Métodos para a tomada de decisão em portfólio de produtos: um levantamento em empresas dos setores eletrônico, óptico e de informática

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

Pattern and timing of the coronary sinus activation to guide rapid diagnosis of atrial tachycardia after atrial fibrillation ablation

BACKGROUND Atrial tachycardias (AT) during or after ablation of atrial fibrillation frequently pose a diagnostic challenge. We hypothesized that both the patterns and the timing of coronary sinus (CS) activation could facilitate AT mapping. METHODS AND RESULTS A total of 140 consecutive postpersistent atrial fibrillation ablation patients with sustained AT were investigated by conventional mapping. CS activation pattern was defined as chevron or reverse chevron when the activations recorded on both the proximal and the distal CS dipoles were latest or earliest, respectively. The local activation of mid-CS was timed with reference to Ppeak-Ppeak (P-P) interval in lead V1. A ratio, mid-CS activation time to AT cycle length, was computed. Of 223 diagnosed ATs, 124 were macroreentrant (56%) and 99 were centrifugal (44%). When CS activation was chevron/reverse chevron (n=44; 20%), macroreentries were mostly roof dependent. With reference to P-P interval, mid-CS activation timing showed specific consistency for peritricuspid and perimitral AT. Proximal to distal CS activation pattern and mid-CS activation at 50% to 70% of the P-P interval (n=30; 13%) diagnosed peritricuspid AT with 81% sensitivity and 89% specificity. Distal to proximal CS activation and mid-CS activation at 10% to 40% of the P-P interval (n=44; 20%) diagnosed perimitral AT with 88% sensitivity and 75% specificity. CONCLUSIONS The analysis of the patterns and timing of CS activation provides a rapid stratification of most likely macroreentrant ATs and points toward the likely origin of centrifugal ATs. It can be included in a stepwise diagnostic approach to rapidly select the most critical mapping maneuvers.

Catheter ablation of persistent and long-standing persistent atrial fibrillation. Strategies and results

Catheter ablation for paroxysmal atrial fibrillation is a meanwhile established therapy option, which is most frequently performed using radiofrequency ablation. Mid-term success rate of 70 % are achievable with a single ablation procedure. However, the mechanistics of persistent atrial fibrillation are less well understood and catheter ablation is a far more challenging procedure. Different ablation approaches are being performed to treat persistent atrial fibrillation ranging from sole pulmonary vein isolation to additional ablation of fractionated electrograms aiming for termination of atrial fibrillation. Thus far, it has not been investigated which strategy is most successful in treating persistent atrial fibrillation. After extended ablation of atrial fibrillation, occurrence of organized atrial arrhythmias is not uncommon and can be successfully ablated. These consecutive arrhythmias can be considered as a next step towards stable sinus rhythm after repeat ablation. Improvement of mapping methods as well as a better understanding of mechanisms of atrial fibrillation may increase success rate of catheter ablation of persistent atrial fibrillation and may also help to improve success rate of these complex procedures.

Clinical Use of Quantitative Computed Tomography–Based Advanced Techniques in the Management of Osteoporosis in Adults: the 2015 ISCD Official Positions—Part III

The International Society for Clinical Densitometry (ISCD) has developed new official positions for the clinical use of computed tomography (CT) scans acquired without a calibration phantom, for example, CT scans obtained for other diagnosis such as colonography. This also addresses techniques suggested for opportunistic screening of osteoporosis. The ISCD task force for quantitative CT reviewed the evidence for clinical applications of these new techniques and presented a report with recommendations at the 2015 ISCD Position Development Conference. Here we discuss the agreed upon ISCD official positions with supporting medical evidence, rationale, controversy, and suggestions for further study. Advanced techniques summarized as statistical parameter mapping methods were also reviewed. Their future use is promising but the clinical application is premature. The clinical use of QCT of the hip is addressed in part I and of finite element analysis of the hip and spine in part II.

Diagnóstico de sistema integrado de transporte de passageiros com uso de sistema de informação geográfica : o caso da cidade de Macaé – RJ – Brasil : resultados preliminares

O Sistema Integrado de Transporte Coletivo do município de Macaé – RJ tem sido alvo de diversas críticas atualmente e reflete a dificuldade dos gestores urbanos em acompanhar as rápidas transformações da “capital nacional do petróleo", levantando a necessidade de métodos de diagnósticos eficientes em sistemas de transporte de passageiros. Desta forma, o objetivo do trabalho é diagnosticar o sistema de transporte público de Macaé - RJ e analisar o uso de Sistema de Informação Geográfica, tendo em vista a eficiência do diagnóstico. A metodologia se baseia em dados operacionais do sistema de transporte, confecção de mapas e análises espaciais com uso do software Transcad 4.5 Full. Os resultados apontam dificuldades estruturais no sistema como, por exemplo, a localização indevida de 2 Terminais, a sobrecarga de linhas alimentadoras com necessidade demasiada de transbordo, a falta de atendimento direto de importantes linhas de desejo, a desestabilidade na operação, etc. A utilização do SIG demonstrou expressivo ganho de tempo na gestão e análise de informações de forma integrada, devendo-se ponderar, em alguns casos, o método de mapeamento e a relação tempo de trabalho x ganho de conhecimento, assim como a necessidade de integração com informações operacionais do sistema de transporte.

Predicting EQ-5D from the Parkinson's disease questionnaire PDQ-8 using multi-dimensional Bayesian network classifiers

The impact of the Parkinson's disease and its treatment on the patients' health-related quality of life can be estimated either by means of generic measures such as the european quality of Life-5 Dimensions (EQ-5D) or specific measures such as the 8-item Parkinson's disease questionnaire (PDQ-8). In clinical studies, PDQ-8 could be used in detriment of EQ-5D due to the lack of resources, time or clinical interest in generic measures. Nevertheless, PDQ-8 cannot be applied in cost-effectiveness analyses which require generic measures and quantitative utility scores, such as EQ-5D. To deal with this problem, a commonly used solution is the prediction of EQ-5D from PDQ-8. In this paper, we propose a new probabilistic method to predict EQ-5D from PDQ-8 using multi-dimensional Bayesian network classifiers. Our approach is evaluated using five-fold cross-validation experiments carried out on a Parkinson's data set containing 488 patients, and is compared with two additional Bayesian network-based approaches, two commonly used mapping methods namely, ordinary least squares and censored least absolute deviations, and a deterministic model. Experimental results are promising in terms of predictive performance as well as the identification of dependence relationships among EQ-5D and PDQ-8 items that the mapping approaches are unable to detect

Modelling pre-clearing vegetation distribution using GIS-integrated statistical, ecological and data models: A case study from the wet tropics of Northeastern Australia

Traditional vegetation mapping methods use high cost, labour-intensive aerial photography interpretation. This approach can be subjective and is limited by factors such as the extent of remnant vegetation, and the differing scale and quality of aerial photography over time. An alternative approach is proposed which integrates a data model, a statistical model and an ecological model using sophisticated Geographic Information Systems (GIS) techniques and rule-based systems to support fine-scale vegetation community modelling. This approach is based on a more realistic representation of vegetation patterns with transitional gradients from one vegetation community to another. Arbitrary, though often unrealistic, sharp boundaries can be imposed on the model by the application of statistical methods. This GIS-integrated multivariate approach is applied to the problem of vegetation mapping in the complex vegetation communities of the Innisfail Lowlands in the Wet Tropics bioregion of Northeastern Australia. The paper presents the full cycle of this vegetation modelling approach including sampling sites, variable selection, model selection, model implementation, internal model assessment, model prediction assessments, models integration of discrete vegetation community models to generate a composite pre-clearing vegetation map, independent data set model validation and model prediction's scale assessments. An accurate pre-clearing vegetation map of the Innisfail Lowlands was generated (0.83r(2)) through GIS integration of 28 separate statistical models. This modelling approach has good potential for wider application, including provision of. vital information for conservation planning and management; a scientific basis for rehabilitation of disturbed and cleared areas; a viable method for the production of adequate vegetation maps for conservation and forestry planning of poorly-studied areas. (c) 2006 Elsevier B.V. All rights reserved.

Uma proposta de slam com determinação de informações geométricas do ambiente

PEDROSA, Diogo P. F. ; MEDEIROS, Adelardo A. D. ; ALSINA, Pablo J. . Uma Proposta de SLAM com Determinação de Informações Geométricas do Ambiente. In: CONGRESSO BRASILEIRO DE AUTOMÁTICA, 16, Salvador, BA, 2006. Anais... Salvador: CBA, 2006. v. 1. p. 1704-1709

Uma proposta de slam com determinação de informações geométricas do ambiente

PEDROSA, Diogo P. F. ; MEDEIROS, Adelardo A. D. ; ALSINA, Pablo J. . Uma Proposta de SLAM com Determinação de Informações Geométricas do Ambiente. In: CONGRESSO BRASILEIRO DE AUTOMÁTICA, 16, Salvador, BA, 2006. Anais... Salvador: CBA, 2006. v. 1. p. 1704-1709

Utility and safety of invasive (fractional flow reserve) and non-invasive (cardiac magnetic resonance imaging) diagnostic tests in patients with NSTEMI

A prospective randomised controlled clinical trial of treatment decisions informed by invasive functional testing of coronary artery disease severity compared with standard angiography-guided management was implemented in 350 patients with a recent non-ST elevation myocardial infarction (NSTEMI) admitted to 6 hospitals in the National Health Service. The main aims of this study were to examine the utility of both invasive fractional flow reserve (FFR) and non-invasive cardiac magnetic resonance imaging (MRI) amongst patients with a recent diagnosis of NSTEMI. In summary, the findings of this thesis are: (1) the use of FFR combined with intravenous adenosine was feasible and safe amongst patients with NSTEMI and has clinical utility; (2) there was discordance between the visual, angiographic estimation of lesion significance and FFR; (3). The use of FFR led to changes in treatment strategy and an increase in prescription of medical therapy in the short term compared with an angiographically guided strategy; (4) in the incidence of major adverse cardiac events (MACE) at 12 months follow up was similar in the two groups. Cardiac MRI was used in a subset of patients enrolled in two hospitals in the West of Scotland. T1 and T2 mapping methods were used to delineate territories of acute myocardial injury. T1 and T2 mapping were superior when compared with conventional T2-weighted dark blood imaging for estimation of the ischaemic area-at-risk (AAR) with less artifact in NSTEMI. There was poor correlation between the angiographic AAR and MRI methods of AAR estimation in patients with NSTEMI. FFR had a high accuracy at predicting inducible perfusion defects demonstrated on stress perfusion MRI. This thesis describes the largest randomized trial published to date specifically looking at the clinical utility of FFR in the NSTEMI population. We have provided evidence of the diagnostic and clinical utility of FFR in this group of patients and provide evidence to inform larger studies. This thesis also describes the largest ever MRI cohort, including with myocardial stress perfusion assessments, specifically looking at the NSTEMI population. We have demonstrated the diagnostic accuracy of FFR to predict reversible ischaemia as referenced to a non-invasive gold standard with MRI. This thesis has also shown the futility of using dark blood oedema imaging amongst all comer NSTEMI patients when compared to novel T1 and T2 mapping methods.

Correlations between cardiac magnetic resonance and histologic findings in Anderson Fabry disease

ABSTRACT Background Cardiac magnetic resonance (CMR) has been shown as promising diagnostic tool in Anderson-Fabry disease (AFD) cardiomyopathy due to its ability to detect fat deposits through lower native T1 values. However no histological validation has been provided to date. Objectives To correlate CMR and histologic findings in different cardiac stages of AFD focusing on T1 mapping. Methods Fifteen AFD patients (49 years [IQR 39-63], 60% females) undergoing CMR (cines, native T1 and T2 mapping, LGE and post-contrast T1 imaging) and endomyocardial biopsy (EMB, n=11) or septal myectomy (n=4), were retrospectively evaluated. Tissue specimens were analyzed with light/electron microscopy and vacuolization amount calculated as percentages of vacuolated myocytes and vacuolated myocyte area (%VMA) through a quantitative histomorphometric color-based analysis. Results In patients without increased indexed left ventricular mass (LVMi) at CMR (67%), T1 fell as %VMA increased (r= -0.883; p<0.001), whereas no clear relationship was evident once increased LVMi occurred (r= -0.501; p=0.389). At least 45% of vacuolized myocytes and 10% of VMA were needed for low T1 to occur. %VMA positively correlate with maximal wall thickness (MWT, r=0.860, p<0.0001) and LVMi (r= 0.762; p<0.001). Increased MWT and LVMi were present with at least 45% and 80% of vacuolated myocytes, respectively, and 18% and 22% of VMA. Conclusions This study demonstrated an inverse correlation between native T1 and the vacuolization amount in patients without increased LVMi at CMR, providing a histological validation of low native T1 in AFD. Importantly, a significant vacuolization burden was needed before low T1 and left ventricle hypertrophy occurred.

Mapping the Pasture Steppe in Bayankhongor, Mongolia: comparison of classification methods, using Landsat-8 and geophysical data

Grasslands in semi-arid regions, like Mongolian steppes, are facing desertification and degradation processes, due to climate change. Mongolia’s main economic activity consists on an extensive livestock production and, therefore, it is a concerning matter for the decision makers. Remote sensing and Geographic Information Systems provide the tools for advanced ecosystem management and have been widely used for monitoring and management of pasture resources. This study investigates which is the higher thematic detail that is possible to achieve through remote sensing, to map the steppe vegetation, using medium resolution earth observation imagery in three districts (soums) of Mongolia: Dzag, Buutsagaan and Khureemaral. After considering different thematic levels of detail for classifying the steppe vegetation, the existent pasture types within the steppe were chosen to be mapped. In order to investigate which combination of data sets yields the best results and which classification algorithm is more suitable for incorporating these data sets, a comparison between different classification methods were tested for the study area. Sixteen classifications were performed using different combinations of estimators, Landsat-8 (spectral bands and Landsat-8 NDVI-derived) and geophysical data (elevation, mean annual precipitation and mean annual temperature) using two classification algorithms, maximum likelihood and decision tree. Results showed that the best performing model was the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), using the decision tree. For maximum likelihood, the model that incorporated Landsat-8 bands with mean annual precipitation (Model 5) and the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), achieved the higher accuracies for this algorithm. The decision tree models consistently outperformed the maximum likelihood ones.

A Modulated Closed Form solution for Quantitative Susceptibility Mapping - A thorough evaluation and comparison to iterative methods based on edge prior knowledge.

The aim of this study is to perform a thorough comparison of quantitative susceptibility mapping (QSM) techniques and their dependence on the assumptions made. The compared methodologies were: two iterative single orientation methodologies minimizing the l2, l1TV norm of the prior knowledge of the edges of the object, one over-determined multiple orientation method (COSMOS) and anewly proposed modulated closed-form solution (MCF). The performance of these methods was compared using a numerical phantom and in-vivo high resolution (0.65mm isotropic) brain data acquired at 7T using a new coil combination method. For all QSM methods, the relevant regularization and prior-knowledge parameters were systematically changed in order to evaluate the optimal reconstruction in the presence and absence of a ground truth. Additionally, the QSM contrast was compared to conventional gradient recalled echo (GRE) magnitude and R2* maps obtained from the same dataset. The QSM reconstruction results of the single orientation methods show comparable performance. The MCF method has the highest correlation (corrMCF=0.95, r(2)MCF =0.97) with the state of the art method (COSMOS) with additional advantage of extreme fast computation time. The l-curve method gave the visually most satisfactory balance between reduction of streaking artifacts and over-regularization with the latter being overemphasized when the using the COSMOS susceptibility maps as ground-truth. R2* and susceptibility maps, when calculated from the same datasets, although based on distinct features of the data, have a comparable ability to distinguish deep gray matter structures.

Mapping of Environmental Data Using Kernel-Based Methods

Recently, kernel-based Machine Learning methods have gained great popularity in many data analysis and data mining fields: pattern recognition, biocomputing, speech and vision, engineering, remote sensing etc. The paper describes the use of kernel methods to approach the processing of large datasets from environmental monitoring networks. Several typical problems of the environmental sciences and their solutions provided by kernel-based methods are considered: classification of categorical data (soil type classification), mapping of environmental and pollution continuous information (pollution of soil by radionuclides), mapping with auxiliary information (climatic data from Aral Sea region). The promising developments, such as automatic emergency hot spot detection and monitoring network optimization are discussed as well.

Data-driven topo-climatic mapping with machine learning methods

Automatic environmental monitoring networks enforced by wireless communication technologies provide large and ever increasing volumes of data nowadays. The use of this information in natural hazard research is an important issue. Particularly useful for risk assessment and decision making are the spatial maps of hazard-related parameters produced from point observations and available auxiliary information. The purpose of this article is to present and explore the appropriate tools to process large amounts of available data and produce predictions at fine spatial scales. These are the algorithms of machine learning, which are aimed at non-parametric robust modelling of non-linear dependencies from empirical data. The computational efficiency of the data-driven methods allows producing the prediction maps in real time which makes them superior to physical models for the operational use in risk assessment and mitigation. Particularly, this situation encounters in spatial prediction of climatic variables (topo-climatic mapping). In complex topographies of the mountainous regions, the meteorological processes are highly influenced by the relief. The article shows how these relations, possibly regionalized and non-linear, can be modelled from data using the information from digital elevation models. The particular illustration of the developed methodology concerns the mapping of temperatures (including the situations of Föhn and temperature inversion) given the measurements taken from the Swiss meteorological monitoring network. The range of the methods used in the study includes data-driven feature selection, support vector algorithms and artificial neural networks.