One of the most recent advancements in laser technology is the development of ultrashort pulsed femtosecond lasers (FSLs). FSLs are improving many fields due to their unique extreme precision, low energy and ablation characteristics. In the area of laser medicine, ophthalmic surgeries have seen very promising developments. Some of the most commonly performed surgical operations in the world, including laser-assisted in-situ keratomileusis (LASIK), lens replacement (cataract surgery), and keratoplasty (cornea transplant), now employ FSLs for their unique abilities that lead to improved clinical outcome and patient satisfaction. The application of FSLs in medical therapeutics is a recent development, and although they offer many benefits, FSLs also stimulate nonlinear optical effects (NOEs), many of which were insignificant with previously developed lasers. NOEs can change the laser characteristics during propagation through a medium, which can subsequently introduce unique safety concerns for the surrounding tissues. Traditional approaches for characterizing optical effects, laser performance, safety and efficacy do not properly account for NOEs, and there remains a lack of data that describe NOEs in clinically relevant procedures and tissues. As FSL technology continues to expand towards new applications, FSL induced NOEs need to be better understood in order to ensure safety as FSL medical devices and applications continue to evolve at a rapid pace. In order to improve the understanding of FSL-tissue interactions related to NOEs stimulated during laser beam propagation though corneal tissue, research investigations were conducted to evaluate corneal optical properties and determine how corneal tissue properties including corneal layer, collagen orientation and collagen crosslinking, and laser parameters including pulse energy, repetition rate and numerical aperture affect second and third-harmonic generation (HG) intensity, duration and efficiency. The results of these studies revealed that all laser parameters and tissue properties had a substantial influence on HG. The dynamic relationship between optical breakdown and HG was responsible for many observed changes in HG metrics. The results also demonstrated that the new generation of therapeutic FSLs has the potential to generate hazardous effects if not carefully controlled. Finally, recommendations are made to optimize current and guide future FSL applications.

Dentre as diversas aplicações da luz em nosso dia-a-dia, as ligadas à área biomédica merecem destaque e são frequentemente objetos de pesquisa tanto para o desenvolvimento quanto para o aprimoramento de técnicas para o diagnóstico e terapias. Os tecidos biológicos são, em sua maioria, estruturas complexas, não-homogêneas e opticamente muito espalhadoras. Apesar das centenas de estudos existentes acerca da propagação da luz em tecidos biológicos, sua complexidade exige que novos estudos sejam conduzidos a fim de aprimorar o conhecimento já existente, que ainda apresenta muitas lacunas. A presença de heterogeneidades nos tecidos (vasos sanguíneos, hematomas, cistos, tumores e outras alterações macroscópicas) mudam a propagação da luz e dificultam a previsibilidade do seu comportamento por modelos matemáticos. O presente trabalho teve por objetivo estabelecer um método empírico que utiliza imagens de refletância difusa obtidas através de uma instrumentação simples, baseada em uma fonte de luz contínua no visível (laser de diodo em 660 nm) e uma câmera CMOS monocromática, para verificar a possibilidade de localização de inclusões absorvedoras embebidas em phantoms altamente espalhadores. Foi avaliada a capacidade de detectar inclusões de dois diferentes tipos de materiais em diversas geometrias e tamanhos, posicionadas em diferentes profundidades. O ângulo de incidência do feixe laser também foi variado, bem como a distância entre a fonte e o objeto, a fim de avaliar quais as melhores condições experimentais. Os resultados obtidos mostraram que os objetos puderam ser detectados, e suas formas puderam ser satisfatoriamente recuperadas através de um algoritmo desenvolvido para o processamento das imagens. Em algumas situações, mesmo para a maior profundidade utilizada, que foi de 20 mm, a inclusão pôde ser detectada nas imagens de refletância difusa processadas. Apesar da capacidade de detecção das formas geométricas representar um avanço com relação às possibilidades de identificação de estruturas em meios túrbidos, a determinação da profundidade ainda é um desafio a ser superado. / Among the various applications of light in our daily life, those connected with biomedicine should be highlighted and are frequently subject of researches aiming for the development and for the enhancement of techniques for diagnosis and therapy. Biological tissues are mostly complex, non-homogeneous and optically highly scattering structures. Despite the hundreds of existent studies on the propagation of light in biological tissues, its complexity requires new studies to be conducted in order to improve the existing knowledge, which still has many gaps. The presence of heterogeneities in tissue (blood vessels, bruises, cysts, tumors and other macroscopic alteration) changes the light propagation and impedes the predictability of its behavior by mathematical models. This work aimed to establish an empirical method using diffuse reflectance images acquired with simple instrumentation, based on a source of continuous light in the visible (diode laser at 660 nm) and a monochromatic CMOS camera, to check the possibility of the location of absorbing inclusions embedded in highly scattering phantoms. The ability to detect inclusions of two different kinds of materials in different sizes and geometries, positioned at different depths were evaluated. The laser beam angle of incidence was also varied, as well as the distance between the source and the object, in order to evaluate the best experimental conditions. The results showed that the objects could be detected, and their shapes might be satisfactorily recovered by an algorithm developed for image processing. In some situations, even at the greatest depth used, which was 20 mm, the inclusion could be detected in diffuse reflectance processed images. Although the detection capability of geometric shapes represents an improvement over the structures of identification possibilities in turbid media, the determination of depth is still a challenge to be overcome.

Probiotics are marketed throughout the world to promote the health of the consumer by improving the microorganisms that normally occur in the intestinal tract (Tannock, 1997). It has also been suggested that probiotics can prevent pathogen infections by adhering to the intestinal mucosa (Lee, Lim, Teng, Ouwehand, Tuomola, & Salminen, 2000). While probiotics can be delivered to the infected areas in multiple fashions, microencapsulation is a newer form of delivering probiotics straight to the infected area. A whey protein microcapsule is thought to protect the probiotics from stomach acid and delivers the treatment to the affected area. To ensure this microencapsulation treatment is affective, the microcapsules will be stained and imaged to see if the microcapsules are constructed in a way which is consistent with the theory: a whey protein microcapsule surrounding bacteria and fat droplets. Through these experiments, it was shown that the microcapsule was not constructed as previously thought. Instead of a thin layer of protein surrounding the bacteria, it more closely resembled a solid ball of protein with bacteria and fat trapped inside. The bacteria are able to survive stomach like conditions (0.1M HCl for 8 hours) due to other forms of microencapsulation.

The application of high frequency ultrasound is the key to higher resolution intravascular ultrasound (IVUS) images. The need to further improve the IVUS spatial resolution may drive the transducer center frequency even higher than the current 40 MHz range. However, increasing the center frequency may be challenging as it leads to stronger scattering echoes from blood. The high level of blood scattering echoes may obscure the arterial lumen and make image interpretation difficult. Blood backscatter levels increase with transmission center frequency at a much greater rate compared to arterial tissue. These different frequency dependencies provide a potential method to distinguish blood from tissues by means of multi-frequency processing techniques. To obtain a good blood-tissue contrast with sufficient signal-to-noise ratio, a system with a wider bandwidth is highly desirable. The method described in this paper is based on the ratio of the received signal power between the high (60 MHz) and low (25 MHz) frequency ranges from a novel 40 MHz wideband IVUS catheter. In this paper we will present our in vitro experiment work on porcine blood and a tissue-mimicking arterial wall. Results of multi-frequency processing indicate that blood, at higher frequencies, has a greater backscatter power that is 8X greater than arterial tissue, suggesting this technique will provide a greater contrast between the blood-wall lumen boundary for coronary imaging.

Cervical cancer remains the third most commonly diagnosed gynecological malignancy in the United States and throughout the world despite being potentially preventable. Patients diagnosed with cervical cancer may develop local recurrence in the cervix and surrounding structures (vaginal apex, parametrial, or paracervical), regional recurrence in pelvic lymph nodes, distant metastasis, or a combination of all. The management of such treatment outcomes has not been subject to rigorous investigation. Therefore, there is a need for studies and clinical trials that focus on decision making to support the choice of the best treatment modality that leads to the minimal number of adverse treatment outcomes. Medical imaging plays a vital role in the initial diagnosis, staging, and guiding treatment decisions for cancer patients. Positron Emission Tomography-Computed Tomography (PET/CT) hybrid scanner has proven to be a primary functional imaging modality in the oncology clinic. A typical oncological application of PET/CT aims to examine the whole body for high tracer uptake as a sign of tumorous lesions or metastasis using 18F-Fluoro-2-deoxy-D-glucose (18F-FDG). This radiopharmaceutical has been proven to be useful for the quantitative determination of regional glucose metabolism localized in the brain, heart, bladder, and, fortunately, in tumors. Currently, 18F-FDG measured on PET is the prominent radiotracer in cancer staging and follow-up imaging. In the –omics1 era, mining data to derive inherent information about a system has influenced the medical field, especially oncological imaging. The process of radiomics involves high throughput analysis of medical images to extract a large number of quantified features that are presented as a decision supporting tool for clinicians in terms of various clinical tasks such as staging, prediction, and prognosis. In recent studies, the focus of radiomics has exceeded the whole-tumor analysis to include the quantification of habitats, sub-regions within the tumor volume defined based on specific criteria, with the intent to investigate the diversity extent of the intratumor heterogeneity as robust descriptors and predictors of clinicopathological factors. The presented work is a retrospective analysis of a cohort consisting of pretreatment Positron Emission Tomography and Computed Tomography (PET/CT) hybrid scans of cervical cancer patients consecutively treated with radiochemotherapy. We extracted radiomic features from the primary cervical tumor volumes, and voxel intensity-based features from tumor habitats to analyze the tumors’ heterogeneity based on 18Flourodeoxyglocuse (18F-FDG) uptake of PET, and Hounsfield Units (HU) of CT to obtain useful tumor information, which might be associated with treatment outcomes. To our knowledge, a limited number of studies have focused on investigating the potential role of radiomic features on cervical cancer PET/CT images. Briefly, the workflow of this study consisted of investigating parameters that might affect radiomic features predictive performance by evaluating the reproducibility of radiomic features extracted from 18F-FDG PET images for segmentation methods, gray levels discretization, and PET reconstruction algorithms. Afterward, we used these features to predict cervical treatment outcomes after radiochemotherapy. Due to the use of human data, this research study acquired the approval of the institutional review board (IRB) at the University of South Florida.

Radiomics treats images as quantitative data and promises to improve cancer prediction in radiology and therapy response assessment in radiation oncology. However, there are a number of fundamental problems that need to be solved in order to potentially apply radiomic features in clinic. The first basic step in computed tomography (CT) radiomic analysis is the acquisition of images using selectable image acquisition and reconstruction parameters. Radiomic features have shown large variability due to variation of these parameters. Therefore, it is important to develop methods to address these variability issues in radiomic features due to each CT parameter. To this end, texture phantoms provide a stable geometry and Hounsfield Units (HU) to characterize the radiomic features with respect to image acquisition and reconstruction parameters. In this project, normalization methods were developed to address the variability issues in CT Radiomics using texture phantoms. In the first part of this project, variability in radiomic features due to voxel size variation was addressed. A voxel size resampling method is presented as a preprocessing step for imaging data acquired with variable voxel sizes. After resampling, variability due to variable voxel size in 42 radiomic features was reduced significantly. Voxel size normalization is presented to address the intrinsic dependence of some key radiomic features. After normalization, 10 features became robust as a function of voxel size. Some of these features were identified as predictive biomarkers in diagnostic imaging or useful in response assessment in radiation therapy. However, these key features were found to be intrinsically dependent on voxel size (which also implies dependence on lesion volume). The normalization factors are also developed to address the intrinsic dependence of texture features on the number of gray levels. After normalization, the variability due to gray levels in 17 texture features was reduced significantly. In the second part of the project, voxel size and gray level (GL) normalizations developed based on phantom studies, were tested on the actual lung cancer tumors. Eighteen patients with non-small cell lung cancer of varying tumor volumes were studied and compared with phantom scans acquired on 8 different CT scanners. Eight out of 10 features showed high (Rs > 0.9) and low (Rs < 0.5) Spearman rank correlations with voxel size before and after normalizations, respectively. Likewise, texture features were unstable (ICC < 0.6) and highly stable (ICC > 0.9) before and after gray level normalizations, respectively. This work showed that voxel size and GL normalizations derived from texture phantom also apply to lung cancer tumors. This work highlights the importance and utility of investigating the robustness of CT radiomic features using CT texture phantoms. Another contribution of this work is to develop correction factors to address the variability issues in radiomic features due to reconstruction kernels. Reconstruction kernels and tube current contribute to noise texture in CT. Most of texture features were sensitive to correlated noise texture due to reconstruction kernels. In this work, noise power spectra (NPS) was measured on 5 CT scanners using standard ACR phantom to quantify the correlated noise texture. The variability in texture features due to different kernels was reduced by applying the NPS peak frequency and the region of interest (ROI) maximum intensity as correction factors. Most texture features were radiation dose independent but were strongly kernel dependent, which is demonstrated by a significant shift in NPS peak frequency among kernels. Percent improvements in robustness of 19 features were in the range of 30% to 78% after corrections. In conclusion, most texture features are sensitive to imaging parameters such as reconstruction kernels, reconstruction Field of View (FOV), and slice thickness. All reconstruction parameters contribute to inherent noise in CT images. The problem can be partly solved by quantifying noise texture in CT radiomics using a texture phantom and an ACR phantom. Texture phantoms should be a pre-requisite to patient studies as they provide stable geometry and HU distribution to characterize the radiomic features and provide ground truths for multi-institutional validation studies.

Virtual aperture culling of the eigenmodes of a resonator (VACER) is a technique to focus light within turbid media at arbitrary locations. A seed pulse of light is directed through a phase-conjugate mirror (PCM) into a turbid medium. Though much of the light may be lost, any light which reaches the second PCM is phase conjugated and thus returned to the first PCM where the light will be phase conjugated again. Amplification by the PCMs can prevent decay of the light cycling between the PCMs. Introducing a mechanism which filters light based on position enables attenuation of the modes not traveling through the center of the virtual aperture resulting in a focusing of light at the center of the virtual aperture. The seed pulse and the positioning of the PCMs on opposite sides of the virtual aperture ensure that modes cannot bypass the virtual aperture. Magnetic fields and ultrasound waves are potential means for implementation of a virtual aperture. Generally, only weak filtration mechanisms like magnetic fields and ultrasound waves are innocuous to turbid media. Fortunately, weak effects can strongly cull modes in VACER because the filtration mechanism affects the modes during each pass between PCMs and the modes compete. A combination of theory and computational modeling prove that sound physical principles underlie VACER. Moreover, computational modeling reveals how mode overlap, the seed pulse, and other variables impact VACER performance. Good experimental performance is predicted. / text

Magnetic resonance imaging (MRI) is an imaging technique to visualize internal structures of the body. Diffusion MRI is an MRI modality that measures overall diffusion effect of molecules in vivo and non-invasively. Diffusion tensor imaging (DTI) is an extended technique of diffusion MRI. The major application of DTI is to measure the location, orientation and anisotropy of fiber tracts in white matter. It enables non-invasive investigation of major neural pathways of human brain, namely tractography. As spatial resolution of MRI is limited, it is possible that there are multiple fiber bundles within the same voxel. However, diffusion tensor model is only capable of resolving a single direction. The goal of this dissertation is to investigate complex anatomical structures using high angular resolution diffusion imaging (HARDI) data without any assumption on the parameters. The dissertation starts with a study of the noise distribution of truncated MRI data. The noise is often not an issue in diffusion tensor model. However, in HARDI studies, with many more gradient directions being scanned, the number of repetitions of each gradient direction is often small to restrict total acquisition time, making signal-to-noise ratio (SNR) lower. Fitting complex diffusion models to data with reduced SNR is a major interest of this study. We focus on fitting diffusion models to data using maximum likelihood estimation (MLE) method, in which the noise distribution is used to maximize the likelihood. In addition to the parameters being estimated, we use likelihood values for model selection when multiple models are fit to the same data. The advantage of carrying out model selection after fitting the models is that both the quality of data and the quality of fitting results are taken into account. When it comes to tractography, we extend streamline method by using covariance of the estimated parameters to generate probabilistic tracts according to the uncertainty of local tract orientations.

Dentre as diversas aplicações da luz em nosso dia-a-dia, as ligadas à área biomédica merecem destaque e são frequentemente objetos de pesquisa tanto para o desenvolvimento quanto para o aprimoramento de técnicas para o diagnóstico e terapias. Os tecidos biológicos são, em sua maioria, estruturas complexas, não-homogêneas e opticamente muito espalhadoras. Apesar das centenas de estudos existentes acerca da propagação da luz em tecidos biológicos, sua complexidade exige que novos estudos sejam conduzidos a fim de aprimorar o conhecimento já existente, que ainda apresenta muitas lacunas. A presença de heterogeneidades nos tecidos (vasos sanguíneos, hematomas, cistos, tumores e outras alterações macroscópicas) mudam a propagação da luz e dificultam a previsibilidade do seu comportamento por modelos matemáticos. O presente trabalho teve por objetivo estabelecer um método empírico que utiliza imagens de refletância difusa obtidas através de uma instrumentação simples, baseada em uma fonte de luz contínua no visível (laser de diodo em 660 nm) e uma câmera CMOS monocromática, para verificar a possibilidade de localização de inclusões absorvedoras embebidas em phantoms altamente espalhadores. Foi avaliada a capacidade de detectar inclusões de dois diferentes tipos de materiais em diversas geometrias e tamanhos, posicionadas em diferentes profundidades. O ângulo de incidência do feixe laser também foi variado, bem como a distância entre a fonte e o objeto, a fim de avaliar quais as melhores condições experimentais. Os resultados obtidos mostraram que os objetos puderam ser detectados, e suas formas puderam ser satisfatoriamente recuperadas através de um algoritmo desenvolvido para o processamento das imagens. Em algumas situações, mesmo para a maior profundidade utilizada, que foi de 20 mm, a inclusão pôde ser detectada nas imagens de refletância difusa processadas. Apesar da capacidade de detecção das formas geométricas representar um avanço com relação às possibilidades de identificação de estruturas em meios túrbidos, a determinação da profundidade ainda é um desafio a ser superado. / Among the various applications of light in our daily life, those connected with biomedicine should be highlighted and are frequently subject of researches aiming for the development and for the enhancement of techniques for diagnosis and therapy. Biological tissues are mostly complex, non-homogeneous and optically highly scattering structures. Despite the hundreds of existent studies on the propagation of light in biological tissues, its complexity requires new studies to be conducted in order to improve the existing knowledge, which still has many gaps. The presence of heterogeneities in tissue (blood vessels, bruises, cysts, tumors and other macroscopic alteration) changes the light propagation and impedes the predictability of its behavior by mathematical models. This work aimed to establish an empirical method using diffuse reflectance images acquired with simple instrumentation, based on a source of continuous light in the visible (diode laser at 660 nm) and a monochromatic CMOS camera, to check the possibility of the location of absorbing inclusions embedded in highly scattering phantoms. The ability to detect inclusions of two different kinds of materials in different sizes and geometries, positioned at different depths were evaluated. The laser beam angle of incidence was also varied, as well as the distance between the source and the object, in order to evaluate the best experimental conditions. The results showed that the objects could be detected, and their shapes might be satisfactorily recovered by an algorithm developed for image processing. In some situations, even at the greatest depth used, which was 20 mm, the inclusion could be detected in diffuse reflectance processed images. Although the detection capability of geometric shapes represents an improvement over the structures of identification possibilities in turbid media, the determination of depth is still a challenge to be overcome.

Recent evidence suggests that cardiac mechanics (e.g. cardiac strains) are better measures of heart function compared to common clinical metrics like ejection fraction. However, commonly-used parameters of cardiac mechanics remain limited to just a few measurements averaged over the whole left ventricle. We hypothesized that recent advances in cardiac magnetic resonance imaging (MRI) could be extended to provide measures of cardiac mechanics throughout the left and right ventricles (LV and RV, respectively). Displacement Encoding with Stimulated Echoes (DENSE) is a cardiac MRI technique that has been validated for measuring LV mechanics at a magnetic field strength of 1.5 T but not at higher field strengths such as 3.0 T. However, it is desirable to perform DENSE at 3.0 T, which would yield a better signal to noise ratio for imaging the thin RV wall. Results in Chapter 2 support the hypothesis that DENSE has similar accuracy at 1.5 and 3.0 T. Compared to standard, clinical cardiac MRI, DENSE requires more expertise to perform and is not as widely used. If accurate mechanics could be measured from standard MRI, the need for DENSE would be reduced. However, results from Chapter 3 support the hypothesis that measured cardiac mechanics from standard MRI do not agree with, and thus cannot be used in place of, measurements from DENSE. Imaging the thin RV wall with its complex contraction pattern requires both three-dimensional (3D) measures of myocardial motion and higher resolution imaging. Results from Chapter 4 support the hypothesis that a lower displacement-encoding frequency can be used to allow for easier processing of 3D DENSE images. Results from Chapter 5 support the hypothesis that images with higher resolution (decreased blurring) can be achieved by using more spiral interleaves during the DENSE image acquisition. Finally, processing DENSE images to yield measures of cardiac mechanics in the LV is relatively simple due to the LV’s mostly cylindrical geometry. Results from Chapter 6 support the hypothesis that a local coordinate system can be adapted to the geometry of the RV to quantify mechanics in an equivalent manner as the LV. In summary, cardiac mechanics can now be quantified throughout the left and right ventricles using DENSE cardiac MRI.