Efeitos do dano muscular sobre indicadores neuromusculares e de aptidão aeróbia

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Efeito de métodos de desgaste com pontas diamantadas e da ressinterização sobre o limite de fadiga flexural de uma zircônia parcialmente estabilizada por ítria

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Response of mice connective tissue to intracanal dressings containing chlorhexidine

Substances containing chlorhexidine (CHX) have been studied as intracanal medicaments. The aim of the present study was to characterize the response of mouse subcutaneous connective tissue to CHX-containing medications by conventional optical microscopy. The tissue response was evaluated by implanting polyethylene tubes containing one of the substances evaluated: Calen paste + 0.5% CHX, Calen + 2% CHX, 2% CHX gel, and Calen paste (control). After experimental periods of 7, 21, and 63 days, the implants (n = 10) were removed along with the subcutaneous connective tissue. Tissue samples were subjected to histological processing, and sections were stained with hematoxylin and eosin. Qualitative and quantitative analyses of the number of inflammatory cells, blood vessels, and vascularized areas were performed. Results were analyzed by ANOVA and Tukey tests with the significance level set at 5%. We concluded that Calen + 0.5% CHX led to reparative tissue response in contrast with Calen + 2% CHX and 2% CHX gel, which induced persistent inflammatory response, pointing to the aggressive nature of this mixture. When Calen + 2% CHX and 2% CHX gel were compared, the latter induced more intense inflammatory response. Microsc. Res. Tech., 2012. (C) 2012 Wiley Periodicals, Inc.

Efficient ultrasonic signal processing techniques for aided medical diagnostics

Ultrasound imaging is widely used in medical diagnostics as it is the fastest, least invasive, and least expensive imaging modality. However, ultrasound images are intrinsically difficult to be interpreted. In this scenario, Computer Aided Detection (CAD) systems can be used to support physicians during diagnosis providing them a second opinion. This thesis discusses efficient ultrasound processing techniques for computer aided medical diagnostics, focusing on two major topics: (i) Ultrasound Tissue Characterization (UTC), aimed at characterizing and differentiating between healthy and diseased tissue; (ii) Ultrasound Image Segmentation (UIS), aimed at detecting the boundaries of anatomical structures to automatically measure organ dimensions and compute clinically relevant functional indices. Research on UTC produced a CAD tool for Prostate Cancer detection to improve the biopsy protocol. In particular, this thesis contributes with: (i) the development of a robust classification system; (ii) the exploitation of parallel computing on GPU for real-time performance; (iii) the introduction of both an innovative Semi-Supervised Learning algorithm and a novel supervised/semi-supervised learning scheme for CAD system training that improve system performance reducing data collection effort and avoiding collected data wasting. The tool provides physicians a risk map highlighting suspect tissue areas, allowing them to perform a lesion-directed biopsy. Clinical validation demonstrated the system validity as a diagnostic support tool and its effectiveness at reducing the number of biopsy cores requested for an accurate diagnosis. For UIS the research developed a heart disease diagnostic tool based on Real-Time 3D Echocardiography. Thesis contributions to this application are: (i) the development of an automated GPU based level-set segmentation framework for 3D images; (ii) the application of this framework to the myocardium segmentation. Experimental results showed the high efficiency and flexibility of the proposed framework. Its effectiveness as a tool for quantitative analysis of 3D cardiac morphology and function was demonstrated through clinical validation.

Studio e sviluppo di un metodo di detezione della camera atriale in ecografia intracardiaca

Il lavoro di tesi si è svolto in collaborazione con il laboratorio di elettrofisiologia, Unità Operativa di Cardiologia, Dipartimento Cardiovascolare, dell’ospedale “S. Maria delle Croci” di Ravenna, Azienda Unità Sanitaria Locale della Romagna, ed ha come obiettivo lo sviluppo di un metodo per l’individuazione dell’atrio sinistro in sequenze di immagini ecografiche intracardiache acquisite durante procedure di ablazione cardiaca transcatetere per il trattamento della fibrillazione atriale. La localizzazione della parete posteriore dell'atrio sinistro in immagini ecocardiografiche intracardiache risulta fondamentale qualora si voglia monitorare la posizione dell'esofago rispetto alla parete stessa per ridurre il rischio di formazione della fistola atrio esofagea. Le immagini derivanti da ecografia intracardiaca sono state acquisite durante la procedura di ablazione cardiaca ed esportate direttamente dall’ecografo in formato Audio Video Interleave (AVI). L’estrazione dei singoli frames è stata eseguita implementando un apposito programma in Matlab, ottenendo così il set di dati su cui implementare il metodo di individuazione della parete atriale. A causa dell’eccessivo rumore presente in alcuni set di dati all’interno della camera atriale, sono stati sviluppati due differenti metodi per il tracciamento automatico del contorno della parete dell’atrio sinistro. Il primo, utilizzato per le immagini più “pulite”, si basa sull’utilizzo del modello Chan-Vese, un metodo di segmentazione level-set region-based, mentre il secondo, efficace in presenza di rumore, sfrutta il metodo di clustering K-means. Entrambi i metodi prevedono l’individuazione automatica dell’atrio, senza che il clinico fornisca informazioni in merito alla posizione dello stesso, e l’utilizzo di operatori morfologici per l’eliminazione di regioni spurie. I risultati così ottenuti sono stati valutati qualitativamente, sovrapponendo il contorno individuato all'immagine ecografica e valutando la bontà del tracciamento. Inoltre per due set di dati, segmentati con i due diversi metodi, è stata eseguita una valutazione quantitativa confrontatoli con il risultato del tracciamento manuale eseguito dal clinico.

L'informazione di fase per la segmentazione volumetrica di dati ecocardiografici

L’imaging ad ultrasuoni è una tecnica di indagine utilizzata comunemente per molte applicazioni diagnostiche e terapeutiche. La tecnica ha numerosi vantaggi: non è invasiva, fornisce immagini in tempo reale e l’equipaggiamento necessario è facilmente trasportabile. Le immagini ottenute con questa tecnica hanno tuttavia basso rapporto segnale rumore a causa del basso contrasto e del rumore caratteristico delle immagini ad ultrasuoni, detto speckle noise. Una corretta segmentazione delle strutture anatomiche nelle immagini ad ultrasuoni è di fondamentale importanza in molte applicazioni mediche . Nella pratica clinica l’identificazione delle strutture anatomiche è in molti casi ancora ottenuta tramite tracciamento manuale dei contorni. Questo processo richiede molto tempo e produce risultati scarsamente riproducibili e legati all’esperienza del clinico che effettua l’operazione. In ambito cardiaco l’indagine ecocardiografica è alla base dello studio della morfologia e della funzione del miocardio. I sistemi ecocardiografici in grado di acquisire in tempo reale un dato volumetrico, da pochi anni disponibili per le applicazioni cliniche, hanno dimostrato la loro superiorità rispetto all’ecocardiografia bidimensionale e vengono considerati dalla comunità medica e scientifica, la tecnica di acquisizione che nel futuro prossimo sostituirà la risonanza magnetica cardiaca. Al fine di sfruttare appieno l’informazione volumetrica contenuta in questi dati, negli ultimi anni sono stati sviluppati numerosi metodi di segmentazione automatici o semiautomatici tesi alla valutazione della volumetria del ventricolo sinistro. La presente tesi descrive il progetto, lo sviluppo e la validazione di un metodo di segmentazione ventricolare quasi automatico 3D, ottenuto integrando la teoria dei modelli level-set e la teoria del segnale monogenico. Questo approccio permette di superare i limiti dovuti alla scarsa qualità delle immagini grazie alla sostituzione dell’informazione di intensità con l’informazione di fase, che contiene tutta l’informazione strutturale del segnale.

Automated cement segmentation in vertebroplasty

Vertebroplasty is a minimally invasive procedure with many benefits; however, the procedure is not without risks and potential complications, of which leakage of the cement out of the vertebral body and into the surrounding tissues is one of the most serious. Cement can leak into the spinal canal, venous system, soft tissues, lungs and intradiscal space, causing serious neurological complications, tissue necrosis or pulmonary embolism. We present a method for automatic segmentation and tracking of bone cement during vertebroplasty procedures, as a first step towards developing a warning system to avoid cement leakage outside the vertebral body. We show that by using active contours based on level sets the shape of the injected cement can be accurately detected. The model has been improved for segmentation as proposed in our previous work by including a term that restricts the level set function to the vertebral body. The method has been applied to a set of real intra-operative X-ray images and the results show that the algorithm can successfully detect different shapes with blurred and not well-defined boundaries, where the classical active contours segmentation is not applicable. The method has been positively evaluated by physicians.

GoCARB in the Context of an Artificial Pancreas

Background: In an artificial pancreas (AP), the meals are either manually announced or detected and their size estimated from the blood glucose level. Both methods have limitations, which result in suboptimal postprandial glucose control. The GoCARB system is designed to provide the carbohydrate content of meals and is presented within the AP framework. Method: The combined use of GoCARB with a control algorithm is assessed in a series of 12 computer simulations. The simulations are defined according to the type of the control (open or closed loop), the use or not-use of GoCARB and the diabetics’ skills in carbohydrate estimation. Results: For bad estimators without GoCARB, the percentage of the time spent in target range (70-180 mg/dl) during the postprandial period is 22.5% and 66.2% for open and closed loop, respectively. When the GoCARB is used, the corresponding percentages are 99.7% and 99.8%. In case of open loop, the time spent in severe hypoglycemic events (<50 mg/dl) is 33.6% without the GoCARB and is reduced to 0.0% when the GoCARB is used. In case of closed loop, the corresponding percentage is 1.4% without the GoCARB and is reduced to 0.0% with the GoCARB. Conclusion: The use of GoCARB improves the control of postprandial response and glucose profiles especially in the case of open loop. However, the most efficient regulation is achieved by the combined use of the control algorithm and the GoCARB.

Seaweed - epiphyte - mesograzer communities were tested for their responses to elevated seawater temperature and [CO2] in benthic mesocosms experiments across four consecutive seasons of one year in Kiel, Germany

Rising seawater temperature and CO2 concentrations (ocean acidification) represent two of the most influential factors impacting marine ecosystems in the face of global climate change. In ecological climate change research full-factorial experiments across seasons in multi-species, cross-trophic level set-ups are essential as they allow making realistic estimations about direct and indirect effects and the relative importance of both major environmental stressors on ecosystems. In benthic mesocosm experiments we tested the responses of coastal Baltic Sea Fucus vesiculosus communities to elevated seawater temperature and CO2 concentrations across four seasons of one year. While increasing [CO2] levels only had minor effects, warming had strong and persistent effects on grazers which affected the Fucus community differently depending on season. In late summer a temperature-driven collapse of grazers caused a cascading effect from the consumers to the foundation species resulting in overgrowth of Fucus thalli by epiphytes. In fall/ winter, outside the growing season of epiphytes, intensified grazing under warming resulted in a significant reduction of Fucus biomass. Thus, we confirm the prediction that future increasing water temperatures influence marine food-web processes by altering top-down control, but we also show that specific consequences for food-web structure depend on season. Since Fucus vesiculosus is the dominant habitat-forming brown algal system in the Baltic Sea, its potential decline under global warming implicates the loss of key functions and services such as provision of nutrient storage, substrate, food, shelter and nursery grounds for a diverse community of marine invertebrates and fish in Baltic Sea coastal waters.

Higher-order regularization and morphological techniques for image segmentation

La segmentación de imágenes es un campo importante de la visión computacional y una de las áreas de investigación más activas, con aplicaciones en comprensión de imágenes, detección de objetos, reconocimiento facial, vigilancia de vídeo o procesamiento de imagen médica. La segmentación de imágenes es un problema difícil en general, pero especialmente en entornos científicos y biomédicos, donde las técnicas de adquisición imagen proporcionan imágenes ruidosas. Además, en muchos de estos casos se necesita una precisión casi perfecta. En esta tesis, revisamos y comparamos primero algunas de las técnicas ampliamente usadas para la segmentación de imágenes médicas. Estas técnicas usan clasificadores a nivel de pixel e introducen regularización sobre pares de píxeles que es normalmente insuficiente. Estudiamos las dificultades que presentan para capturar la información de alto nivel sobre los objetos a segmentar. Esta deficiencia da lugar a detecciones erróneas, bordes irregulares, configuraciones con topología errónea y formas inválidas. Para solucionar estos problemas, proponemos un nuevo método de regularización de alto nivel que aprende información topológica y de forma a partir de los datos de entrenamiento de una forma no paramétrica usando potenciales de orden superior. Los potenciales de orden superior se están popularizando en visión por computador, pero la representación exacta de un potencial de orden superior definido sobre muchas variables es computacionalmente inviable. Usamos una representación compacta de los potenciales basada en un conjunto finito de patrones aprendidos de los datos de entrenamiento que, a su vez, depende de las observaciones. Gracias a esta representación, los potenciales de orden superior pueden ser convertidos a potenciales de orden 2 con algunas variables auxiliares añadidas. Experimentos con imágenes reales y sintéticas confirman que nuestro modelo soluciona los errores de aproximaciones más débiles. Incluso con una regularización de alto nivel, una precisión exacta es inalcanzable, y se requeire de edición manual de los resultados de la segmentación automática. La edición manual es tediosa y pesada, y cualquier herramienta de ayuda es muy apreciada. Estas herramientas necesitan ser precisas, pero también lo suficientemente rápidas para ser usadas de forma interactiva. Los contornos activos son una buena solución: son buenos para detecciones precisas de fronteras y, en lugar de buscar una solución global, proporcionan un ajuste fino a resultados que ya existían previamente. Sin embargo, requieren una representación implícita que les permita trabajar con cambios topológicos del contorno, y esto da lugar a ecuaciones en derivadas parciales (EDP) que son costosas de resolver computacionalmente y pueden presentar problemas de estabilidad numérica. Presentamos una aproximación morfológica a la evolución de contornos basada en un nuevo operador morfológico de curvatura que es válido para superficies de cualquier dimensión. Aproximamos la solución numérica de la EDP de la evolución de contorno mediante la aplicación sucesiva de un conjunto de operadores morfológicos aplicados sobre una función de conjuntos de nivel. Estos operadores son muy rápidos, no sufren de problemas de estabilidad numérica y no degradan la función de los conjuntos de nivel, de modo que no hay necesidad de reinicializarlo. Además, su implementación es mucho más sencilla que la de las EDP, ya que no requieren usar sofisticados algoritmos numéricos. Desde un punto de vista teórico, profundizamos en las conexiones entre operadores morfológicos y diferenciales, e introducimos nuevos resultados en este área. Validamos nuestra aproximación proporcionando una implementación morfológica de los contornos geodésicos activos, los contornos activos sin bordes, y los turbopíxeles. En los experimentos realizados, las implementaciones morfológicas convergen a soluciones equivalentes a aquéllas logradas mediante soluciones numéricas tradicionales, pero con ganancias significativas en simplicidad, velocidad y estabilidad. ABSTRACT Image segmentation is an important field in computer vision and one of its most active research areas, with applications in image understanding, object detection, face recognition, video surveillance or medical image processing. Image segmentation is a challenging problem in general, but especially in the biological and medical image fields, where the imaging techniques usually produce cluttered and noisy images and near-perfect accuracy is required in many cases. In this thesis we first review and compare some standard techniques widely used for medical image segmentation. These techniques use pixel-wise classifiers and introduce weak pairwise regularization which is insufficient in many cases. We study their difficulties to capture high-level structural information about the objects to segment. This deficiency leads to many erroneous detections, ragged boundaries, incorrect topological configurations and wrong shapes. To deal with these problems, we propose a new regularization method that learns shape and topological information from training data in a nonparametric way using high-order potentials. High-order potentials are becoming increasingly popular in computer vision. However, the exact representation of a general higher order potential defined over many variables is computationally infeasible. We use a compact representation of the potentials based on a finite set of patterns learned fromtraining data that, in turn, depends on the observations. Thanks to this representation, high-order potentials can be converted into pairwise potentials with some added auxiliary variables and minimized with tree-reweighted message passing (TRW) and belief propagation (BP) techniques. Both synthetic and real experiments confirm that our model fixes the errors of weaker approaches. Even with high-level regularization, perfect accuracy is still unattainable, and human editing of the segmentation results is necessary. The manual edition is tedious and cumbersome, and tools that assist the user are greatly appreciated. These tools need to be precise, but also fast enough to be used in real-time. Active contours are a good solution: they are good for precise boundary detection and, instead of finding a global solution, they provide a fine tuning to previously existing results. However, they require an implicit representation to deal with topological changes of the contour, and this leads to PDEs that are computationally costly to solve and may present numerical stability issues. We present a morphological approach to contour evolution based on a new curvature morphological operator valid for surfaces of any dimension. We approximate the numerical solution of the contour evolution PDE by the successive application of a set of morphological operators defined on a binary level-set. These operators are very fast, do not suffer numerical stability issues, and do not degrade the level set function, so there is no need to reinitialize it. Moreover, their implementation is much easier than their PDE counterpart, since they do not require the use of sophisticated numerical algorithms. From a theoretical point of view, we delve into the connections between differential andmorphological operators, and introduce novel results in this area. We validate the approach providing amorphological implementation of the geodesic active contours, the active contours without borders, and turbopixels. In the experiments conducted, the morphological implementations converge to solutions equivalent to those achieved by traditional numerical solutions, but with significant gains in simplicity, speed, and stability.

An O(N log N) algorithm for shape modeling.

We present a shape-recovery technique in two dimensions and three dimensions with specific applications in modeling anatomical shapes from medical images. This algorithm models extremely corrugated structures like the brain, is topologically adaptable, and runs in O(N log N) time, where N is the total number of points in the domain. Our technique is based on a level set shape-recovery scheme recently introduced by the authors and the fast marching method for computing solutions to static Hamilton-Jacobi equations.

Calmness modulus of linear semi-infinite programs

Our main goal is to compute or estimate the calmness modulus of the argmin mapping of linear semi-infinite optimization problems under canonical perturbations, i.e., perturbations of the objective function together with continuous perturbations of the right-hand side of the constraint system (with respect to an index ranging in a compact Hausdorff space). Specifically, we provide a lower bound on the calmness modulus for semi-infinite programs with unique optimal solution which turns out to be the exact modulus when the problem is finitely constrained. The relationship between the calmness of the argmin mapping and the same property for the (sub)level set mapping (with respect to the objective function), for semi-infinite programs and without requiring the uniqueness of the nominal solution, is explored, too, providing an upper bound on the calmness modulus of the argmin mapping. When confined to finitely constrained problems, we also provide a computable upper bound as it only relies on the nominal data and parameters, not involving elements in a neighborhood. Illustrative examples are provided.

Catheter-related bloodstream infection: burden of disease in a tertiary hospital

Background: Surveillance programmes have become the most effective tool for controlling catheter-related bloodstream infections (CRBSI). However, few studies have investigated programmes covering all hospital settings. Aim: To describe the results of a control and prevention programme for CRBSI based on compliance with recommendations for insertion and maintenance, using annual burden of disease in a tertiary level hospital. Methods: A CRBSI control and prevention programme involving all hospital settings was implemented. The programme consisted of CRBSI surveillance, direct observation of insertion and maintenance of catheters to determine performance, and education for healthcare workers. Findings: In total, 2043 short-term catheters were inserted in 1546 patients for 18,570 catheter-days, and 279 long-term catheters were inserted in 243 patients for 40,440 catheter-days. The annual incidence density was 5.98 (first semester 6.40, second semester 5.64) CRBSI per 1000 catheter-days for short-term catheters, and 0.57 (first semester 0.66, second semester 0.43) CRBSI per 1000 catheter-days for long-term catheters. One hundred and forty insertion procedures were observed, with an average insertion time of 13 (standard deviation 7) min. Compliance with recommendations was as follows: hand hygiene, 86.8%; use of alcoholic chlorhexidine solution for skin disinfection, 35.5%; use of mask, 93.4%; use of gloves, 98.7%; use of gown, 75.0%; use of sterile cloth, 93.8%; use of cap, 92.2%; bandage application, 62.7%; and use of aseptic technique, 89.5%. Forty-five maintenance procedures were observed, and compliance rates were as follows: hand hygiene, 42.1%; use of gloves, 78.1%; and port disinfection with alcoholic chlorhexidine solution, 32.5%. Conclusion: The CRBSI control and prevention programme implemented at the study hospital has decreased the rate of CRBSI, provided important information about the total burden of disease, and revealed possible ways to improve interventions in the future.

Using the effect size to model change in preference values from descriptive health status

Objectives: This pilot study describes a modelling approach to translate group-level changes in health status into changes in preference values, by using the effect size (ES) to summarize group-level improvement. Methods: ESs are the standardized mean difference between treatment groups in standard deviation (SD) units. Vignettes depicting varying severity in SD decrements on the SF-12 mental health summary scale, with corresponding symptom severity profiles, were valued by a convenience sample of general practitioners (n = 42) using the rating scale (RS) and time trade-off methods. Translation factors between ES differences and change in preference value were developed for five mental disorders, such that ES from published meta-analyses could be transformed into predicted changes in preference values. Results: An ES difference in health status was associated with an average 0.171-0.204 difference in preference value using the RS, and 0.104-0.158 using the time trade off. Conclusions: This observed relationship may be particular to the specific versions of the measures employed in the present study. With further development using different raters and preference measures, this approach may expand the evidence base available for modelling preference change for economic analyses from existing data.

Kidney dysfunction and hypertension: Role for cadmium, P450 and heme oxygenases?

Cadmium (Cd) is a metal toxin of continuing worldwide concern. Daily intake of Cd, albeit in small quantities, is associated with a number of adverse health effects which are attributable to distinct pathological changes in a variety of tissues and organs. In the present review, we focus on its renal tubular effects in people who have been exposed environmentally to Cd at levels below the provisional tolerable intake level set for the toxin. We highlight the data linking such low-level Cd intake with tubular injury, altered abundance of cytochromes P450 (CYPs) in the kidney and an expression of a hypertensive phenotype. We provide updated knowledge on renal and vascular effects of the eicosanoids 20-hydroxyeicosatetraenoic acid (20-HETE) and eicosatrienoic acids (EETs), which are biologically active metabolites from arachidonate metabolism mediated by certain CYPs in the kidney. We note the ability of Cd to elicit oxidative stress and to alter metal homeostasis notably of zinc which may lead to augmentation of the defense mechanisms involving induction of the antioxidant enzyme heme oxygenase-1 (HO-1) and the metal binding protein metallothionein (MT) in the kidney. We hypothesize that renal Cd accumulation triggers the host responses mediated by HO-I and MT in an attempt to protect the kidney against injurious oxidative stress and to resist a rise in blood pressure levels. This hypothesis predicts that individuals with less active HO-1 (caused by the HO-1 genetic polymorphisms) are more likely to have renal injury and express a hypertensive phenotype following chronic ingestion of low-level Cd, compared with those having more active HO-1. Future analytical and molecular epidemiologic research should pave the way to the utility of induction of heme oxygenases together with dietary antioxidants in reducing the risk of kidney injury and hypertension in susceptible people.