The use of lasers for diagnosis and treatment in medical and cosmetic applications is increasing worldwide. Not all of these modalities are superficial and many require laser light to penetrate some distance into the tissue or skin to reach the treatment site. Human skin is highly scattering for light in the visible and near infrared wavelength regions, with a consequent reduction of the fluence rate. Melanin, which occurs in the epidermis of the skin, acts as an absorber in these wavelength regions and further reduces the fluence rate of light that penetrates through the epidermis to a treatment site. In vivo fluence rate measurements are not viable, but validated and calibrated computer models may play a role in predicting the fluence rate reaching the treatment site. A layered planar computer model to predict laser fluence rate at some depth into skin was developed in a commercial raytracing environment (ASAP). The model describes the properties of various skin layers and accounts for both the absorption and scattering taking place in the skin. The model was validated with optical measurements on skin-simulating phantoms in both reflectance and transmission configurations. It was shown that a planar epidermal/dermal interface is adequate for simulation purposes. In the near infrared wavelength region (676 nm), melanin (consisting of eumelanin and pheomelanin) is the major absorber of light in the epidermis. The epidermal absorption coefficient is one of the required input parameters for the computer model. The range of absorption coefficients expected for typical South African skin phototypes (ranging from photo-sensitive light skin, phototype I on the Fitzpatrick scale, to the photo-insensitive darker skin phototype V) was not available. Non-invasive diffuse reflectance spectroscopy measurements were done on 30 volunteers to establish the expected range of absorption coefficients. In the analysis it became apparent that the contributions of the eumelanin and pheomelanin must be accounted for separately, specifically for the Asian volunteers. This is a new concept that was introduced in the diffuse reflectance probe analysis. These absorption coefficient measurements were the first to be done on the expected range of skin phototypes for the South African population. Other authors dealing with diffuse reflectance probe analysis only account for the dominant eumelanin. Both the epidermal absorption coefficient and thickness are important in the prediction of the fluence rate loss. The computer model was used to evaluate the effect of the epidermal absorption coefficient (a parameter dictated by an individual’s skin phototype) and the epidermal thickness on the fluence rate loss through the skin. The epidermal absorption is strongly wavelength dependent with the higher absorption at the shorter wavelengths. In the computer model a longer wavelength of 676 nm (typical for a photodynamic treatment (PDT) of cancer) was used. For the darker skin phototypes (V) only about 30% of the initial laser fluence rate reached a depth of 200 ìm into the skin (just into the dermis). For the PDT application, results from the computer model indicated that treatment times need to be increased by as much as 50% for very dark skin phototypes when compared to that of very light phototypes. / Thesis (PhD)--University of Pretoria, 2012. / Physics / unrestricted

No description available.

This study investigates the possibility of using a time-resolved Fluorescence and Diffuse Reflectance Spectroscopy (tr-FRS) system to define tumour surgical margins of invasive ducal carcinoma of breast. UV excitation light was used for the fluorescence component and data was collected from the 370-550 nm range. A broadband source was used for diffuse reflectance collection and the emitted response was in the 400-800 nm range. 40 matched pair cases were collected from patients undergoing breast conservation surgeries. Histological analysis was performed on each sample to determine the fat and tumour content within each normal and tumour sample respectively. Statistical analysis was performed on the optical data to reveal biochemical changes in the endogenous fluorophores collagen, reduced nicotinamide adenine dinucleotide (NADH), and flavin adenine dinucleotide (FAD) as well as changes in absorption and scattering properties attributed to variances in absorber concentrations and cell density respectively. Statistical significant differences in collagen, NADH, and FAD lifetimes, collagen, NADH, FAD and NADH/FAD intensity, diffuse reflectance and reduced scatter coefficient were observed between tumour and normal breast samples. These significant factors were used in Principle Component Analysis model construction and a binary classification scheme using Soft Independent Modeling of Class Analogy (SIMCA) was used as a classification tool to predict unknown breast samples as either normal or tumour with specificity of 60% and sensitivity slightly over 50%. / Thesis / Master of Science (MSc)

Biomedical optics is a rapidly expanding field of research focusing on the development of methods to detect, diagnose, and treat disease using light. While there are a myriad of optical systems that have been developed for biological tissue imaging, optical diagnostics, and optical therapeutics, all of these methods suffer severely limited penetration depths due to attenuation of light by tissue constituent chromophores, including cells, water, blood, and protein structures. Tissue optical clearing is a recent area of study within biomedical optics and photonics, where chemical agents have been used to alter tissue optical properties, reducing optical absorption and scattering and enabling light delivery to and collection from deeper tissue regions. However, there are concerns as to the safety and efficacy of these chemical clearing agents in vivo, especially in the skin, where the projective barrier function of the stratum corneum must be removed. Mechanical optical clearing is a recently developed technology which utilizes mechanical loading to reversibly modify light transport through soft tissues, and much of the work published on this technique has focused on applications in skin tissue. This clearing technique enables deeper light delivery into soft tissues but does not require use of exogenous chemicals, nor does it compromise the skin barrier function. While this clearing effect is thought to be resultant from interstitial water and blood transport, the underlying mechanism has not been concretely identified nor characterized. The hypothesis of this body of work was that interstitial transport of tissue chromophores (e.g. water and blood) causes intrinsic optical property changes, reduces tissue optical absorption and scattering, and improves light delivery in diagnostic applications. To test this hypothesis, we first developed a mathematical framework to simulate mechanical optical clearing, using both mechanical finite element models and optical Monte Carlo simulations. By directly simulating interstitial water transport in response to loading, data from mechanical simulations was combined with optical Monte Carlo simulations, which enabled prediction of light transmission measurements made during mechanical indentation experiments. We also investigated changes in optical properties during mechanical indentation using diffuse reflectance spectroscopy. These studies used controlled flat indentation by a fiberoptic probe to dynamically measure intrinsic optical properties as they changed over time. Finally, we apply mechanical optical clearing principles to functional near-infrared spectroscopy for neuroimaging. By building a prototypical mechanical optical clearing device for measuring cerebral hemodynamics, we demonstrated that mechanical optical clearing devices modify measured cerebral hemodynamic signals in human subjects, improving signal quality. / Ph. D.

Thesis (MScEng (Process Engineering))--University of Stellenbosch, 2010. / Thesis submitted in partial fulfilment of the requirements for the degree of MASTER OF SCIENCE IN ENGINEERING (MINERAL PROCESSING) in the Department of Processing Engineering at the University of Stellenbosch / ENGLISH ABSTRACT: This work evaluates the use of inverse least squares (ILS) and classical least squares (CLS) models for calibration of a diffuse reflectance spectrophotometer for on-line monitoring of the aqueous phase in a flotation cells. Both models use a Beer's law for the quantification of the metals. The formulated statistical models are compared to a proprietary Blue Cube model in terms of prediction ability to determine the potential applicability of the models. A diffuse reflectance spectrophotometry was used for simultaneous analysis of copper (Cu), cobalt (Co) and zinc (Zn) in the solutions. The laboratory set-up of Blue Cube instrument was used for the experimental analysis. The concentrations and matrix compositions of the samples are simulated according to Skorpion zinc mine plant conditions. The calibration samples were prepared using a simplex-centroid mixture design with the triplicates of the centroid run. The unknown or test samples were prepared randomly within the same concentration of the calibration samples. The effects of temperature and nickel concentration on absorption of the metals were evaluated in the following range, 20 - 80 °C and 125 - 400 ppm, respectively. The statistical models (ILS and CLS) were calibrated from visible and near infrared (VNIR) spectra data of the calibration samples. A modified Beer's method was used as a preprocessing technique to convert the raw data into absorbance values. The manual wavelength selection procedure was used to select the wavelengths to be used in both models. The quality of the models was evaluated based on Rª and % root mean squared error (RMSE) values with 0.90 and 10% used as the guideline for the respective statistical parameters. Both ILS and CLS models showed good results for all three metals (Cu, Co and Zn) during their calibration steps. It was further shown that both models give worse predictions for Zn as compared to other metals due to its low relative intensity in the mixture. The derivative orders of absorbance spectra that were used to enhance the prediction results of Zn had no positive effect but they rather lowered accuracy of predictions. An increase in temperature was found to increase the intensities of the absorption spectra of all the metals while an increase in nickel concentration decreases the prediction ability of model. The developed statistical models were compared to a Blue Cube model in terms of prediction ability using analysis of variance (ANOVA) test. The ANOVA results revealed that there is no statistical difference between the developed models and Blue Cube model since the F-values for all the metals were below the critical F-value. Furthermore, the partial least squares (PLS) model shows an increased accuracy results for prediction of zinc metal as compared to both the ILS and CLS models. Finally, good comparisons of the statistical models results with atomic absorption spectroscopy (AAS) analyses were establish for the unknown samples. The study demonstrates that chemometric models (ILS and CLS) developed here can be used for quantification of several metals in real hydrometallurgical solutions as samples were simulated according to a plant conditions. However, in order to have confidence in the results of the models, a factorial-mixture design must be used to study the effect of temperature and nickel concentration. Moreover the models must be further tested and validated on the real samples from a plant. / AFRIKAANSE OPSOMMING: Hierdie werkstuk evalueer die gebruik van inverse kleinste kwadraatmetodes (IKK) en klassieke kleinste kwadraatmetodes (KKK) vir die kalibrasie van 'n diffuse reflektansiespektrofotometer vir die aanlyn monitering van die waterige fase in flottasieselle. Beer se wet word vir die kwantifisering van metale vir albei modelle gebruik. Die omskrewe data-gebaseerde modelle is op grond van voorspellingsvermoë vergelyk met'n. Blue Cube model, sodat die moontlike toepaslikheid van hierdie modelle bepaal kan word. 'n Diffuse reflectantie spektrofotometrie is ingespan vir die gelyktydige analise van koper (Cu), kobalt (Co) en sink (Zn) in oplossing. Eksperimentele analises is met behulp van 'n laboratoriumopstelling met 'n Blue Cube instrument uitgevoer. Die konsentrasies en matriks-samestellings van monsters is gesimuleer om Skorpion sinkmyn aanlegkondisies na te boots. Kalibrasie monsters is voorberei volgens . simpleks-sentroïed mengselontwerp met drievoudige sentroïede lopies. Onbekende (toets) monsters is ewekansig voorberei binne dieselfde konsentrasie spesifikasies as die kalibrasie monsters. Die invloed van temperatuur en nikkelkonsenstrasie op die absorpsie van die metale is in die bestek van 20 - 80 °C en 125 - 400 dpm, onderskeidelik, bepaal. Die data-gebaseerde modelle (IKK en KKK) is met sigbare en naby infrarooi (SNIR) spektra data van die kalibrasie monsters gekalibreer. 'n Gewysigde Beer metode is vir data voorbereiding benut om rou data na absorbansie waardes om te skakel. Die handgolflengte-seleksieprosedure is vir beide modelle gebruik om die golflengtes te kies. Die kwaliteit van die modelle is op grond van Rª en % wortel gemiddelde kwadratiese fout (WGKF) geevalueer, met waardes van 0.90 en 10% (onderskeidelik) as riglyne vir hierdie statistiese parameters. Beide IKK en KKK modelle het vir hul kalibrasie stappe vir al drie metale (Cu, Co en Zn) goeie resultate getoon. Dit is verder getoon dat albei modelle die slegste voorspellings lewer vir Zn (vergeleke met die ander metale) as gevolg van Zn se lae relatiewe intensiteit in die mengsel. Afgeleide ordes van absorbansie spektra is gebruik om die Zn voorspellings te versterk, maar het geen positiewe effek gehad nie; inteendeel, voorspellingakkuraatheid is verlaag. ʼn Verhoging in temperatuur het die intensiteite van die absorpsie spektra van alle metale verhoog, terwyl ʼn verhoging in nikkelkonsentrasie die voorspellingakkuraatheid van die modelle verlaag het. Die ontwikkelde data-gebaseerde modelle is met ʼn Blue Cube model vergelyk in terme van voorspellingsvermoë met behulp van variansie-analise (ANOVA). Die ANOVA resultate toon dat daar geen statistiese verskil tussen die ontwikkelde modelle en die Blue Cube model is nie, aangesien die F-waardes vir al die metale onder die kritiese F-waarde is. Die gedeeltelike kleinste kwadraatmodel (GKK) toon verder verhoogde voorspellingakkuraat-heid vir sinkmetaal tenoor beide die IKK en KKK modelle. Ten slotte, goeie ooreenstemming van die data-gebaseerde modelresultate met atoomabsorpsie spektroskopie (AAS) analise is vir die onbekende monsters gevind. Hierdie werkstuk toon dat die chemometriese modelle (IKK en KKK) wat hier ontwikkel is, gebruik kan word vir die kwantifisering van verskeie metale in werklike hidrometallurgiese oplossings, aangesien monsters gesimuleer is volgens aanlegkondisies. Om egter verdere vertroue te hê in die modelresultate, sal ʼn faktoriaal-mengselontwerp toegepas moet word om die effek van temperatuur en nikkelkonsentrasie te ondersoek. Voorts moet die modelle verder getoets en gevalideer word op werklike monsters van ʼn aanleg.

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal.

Les travaux effectués au cours de cette thèse concernent le développement d’un instrument à faible coût et porté sur la personne permettant le suivi quantitatif des paramètres physiologiques de la peau in vivo et de manière non invasive. L’instrument est fondé sur la technique de Spectroscopie de Réflectance Diffuse résolue spatialement (srDRS). Cette technique fournit une quantification absolue des propriétés optiques endogènes d’absorption et de diffusion du tissu sondé et possède un potentiel pour la caractérisation de ces propriétés en couches de la peau.Afin de maximiser ce potentiel, notre approche repose sur l’utilisation d’un capteur matriciel placé en contact avec le tissu et permettant l’imagerie de réflectance diffuse à haute résolution spatiale. Les travaux présentés ici comprennent la spécification et la validation d’une architecture innovante permettant la mise en œuvre de l’approche proposée, l’implémentation d’un système porté sur la personne et bas coût basé sur cette architecture et l’évaluation des performances de ce système au travers d’expérimentations à la fois sur fantômes de peau et in vivo. Les résultats obtenus valident le potentiel de l’instrument développé pour le suivi quantitatif et non-invasif des propriétés de la peau. L’approche proposée est prometteuse pour l’analyse de milieux en couches tels que la peau et ouvre la voie au développement d’une nouvelle génération d’instruments portés sur la personne et bas coûts pour le suivi en continu des propriétés optiques des tissus. / This work presents the development of a low-cost, wearable instrument for quantitative monitoring of skin physiological parameters toward non-invasive diagnostics in vivo. The instrument is based on the spatially resolved Diffuse Reflectance Spectroscopy (srDRS) technique, which provides absolute quantification of absorption and scattering endogenous properties of the probed tissue volume with a potential to discriminate between properties of individual skin layers. In the developed instrument, this potential is maximized by the use of a multi-pixel image sensor to perform contact, high resolution imaging of the diffuse reflectance. This study comprises the specification and validation of a novel srDRS system architecture based on the proposed approach, the implementation of this architecture into a low-cost, wearable device and the evaluation of the device performance both on tissue-simulating phantoms and in vivo. Results validate the potential of the instrument for the non-invasive, quantitative monitoring of tissue properties. The described approach is promising for addressing the analysis of layered tissue suchas skin and paves the way for the development of low-cost, wearable devices for continuous, passive monitoring of tissue optical properties.

Made available in DSpace on 2017-07-21T18:53:14Z (GMT). No. of bitstreams: 1 Elisangela Serenato.pdf: 1216828 bytes, checksum: 1e4a058b95c9b4cbdc1c0a22185ded54 (MD5) Previous issue date: 2010-02-25 / Fundação Araucária de Apoio ao Desenvolvimento Científico e Tecnológico do Paraná / Ricotta is a kind of fresh cheese, obtained by the precipitation of the proteins in the cheese whey. According to the current legislation, ricotta is framed on standards of identity and quality of low-fat cheeses, however, studies show a great variability on the centesimal composition. It justifies the necessity of establishing quality standards, and the development of methodologies that allow a fast and efficient control of the product. Besides it, conventional methodologies used to determine the centesimal composition of the ricotta, though they are part of the routine analysis in laboratories of quality control, they are onerous, time consuming and generate residues. In this sense, the objective of this study was to develop a method for the quantification of physical/chemical standards, using Near Infrared Diffuse Spectroscopy (NIRRS), associating to methods of multivariate calibration. For the construction of multivariate models (specially PLSR) it were used the media of concentration of acidity, carbohydrates, ashes, chlorides, fat, pH, protein and moisture, obtained by conventional methodologies (titration method, spectroscopic, muffle carbonization, titration, Gerber, potentiometric, Kjeldahl and gravimetric method, respectively), as well as data of the near infrared spectroscopy. It was collected spectra in duplicate, 33 spectra were used for the calibration phase, and the 5 remaining used to the external validation phase. The best results for fat, protein and moisture levels were obtained on the spectral region between 1100 to 2500 nm. The optimized model for determination of fat used the Multiplicative Scatter Correction (MSC), with 6 latent variable (VLs), acquiring correlation coefficients of Rcal= 0.968 and Rval= 0.936 allowing the quantification of fat with a medium prevision error (Er) of 6.37%. For the protein level, the best result was obtained using MSC and data centered on media (DCM). The model of regression, with 6 VLs, presented correlation coefficients of Rcal= 0.968 and Rval= 0.885, and determination of protein with Er of 5.95%. The best model for determination of moisture used normalization, with 4 VLs correlation coefficients of Rcal= 0.851 and Rval= 0.757 and allowing the quantification of moisture with and Er of 1.91%. It was not possible to build models for acidity, carbohydrates, ashes, chloride and pH parameters, presenting low values of Rcal and Rval, demonstrating the low capacity of forecasting even for samples that compose the calibration set through the proposed methodology. These results demonstrate the potential of multivariate models on determination of fat, protein and moisture levels on samples with complex matrices (ricotta) and also show the advantages of the association NIRRS-PLSR which allows a fast quality control with minimum manipulation of the sample. / A ricota é um tipo de queijo fresco, obtido pela precipitação das proteínas do soro do queijo. Segundo a legislação vigente, a ricota é enquadrada nos padrões de identidade e qualidade de queijos magros, no entanto, estudos demonstram a grande variabilidade na sua composição centesimal. Isto justifica a necessidade de estabelecimento de padrões de qualidade, e o desenvolvimento de metodologias que possibilitem um controle rápido e eficiente do produto. Além disso, as metodologias convencionais empregadas para a determinação da composição centesimal da ricota, embora façam parte das análises de rotina em laboratórios de controle de qualidade, são onerosas, demoradas e geram resíduos. Neste sentido, o objetivo deste estudo foi desenvolver um método para a quantificação dos parâmetros físico-químicos, utilizando-se espectroscopia no infravermelho próximo por reflectância difusa (NIRRS) associado a métodos de calibração multivariada. Para a construção dos modelos multivariados (principalmente PLSR) foram utilizadas as médias das concentrações de acidez, carboidratos, cinzas, cloretos, gordura, pH, proteína e umidade, obtidas pelas metodologias convencionais (método titulométrico, espectroscópico, carbonização em mufla, titulométrico, Gerber, potenciométrico, Kjeldahl e método gravimétrico, respectivamente), bem como, os dados de espectroscopia no infravermelho próximo. Foram coletados espectros em duplicata, sendo que 33 desses espectros foram utilizados para a fase de calibração e os 5 restantes utilizados para a fase de validação externa. O melhores resultados para os teores de gordura, proteína e umidade foram obtidos na região espectral entre 1100 a 2500 nm. O modelo otimizado para a determinação de gordura empregou a correção do espalhamento multiplicativo (MSC), com 6 variáveis latentes (VLs), obtendo-se coeficientes de correlação de Rcal= 0,968 e Rval= 0,936 possibilitando a quantificação de gordura com um erro médio de previsão (Er) de 6,37%. Para o teor de proteína, o melhor resultado foi obtido utilizando-se a MSC e dados centrados na média (DCM). O modelo de regressão, com 6 VLs, apresentou coeficientes de correlação de Rcal= 0,968 e Rval= 0,885, e determinação de proteína com Er de 5,95%. O melhor modelo para a determinação de umidade empregou a normalização, com 4 VLs, obtendo-se coeficientes de correlação de Rcal= 0,851 e Rval= 0,757 e possibilitando a quantificação de umidade com um Er de 1,91%. Não foi possível a construção de modelos para os parâmetros acidez, carboidratos, cinzas, cloretos e pH, apresentando baixos valores de Rcal e Rval, demonstrando a baixa capacidade de previsão mesmo para as amostras que compõem o conjunto de calibração através da metodologia proposta. Estes resultados além de demonstrarem o potencial dos modelos multivariados na determinação dos teores de gordura, proteína e umidade em amostras com matrizes complexas (ricota) evidenciam as vantagens da associação NIRRS-PLSR que permite um controle de qualidade rápido com uma manipulação mínima da amostra.

<p>To estimate the propagation of light in tissue-like optical phantoms (fat emulsions), this thesis utilized the diffuse reflectance spectroscopy in combination with Monte Carlo simulations. A method for determining the two-parametric Gegenbauer-kernal phase function was utilized in order to accurately describe the diffuse reflectance from poly-dispersive scattering optical phantoms with small source-detector separations. The method includes the spectral collimated transmission, spatially resolved diffuse reflectance spectra (SRDR) and the inverse technique of matching spectra from Monte Carlo simulations to those measured. An absolute calibration method using polystyrene micro-spheres was utilized to estimate the relation between simulated and measured SRDR intensities. The phase function parameters were comparable with previous studies and were able to model measured spectra with good accuracy. Significant differences between the phase functions for homogenized milk and the nutritive fat emulsions were found.</p><p> </p>

To estimate the propagation of light in tissue-like optical phantoms (fat emulsions), this thesis utilized the diffuse reflectance spectroscopy in combination with Monte Carlo simulations. A method for determining the two-parametric Gegenbauer-kernal phase function was utilized in order to accurately describe the diffuse reflectance from poly-dispersive scattering optical phantoms with small source-detector separations. The method includes the spectral collimated transmission, spatially resolved diffuse reflectance spectra (SRDR) and the inverse technique of matching spectra from Monte Carlo simulations to those measured. An absolute calibration method using polystyrene micro-spheres was utilized to estimate the relation between simulated and measured SRDR intensities. The phase function parameters were comparable with previous studies and were able to model measured spectra with good accuracy. Significant differences between the phase functions for homogenized milk and the nutritive fat emulsions were found.