Applications of Monte Carlo Methods in Biology, Medicine and Other Fields of Science

This volume is an eclectic mix of applications of Monte Carlo methods in many fields of research should not be surprising, because of the ubiquitous use of these methods in many fields of human endeavor. In an attempt to focus attention on a manageable set of applications, the main thrust of this book is to emphasize applications of Monte Carlo simulation methods in biology and medicine

Design and Verification of an Optical System to Interrogate Dermally-implanted Microparticle Sensors

Diabetes mellitus affects 25.8 million Americans (8.3%) and over 300 million people worldwide. Clinical trials indicate that proper management of blood glucose levels is critical in preventing or delaying complications associated with diabetes. Thus, there is a common need to monitor and manage blood glucose properly for people with diabetes. However, the patients’ compliance for recommended monitoring frequency is low due to the pain and inconvenience of current standard finger-pricking tests. To promote patient adherence to the recommended self-monitoring frequency, non-invasive/ minimally invasive glucose testing approaches are needed. Luminescent microparticle sensor is an attractive solution. For these sensors to be deployed in vivo, a matched optical system is needed to interrogate dermally-implanted sensors. This research project investigated the light propagation in skin and the interaction with implants using Monte Carlo modeling. The results of the modeling were used to design an optical system with high interrogation and collection efficiency (40~300 times improvement). The optical system was then constructed and evaluated experimentally. A stable skin phantom mimicking the optical properties of human skin was developed as a permanent evaluation medium to minimize the use of animals. The optical properties of the skin phantom matched the maximum published values of human skin in scattering and absorption over the spectral range of 540~700nm in order to avoid overestimation of the capability of the system. The significant photon loss observed at the connection between the designed system and a commercial spectrometer was overcome using two optimized designs: a two-detector system and a customized low-resolution spectrometer system. Both optimization approaches effectively address the photon loss problem and each showed good SNR (>100) while maintaining a sufficient system resolution for use with fluorescent materials. Both systems are suitable for luminescence measurement, because broad bands of the luminescent spectrum are of interest. In the future, either system can be easily modified into a more compact system (e.g. handheld), and it can be directly coupled to an analog-to-digital converter and integrated circuits offering potential for a single compact and portable device for field use with luminescent diagnostic systems as well as implanted sensors

NON-INVASIVE OPTICAL DETECTION OF EPITHELIAL CANCER USING OBLIQUE INCIDENCE DIFFUSE REFLECTANCE SPECTROSCOPY

This dissertation describes the design, fabrication and testing of an oblique incidence diffuse reflectance spectrometry (OIDRS) system for in-vivo and noninvasive detection of epithelial cancer. Two probes were fabricated using micromachining technology, which plays a significant role in the probe development by enabling device miniaturization, low-cost fabrication and precise assembly. The fist probe was developed and clinically tested for skin cancer detection. This probe consists of three source fibers, two linear array of collection fibers and four micromachined positioning devices for accurate alignment of the fibers. The spatially resolved diffuse reflectance spectra from 167 pigmented and 78 non-pigmented skin abnormalities were measured and used to design a set of classifiers to separate them into benign or malignant ones. These classifiers perform with an overall classification rate of 91%. The absorption and reduced scattering coefficient spectra were estimated to link the anatomic and physiologic properties of the lesions with the optical diagnosis. The melanoma cases presented larger average absorption and reduced scattering spectra than the dysplastic and benign ones. A second probe was designed to demonstrate the feasibility of a miniaturized ?side viewing? optical sensor probe for OIDRS. The sensor probe consists of a lithographically patterned polymer waveguides chip and two micromachined positioning substrates. This miniaturize probe was used to measure twenty ex-vivo esophageal samples. Two statistical classifiers were designed to separate the esophageal cases. The first one distinguishes benign and low dysplastic from high dysplastic and cancerous lesions. The second classifier separates benign lesions from low dysplastic ones. Both classifiers generated a classification rate of 100%

Recovering the optical properties of a tissue using maximum a posteriori based estimation

The spectral reflectance of a biological tissue is known to be affected by its physical and optical properties such as thickness, chromophore concentrations and scattering coefficient. There exist numerous methods that aim to extract the optical parameters of a tissue by relating reflectance measurements to a theoretical model of light transport. During the parameter recovery process, assumptions are often made about the characteristics of the tissue. However, incorrect assumptions lead to inaccurate or even erroneous results. We present a method based on the maximum a posteriori estimation technique to recover some optical properties of the biological tissue from reflectance measurements. The method provides correct results even in the presence of significant uncertainty in the underlying specification of the tissue. A light transport model of the inspected medium is developed and used in the estimation process. The analysis of the results obtained from simulated skin data and phantoms suggests that the proposed MAP based method is a good parameter recovery technique that provides accurate estimates and is robust against a high level of uncertainty in the tissue's model

Probing Biological Systems using Reflectance and Fluorescence Spectroscopy.

Pancreatic adenocarcinoma is a leading cause of cancer death with a five-year survival rate of only 5%. Endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA), the current diagnostic standard, cannot reliably rule out malignancy and is insensitive to distinguishing adenocarcinoma from chronic pancreatitis (inflammation). To investigate the ability of multi-modal optical spectroscopy to detect signals from human pancreatic tissue, a clinically-compatible instrument was developed for rapid, quantitative reflectance and fluorescence spectroscopy in tissues, including fluorescence lifetime sensing. Reflectance and fluorescence spectra and time-resolved fluorescence decay curves were successfully measured for the first time from freshly excised human pancreatic tissues and in vivo human pancreatic cancer xenografts in mice. For the first time, pancreatic tissue classification algorithms using optical spectroscopy data were developed. A total of 96 fluorescence and 96 reflectance spectra were considered from 50 sites (adenocarcinoma, chronic pancreatitis, and normal tissues) on 9 patients. The SpARC (Spectral Areas and Ratios Classifier) and PCA (principal component analysis) algorithms employed linear discriminant analysis on classification variables extracted from optical data. Maximum sensitivity, specificity, NPV, and PPV (85%, 89%, 92%, and 80%, respectively for the SpARC, and 91%, 90%, 95%, 83%, respectively for the PCA algorithm) for correctly identifying adenocarcinoma were achieved employing both reflectance and fluorescence spectra. Inclusion of time-resolved fluorescence data in the PCA algorithm further improved the distinction between pancreatitis and normal tissues in a limited data set. Importantly, the sensitivity of both algorithms far exceeds reported EUS-FNA sensitivity (54%) at distinguishing adenocarcinoma from chronic pancreatitis. The developed algorithms show promise for rapid automated pancreatic tissue classification using multi-modal optical spectroscopy and could be employed in a clinical setting. The possibility of applying optical spectroscopy to evaluate tissue engineered devices was also investigated. Tissue engineered constructs are functional biologic devices employed for grafting wounds or replacing diseased tissue. Non-invasive methods are required to assess the viability of these engineered constructs. Monte Carlo simulations and multi-modal optical spectroscopy were coupled to assess porcine articular cartilage and oral mucosa constructs for the first time. The developed methods would be safe for clinical human use as they employ endogenous contrast for non-invasive quantitative assessment.Ph.D.Applied PhysicsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/75958/1/malavika_1.pd

Imaging light transport at the femtosecond scale

Paper, milk, clouds and white paint share a common property: they are opaque disordered media through which light scatters randomly rather than propagating in a straight path. For very thick and turbid media, indeed, light eventually propagates in a ‘diffusive’ way, i.e. similarly to how tea infuses through hot water. Frequently though, a material is neither perfectly opaque nor transparent and the simple diffusion model does not hold. In this work, we developed a novel optical-gating setup that allowed us to observe light transport in scattering media with sub-ps time resolution. An array of unexplored aspects of light propagation emerged from this spatio-temporal description, unveiling transport regimes that were previously inaccessibile due to the extreme time scales involved and the lack of analytical models