OBJECTIVE: Ocular function is fundamental for environmental adaptation and survival capacity. Growth factors are necessary for a mature eyeball, needed for adequate vision. However, the consequences of the deficiency of circulating growth hormone (GH) and its effector insulin-like growth factor I (IGF-I) on the physical aspects of the human eye are still debated. A model of untreated isolated GH deficiency (IGHD), with low but measurable serum GH, may clarify this issue. The aim of this study was to assess the ocular aspects of adult IGHD individuals who have never received GH therapy. DESIGN: Cross sectional study. METHODS: Setting University Hospital, Federal University of Sergipe, Brazil. Patients: Twenty-five adult (13 males, mean age 50.1 years, range 26 to 70 years old) IGHD subjects homozygous for a null mutation (c.57+1G>A) in the GHRH receptor gene, and 28 (15 males, mean age 51.1 years, range 26 to 67 years old) controls were submitted to an endocrine and ophthalmological assessment. Forty-six IGHD and 50 control eyes were studied. Main outcome measures: Visual acuity, intraocular pressure (IOP), refraction (spherical equivalent), ocular axial length (AL), anterior chamber depth (ACD),lens thickness (LT), vitreous depth (VD), mean corneal curvature (CC) and central corneal thickness (CCT). RESULTS: IGHD subjects exhibited unmeasurable serum IGF-I levels, similar visual acuity, intraocular pressure and LT, higher values of spherical equivalent and CC, and lower measures of AL, ACD, VD and CCT in comparison to controls, but within their respective normal ranges. While mean stature in IGHD group was 78 % of the control group, mean head circumference was 92 % and axial AL was 96 %. CONCLUSIONS: These observations suggest mild ocular effects in adult subjects with severe IGF-I deficiency due to non-treated IGHD. / OBJETIVO: A função ocular é fundamental para a adaptação ambiental e a capacidade de sobrevivência. Fatores de crescimento são julgados necessáriospara alcançar um globo ocular maduro, e conseqüente visão adequada. No entanto, as consequências da deficiência isoladadohormônio de crescimento circulante (GH) edo seu efetor, o fator de crescimento semelhante à insulina I (IGF-I) nos aspectos físicos do olho humano ainda são debatidas. Um modelo de deficiência isolada de GH não tratada (DIGH) pode esclarecer esta questão. O objetivo deste estudo foi avaliar os aspectos físicos do globo ocular de indivíduos adultos com DIGH que nunca receberam terapia com GH. DESENHO: Estudo transversal. MÉTODOS: Ambiente: Hospital Universitário, Universidade Federal de Sergipe, Brasil. Pacientes: 25 indivíduosadultos (13 homens,com média de idade de 50,1 anos, entre 26 e 70 anos), com DIGH homozigotos para uma mutação nula (c.57 + 1G> A) no gene do receptorGHRH do grupo DIGH e 28 controles (15 homens, com média de idade de 51,1 anos, entre 26 e 67 anos), pareados, foram submetidos à avaliação endócrina e oftalmológica. Principais medidas: acuidade visual(AV), pressão intraocular(PIO),refração (equivalente esférico, EE), comprimento axial ocular (CA), profundidade da câmara anterior(PCA), medida da espessura do cristalino(EC), profundidade do vítreo(PV), curvatura corneana média(CCM) e espessura central corneana(ECC). RESULTADOS:Indivíduos com DIGH apresentaram IGF-I sérico não mensurável, similarAV, PIO e EC, valores mais altos doEEe CCM, e menores valores do CA, PCA, PV e ECC em comparação com os controles, mas dentro das respectivas faixas normais. Enquanto a estaturamédia no grupo DIGH foi de 78% do grupo de controle, a média da circunferência da cabeça foi de 92% e a média docomprimento axial foi de 96%. CONCLUSÃO: Essas observações sugerem efeitos oculares discretosem indivíduos adultos com grave deficiência de IGF-I devido à DIGH não tratada.

Les tessellations, aussi appelées mosaïques, permettent de modéliser de nombreuses structures, comme des assemblages de cellules en biologie ou de grains en science des matériaux. La tessellation aléatoire la plus connue est le diagramme de Voronoï qui à partir d'un ensemble de points, appelés germes, partitionne le plan. L'approche innovante de cette thèse est d'utiliser des champs aléatoires gaussiens pour générer des germes et des distances aléatoires, qui vont permettre de simuler une grande variété de tessellations en termes de formes et de tailles des cellules.Pour connaître les propriétés des tessellations simulées à partir de champs aléatoires gaussiens, celles-ci vont être caractérisées et comparées à d'autres tessellations. Tout d'abord par une approche ponctuelle en étudiant les germes, dont leur distribution spatiale. Puis par une approche par région, en étudiant la géométrie et la morphométrie des cellules.L'endothélium cornéen humain est une monocouche de cellules formant un pavage hexagonal régulier à la naissance, et perdant de sa régularité ensuite. La qualité du greffon cornéen est donnée par certaines observations, comme la densité, l'homogénéité de la forme et des tailles des cellules endothéliales.L'évolution avec l'âge de cette mosaïque cornéenne va être caractérisée à partir d’une base d’images de l’endothélium. L'originalité est ensuite d'effectuer une estimation de l'âge d’un endothélium à partir des différentes mesures permettant de caractériser les tessellations, et enfin de mettre en place une méthode prometteuse afin de savoir si une cornée a une évolution normale. / Tessellations, also called mosaics, are used to model many structures, for example cellular arrangements in biology or grains in material science. The most known tessellation is the Voronoï diagram which partitions the space from a set of points, called germs. The innovative approach of this thesis is to use Gaussian random fields to generate germs and random distances. The use of random fields allows to simulate a great variety of tessellations in terms of cells forms and sizes.To study the properties of each type of tessellation, they are characterized: first, by studying the germs, including their spatial distribution, and then by analyzing the cells geometry and morphometry. These tessellations are also compared to other known tessellations.The human corneal endothelium is a mono-layer of cells forming a regular hexagonal mosaic at birth, and losing his regularity later. The corneal graft quality is given by some observations made on the endothelial mosaic (cells density, the homogeneity of cells sizes and shapes).A database of endothelium images allows to characterize the evolution with age of the corneal mosaic. The originality is to estimate the age of an endothelium based on the measures computed to characterize the tessellations, and finally to set up a promising method to evaluate if a corneal evolution is normal.

In this work is describe anatomy and physiology of the cornea. The following are the primary non-inflamatory degeneration of the cornea. Then describe the physical principles diagnostic devices for cornea – keratometer, pachymeter, Michelson interferometr and optical coherence tomography (OCT). At the end of the theoretical introduction is describes the principle of laser correction surgery – LASIK. The practical part is divided into two main objectives. The first task is propose an algorithm for automatic detection of corneal surface and then calculation of corneal thickness and size of the chamber angle in Matlab. The aim of the second task is image flap analysis for boundary detection.

In dieser Arbeit wurden Methoden entwickelt und verglichen, um aus Corneoskleralringen langzeitorgankonservierter Hornhäute und intakten, kryokonservierten Amnionmembranen Limbusepithel-Amnion-Transplantate herzustellen. Als erfolgreichste Kultivierungsmethode stellte sich hierbei signifikant die Explantat-Technik mit nach unten gerichtetem Limbusepithel heraus. Hier konnte eine Auswachsrate von 42 % erzielt werden. Es wurde weiterhin gezeigt, dass das ausgewachsene, mehrschichtige Limbusepithel proliferationsfähige TACs (Transient Amplifying Cells) enthält. Weiterhin konnten mittels Regressionsanalyse signifikante Zusammenhänge zwischen Spenderalter, Post-mortem-Zeit, Organkultur-Dauer und der Auswachsrate beschrieben werden. Kurzgefasst wurde die Vermutung bestätigt, dass jede Verlängerung der unterschiedlichen Zeiten eine Verringerung der Auswachsrate zur Folge hat. Die hergestellten Limbusepithel-Amnion-Transplantate könnten für Patienten mit Limbusstammzellinsuffizienz unterschiedlicher Genese verwendet werden.

Cette thèse cherche à examiner les conditions optimales dans lesquelles les surfaces cornéennes antérieures peuvent être efficacement pré-traitées, classifiées et prédites en utilisant des techniques de modélisation géométriques (MG) et d’apprentissage automatiques (AU). La première étude (Chapitre 2) examine les conditions dans lesquelles la modélisation géométrique peut être utilisée pour réduire la dimensionnalité des données utilisées dans un projet d’apprentissage automatique. Quatre modèles géométriques ont été testés pour leur précision et leur rapidité de traitement : deux modèles polynomiaux (P) – polynômes de Zernike (PZ) et harmoniques sphériques (PHS) – et deux modèles de fonctions rationnelles (R) : fonctions rationnelles de Zernike (RZ) et fonctions rationnelles d’harmoniques sphériques (RSH). Il est connu que les modèles PHS et RZ sont plus précis que les modèles PZ pour un même nombre de coefficients (J), mais on ignore si les modèles PHS performent mieux que les modèles RZ, et si, de manière plus générale, les modèles SH sont plus précis que les modèles R, ou l’inverse. Et prenant en compte leur temps de traitement, est-ce que les modèles les plus précis demeurent les plus avantageux? Considérant des valeurs de J (nombre de coefficients du modèle) relativement basses pour respecter les contraintes de dimensionnalité propres aux taches d’apprentissage automatique, nous avons établi que les modèles HS (PHS et RHS) étaient tous deux plus précis que les modèles Z correspondants (PZ et RR), et que l’avantage de précision conféré par les modèles HS était plus important que celui octroyé par les modèles R. Par ailleurs, les courbes de temps de traitement en fonction de J démontrent qu’alors que les modèles P sont traités en temps quasi-linéaires, les modèles R le sont en temps polynomiaux. Ainsi, le modèle SHR est le plus précis, mais aussi le plus lent (un problème qui peut en partie être remédié en appliquant une procédure de pré-optimisation). Le modèle ZP était de loin le plus rapide, et il demeure une option intéressante pour le développement de projets. SHP constitue le meilleur compromis entre la précision et la rapidité. La classification des cornées selon des paramètres cliniques a une longue tradition, mais la visualisation des effets moyens de ces paramètres sur la forme de la cornée par des cartes topographiques est plus récente. Dans la seconde étude (Chapitre 3), nous avons construit un atlas de cartes d’élévations moyennes pour différentes variables cliniques qui pourrait s’avérer utile pour l’évaluation et l’interprétation des données d’entrée (bases de données) et de sortie (prédictions, clusters, etc.) dans des tâches d’apprentissage automatique, entre autres. Une base de données constituée de plusieurs milliers de surfaces cornéennes antérieures normales enregistrées sous forme de matrices d’élévation de 101 by 101 points a d’abord été traitée par modélisation géométrique pour réduire sa dimensionnalité à un nombre de coefficients optimal dans une optique d’apprentissage automatique. Les surfaces ainsi modélisées ont été regroupées en fonction de variables cliniques de forme, de réfraction et de démographie. Puis, pour chaque groupe de chaque variable clinique, une surface moyenne a été calculée et représentée sous forme de carte d’élévations faisant référence à sa SMA (sphère la mieux ajustée). Après avoir validé la conformité de la base de donnée avec la littérature par des tests statistiques (ANOVA), l’atlas a été vérifié cliniquement en examinant si les transformations de formes cornéennes présentées dans les cartes pour chaque variable étaient conformes à la littérature. C’était le cas. Les applications possibles d’un tel atlas sont discutées. La troisième étude (Chapitre 4) traite de la classification non-supervisée (clustering) de surfaces cornéennes antérieures normales. Le clustering cornéen un domaine récent en ophtalmologie. La plupart des études font appel aux techniques d’extraction des caractéristiques pour réduire la dimensionnalité de la base de données cornéennes. Le but est généralement d’automatiser le processus de diagnostique cornéen, en particulier en ce qui a trait à la distinction entre les cornées normales et les cornées irrégulières (kératocones, Fuch, etc.), et dans certains cas, de distinguer différentes sous-classes de cornées irrégulières. L’étude de clustering proposée ici se concentre plutôt sur les cornées normales afin de mettre en relief leurs regroupements naturels. Elle a recours à la modélisation géométrique pour réduire la dimensionnalité de la base de données, utilisant des polynômes de Zernike, connus pour leur interprétativité transparente (chaque terme polynomial est associé à une caractéristique cornéenne particulière) et leur bonne précision pour les cornées normales. Des méthodes de différents types ont été testées lors de prétests (méthodes de clustering dur (hard) ou souple (soft), linéaires or non-linéaires. Ces méthodes ont été testées sur des surfaces modélisées naturelles (non-normalisées) ou normalisées avec ou sans traitement d’extraction de traits, à l’aide de différents outils d’évaluation (scores de séparabilité et d’homogénéité, représentations par cluster des coefficients de modélisation et des surfaces modélisées, comparaisons statistiques des clusters sur différents paramètres cliniques). Les résultats obtenus par la meilleure méthode identifiée, k-means sans extraction de traits, montrent que les clusters produits à partir de surfaces cornéennes naturelles se distinguent essentiellement en fonction de la courbure de la cornée, alors que ceux produits à partir de surfaces normalisées se distinguent en fonction de l’axe cornéen. La dernière étude présentée dans cette thèse (Chapitre 5) explore différentes techniques d’apprentissage automatique pour prédire la forme de la cornée à partir de données cliniques. La base de données cornéennes a d’abord été traitée par modélisation géométrique (polynômes de Zernike) pour réduire sa dimensionnalité à de courts vecteurs de 12 à 20 coefficients, une fourchette de valeurs potentiellement optimales pour effectuer de bonnes prédictions selon des prétests. Différentes méthodes de régression non-linéaires, tirées de la bibliothèque scikit-learn, ont été testées, incluant gradient boosting, Gaussian process, kernel ridge, random forest, k-nearest neighbors, bagging, et multi-layer perceptron. Les prédicteurs proviennent des variables cliniques disponibles dans la base de données, incluant des variables géométriques (diamètre horizontal de la cornée, profondeur de la chambre cornéenne, côté de l’œil), des variables de réfraction (cylindre, sphère et axe) et des variables démographiques (âge, genre). Un test de régression a été effectué pour chaque modèle de régression, défini comme la sélection d’une des 256 combinaisons possibles de variables cliniques (les prédicteurs), d’une méthode de régression, et d’un vecteur de coefficients de Zernike d’une certaine taille (entre 12 et 20 coefficients, les cibles). Tous les modèles de régression testés ont été évalués à l’aide de score de RMSE établissant la distance entre les surfaces cornéennes prédites (les prédictions) et vraies (les topographies corn¬éennes brutes). Les meilleurs d’entre eux ont été validés sur l’ensemble de données randomisé 20 fois pour déterminer avec plus de précision lequel d’entre eux est le plus performant. Il s’agit de gradient boosting utilisant toutes les variables cliniques comme prédicteurs et 16 coefficients de Zernike comme cibles. Les prédictions de ce modèle ont été évaluées qualitativement à l’aide d’un atlas de cartes d’élévations moyennes élaborées à partir des variables cliniques ayant servi de prédicteurs, qui permet de visualiser les transformations moyennes d’en groupe à l’autre pour chaque variables. Cet atlas a permis d’établir que les cornées prédites moyennes sont remarquablement similaires aux vraies cornées moyennes pour toutes les variables cliniques à l’étude. / This thesis aims to investigate the best conditions in which the anterior corneal surface of normal corneas can be preprocessed, classified and predicted using geometric modeling (GM) and machine learning (ML) techniques. The focus is on the anterior corneal surface, which is the main responsible of the refractive power of the cornea. Dealing with preprocessing, the first study (Chapter 2) examines the conditions in which GM can best be applied to reduce the dimensionality of a dataset of corneal surfaces to be used in ML projects. Four types of geometric models of corneal shape were tested regarding their accuracy and processing time: two polynomial (P) models – Zernike polynomial (ZP) and spherical harmonic polynomial (SHP) models – and two corresponding rational function (R) models – Zernike rational function (ZR) and spherical harmonic rational function (SHR) models. SHP and ZR are both known to be more accurate than ZP as corneal shape models for the same number of coefficients, but which type of model is the most accurate between SHP and ZR? And is an SHR model, which is both an SH model and an R model, even more accurate? Also, does modeling accuracy comes at the cost of the processing time, an important issue for testing large datasets as required in ML projects? Focusing on low J values (number of model coefficients) to address these issues in consideration of dimensionality constraints that apply in ML tasks, it was found, based on a number of evaluation tools, that SH models were both more accurate than their Z counterparts, that R models were both more accurate than their P counterparts and that the SH advantage was more important than the R advantage. Processing time curves as a function of J showed that P models were processed in quasilinear time, R models in polynomial time, and that Z models were fastest than SH models. Therefore, while SHR was the most accurate geometric model, it was the slowest (a problem that can partly be remedied by applying a preoptimization procedure). ZP was the fastest model, and with normal corneas, it remains an interesting option for testing and development, especially for clustering tasks due to its transparent interpretability. The best compromise between accuracy and speed for ML preprocessing is SHP. The classification of corneal shapes with clinical parameters has a long tradition, but the visualization of their effects on the corneal shape with group maps (average elevation maps, standard deviation maps, average difference maps, etc.) is relatively recent. In the second study (Chapter 3), we constructed an atlas of average elevation maps for different clinical variables (including geometric, refraction and demographic variables) that can be instrumental in the evaluation of ML task inputs (datasets) and outputs (predictions, clusters, etc.). A large dataset of normal adult anterior corneal surface topographies recorded in the form of 101×101 elevation matrices was first preprocessed by geometric modeling to reduce the dimensionality of the dataset to a small number of Zernike coefficients found to be optimal for ML tasks. The modeled corneal surfaces of the dataset were then grouped in accordance with the clinical variables available in the dataset transformed into categorical variables. An average elevation map was constructed for each group of corneal surfaces of each clinical variable in their natural (non-normalized) state and in their normalized state by averaging their modeling coefficients to get an average surface and by representing this average surface in reference to the best-fit sphere in a topographic elevation map. To validate the atlas thus constructed in both its natural and normalized modalities, ANOVA tests were conducted for each clinical variable of the dataset to verify their statistical consistency with the literature before verifying whether the corneal shape transformations displayed in the maps were themselves visually consistent. This was the case. The possible uses of such an atlas are discussed. The third study (Chapter 4) is concerned with the use of a dataset of geometrically modeled corneal surfaces in an ML task of clustering. The unsupervised classification of corneal surfaces is recent in ophthalmology. Most of the few existing studies on corneal clustering resort to feature extraction (as opposed to geometric modeling) to achieve the dimensionality reduction of the dataset. The goal is usually to automate the process of corneal diagnosis, for instance by distinguishing irregular corneal surfaces (keratoconus, Fuch, etc.) from normal surfaces and, in some cases, by classifying irregular surfaces into subtypes. Complementary to these corneal clustering studies, the proposed study resorts mainly to geometric modeling to achieve dimensionality reduction and focuses on normal adult corneas in an attempt to identify their natural groupings, possibly in combination with feature extraction methods. Geometric modeling was based on Zernike polynomials, known for their interpretative transparency and sufficiently accurate for normal corneas. Different types of clustering methods were evaluated in pretests to identify the most effective at producing neatly delimitated clusters that are clearly interpretable. Their evaluation was based on clustering scores (to identify the best number of clusters), polar charts and scatter plots (to visualize the modeling coefficients involved in each cluster), average elevation maps and average profile cuts (to visualize the average corneal surface of each cluster), and statistical cluster comparisons on different clinical parameters (to validate the findings in reference to the clinical literature). K-means, applied to geometrically modeled surfaces without feature extraction, produced the best clusters, both for natural and normalized surfaces. While the clusters produced with natural corneal surfaces were based on the corneal curvature, those produced with normalized surfaces were based on the corneal axis. In each case, the best number of clusters was four. The importance of curvature and axis as grouping criteria in corneal data distribution is discussed. The fourth study presented in this thesis (Chapter 5) explores the ML paradigm to verify whether accurate predictions of normal corneal shapes can be made from clinical data, and how. The database of normal adult corneal surfaces was first preprocessed by geometric modeling to reduce its dimensionality into short vectors of 12 to 20 Zernike coefficients, found to be in the range of appropriate numbers to achieve optimal predictions. The nonlinear regression methods examined from the scikit-learn library were gradient boosting, Gaussian process, kernel ridge, random forest, k-nearest neighbors, bagging, and multilayer perceptron. The predictors were based on the clinical variables available in the database, including geometric variables (best-fit sphere radius, white-towhite diameter, anterior chamber depth, corneal side), refraction variables (sphere, cylinder, axis) and demographic variables (age, gender). Each possible combination of regression method, set of clinical variables (used as predictors) and number of Zernike coefficients (used as targets) defined a regression model in a prediction test. All the regression models were evaluated based on their mean RMSE score (establishing the distance between the predicted corneal surfaces and the raw topographic true surfaces). The best model identified was further qualitatively assessed based on an atlas of predicted and true average elevation maps by which the predicted surfaces could be visually compared to the true surfaces on each of the clinical variables used as predictors. It was found that the best regression model was gradient boosting using all available clinical variables as predictors and 16 Zernike coefficients as targets. The most explicative predictor was the best-fit sphere radius, followed by the side and refractive variables. The average elevation maps of the true anterior corneal surfaces and the predicted surfaces based on this model were remarkably similar for each clinical variable.

The utilization of in vitro tests with a tiered testing strategy for detection of mild ocular irritants can reduce the use of animals for testing, provide mechanistic data on toxic effects, and reduce the uncertainty associated with dose selection for clinical trials. The first section of this thesis describes how in vitro methods can be used to improve the prediction of the toxicity of chemicals and ophthalmic products. The proper utilization of in vitro methods can accurately predict toxic threshold levels and reduce animal use in product development. Sections two, three and four describe the development of new sensitive in vitro methods for predicting ocular toxicity. Maintaining the barrier function of the cornea is critical for the prevention of the penetration of infections microorganisms and irritating chemicals into the eye. Chapter 2 describes the development of a method for assessing the effects of chemicals on tight junctions using a human corneal epithelial and canine kidney epithelial cell line. In Chapter 3 a method that uses a primary organ culture for assessing single instillation and multiple instillation toxic effects is described. The ScanTox system was shown to be an ideal system to monitor the toxic effects over time as multiple readings can be taken of treated bovine lenses using the nondestructive method of assessing for the lens optical quality. Confirmations of toxic effects were made with the utilization of the viability dye alamarBlue. Chapter 4 describes the development of sensitive in vitro assays for detecting ocular toxicity by measuring the effects of chemicals on the mitochondrial integrity of bovine cornea, bovine lens epithelium and corneal epithelial cells, using fluorescent dyes. The goal of this research was to develop an in vitro test battery that can be used to accurately predict the ocular toxicity of new chemicals and ophthalmic formulations. By comparing the toxicity seen in vivo animals and humans with the toxicity response in these new in vitro methods, it was demonstrated that these in vitro methods can be utilized in a tiered testing strategy in the development of new chemicals and ophthalmic formulations.

The utilization of in vitro tests with a tiered testing strategy for detection of mild ocular irritants can reduce the use of animals for testing, provide mechanistic data on toxic effects, and reduce the uncertainty associated with dose selection for clinical trials. The first section of this thesis describes how in vitro methods can be used to improve the prediction of the toxicity of chemicals and ophthalmic products. The proper utilization of in vitro methods can accurately predict toxic threshold levels and reduce animal use in product development. Sections two, three and four describe the development of new sensitive in vitro methods for predicting ocular toxicity. Maintaining the barrier function of the cornea is critical for the prevention of the penetration of infections microorganisms and irritating chemicals into the eye. Chapter 2 describes the development of a method for assessing the effects of chemicals on tight junctions using a human corneal epithelial and canine kidney epithelial cell line. In Chapter 3 a method that uses a primary organ culture for assessing single instillation and multiple instillation toxic effects is described. The ScanTox system was shown to be an ideal system to monitor the toxic effects over time as multiple readings can be taken of treated bovine lenses using the nondestructive method of assessing for the lens optical quality. Confirmations of toxic effects were made with the utilization of the viability dye alamarBlue. Chapter 4 describes the development of sensitive in vitro assays for detecting ocular toxicity by measuring the effects of chemicals on the mitochondrial integrity of bovine cornea, bovine lens epithelium and corneal epithelial cells, using fluorescent dyes. The goal of this research was to develop an in vitro test battery that can be used to accurately predict the ocular toxicity of new chemicals and ophthalmic formulations. By comparing the toxicity seen in vivo animals and humans with the toxicity response in these new in vitro methods, it was demonstrated that these in vitro methods can be utilized in a tiered testing strategy in the development of new chemicals and ophthalmic formulations.