Validation of angle-resolved polarized light scattering spectroscopy as a diagnostic tool for pre-cancer detection

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemistry, 2009.Vita.Includes bibliographical references.Light scattering spectroscopy has emerged as a valuable diagnostic tool for cancer diagnoses in the past ten years. The interaction of light with cellular structures brings out information about morphological changes accompanying malignancy at early stages. The virtue of this technique is to extract key morphological information such as size distribution of nucleus and submicron-sized particles with minimal data acquisition and model-based data analysis. This enables wide area screening and onsite analysis, critical to the clinical applications. The extracted information, however, strongly depends on the selection of the specific model of the cell/tissue scattering and on constraints from prior knowledge about the sample, leaving the validity of the information questionable. The main focus of this thesis work is to validate various models of cell/tissue scattering used in light scattering spectroscopy. Conventional intensity-based light scattering spectroscopy, which records intensity distribution at the angular plane, was set up to measure angular and wavelength distribution of scattered light in cell monolayers, cell suspensions and rat esophagus tissues for both forward and backward scattering. Morphological information was extracted from cell models such as the cell model based on Mie theory and the power-law model. At the same time, field-based microscopy was used to measure 3D refractive index distributions of single live cells and to provide intensity-based light scattering spectroscopy with a more realistic optical model of a cell.(cont.) From the index tomogram, the contribution of individual organelles and cellular components to the light scattering was determined without the need for modeling. Indeed, field-based microscopy was used as a validation tool for the various models and assumptions used in the intensity-based approach. Two types of scattering behavior had been previously reported for a visible range of wavelengths and an angular range of forward-to-backscattering in cells and tissues: an oscillatory behavior of scattering intensity in angle near exact forward and exact backward scatterings associated with cell body or nuclei, and smooth power-like behavior in wavelength for all scattering angles except near forward scattering. This study addresses two key questions related to the two types of behavior mentioned above: feasibility of extracting nuclear size distribution from oscillatory behavior, and extracting cellular parameter(s) characterizing smooth power law decay. To answer the first question, we performed a light scattering study with a single cell using field-based microscopy. Relative contributions to forward scattering of the cell border, the nucleus and other sub-cellular structures were established for the HT29 cell. Nuclear scattering is found to be small compared to the cell border scattering and sensitive to scattering by other sub-cellular structures. In agreement with single cell results, the cell border signal dominates forward scattering in cell suspensions of HeLa cells. This was confirmed by modeling with Mie theory and by index-matching the cell-media interface.(cont.) Cell border signal was not observed in backscattering from cell suspensions, even with the use of large particle signal enhancement methods. Thus, the nuclear signal is estimated to be a few orders of magnitude below the current system sensitivity level and mixed with other scatterers' signals. The main scattering feature is a smooth power law in scattering wavelength. The exponent characterizing smooth power law decay, can separate normal and pre-cancerous tissues within the same tissue type, such as rat esophagus tissue. The range of power law exponents observed in the rat tissue experiments overlaps with the range of power law exponents extracted from HeLa, HT29 and T84 monolayers. Therefore, the power law exponent does not have enough dynamic range to separate independent samples with quite different morphology. In conjunction with the last statement, the power law behavior is explained by three different morphological base sets: the Mie model, describing cell as a collection of spheres, the Fourier model, in which cell is described as combination of periodic structures with a continuous range of spatial frequencies, and a fractal model, in which index fluctuations inside the cell are described by von Karman correlation function. Although all three models can explain the power law behavior, the Fourier model is the most feasible one, because, unlike the other models, no assumptions are made about structure of the sample.by Maxim M. Kalashnikov.Ph.D

Determination of particle size by using the angular distribution of backscattered light as measured with low-coherence interferometry

We employ a novel interferometer to measure the angular distribution of light backscattered by a turbid medium. Through comparison of the measured data with the predictions of Mie theory, we are able to determine the size of the scatterers comprising the medium with subwavelength precision. As the technique is based on low-coherence interferometry, we are able to examine the evolution of the angular distribution of scattered light as it propagates into the medium. The effects of multiple scattering as a function of penetration depth in the medium are analyzed. We also present various considerations for extending this technique to determining structural information in biological tissues, such as the effects of a distribution of particle sizes and the need to average out speckle contributions

Optimization of Stress-Based Microfluidic Testing for Methicillin Resistance in Staphylococcus aureus Strains

The rapid evolution of antibiotic resistance in bacterial pathogens is driving the development of innovative, rapid antibiotic susceptibility testing (AST) tools as a way to provide more targeted and timely antibiotic treatment. We have previously presented a stress-based microfluidic method for the rapid determination of antibiotic susceptibility in methicillin-susceptible Staphylococcus aureus (MSSA) and methicillin-resistant Staphylococcus aureus (MRSA). In this method, stress is used to potentiate the action of antibiotics, and cell death is measured as a proxy for susceptibility. The method allows antibiotic susceptibility to be determined within an hour from the start of the antibiotic introduction. However, the relatively low dynamic range of the signal (2–10% cell response) even with high antibiotic concentrations (10–50 µg/mL) left room for the method’s optimization. We have conducted studies in which we varied the flow patterns, the media composition, and the antibiotic concentration to increase the cell death response and concordantly decrease the required antibiotic concentration down to 1–3 µg/mL, in accordance with the Clinical and Laboratory Standards Institute’s (CLSI) guidelines for AST breakpoint concentrations

Rapid phenotypic stress-based microfluidic antibiotic susceptibility testing of Gram-negative clinical isolates

Bacteremia is a life-threatening condition for which antibiotics must be prescribed within hours of clinical diagnosis. Since the current gold standard for bacteremia diagnosis is based on conventional methods developed in the mid-1800s—growth on agar or in broth—identification and susceptibility profiling for both Gram-positive and Gram-negative bacterial species requires at least 48–72 h. Recent advancements in accelerated phenotypic antibiotic susceptibility testing have centered on the microscopic growth analysis of small bacterial populations. These approaches are still inherently limited by the bacterial growth rate. Our approach is fundamentally different. By applying environmental stress to bacteria in a microfluidic platform, we can correctly assign antibiotic susceptibility profiles of clinically relevant Gram-negative bacteria within two hours of antibiotic introduction rather than 8–24 h. The substantial expansion to include a number of clinical isolates of important Gram-negative species—Enterobacter cloacae, Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa—reported here underscores the broad utility of our approach, complementing the method’s proven utility for Gram-positive bacteria. We also demonstrate that the platform is compatible with antibiotics that have varying mechanisms of action—meropenem, gentamicin, and ceftazidime—highlighting the versatility of this platform