Diagnostic approach in a patient with Creutzfeldt-Jakob disease / Abordagem diagnóstica em uma paciente com doença de Creutzfeldt-Jakob

ABSTRACT Prion diseases are an important cause of rapidly progressive dementias. Among them, the most common is sporadic Creutzfeldt-Jakob disease (CJD). It is a rare and incurable disease, with rapid progression to death. Objective: To describe the diagnostic approach of a patient with Creutzfeldt-Jakob disease. Methods: The diagnosis is established through the clinical picture associated with characteristic changes in the brain magnetic resonance imaging, the electroencephalogram, and analysis of specific changes in the cerebrospinal fluid. Results: The present report describes the case of a 53-year-old patient in the city of Fortaleza-CE. The diagnosis was made based on the clinical condition and through diagnostic tests, including 14-3-3 protein and RT QUIC analysis. Differential diagnosis was performed with other rapidly progressive causes, such as infectious and immune-mediated diseases. Conclusions: The diagnosis of probable sporadic CJD was established.

RESUMO As doenças priônicas são uma importante causa de demências rapidamente progressivas. Entre elas, a mais comum é a doença de Creutzfeldt-Jakob (DCJ) esporádica. É uma enfermidade rara e incurável, com rápida progressão para óbito. Objetivo: Descrever a abordagem diagnóstica de uma paciente com doença de Creutzfeldt-Jakob. Métodos: O diagnóstico é estabelecido pelo quadro clínico associado a alterações características na ressonância magnética cerebral, no eletroencefalograma e pela análise de alterações específicas no líquido cefalorraquidiano. Resultados: O presente relato descreve o caso de um paciente de 53 anos na cidade de Fortaleza (CE). O diagnóstico foi feito com base na condição clínica e por meio de testes diagnósticos, incluindo proteína 14-3-3 e análise Real-Time Quaking-Induced Conversion (RT QUIC). O diagnóstico diferencial foi realizado com outras causas rapidamente progressivas, como doenças infecciosas e imunomediadas. Conclusões: Por fim, foi estabelecido o diagnóstico de provável DCJ esporádica.

Diagnostic approach in a patient with Creutzfeldt-Jakob disease.

Prion diseases are an important cause of rapidly progressive dementias. Among them, the most common is sporadic Creutzfeldt-Jakob disease (CJD). It is a rare and incurable disease, with rapid progression to death. Objective: To describe the diagnostic approach of a patient with Creutzfeldt-Jakob disease. Methods: The diagnosis is established through the clinical picture associated with characteristic changes in the brain magnetic resonance imaging, the electroencephalogram, and analysis of specific changes in the cerebrospinal fluid. Results: The present report describes the case of a 53-year-old patient in the city of Fortaleza-CE. The diagnosis was made based on the clinical condition and through diagnostic tests, including 14-3-3 protein and RT QUIC analysis. Differential diagnosis was performed with other rapidly progressive causes, such as infectious and immune-mediated diseases. Conclusions: The diagnosis of probable sporadic CJD was established.

As doenças priônicas são uma importante causa de demências rapidamente progressivas. Entre elas, a mais comum é a doença de Creutzfeldt-Jakob (DCJ) esporádica. É uma enfermidade rara e incurável, com rápida progressão para óbito. Objetivo: Descrever a abordagem diagnóstica de uma paciente com doença de Creutzfeldt-Jakob. Métodos: O diagnóstico é estabelecido pelo quadro clínico associado a alterações características na ressonância magnética cerebral, no eletroencefalograma e pela análise de alterações específicas no líquido cefalorraquidiano. Resultados: O presente relato descreve o caso de um paciente de 53 anos na cidade de Fortaleza (CE). O diagnóstico foi feito com base na condição clínica e por meio de testes diagnósticos, incluindo proteína 14-3-3 e análise Real-Time Quaking-Induced Conversion (RT QUIC). O diagnóstico diferencial foi realizado com outras causas rapidamente progressivas, como doenças infecciosas e imunomediadas. Conclusões: Por fim, foi estabelecido o diagnóstico de provável DCJ esporádica.

Applying Fully Convolutional Architectures for Semantic Segmentation of a Single Tree Species in Urban Environment on High Resolution UAV Optical Imagery.

This study proposes and evaluates five deep fully convolutional networks (FCNs) for the semantic segmentation of a single tree species: SegNet, U-Net, FC-DenseNet, and two DeepLabv3+ variants. The performance of the FCN designs is evaluated experimentally in terms of classification accuracy and computational load. We also verify the benefits of fully connected conditional random fields (CRFs) as a post-processing step to improve the segmentation maps. The analysis is conducted on a set of images captured by an RGB camera aboard a UAV flying over an urban area. The dataset also contains a mask that indicates the occurrence of an endangered species called Dipteryx alata Vogel, also known as cumbaru, taken as the species to be identified. The experimental analysis shows the effectiveness of each design and reports average overall accuracy ranging from 88.9% to 96.7%, an F1-score between 87.0% and 96.1%, and IoU from 77.1% to 92.5%. We also realize that CRF consistently improves the performance, but at a high computational cost.

Assessment of CNN-Based Methods for Individual Tree Detection on Images Captured by RGB Cameras Attached to UAVs.

Detection and classification of tree species from remote sensing data were performed using mainly multispectral and hyperspectral images and Light Detection And Ranging (LiDAR) data. Despite the comparatively lower cost and higher spatial resolution, few studies focused on images captured by Red-Green-Blue (RGB) sensors. Besides, the recent years have witnessed an impressive progress of deep learning methods for object detection. Motivated by this scenario, we proposed and evaluated the usage of Convolutional Neural Network (CNN)-based methods combined with Unmanned Aerial Vehicle (UAV) high spatial resolution RGB imagery for the detection of law protected tree species. Three state-of-the-art object detection methods were evaluated: Faster Region-based Convolutional Neural Network (Faster R-CNN), YOLOv3 and RetinaNet. A dataset was built to assess the selected methods, comprising 392 RBG images captured from August 2018 to February 2019, over a forested urban area in midwest Brazil. The target object is an important tree species threatened by extinction known as Dipteryx alata Vogel (Fabaceae). The experimental analysis delivered average precision around 92% with an associated processing times below 30 miliseconds.

Automatic tracking of vessel-like structures from a single starting point.

The identification of vascular networks is an important topic in the medical image analysis community. While most methods focus on single vessel tracking, the few solutions that exist for tracking complete vascular networks are usually computationally intensive and require a lot of user interaction. In this paper we present a method to track full vascular networks iteratively using a single starting point. Our approach is based on a cloud of sampling points distributed over concentric spherical layers. We also proposed a vessel model and a metric of how well a sample point fits this model. Then, we implement the network tracking as a min-cost flow problem, and propose a novel optimization scheme to iteratively track the vessel structure by inherently handling bifurcations and paths. The method was tested using both synthetic and real images. On the 9 different data-sets of synthetic blood vessels, we achieved maximum accuracies of more than 98%. We further use the synthetic data-set to analyze the sensibility of our method to parameter setting, showing the robustness of the proposed algorithm. For real images, we used coronary, carotid and pulmonary data to segment vascular structures and present the visual results. Still for real images, we present numerical and visual results for networks of nerve fibers in the olfactory system. Further visual results also show the potential of our approach for identifying vascular networks topologies. The presented method delivers good results for the several different datasets tested and have potential for segmenting vessel-like structures. Also, the topology information, inherently extracted, can be used for further analysis to computed aided diagnosis and surgical planning. Finally, the method's modular aspect holds potential for problem-oriented adjustments and improvements.

Urban area extent extraction in spaceborne HR and VHR data using multi-resolution features.

Detection of urban area extents by means of remotely sensed data is a difficult task, especially because of the multiple, diverse definitions of what an "urban area" is. The models of urban areas listed in technical literature are based on the combination of spectral information with spatial patterns, possibly at different spatial resolutions. Starting from the same data set, "urban area" extraction may thus lead to multiple outputs. If this is done in a well-structured framework, however, this may be considered as an advantage rather than an issue. This paper proposes a novel framework for urban area extent extraction from multispectral Earth Observation (EO) data. The key is to compute and combine spectral and multi-scale spatial features. By selecting the most adequate features, and combining them with proper logical rules, the approach allows matching multiple urban area models. Experimental results for different locations in Brazil and Kenya using High-Resolution (HR) data prove the usefulness and flexibility of the framework.

Geographic Object-Based Image Analysis - Towards a new paradigm.

The amount of scientific literature on (Geographic) Object-based Image Analysis - GEOBIA has been and still is sharply increasing. These approaches to analysing imagery have antecedents in earlier research on image segmentation and use GIS-like spatial analysis within classification and feature extraction approaches. This article investigates these development and its implications and asks whether or not this is a new paradigm in remote sensing and Geographic Information Science (GIScience). We first discuss several limitations of prevailing per-pixel methods when applied to high resolution images. Then we explore the paradigm concept developed by Kuhn (1962) and discuss whether GEOBIA can be regarded as a paradigm according to this definition. We crystallize core concepts of GEOBIA, including the role of objects, of ontologies and the multiplicity of scales and we discuss how these conceptual developments support important methods in remote sensing such as change detection and accuracy assessment. The ramifications of the different theoretical foundations between the 'per-pixel paradigm' and GEOBIA are analysed, as are some of the challenges along this path from pixels, to objects, to geo-intelligence. Based on several paradigm indications as defined by Kuhn and based on an analysis of peer-reviewed scientific literature we conclude that GEOBIA is a new and evolving paradigm.

The introduction of navigation in liver surgery in Brazil.

The authors thoroughly report the development, the technical aspects and the performance of the first navigated liver resections, by laparotomy and laparoscopy, in Brazil, done at the National Cancer Institute, Ministry of Health, using a surgical navigator.

Immunoexpression of cyclooxygenase-2 in primary gastric carcinomas and lymph node metastases.

AIM: To evaluate immunoexpression of cyclooxygenase-2 (COX-2) in primary gastric carcinomas and respective lymph node metastases. METHODS: Immunohistochemistry to analyze COX-2 expression was performed on tissue microarray slices obtained from 36 specimens of gastrectomy and satellite lymph nodes from patients with gastric carcinoma. RESULTS: Immunostaining was seen in most cases, and COX-2 expression was higher in lymph node metastases than in corresponding primary gastric tumors of intestinal, diffuse and mixed carcinomas, with a statistically significant difference in the diffuse histotype (P = 0.0108). CONCLUSION: COX-2 immunoexpression occurs frequently in primary gastric carcinomas, but higher expression of this enzyme is observed in lymph node metastases of the diffuse histotype.

Avaliação da capacidade cardiorrespiratória (vo2máx) em policiais militares, com testes indiretos / Assessment of cardiorespiratory fitness (VO2máx) in the military police of, with indirect tests

O objetivo deste estudo foi avaliar o (VO2máx) de militares com testes indiretos de 1600m (ALMEIDA et al., 2010) e 12min (COOPER,1968). Participaram 49 militares masculinos, aptos fisicamente, média de idade de 25,6 ±3,10 anos, IMC 23 ±1,4 Kg.m2, selecionados aleatoriamente. O (VO2máx) foi mensurado através das equações de Cooper e Almeida após os testes; coletados e analisados os parâmetros fisiológicos: frequência cardíaca, glicemia e lactato pré e pós-testes e percepção subjetiva do esforço ao final. Observou-se grande fidedignidade entre eles, sendo o valor do (VO2máx) de 1600m (43,63±3,21) superior ao de 12min (39,42±4,18), mostrando aumento significativo (p<0,0001), atribuída à potência de exercício desenvolvida durante o teste, que pode ser observada nos valores de lactato no de 1600m. A prova de 1600m, mostrou-se como uma alternativa eficaz na mensuração do (VO2máx) em militares, portanto sendo uma medida indireta de baixo custo e fácil uso e de grande valia sua aplicabilidade nas Instituições Militares.

The objective of this research was to evaluate the (VO2máx), in indirect tests of 1600m (Almeida et al., 2010) and 12 min (Cooper, 1968). 49 physically fit military aged 25.6±3.10 years, BMI23±1.4 kg.m2, where randomly chosen according to the inclusion criteria of the research took part of it. The (VO2máx) was measured through COOPER and Almeida equations after the tests of 1600m and 12min run, collected and analyzed physiological parameters of cardiac frequency glycemia and lactate were collected before and after the tests. Besides, the subjective perception of effort at the end of each test was evaluated. Through the physiological parameters, it could be observed a great reliability between the 1600m and 12min run tests, in which the (vo2máx) value in the former (43.63±3.21) was higher than in the latter test (39.42±4.18), showing a significant incriase (p<0.0001), attributed to the power developedduring the exercise test, which can be observed for lactate in the 1600m. The 1600m test, proved to be an effective alternative in measuring (vo2máx) in milytary, being an indirect measure of cost and ease of use and great value for their applicability in the military institutions.

Segmentation of liver, its vessels and lesions from CT images for surgical planning.

BACKGROUND: Cancer treatments are complex and involve different actions, which include many times a surgical procedure. Medical imaging provides important information for surgical planning, and it usually demands a proper segmentation, i.e., the identification of meaningful objects, such as organs and lesions. This study proposes a methodology to segment the liver, its vessels and nodules from computer tomography images for surgical planning. METHODS: The proposed methodology consists of four steps executed sequentially: segmentation of liver, segmentation of vessels and nodules, identification of hepatic and portal veins, and segmentation of Couinaud anatomical segments. Firstly, the liver is segmented by a method based on a deformable model implemented through level sets, of which parameters are adjusted by using a supervised optimization procedure. Secondly, a mixture model is used to segment nodules and vessels through a region growing process. Then, the identification of hepatic and portal veins is performed using liver anatomical knowledge and a vein tracking algorithm. Finally, the Couinaud anatomical segments are identified according to the anatomical liver model proposed by Couinaud. RESULTS: Experiments were conducted using data and metrics brought from the liver segmentation competition held in the Sliver07 conference. A subset of five exams was used for estimation of segmentation parameter values, while 15 exams were used for evaluation. The method attained a good performance in 17 of the 20 exams, being ranked as the 6th best semi-automatic method when comparing to the methods described on the Sliver07 website (2008). It attained visual consistent results for nodules and veins segmentation, and we compiled the results, showing the best, worst, and mean results for all dataset. CONCLUSIONS: The method for liver segmentation performed well, according to the results of the numerical evaluation implemented, and the segmentation of liver internal structures were consistent with the anatomy of the liver, as confirmed by a specialist. The analysis provided evidences that the method to segment the liver may be applied to segment other organs, especially to those whose distribution of voxel intensities is nearly Gaussian shaped.