Towards an efficient and robust foot classification from pedobarographic images

O documento em anexo encontra-se na versão post-print (versão corrigida pelo editor).

Finite element studies of the mechanical behaviour of the diaphragm in normal and pathological cases

The diaphragm is a muscular membrane separating the abdominal and thoracic cavities, and its motion is directly linked to respiration. In this study, using data from a 59-year-old female cadaver obtained from the Visible Human Project, the diaphragm is reconstructed and, from the corresponding solid object, a shell finite element mesh is generated and used in several analyses performed with the ABAQUS 6.7 software. These analyses consider the direction of the muscle fibres and the incompressibility of the tissue. The constitutive model for the isotropic strain energy as well as the passive and active strain energy stored in the fibres is adapted from Humphrey's model for cardiac muscles. Furthermore, numerical results for the diaphragmatic floor under pressure and active contraction in normal and pathological cases are presented.

Estimativa de validade de um novo método de isolamento de vírus rábico

OBJETIVOS: Nenhum estudo de base populacional foi realizado para mostrar o uso potencial de diagnóstico virológico do vírus rábico. O estudo realizado teve por objetivo estimar parâmetros de acurácia para o isolamento de vírus rábico em célula McCoy, como um método alternativo, e comparar com o uso da célula N2A, considerada método de referência. MÉTODOS: Foi realizado um inquérito em 120 morcegos coletados aleatoriamente, na Mata Atlântica, no Estado de São Paulo. Utilizou-se a reação de imunofluorescência para a detecção do vírus rábico isolado no cérebro desses morcegos, avaliado nos dois sistemas de cultivos celulares. Dois bancos de dados foram formados com os resultados. A análise foi feita com o programa Computer Methods for Diagnosis Tests (CMDT), utilizando a técnica de two-graph-receiver operating characteristic (TG-ROC) para obter os parâmetros de sensibilidade e especificidade, além de outros indicadores, tais como eficácia, valor preditivo positivo, valor preditivo negativo e razão de verossimilhança. RESULTADOS: A célula N2A apresentou 90% de sensibilidade e especificidade, enquanto que a célula McCoy obteve 95% para os mesmos parâmetros. Os valores foram baseados em pontos de cortes otimizados para cada uma das células. CONCLUSÕES: Observou-se que a célula McCoy permite obter estimativas de acurácia superiores aos resultados observados com a célula de N2A, representando um método alternativo eficaz no isolamento do vírus rábico.

BIT: Biosignal Igniter Toolkit

The study of biosignals has had a transforming role in multiple aspects of our society, which go well beyond the health sciences domains to which they were traditionally associated with. While biomedical engineering is a classical discipline where the topic is amply covered, today biosignals are a matter of interest for students, researchers and hobbyists in areas including computer science, informatics, electrical engineering, among others. Regardless of the context, the use of biosignals in experimental activities and practical projects is heavily bounded by the cost, and limited access to adequate support materials. In this paper we present an accessible, albeit versatile toolkit, composed of low-cost hardware and software, which was created to reinforce the engagement of different people in the field of biosignals. The hardware consists of a modular wireless biosignal acquisition system that can be used to support classroom activities, interface with other devices, or perform rapid prototyping of end-user applications. The software comprehends a set of programming APIs, a biosignal processing toolbox, and a framework for real time data acquisition and postprocessing. (C) 2014 Elsevier Ireland Ltd. All rights reserved.

Is multidimensional scaling suitable for mapping the input respiratory impedance in subjects and patients?

This paper presents the application of multidimensional scaling (MDS) analysis to data emerging from noninvasive lung function tests, namely the input respiratory impedance. The aim is to obtain a geometrical mapping of the diseases in a 3D space representation, allowing analysis of (dis)similarities between subjects within the same pathology groups, as well as between the various groups. The adult patient groups investigated were healthy, diagnosed chronic obstructive pulmonary disease (COPD) and diagnosed kyphoscoliosis, respectively. The children patient groups were healthy, asthma and cystic fibrosis. The results suggest that MDS can be successfully employed for mapping purposes of restrictive (kyphoscoliosis) and obstructive (COPD) pathologies. Hence, MDS tools can be further examined to define clear limits between pools of patients for clinical classification, and used as a training aid for medical traineeship.

An R package for the integrated analysis of metabolomics and spectral data

Recently, there has been a growing interest in the field of metabolomics, materialized by a remarkable growth in experimental techniques, available data and related biological applications. Indeed, techniques as Nuclear Magnetic Resonance, Gas or Liquid Chromatography, Mass Spectrometry, Infrared and UV-visible spectroscopies have provided extensive datasets that can help in tasks as biological and biomedical discovery, biotechnology and drug development. However, as it happens with other omics data, the analysis of metabolomics datasets provides multiple challenges, both in terms of methodologies and in the development of appropriate computational tools. Indeed, from the available software tools, none addresses the multiplicity of existing techniques and data analysis tasks. In this work, we make available a novel R package, named specmine, which provides a set of methods for metabolomics data analysis, including data loading in different formats, pre-processing, metabolite identification, univariate and multivariate data analysis, machine learning, and feature selection. Importantly, the implemented methods provide adequate support for the analysis of data from diverse experimental techniques, integrating a large set of functions from several R packages in a powerful, yet simple to use environment. The package, already available in CRAN, is accompanied by a web site where users can deposit datasets, scripts and analysis reports to be shared with the community, promoting the efficient sharing of metabolomics data analysis pipelines.

BIOMedical search engine framework: lightweight and customized implementation of domain-specific biomedical search engines

The Smart Drug Search is publicly accessible at http://sing.ei.uvigo.es/sds/. The BIOMedical Search Engine Framework is freely available for non-commercial use at https://github.com/agjacome/biomsef

Translation of biomechanical concepts in bone tissue engineering: from animal study to revision knee arthroplasty.

Bone defects in revision knee arthroplasty are often located in load-bearing regions. The goal of this study was to determine whether a physiologic load could be used as an in situ osteogenic signal to the scaffolds filling the bone defects. In order to answer this question, we proposed a novel translation procedure having four steps: (1) determining the mechanical stimulus using finite element method, (2) designing an animal study to measure bone formation spatially and temporally using micro-CT imaging in the scaffold subjected to the estimated mechanical stimulus, (3) identifying bone formation parameters for the loaded and non-loaded cases appearing in a recently developed mathematical model for bone formation in the scaffold and (4) estimating the stiffness and the bone formation in the bone-scaffold construct. With this procedure, we estimated that after 3 years mechanical stimulation increases the bone volume fraction and the stiffness of scaffold by 1.5- and 2.7-fold, respectively, compared to a non-loaded situation.

A multidimensional segmentation evaluation for medical image data.

Evaluation of segmentation methods is a crucial aspect in image processing, especially in the medical imaging field, where small differences between segmented regions in the anatomy can be of paramount importance. Usually, segmentation evaluation is based on a measure that depends on the number of segmented voxels inside and outside of some reference regions that are called gold standards. Although some other measures have been also used, in this work we propose a set of new similarity measures, based on different features, such as the location and intensity values of the misclassified voxels, and the connectivity and the boundaries of the segmented data. Using the multidimensional information provided by these measures, we propose a new evaluation method whose results are visualized applying a Principal Component Analysis of the data, obtaining a simplified graphical method to compare different segmentation results. We have carried out an intensive study using several classic segmentation methods applied to a set of MRI simulated data of the brain with several noise and RF inhomogeneity levels, and also to real data, showing that the new measures proposed here and the results that we have obtained from the multidimensional evaluation, improve the robustness of the evaluation and provides better understanding about the difference between segmentation methods.

Effect of a pathological scapular tilt after total shoulder arthroplasty.

Total shoulder arthroplasty (TSA) is an accepted and most successfully used treatment for different shoulder pathologies. Different risk factors for the failure of the prosthesis are known. A pathological scapular orientation, observed in elderly people or in patients suffering from neuromuscular diseases, could be a cause of failure, which has not been investigated yet. To test this hypothesis, a numerical musculoskeletal model of the glenohumeral joint was used to compare two TSA cases: a reference normal case and a case with a pathological anterior tilt of the scapula. An active abduction of 150° was simulated. Joint force, contact pattern, polyethylene and cement stress were evaluated for both cases. The pathological tilt slightly increased the joint force and the contact pressure, but also shifted the contact pattern. This eccentric contact increased the stress level within the polyethylene of the glenoid component and within the surrounding cement layer. This adverse effect occurred mainly during the first 60° of abduction. Therefore, a pathological orientation of the scapula may increase the risk of a failure of the cement layer around the glenoid component. These preliminary numerical results should be confirmed by a clinical study.

Deployment of self-expandable stents in aneurysmatic cerebral vessels: comparison of different computational approaches for interventional planning

In the last few years, there has been a growing focus on faster computational methods to support clinicians in planning stenting procedures. This study investigates the possibility of introducing computational approximations in modelling stent deployment in aneurysmatic cerebral vessels to achieve simulations compatible with the constraints of real clinical workflows. The release of a self-expandable stent in a simplified aneurysmatic vessel was modelled in four different initial positions. Six progressively simplified modelling approaches (based on Finite Element method and Fast Virtual Stenting – FVS) have been used. Comparing accuracy of the results, the final configuration of the stent is more affected by neglecting mechanical properties of materials (FVS) than by adopting 1D instead of 3D stent models. Nevertheless, the differencesshowed are acceptable compared to those achieved by considering different stent initial positions. Regarding computationalcosts, simulations involving 1D stent features are the only ones feasible in clinical context.

Dense deformation field estimation for atlas-based segmentation of pathological MR brain images.

Atlas registration is a recognized paradigm for the automatic segmentation of normal MR brain images. Unfortunately, atlas-based segmentation has been of limited use in presence of large space-occupying lesions. In fact, brain deformations induced by such lesions are added to normal anatomical variability and they may dramatically shift and deform anatomically or functionally important brain structures. In this work, we chose to focus on the problem of inter-subject registration of MR images with large tumors, inducing a significant shift of surrounding anatomical structures. First, a brief survey of the existing methods that have been proposed to deal with this problem is presented. This introduces the discussion about the requirements and desirable properties that we consider necessary to be fulfilled by a registration method in this context: To have a dense and smooth deformation field and a model of lesion growth, to model different deformability for some structures, to introduce more prior knowledge, and to use voxel-based features with a similarity measure robust to intensity differences. In a second part of this work, we propose a new approach that overcomes some of the main limitations of the existing techniques while complying with most of the desired requirements above. Our algorithm combines the mathematical framework for computing a variational flow proposed by Hermosillo et al. [G. Hermosillo, C. Chefd'Hotel, O. Faugeras, A variational approach to multi-modal image matching, Tech. Rep., INRIA (February 2001).] with the radial lesion growth pattern presented by Bach et al. [M. Bach Cuadra, C. Pollo, A. Bardera, O. Cuisenaire, J.-G. Villemure, J.-Ph. Thiran, Atlas-based segmentation of pathological MR brain images using a model of lesion growth, IEEE Trans. Med. Imag. 23 (10) (2004) 1301-1314.]. Results on patients with a meningioma are visually assessed and compared to those obtained with the most similar method from the state-of-the-art.