Multi-Scale Modeling for Image Analysis of Brain Tumor Studies

Image-based modeling of tumor growth combines methods from cancer simulation and medical imaging. In this context, we present a novel approach to adapt a healthy brain atlas to MR images of tumor patients. In order to establish correspondence between a healthy atlas and a pathologic patient image, tumor growth modeling in combination with registration algorithms is employed. In a first step, the tumor is grown in the atlas based on a new multi-scale, multi-physics model including growth simulation from the cellular level up to the biomechanical level, accounting for cell proliferation and tissue deformations. Large-scale deformations are handled with an Eulerian approach for finite element computations, which can operate directly on the image voxel mesh. Subsequently, dense correspondence between the modified atlas and patient image is established using nonrigid registration. The method offers opportunities in atlasbased segmentation of tumor-bearing brain images as well as for improved patient-specific simulation and prognosis of tumor progression.

Coherent phase contrast imaging of THz phonon-polariton tunneling

We report on coherent spatiotemporal imaging of single-cycle THz waves in frustrated total internal reflection geometry. Our technique yields images of the spatiotemporal electric field distribution before and after tunneling through an air gap in between two LiNbO3 crystals. Measurements of the reflected and the transmitted THz waveforms for different tunnel distances allow for a direct comparison with results from a causal linear dispersion theory and excellent agreement is found.

Effects of enamel abrasion, salivary pellicle, and measurement angle on the optical assessment of dental erosion

The present study assessed the effects of abrasion, salivary proteins, and measurement angle on the quantification of early dental erosion by the analysis of reflection intensities from enamel. Enamel from 184 caries-free human molars was used for in vitro erosion in citric acid (pH 3.6). Abrasion of the eroded enamel resulted in a 6% to 14% increase in the specular reflection intensity compared to only eroded enamel, and the reflection increase depended on the erosion degree. Nevertheless, monitoring of early erosion by reflection analysis was possible even in the abraded eroded teeth. The presence of the salivary pellicle induced up to 22% higher reflection intensities due to the smoothing of the eroded enamel by the adhered proteins. However, this measurement artifact could be significantly minimized (p<0.05) by removing the pellicle layer with 3% NaOCl solution. Change of the measurement angles from 45 to 60 deg did not improve the sensitivity of the analysis at late erosion stages. The applicability of the method for monitoring the remineralization of eroded enamel remained unclear in a demineralization/remineralization cycling model of early dental erosion in vitro.

Evaluation and quantification of spectral information in tissue by confocal microscopy

A confocal imaging and image processing scheme is introduced to visualize and evaluate the spatial distribution of spectral information in tissue. The image data are recorded using a confocal laser-scanning microscope equipped with a detection unit that provides high spectral resolution. The processing scheme is based on spectral data, is less error-prone than intensity-based visualization and evaluation methods, and provides quantitative information on the composition of the sample. The method is tested and validated in the context of the development of dermal drug delivery systems, introducing a quantitative uptake indicator to compare the performances of different delivery systems is introduced. A drug penetration study was performed in vitro. The results show that the method is able to detect, visualize and measure spectral information in tissue. In the penetration study, uptake efficiencies of different experiment setups could be discriminated and quantitatively described. The developed uptake indicator is a step towards a quantitative assessment and, in a more general view apart from pharmaceutical research, provides valuable information on tissue composition. It can potentially be used for clinical in vitro and in vivo applications.

Three-dimensional surface reconstruction within noncontact diffuse optical tomography using structured light

A main field in biomedical optics research is diffuse optical tomography, where intensity variations of the transmitted light traversing through tissue are detected. Mathematical models and reconstruction algorithms based on finite element methods and Monte Carlo simulations describe the light transport inside the tissue and determine differences in absorption and scattering coefficients. Precise knowledge of the sample's surface shape and orientation is required to provide boundary conditions for these techniques. We propose an integrated method based on structured light three-dimensional (3-D) scanning that provides detailed surface information of the object, which is usable for volume mesh creation and allows the normalization of the intensity dispersion between surface and camera. The experimental setup is complemented by polarization difference imaging to avoid overlaying byproducts caused by inter-reflections and multiple scattering in semitransparent tissue.

Determining the optical properties of a gelatin-TiO2 phantom at 780 nm

Tissue phantoms play a central role in validating biomedical imaging techniques. Here we employ a series of methods that aim to fully determine the optical properties, i.e., the refractive index n, absorption coefficient μa, transport mean free path ℓ∗, and scattering coefficient μs of a TiO2 in gelatin phantom intended for use in optoacoustic imaging. For the determination of the key parameters μa and ℓ∗, we employ a variant of time of flight measurements, where fiber optodes are immersed into the phantom to minimize the influence of boundaries. The robustness of the method was verified with Monte Carlo simulations, where the experimentally obtained values served as input parameters for the simulations. The excellent agreement between simulations and experiments confirmed the reliability of the results. The parameters determined at 780 nm are n=1.359(±0.002), μ′s=1/ℓ∗=0.22(±0.02) mm-1, μa= 0.0053(+0.0006-0.0003) mm-1, and μs=2.86(±0.04) mm-1. The asymmetry parameter g obtained from the parameters ℓ∗ and μ′s is 0.93, which indicates that the scattering entities are not bare TiO2 particles but large sparse clusters. The interaction between the scattering particles and the gelatin matrix should be taken into account when developing such phantoms.

Control algorithms for large scale adaptive optics

In this dissertation, the problem of creating effective large scale Adaptive Optics (AO) systems control algorithms for the new generation of giant optical telescopes is addressed. The effectiveness of AO control algorithms is evaluated in several respects, such as computational complexity, compensation error rejection and robustness, i.e. reasonable insensitivity to the system imperfections. The results of this research are summarized as follows: 1. Robustness study of Sparse Minimum Variance Pseudo Open Loop Controller (POLC) for multi-conjugate adaptive optics (MCAO). The AO system model that accounts for various system errors has been developed and applied to check the stability and performance of the POLC algorithm, which is one of the most promising approaches for the future AO systems control. It has been shown through numerous simulations that, despite the initial assumption that the exact system knowledge is necessary for the POLC algorithm to work, it is highly robust against various system errors. 2. Predictive Kalman Filter (KF) and Minimum Variance (MV) control algorithms for MCAO. The limiting performance of the non-dynamic Minimum Variance and dynamic KF-based phase estimation algorithms for MCAO has been evaluated by doing Monte-Carlo simulations. The validity of simple near-Markov autoregressive phase dynamics model has been tested and its adequate ability to predict the turbulence phase has been demonstrated both for single- and multiconjugate AO. It has also been shown that there is no performance improvement gained from the use of the more complicated KF approach in comparison to the much simpler MV algorithm in the case of MCAO. 3. Sparse predictive Minimum Variance control algorithm for MCAO. The temporal prediction stage has been added to the non-dynamic MV control algorithm in such a way that no additional computational burden is introduced. It has been confirmed through simulations that the use of phase prediction makes it possible to significantly reduce the system sampling rate and thus overall computational complexity while both maintaining the system stable and effectively compensating for the measurement and control latencies.

Development of a wireless platform to generate nitric oxide for implanted biomedical devices

The perturbation of homeostatic mechanisms caused by interactions between any indwelling biomedical device and the biological medium into which it is implanted initiates a dynamic wound healing response from the host which can be rigorous and ongoing. The typical result of this response is a severe degradation in the performance and safety of the device, often to the extent of precluding their clinical use. Nitric oxide (NO) is an endogenously produced biomolecule capable of mediating many of the cellular processes leveraged against implanted devices. The in vivo performance of indwelling devices prepared with NO release coatings has recently been evaluated with very encouraging results. This work developed a platform capable of both generating programmable fluxes of NO and directly evaluating the performance of indwelling probes under different profiles of NO generation. This platform can be used to improve the efficacy of NO release materials in mitigating the host response.

MAGNETO-PHOTONIC CRYSTALS FOR OPTICAL SENSING APPLICATIONS

Among the optical structures investigated for optical sensing purpose, a significant amount of research has been conducted on photonic crystal based sensors. A particular advantage of photonic crystal based sensors is that they show superior sensitivity for ultra-small volume sensing. In this study we investigate polarization changes in response to the changes in the cover index of magneto-optic active photonic band gap structures. One-dimensional photonic-band gap structures fabricated on iron garnet materials yield large polarization rotations at the band gap edges. The enhanced polarization effects serve as an excellent tool for chemical sensing showing high degree of sensitivity for photonic crystal cover refractive index changes. The one dimensional waveguide photonic crystals are fabricated on single-layer bismuth-substituted rare earth iron garnet films ((Bi, Y, Lu)3(Fe, Ga)5O12 ) grown by liquid phase epitaxy on gadolinium gallium garnet substrates. Band gaps have been observed where Bragg scattering conditions links forward-going fundamental waveguide modes to backscattered high-order waveguide modes. Large near-band-edge polarization rotations which increase progressively with backscattered-mode order have been experimentally demonstrated for multiple samples with different composition, film thickness and fabrication parameters. Experimental findings are supported by theoretical analysis of Bloch modes polarization states showing that large near stop-band edge rotations are induced by the magneto-photonic crystal. Theoretical and experimental analysis conducted on polarization rotation sensitivity to waveguide photonic crystal cover refractive index changes shows a monotonic enhancement of the rotation with cover index. The sensor is further developed for selective chemical sensing by employing Polypyrrole as the photonic crystal cover layer. Polypyrrole is one of the extensively studied conducting polymers for selective analyte detection. Successful detection of aqueous ammonia and methanol has been achieved with Polypyrrole deposited magneto-photonic crystals.