructure and atrial fibrillation dynamics, micrometer scale imaging with optical coherence tomography has significant potential to provide further insight on arrhythmia mechanisms and improve treatment guidance. However, optical coherence tomography imaging of cardiac tissue in humans is largely unexplored, and the ability of optical coherence tomography to identify the structural substrate of atrial fibrillation has not yet been investigated. Therefore, the objective of this thesis was to develop an optical coherence tomography imaging atlas of the human heart, study the utility of optical coherence tomography in providing useful features of human left atrial tissues, and develop a framework for optical coherence tomography-informed cardiac modeling that could be used to probe dynamics between electrophysiology and tissue structure. Human left atrial tissues were comprehensively imaged by optical coherence tomography for the first time, providing an imaging atlas that can guide identification of left atrial tissue features from optical coherence tomography imaging. Optical coherence tomography image features corresponding to myofiber and collagen fiber orientation, adipose tissue, endocardial thickness and composition, and venous media were established. Varying collagen fiber distributions in the myocardial sleeves were identified within the pulmonary veins. A scheme for mapping optical coherence tomography data of dissected left atrial tissues to a three-dimensional, anatomical model of the human left atrium was also developed, enabling the mapping of distributions of imaged adipose tissue and fiber orientation to the whole left atrial geometry. These results inform future applications of structural substrate mapping in the human left atrium using optical coherence tomography-integrated catheters, as well as potential directions of ex vivo optical coherence tomography atrial imaging studies. Additionally, we developed a workflow for creating optical mapping models of atrial tissue as informed by optical coherence tomography. Tissue geometry, fiber orientation, ablation lesion geometry, and heterogeneous tissue types were extracted from optical coherence tomography images and incorporated into tissue-specific meshes. Electrophysiological propagation was simulated and combined with photon scattering simulations to evaluate the influence of tissue-specific structure on electrical and optical mapping signals. Through tissue-specific modeling of myofiber orientation, ablation lesions, and heterogeneous tissue types, the influence of myofiber orientation on transmural activation, the relationship between fluorescent signals and lesion geometry, and the blurring of optical mapping signals in the presence of heterogeneous tissue types were investigated. By providing a comprehensive optical coherence tomography image database of the human left atrium and a workflow for developing optical coherence tomography-informed cardiac tissue models, this work establishes the foundation for utilizing optical coherence tomography to improve the structural substrate characterization of atrial fibrillation. Future developments include analysis of optical coherence tomography imaged tissue structure with respect to clinical presentation, development of automated processing to better leverage the large amount of imaging data, enhancements and validation of the modeling scheme, and in vivo evaluation of the left atrial structural substrate through optical coherence tomography-integrated catheter