In-vivo measurement of the concentrations of biological compounds using fluorescence is one of the challenging
biophotonic fields. These measurements are useful in diagnostic and treatment monitoring applications that use
fluorescent probes which may bond to specific proteins and drugs. In some cases the relative concentration of two
compounds is a sufficient biological indicator. For instance, it has been shown that the ratio between Amyloid-Beta and
tau protein in the Cerebrospinal fluid (CSF) may predict the development of Alzheimer’s disease (AD) several years
before current diagnosis. We have previously suggested a system that could measure the concentration ratio of these two
proteins in-vivo without the need to collect CSF samples. This system uses a miniature needle with an optical fiber which
is coupled to a laser source and a detector. The fiber excites fluorescent probes which were injected and bond to the
proteins in the CSF, and collects the fluorescence emission. Using the fluorescence intensity ratio, the concentration ratio
between the proteins is estimated, and AD may be diagnosed.
In this work we present the results of an in-vivo trial performed on mice. Miniature tubes containing two fluorescent
probes in several concentration ratios were inserted into the mice in two locations: subcutaneously, and deeper in the
abdomen. The fluorescent probes were excited and the fluorescence intensity was measured. The concentration ratios
were extracted from the fluorescence intensities using a simple calibration curve. The extracted ratios are compared to
the true ratios and the system’s accuracy is estimated.
KEYWORDS: Luminescence, Tissues, Scattering, In vitro testing, Calibration, Signal attenuation, Absorption, Monte Carlo methods, Tissue optics, Error analysis
The pathogenic process of Alzheimer’s disease (AD) begins years before clinical diagnosis. Here, we suggest a method that may detect AD several years earlier than current exams. The method is based on previous reports that relate the concentration ratio of biomarkers (amyloid-beta and tau) in the cerebrospinal fluid (CSF) to the development of AD. Our method replaces the lumbar puncture process required for CSF drawing by using fluorescence measurements. The system uses an optical fiber coupled to a laser source and a detector. The laser radiation excites two fluorescent probes which may bond to the CSF biomarkers. Their concentration ratio is extracted from the fluorescence intensities and can be used for future AD detection. First, we present a theoretical model for fluorescence concentration ratio estimation. The method’s feasibility was validated using Monte Carlo simulations. Its accuracy was then tested using multilayered tissue phantoms simulating the epidural fat, CSF, and bone. These phantoms have various optical properties, thicknesses, and fluorescence concentrations in order to simulate human anatomy variations and different fiber locations. The method was further tested using ex vivo chicken tissue. The average errors of the estimated concentration ratios were low both in vitro (4.4%) and ex vivo (10.9%), demonstrating high accuracy.
The pathogenic process of Alzheimer’s Disease (AD), characterized by amyloid plaques and neurofibrillary tangles in the brain, begins years before the clinical diagnosis. Here, we suggest a novel method which may detect AD up to nine years earlier than current exams, minimally invasive, with minimal risk, pain and side effects. The method is based on previous reports which relate the concentrations of biomarkers in the Cerebrospinal Fluid (CSF) (Aβ and Tau proteins) to the future development of AD in mild cognitive impairment patients. Our method, which uses fluorescence measurements of the relative concentrations of the CSF biomarkers, replaces the lumbar puncture process required for CSF drawing. The process uses a miniature needle coupled trough an optical fiber to a laser source and a detector. The laser radiation excites fluorescent probes which were prior injected and bond to the CSF biomarkers. Using the ratio between the fluorescence intensities emitted from the two biomarkers, which is correlated to their concentration ratio, the patient’s risk of developing AD is estimated. A theoretical model was developed and validated using Monte Carlo simulations, demonstrating the relation between fluorescence emission and biomarker concentration. The method was tested using multi-layered tissue phantoms simulating the epidural fat, the CSF in the sub-arachnoid space and the bone. These phantoms were prepared with different scattering and absorption coefficients, thicknesses and fluorescence concentrations in order to simulate variations in human anatomy and in the needle location. The theoretical and in-vitro results are compared and the method’s accuracy is discussed.
The diffusion approximation is useful for many optical diagnostics modalities, such as near-infrared spectroscopy. However, the simple normal incidence, semi-infinite layer model may prove lacking in estimation of deep-tissue optical properties such as required for monitoring cerebral hemodynamics, especially in neonates. To answer this need, we present an analytical multilayered, oblique incidence diffusion model. Initially, the model equations are derived in vector-matrix form to facilitate fast and simple computation. Then, the spatiotemporal reflectance predicted by the model for a complex neonate head is compared with time-resolved Monte Carlo (TRMC) simulations under a wide range of physiologically feasible parameters. The high accuracy of the multilayer model is demonstrated in that the deviation from TRMC simulations is only a few percent even under the toughest conditions. We then turn to solve the inverse problem and estimate the oxygen saturation of deep brain tissues based on the temporal and spatial behaviors of the reflectance. Results indicate that temporal features of the reflectance are more sensitive to deep-layer optical parameters. The accuracy of estimation is shown to be more accurate and robust than the commonly used single-layer diffusion model. Finally, the limitations of such approaches are discussed thoroughly.
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