Virtual simulation of the postsurgical cosmetic outcome in patientswith pectus excavatum

Pectus excavatum is the most common congenital deformity of the anterior chest wall, in which several ribs and the sternum grow abnormally. Nowadays, the surgical correction is carried out in children and adults through Nuss technic. This technic has been shown to be safe with major drivers as cosmesis and the prevention of psychological problems and social stress. Nowadays, no application is known to predict the cosmetic outcome of the pectus excavatum surgical correction. Such tool could be used to help the surgeon and the patient in the moment of deciding the need for surgery correction. This work is a first step to predict postsurgical outcome in pectus excavatum surgery correction. Facing this goal, it was firstly determined a point cloud of the skin surface along the thoracic wall using Computed Tomography (before surgical correction) and the Polhemus FastSCAN (after the surgical correction). Then, a surface mesh was reconstructed from the two point clouds using a Radial Basis Function algorithm for further affine registration between the meshes. After registration, one studied the surgical correction influence area (SCIA) of the thoracic wall. This SCIA was used to train, test and validate artificial neural networks in order to predict the surgical outcome of pectus excavatum correction and to determine the degree of convergence of SCIA in different patients. Often, ANN did not converge to a satisfactory solution (each patient had its own deformity characteristics), thus invalidating the creation of a mathematical model capable of estimating, with satisfactory results, the postsurgical outcome

Processing and characterization of alpha-elastin electrospun membranes

Elastin isolated from fresh bovine ligaments was dissolved in a mixture of 1,1,1,3,3,3-Hexafluoro-2-propanol and water and electrospun into fiber membranes under different processing conditions. Fiber mats of randomly and aligned fibers were obtained with fixed and rotating ground collectors and fibrils were composed by thin ribbons whose width depends on electrospinning conditions; fibrils with 721 nm up to 2.12 m width were achieved. After cross-linking with glutaraldehyde, -elastin can uptake as much as 1700 % of PBS solution and a slight increase on fiber thickness was observed. The glass transition temperature of electrospun fiber mats was found to occur at ~ 80 ºC. Moreover, -Elastin showed to be a perfect elastomeric material, and no mechanical hysteresis was found in cycle mechanical measurements. The elastic modulus obtained for oriented and random fibers mats in a PBS solution was 330 ± 10 kPa and 732 ± 165 kPa, respectively. Finally, the electrospinning and cross-linking process does not inhibit MC-3T3-E1 cell adhesion. Cell culture results showed good cell adhesion and proliferation in the cross-linked elastin fiber mats.

An image processing application for quantification of protein aggregates in Caenorhabditis elegans

Protein aggregation became a widely accepted marker of many polyQ disorders, including Machado-Joseph disease (MJD), and is often used as readout for disease progression and development of therapeutic strategies. The lack of good platforms to rapidly quantify protein aggregates in a wide range of disease animal models prompted us to generate a novel image processing application that automatically identifies and quantifies the aggregates in a standardized and operator-independent manner. We propose here a novel image processing tool to quantify the protein aggregates in a Caenorhabditis elegans (C. elegans) model of MJD. Confocal mi-croscopy images were obtained from animals of different genetic conditions. The image processing application was developed using MeVisLab as a platform to pro-cess, analyse and visualize the images obtained from those animals. All segmenta-tion algorithms were based on intensity pixel levels.The quantification of area or numbers of aggregates per total body area, as well as the number of aggregates per animal were shown to be reliable and reproducible measures of protein aggrega-tion in C. elegans. The results obtained were consistent with the levels of aggrega-tion observed in the images. In conclusion, this novel imaging processing applica-tion allows the non-biased, reliable and high throughput quantification of protein aggregates in a C. elegans model of MJD, which may contribute to a significant improvement on the prognosis of treatment effectiveness for this group of disor-ders

Variations of the soft tissue thicknesses external to the ribs in Pectus Excavatum patients

Background: Surgical repair of pectus excavatum (PE) has become more popular due to improvements in the minimally invasive Nuss procedure. The pre-surgical assessment of PE patients requires Computerized Tomography (CT), as the malformation characteristics vary from patient to patient. Objective: This work aims to characterize soft tissue thickness (STT) external to the ribs among PE patients. It also presents a comparative analysis between the anterior chest wall surface before and after surgical correction. Methods: Through surrounding tissue segmentation in CT data, STT values were calculated at different lines along the thoracic wall, with a reference point in the intersection of coronal and median planes. The comparative analysis between the two 3D anterior chest surfaces sets a surgical correction influence area (SCIA) and a volume of interest (VOI) based on image processing algorithms, 3D surface algorithms, and registration methods. Results: There are always variations between left and right side STTs (2.54±2.05 mm and 2.95±2.97 mm for female and male patients, respectively). STTs are dependent on age, sex, and body mass index of each patient. On female patients, breast tissue induces additional errors in bar manual

Estudo de adoção de tecnologias de cloud computing no contexto das PMES portuguesas

A sociedade atual é marcada por uma crescente competição entre as organizações, as quais para garantirem a sua sobrevivência têm que evoluir e utilizar a tecnologia de informação mais adequada. Num período em que as PMES portuguesas necessitam de reduzir custos e concentrarem-se mais no seu processo de negócio surge um novo paradigma tecnológico, a Computação na Nuvem, esta ainda é um paradigma bastante recente, onde os recursos de TI que apresentam características de elasticidade e dinâmicas são oferecidos ao cliente como um serviço, no qual este paga apenas o que consome (pagamento por utilização). A Cloud Computing com o seu novo paradigma permite às organizações, principalmente às PMES reduzirem custos, concentrarem-se no seu processo de negócio sem se preocuparem com a parte informática (cópias de segurança, assistência e perda de dados) e obter um retorno mais rápido do seu investimento. Este trabalho consiste no Estudo da Adoção Individual da Cloud Computing no contexto das PMEs Portuguesas, o qual apresenta como principais objetivos obter uma melhor compreensão do conceito Cloud Computing, entender a sua importância para os indivíduos das PMES, identificar os seus fatores de sucesso e insucesso e identificar as limitações sentidas de uma forma generalizada e de uma forma específica para as PMES Portuguesas. Para cumprir os objetivos mencionados anteriormente, efetuou-se uma extensa revisão de literatura, propôs-se um modelo conceptual de investigação com adaptações à Teoria Unificada de Aceitação e Uso de Tecnologia (UTAUT) e utilizou-se como instrumento de recolha de dados um questionário que foi enviado às PMES Portuguesas.

Dashboard services for pragmatics-based interoperability in cloud and ubiquitous manufacturing

The real Cloud and Ubiquitous Manufacturing systems require effectiveness and permanent availability of resources, their capacity and scalability. One of the most important problems for applications management over cloud based platforms, which are expected to support efficient scalability and resources coordination following SaaS implementation model, is their interoperability. Even application dashboards need to easily incorporate those new applications, their interoperability still remains a big problem to override. So, the possibility to expand these dashboards with efficiently integrated communicational cloud based services (cloudlets) represents a relevant added value as well as contributes to solving the interoperability problem. Following the architecture for integration of enriched existing cloud services, as instances of manufacturing resources, this paper: a) proposes a cloud based web platform to support dashboard integrating communicational services, and b) describe an experimentation to sustain the theory that the effective and efficient interoperability, especially in dynamic environments, could be achieved only with human intervention.

Variations of the soft tissue thicknesses external to the ribs in pectus excavatum patients

Background: Surgical repair of pectus excavatum (PE) has become more popular due to improvements in the minimally invasive Nuss procedure. The pre-surgical assessment of PE patients requires Computerized Tomography (CT), as the malformation characteristics vary from patient to patient. Objective: This work aims to characterize soft tissue thickness (STT) external to the ribs among PE patients. It also presents a comparative analysis between the anterior chest wall surface before and after surgical correction. Methods: Through surrounding tissue segmentation in CT data, STT values were calculated at different lines along the thoracic wall, with a reference point in the intersection of coronal and median planes. The comparative analysis between the two 3D anterior chest surfaces sets a surgical correction influence area (SCIA) and a volume of interest (VOI) based on image processing algorithms, 3D surface algorithms, and registration methods. Results: There are always variations between left and right side STTs (2.54±2.05 mm and 2.95±2.97 mm for female and male patients, respectively). STTs are dependent on age, sex, and body mass index of each patient. On female patients, breast tissue induces additional errors in bar manual

Artificial neural networks for automatic modelling of the pectus excavatum corrective prosthesis

Pectus excavatum is the most common deformity of the thorax and usually comprises Computed Tomography (CT) examination for pre-operative diagnosis. Aiming at the elimination of the high amounts of CT radiation exposure, this work presents a new methodology for the replacement of CT by a laser scanner (radiation-free) in the treatment of pectus excavatum using personally modeled prosthesis. The complete elimination of CT involves the determination of ribs external outline, at the maximum sternum depression point for prosthesis placement, based on chest wall skin surface information, acquired by a laser scanner. The developed solution resorts to artificial neural networks trained with data vectors from 165 patients. Scaled Conjugate Gradient, Levenberg-Marquardt, Resilient Back propagation and One Step Secant gradient learning algorithms were used. The training procedure was performed using the soft tissue thicknesses, determined using image processing techniques that automatically segment the skin and rib cage. The developed solution was then used to determine the ribs outline in data from 20 patient scanners. Tests revealed that ribs position can be estimated with an average error of about 6.82±5.7 mm for the left and right side of the patient. Such an error range is well below current prosthesis manual modeling (11.7±4.01 mm) even without CT imagiology, indicating a considerable step forward towards CT replacement by a 3D scanner for prosthesis personalization.