Spectral imaging in preclinical research and clinical pathology.

Spectral imaging methods are attracting increased interest from researchers and practitioners in basic science, pre-clinical and clinical arenas. A combination of better labeling reagents and better optics creates opportunities to detect and measure multiple parameters at the molecular and cellular level. These tools can provide valuable insights into the basic mechanisms of life, and yield diagnostic and prognostic information for clinical applications. There are many multispectral technologies available, each with its own advantages and limitations. This chapter will present an overview of the rationale for spectral imaging, and discuss the hardware, software and sample labeling strategies that can optimize its usefulness in clinical settings

Algorithms for Fluorescence Lifetime Microscopy and Optical Coherence Tomography Data Analysis: Applications for Diagnosis of Atherosclerosis and Oral Cancer

With significant progress made in the design and instrumentation of optical imaging systems, it is now possible to perform high-resolution tissue imaging in near real-time. The prohibitively large amount of data obtained from such high-speed imaging systems precludes the possibility of manual data analysis by an expert. The paucity of algorithms for automated data analysis has been a major roadblock in both evaluating and harnessing the full potential of optical imaging modalities for diagnostic applications. This consideration forms the central theme of the research presented in this dissertation. Specifically, we investigate the potential of automated analysis of data acquired from a multimodal imaging system that combines fluorescence lifetime imaging (FLIM) with optical coherence tomography (OCT), for the diagnosis of atherosclerosis and oral cancer. FLIM is a fluorescence imaging technique that is capable of providing information about auto fluorescent tissue biomolecules. OCT on the other hand, is a structural imaging modality that exploits the intrinsic reflectivity of tissue samples to provide high resolution 3-D tomographic images. Since FLIM and OCT provide complimentary information about tissue biochemistry and structure, respectively, we hypothesize that the combined information from the multimodal system would increase the sensitivity and specificity for the diagnosis of atherosclerosis and oral cancer. The research presented in this dissertation can be divided into two main parts. The first part concerns the development and applications of algorithms for providing quantitative description of FLIM and OCT images. The quantitative FLIM and OCT features obtained in the first part of the research, are subsequently used to perform automated tissue diagnosis based on statistical classification models. The results of the research presented in this dissertation show the feasibility of using automated algorithms for FLIM and OCT data analysis for performing tissue diagnosis

Seeing the Big Picture: System Architecture Trends in Endoscopy and LED-Based hyperspectral Subsystem Intergration

Early-stage colorectal lesions remain difficult to detect. Early development of neoplasia tends to be small (less than 10 mm) and flat and difficult to distinguish from surrounding mucosa. Additionally, optical diagnosis of neoplasia as benign or malignant is problematic. Low rates of detection of these lesions allow for continued growth in the colorectum and increased risk of cancer formation. Therefore, it is crucial to detect neoplasia and other non-neoplastic lesions to determine risk and guide future treatment. Technology for detection needs to enhance contrast of subtle tissue differences in the colorectum and track multiple biomarkers simultaneously. This work implements one such technology with the potential to achieve the desired multi-contrast outcome for endoscopic screenings: hyperspectral imaging. Traditional endoscopic imaging uses a white light source and a RGB detector to visualize the colorectum using reflected light. Hyperspectral imaging (HSI) acquires an image over a range of individual wavelength bands to create an image hypercube with a wavelength dimension much deeper and more sensitive than that of an RGB image. A hypercube can consist of reflectance or fluorescence (or both) spectra depending on the filtering optics involved. Prior studies using HSI in endoscopy have normally involved ex vivo tissues or xiv optics that created a trade-off between spatial resolution, spectral discrimination and temporal sampling. This dissertation describes the systems design of an alternative HSI endoscopic imaging technology that can provide high spatial resolution, high spectral distinction and video-rate acquisition in vivo. The hyperspectral endoscopic system consists of a novel spectral illumination source for image acquisition dependent on the fluorescence excitation (instead of emission). Therefore, this work represents a novel contribution to the field of endoscopy in combining excitation-scanning hyperspectral imaging and endoscopy. This dissertation describes: 1) systems architecture of the endoscopic system in review of previous iterations and theoretical next-generation options, 2) feasibility testing of a LED-based hyperspectral endoscope system and 3) another LED-based spectral illuminator on a microscope platform to test multi-spectral contrast imaging. The results of the architecture point towards an endoscopic system with more complex imaging and increased computational capabilities. The hyperspectral endoscope platform proved feasibility of a LED-based spectral light source with a multi-furcated solid light guide. Another LED-based design was tested successfully on a microscope platform with a dual mirror array similar to telescope designs. Both feasibility tests emphasized optimization of coupling optics and combining multiple diffuse light sources to a common output. These results should lead to enhanced imagery for endoscopic tissue discrimination and future optical diagnosis for routine colonoscopy

Time-Domain Fluorescence Diffuse Optical Tomography: Algorithms and Applications

Fluorescence diffuse optical tomography provides non-invasive, in vivo imaging of molecular targets in small animals. While standard fluorescence microscopy is limited to shallow depths and small fields of view, tomographic methods allows recovery of the distribution of fluorescent probes throughout the small animal body. In this thesis, we present novel reconstruction algorithms for the tomographic separation of optical parameters using time-domain (TD) measurements. These technique are validated using simulations and with experimental phantom and mouse imaging studies. We outline the contributions of each chapter of the thesis below. First, we explore the TD fluorescence tomography reconstruction problem for single and multiple fluorophores with discrete lifetimes. We focus on late arriving photons and compare a direct inversion approach with a two-step, asymptotic approach operating on the same TD data. We show that for lifetime multiplexing, the two methods produce fundamentally different kinds of solutions. The direct inversion is computationally inefficient and results in poor separation but has overall higher resolution while the asymptotic approach provides better separation, relative quantitation of lifetime components and localization but has overall lower resolution. We verify these results with simulation and experimental phantoms. Second, we introduce novel high resolution lifetime multiplexing algorithms which combine asymptotic methods for separation of fluorophores with the high resolving power of early photon tomography. We show the effectiveness of such methods to achieve high resolution reconstructions of multiple fluorophores in simulations with complex-shaped phantoms, a digital mouse atlas and also experimentally in fluorescent tube phantoms. Third, we compare the performance of tomographic spectral and lifetime multiplexing. We show that both of these techniques involve a two-step procedure, consisting of a diffuse propagation step and a basis-function mixing step. However, in these two techniques, the order of the two steps is switched, which leads to a fundamental difference in imaging performance. As an illustration of this difference, we show that the relative concentrations of three colocalized fluorophores in a diffuse medium can accurately be retrieved with lifetime methods but cannot be retrieved with spectral methods. Fourth, we address the long standing challenge in diffuse optical tomography (DOT) of cross-talk between absorption and scattering. We extend the ideas developed from lifetime multiplexing algorithms by using a constrained optimization approach for separation of absorption and scattering in DOT. Using custom designed phantoms, we demonstrate a novel technique allows better separation of absorption and scattering inclusions compared to existing algorithms for CW and TD diffuse optical tomography. Finally, we show experimental validation of the lifetime multiplexing algorithms developed in this thesis using three experimental models. First, we show the reconstruction of overlapping complex shapes in a dish phantom. Second, we demonstrate the localization accuracy of lifetime based methods using fluorescent pellets embedded in a sacrificed mouse. Third, we show using planar imaging and tomography, the in vivo recovery of multiple anatomically targeted near-infrared fluorophores. In summary, we have presented novel reconstruction algorithms and experimental methods that extend the capability of time-domain fluorescence diffuse optical tomography systems. The methods developed in this thesis should also have applicability for general multi-parameter image reconstruction problems.Engineering and Applied Science

2D and 3D high-speed multispectral optical imaging systems for in-vivo biomedical research

Functional optical imaging encompasses the use of optical imaging techniques to study living biological systems in their native environments. Optical imaging techniques are well-suited for functional imaging because they are minimally-invasive, use non ionizing radiation, and derive contrast from a wide range of biological molecules. Modern transgenic labeling techniques, active and inactive exogenous agents, and intrinsic sources of contrast provide specific and dynamic markers of in-vivo processes at subcellular resolution. A central challenge in building functional optical imaging systems is to acquire data at high enough spatial and temporal resolutions to be able to resolve the in-vivo process(es) under study. This challenge is particularly highlighted within neuroscience where considerable effort in the field has focused on studying the structural and functional relationships within complete neurovascular units in the living brain. Many existing functional optical techniques are limited in meeting this challenge by their imaging geometries, light source(s), and/or hardware implementations. In this thesis we describe the design, construction, and application of novel 2D and 3D optical imaging systems to address this central challenge with a specific focus on functional neuroimaging applications. The 2D system is an ultra-fast, multispectral, wide-field imaging system capable of imaging 7.5 times faster than existing technologies. Its camera-first design allows for the fastest possible image acquisition rates because it is not limited by synchronization challenges that have hindered previous multispectral systems. We present the development of this system from a bench top instrument to a portable, low-cost, modular, open source, laptop based instrument. The constructed systems can acquire multispectral images at >75 frames per second with image resolutions up to 512 x 512 pixels. This increased speed means that spectral analysis more accurately reflects the instantaneous state of tissues and allows for significantly improved tracking of moving objects. We describe 3 quantitative applications of these systems to in-vivo research and clinical studies of cortical imaging and calcium signaling in stem cells. The design and source code of the portable system was released to the greater scientific community to help make high-speed, multispectral imaging more accessible to a larger number of dynamic imaging applications, and to foster further development of the software package. The second system we developed is an entirely new, high-speed, 3D fluorescence microscopy platform called Laser-Scanning Intersecting Plane Tomography (L-SIPT). L-SIPT uses a novel combination of light-sheet illumination and off-axis detection to provide en-face 3D imaging of samples. L-SIPT allows samples to move freely in their native environments, enabling a range of experiments not possible with previous 3D optical imaging techniques. The constructed system is capable of acquiring 3D images at rates >20 volumes per second (VPS) with volume resolutions of 1400 x 50 x 150 pixels, over a 200 fold increase over conventional laser scanning microscopes. Spatial resolution is set by choice of telescope design. We developed custom opto-mechanical components, computer raytracing models to guide system design and to characterize the technique's fundamental resolution limits, and phantoms and biological samples to refine the system's performance capabilities. We describe initial applications development of the system to image freely moving, transgenic Drosophila Melanogaster larvae, 3D calcium signaling and hemodynamics in transgenic and exogenously labeled rodent cortex in-vivo, and 3D calcium signaling in acute transgenic rodent cortical brain slices in-vitro

Descomposición de datos multi-espectrales: interfaz gráfica para Matlab

Avances recientes han permitido el desarrollo de dispositivos capaces de capturar información en múltiples longitudes de onda. Estos datos tienen diversas aplicaciones con el problema en común de cómo interpretarlos. Una de las técnicas utilizadas con este fin es la descomposición espectral, que separa los datos de una muestra en sus componentes básicos y concentraciones proporcionales. Nuestro trabajo previo ha estado enfocado en la descomposición espectral de datos de fluorescencia multiespectral, donde se han desarrollado métodos que proporcionan una solución cuantitativa, robusta y rápida, la cual no está limitada por el número de componentes que se pueden caracterizar. En este trabajo, presentamos una interface desarrollada en Matlab que puede estimar los perfiles característicos de los componentes constituyentes de una muestra y sus abundancias. En caso de que no se tenga información alguna sobre la muestra, nos permite obtener además el número de componentes en ella. El artículo hace una descripción del software y sus herramientas.Además, se ejemplifica su uso en la caracterización de muestras ex-vivo de arterias coronarias. El programa se encuentra disponible de manera gratuita y provee al usuario de una herramienta fácil de usar para el análisis de datos multi o hiper-espectrales.Palabra(s) Clave(s): descomposición ciega, fluorescencia endógena, interfaz gráfica, optimización cuadrática, quimiometría

Real-time multispectral fluorescence and reflectance imaging for intraoperative applications

Fluorescence guided surgery supports doctors by making unrecognizable anatomical or pathological structures become recognizable. For instance, cancer cells can be targeted with one fluorescent dye whereas muscular tissue, nerves or blood vessels can be targeted by other dyes to allow distinction beyond conventional color vision. Consequently, intraoperative imaging devices should combine multispectral fluorescence with conventional reflectance color imaging over the entire visible and near-infrared spectral range at video rate, which remains a challenge. In this work, the requirements for such a fluorescence imaging device are analyzed in detail. A concept based on temporal and spectral multiplexing is developed, and a prototype system is build. Experiments and numerical simulations show that the prototype fulfills the design requirements and suggest future improvements. The multispectral fluorescence image stream is processed to present fluorescent dye images to the surgeon using linear unmixing. However, artifacts in the unmixed images may not be noticed by the surgeon. A tool is developed in this work to indicate unmixing inconsistencies on a per pixel and per frame basis. In-silico optimization and a critical review suggest future improvements and provide insight for clinical translation

Multiplexed nanoparticle-based immunoassays

Multiplexed immunoassays have been explored using the fluorescent and luminescent properties of fluorophores and nanoparticles. Epi-fluorescence microscopy, confocal laser scanning microscopy and programmable array microscopy were used to detect signals from mixtures of conventional organic fluorophores, quantum dots and silica nanoparticles doped with europium, samarium and terbium in single-welled multiplexed immunosorbent assays. Spectral unmixing was investigated using mixtures of fluorophores and cadmium selenide quantum dots. Mixtures of up to four dyes were separated quantitatively using least squares minimisation, with relative standard error ranging from 0.5 to 13 %. Silica nanoparticles doped with luminescent lanthanides were synthesised and used in a model immunoassay system for simultaneous, single-welled detection of human and mouse IgGs. The results indicated the lanthanides are well suited to multiplexed assays, mainly because of their atomic line emission bands. Analytes in a mixture could be quantified with < 5 % error. The multiplexed assay developed was applied to the detection of anti-dengue IgM and IgG in mouse sera, to differentiate primary and secondary dengue infection. The assay traced the kinetics of antibody production for both IgM and IgG with an IgM/IgG ratio of 1

Development of Novel Molecular Imaging Contrast Agents for Detection of Oxidative Stress

An early and precise diagnosis of disease is a crucial requirement for fast and targeted therapy in the era of precision medicine. Most diseases possess molecular alterations in their early stages, which precede noticeable morphological changes. One important molecular change that contributes to dysfunction in a wide range of pathologies, including cancer and neurological disorders, is an increase in levels of reactive oxygen species (ROS) and associated oxidative damage. Our understanding of how ROS influence disease biology is currently limited by our inability to perform sensitive and specific assessment of ROS levels with high spatial and temporal resolution in living systems. The goal of the research described in this thesis was to overcome the challenge of assessing ROS during disease development in cancer and neurodegenerative disease through the design, synthesis and validation of two classes of novel bifunctional, ROS-sensitive contrast agents. To shed light on the complex redox biology in cancer, the new method of photoacoustic imaging was exploited. A novel activatable, targeted near infrared cyanine dye is reported that enables specific detection of pathological levels of hydrogen peroxide, a major and abundant ROS in living organisms. This approach uses photoacoustic and fluorescence imaging in cancerous tissue to evaluate the performance of the new probe under in vitro and in vivo conditions. In neurodegeneration, there exists a bidirectional interaction between oxidative stress and protein aggregates. To scrutinise this relationship, both bulk and single-molecule fluorescence imaging methods were used to assess the capability of novel bifunctional fluorescence dyes to localise the presence of the two putative disease-causing species, ROS and protein aggregates, simultaneously under in vitro conditions. The data shown here provides a promising foundation for the systematic design of contrast agents based on small molecule dyes, that possess ideal optical and biological characteristics to study oxidative stress in a broad range of pathological applications with high temporal and spatial resolution.Cancer Research U