Gender differences in prognostic factors for oral cancer.

The aim of this study was to assess gender differences in prognostic factors among patients treated surgically for oral squamous cell carcinoma (OSCC). The medical records of 477 eligible patients (345 males, 132 females) obtained from the Brazilian Cancer Institute were reviewed. Survival was calculated by Kaplan-Meier method. Cox regression models were used to obtain adjusted hazard ratios (aHR) for males and females. Multivariate analysis showed that past tobacco use (aHR 0.2, 95% confidence interval (CI) 0.1-0.7) and regional metastasis (aHR 2.3, 95% CI 1.5-3.5) in males, and regional metastasis (aHR 2.2, 95% CI 1.2-4.3), distant metastasis (aHR 6.7, 95% CI 1.3-32.7), and hard palate tumours (aHR 11.8, 95% CI 3.3-47.7) in females, were associated with a higher risk of death. There were no differences in survival between males and females. Regional metastasis was found to be a negative prognostic factor in OSCC for both genders. Past tobacco use was an independent prognostic factor for worse survival among males, while distant metastasis and hard palate tumours were independent prognostic factors for worse survival among females. Further studies are necessary to corroborate the relationships found in this study.

Mobile health in emerging countries: a survey of research initiatives in Brazil.

OBJECTIVE: To conduct a comprehensive survey of mobile health (mHealth) research initiatives in Brazil, discussing current challenges, gaps, opportunities and tendencies. METHODS: Systematic review of publicly available electronic documents related to mHealth, including scientific publications, technical reports and descriptions of commercial products. Specifically, 42 projects are analyzed and classified according to their goals. This analysis considers aspects such as security features provided (if any), the health condition that are focus of attention, the main providers involved in the projects development and deployment, types of devices used, target users, where the projects are tested and/or deployed, among others. RESULTS: The study shows a large number (86%) of mHealth solutions focused on the following categories: health surveys, surveillance, patient records and monitoring. Meanwhile, treatment compliance, awareness raising and decision support systems are less explored. The main providers of solutions are the universities (56%) and health units (32%), with considerable cooperation between such entities. Most applications have physicians (55%) and Community Health Agents (CHAs) (33%) as targeted users, the latter being important elements in nation-wide governmental health programs. Projects focused on health managers, however, are a minority (5%). The majority of projects do not focus on specific diseases but rather general health (57%), although solutions for hearth conditions are reasonably numerous (21%). Finally, the lack of security mechanisms in the majority of the surveyed solutions (52%) may hinder their deployment in the field due to the lack of compliance with general regulations for medical data handling. CONCLUSION: There are currently many mHealth initiatives in Brazil, but some areas have not been much explored, such as solutions for treatment compliance and awareness raising, as well as decision support systems. Another research trend worth exploring refers to creating interoperable security mechanisms, especially for widely explored mHealth categories such as health surveys, patient records and monitoring. Challenges for the expansion of mHealth solutions, both in number and coverage, include the further involvement of health managers in the deployment of such solutions and in coordinating efforts among health and research institutions interested in the mHealth trend, possibly exploring the widespread presence of CHAs around the country as users of such technology.

Multiscale representation for automatic identification of structures in medical images.

The identification of structures is a key step in several applications of medical imaging. In this work we propose a method for the identification of structures using a multiscale approach with inclusion of a priori information about the searched objects. After describing the image structures in the multiscale representation, a matching step determines which structure most likely corresponds to the target. Patterns are generated by previous application of the method to a set of images. We present a prototype for identifying structures in 2D images. A set of experiments was carried out to evaluate the prototype leading to encouraging results.

Prontuário eletrônico de pacientes: integrando informações clínicas e imagens médicas / Eletronic patient record: integrating clinical information and image data

O Instituto do Coração tem envidado esforços para integrar todas as informações clínicas dentro da Instituição. Nos últimos anos o InCor implementou com sucesso um sistema para transmissão, arquivamento, recuperação, processamento e visualização de Imagens Médicas e um Sistema de Informações Hospitalares (HIS) que armazena as informações administrativas e clínicas. A integração desses subsistemas forma o Prontuário Eletrônico do Paciente (PEP). O InCor é um dos seis Institutos que compõem o Hospital das Clínicas da Universidade de São Paulo. Como cada um dos Institutos possui o seu próprio sistema de informações, a troca de informações entre os Institutos é também uma questão muito relevante. Este trabalho apresenta a experiência no desenvolvimento de um Prontuário Eletrônico funcional e completo, que inclui controle de acesso, exames laboratoriais, imagens (estáticas, dinâmicas e 3D), laudos, documentos e mesmo sinais vitais de tempo real. Este artigo também discute a modelagem e implantação de um protótipo de um PEP distribuído e homogêneo. Atualmente, um volume superior a 2,5 TB de imagens DICOM já foi armazenado utilizando a arquitetura proposta. Diariamente, o PEP armazena mais de 5GB de dados e tem uma quantidade de acessos superior a 300 usuários. O sistema de armazenamento permite uma visibilidade de seis meses para acesso imediato e mais de dois anos para acesso automático utilizando uma jukebox

The Heart Institute (InCor) of São Paulo has been committed to the goal of integrating all clinical information within the institution. In the last few years, InCor has successfully created a system for transmission, archiving, retrieval, processing and visualization of Medical Images and a Hospital Information System (HIS) that stores the institution administrative and clinical information. These integrated subsystems form InCor's Electronic Patient Record (EPR). Since InCor is one of the six institutes of the University of São Paulo Medical School Hospital (HC) and each institute has its own information system, exchanging information among the institutes is also a very important issue. This work describes the experience in the effort to develop a functional and comprehensive EPR, which includes access control, lab exams, images (static, dynamic and 3D), clinical reports, documents and even real-time vital signals. This paper addresses also the design and prototype for integration of distributed and heterogeneous EPR. Currently, more than 2.5 TB of DICOM images, have been stored using the proposed architecture. The EPR stores more than 5 GB/day of data and presents more than 300 hits per day. The proposed storage subsystem allow six months of visibility for rapid retrieval (online mode) and more than two years for automatic retrieval using the jukebox

Lossy compression techniques, medical images, and the clinician.

There has been increasing interest in the storage and retrieval of medical images in hospitals and clinics here in Brazil and elsewhere. At the Heart Institute of São Paulo, with thousands of image-based procedures performed each month, the pursuit of optimal transmission and storage methods for digital images is a major concern. The use of data-compression techniques can reduce the enormous amount of imaging data to be stored or transmitted across a computer network, so that the efficiency of the computing system is preserved. The techniques for image compression can be categorized as "lossless" or "lossy," with "lossy" techniques being those in which some, supposedly irrelevant information is lost. Lossy techniques are much more efficient than lossless ones, achieving data-compression ratios as high as 100:1.

Lossy compression in nuclear medicine images.

The goal of image compression is to reduce the amount of data needed to represent images. In medical applications, it is not desirable to lose any information and thus lossless compression methods are often used. However, medical imaging systems have intrinsic noise associated to it. The application of a lossy technique, which acts as a low pass filter, reduces the amount of data at a higher rate without any noticeable loss in the information contained in the images. We have compressed images of nuclear medicine using the discrete cosine transform algorithm. The decompressed images were considered reliable for visual inspection. Furthermore, a parameter was computed from these images and no discernible change was found from the results obtained using the original uncompressed images.