Improving knowledge management through the support of image examination and data annotation using DICOM structured reporting

[EN] An important effort has been invested on improving the image diagnosis process in different medical areas using information technologies. The field of medical imaging involves two main data types: medical imaging and reports. Developments based on the DICOM standard have demonstrated to be a convenient and widespread solution among the medical community. The main objective of this work is to design a Web application prototype that will be able to improve diagnosis and follow-on of breast cancer patients. It is based on TRENCADIS middleware, which provides a knowledge-oriented storage model composed by federated repositories of DICOM image studies and DICOM-SR medical reports. The full structure and contents of the diagnosis reports are used as metadata for indexing images. The TRENCADIS infrastructure takes full advantage of Grid technologies by deploying multi-resource grid services that enable multiple views (reports schemes) of the knowledge database. The paper presents a real deployment of such Web application prototype in the Dr. Peset Hospital providing radiologists with a tool to create, store and search diagnostic reports based on breast cancer explorations (mammography, magnetic resonance, ultrasound, pre-surgery biopsy and post-surgery biopsy), improving support for diagnostics decisions. A technical details for use cases (outlining enhanced multi-resource grid services communication and processing steps) and interactions between actors and the deployed prototype are described. As a result, information is more structured, the logic is clearer, network messages have been reduced and, in general, the system is more resistant to failures.The authors wish to thank the financial support received from The Spanish Ministry of Education and Science to develop the project "CodeCloud", with reference TIN2010-17804.Salavert Torres, J.; Segrelles Quilis, JD.; Blanquer Espert, I.; Hernández García, V. (2012). Improving knowledge management through the support of image examination and data annotation using DICOM structured reporting. Journal of Biomedical Informatics. 45(6):1066-1074. https://doi.org/10.1016/j.jbi.2012.07.004S1066107445

Content-Based Organisation of Virtual Repositories of DICOM Objects

The integration of multi-centre medical image data to create knowledge repositories for research and training activities has been an aim targeted since long ago. This paper presents an environment to share, to process and to organise medical imaging data according to a structured framework in which the image reports play a key role. This environment has been validated on a clinical environment, facing problems such as firewalls and security restrictions, in the frame of the CVIMO (Valencian Cyberinfrastructure of Medical Imaging in Oncology) project. The environment uses a middleware called TRENCADIS (Towards a Grid Environment for Processing and Sharing DICOM Objects) that provides users with the management of multiple administrative domains, data encryption and decryption on the fly and semantic indexation of images. Data is structured into four levels: Global data available, virtual federated storages of studies shared across a vertical domain, subsets for projects or experiments on the virtual storage and individual searches on these subsets. This structure of levels gives the needed flexibility for organising authorisation, and hides data that are not relevant for a given experiment. The main components and interactions are shown in the document, outlining the workflows and explaining the different approaches considered, including the protocols used and the difficulties met. © 2009 Elsevier B.V. All rights reserved.The authors wish to thanks the financial support received from Valencia Region Ministry of Enterprises, University (Conselleria de Empresa, Universidad y Ciencia) to develop the project "Ciberinfraestructura Valenciana de Imagen medica Oncologica", with reference GVEMP06/04.Blanquer Espert, I.; Hernández García, V.; Meseguer Anastasio, JE.; Segrelles Quilis, JD. (2009). Content-Based Organisation of Virtual Repositories of DICOM Objects. Future Generation Computer Systems. 25(6):627-637. https://doi.org/10.1016/j.future.2008.12.004S62763725

Automated tracking of quantitative assessments of tumor Burden in clinical trials

There are two key challenges hindering effective use of quantitative assessment of imaging in cancer response assessment: 1) Radiologists usually describe the cancer lesions in imaging studies subjectively and sometimes ambiguously, and 2) it is difficult to repurpose imaging data, because lesion measurements are not recorded in a format that permits machine interpretation and interoperability. We have developed a freely available software platform on the basis of open standards, the electronic Physician Annotation Device (ePAD), to tackle these challenges in two ways. First, ePAD facilitates the radiologist in carrying out cancer lesion measurements as part of routine clinical trial image interpretation workflow. Second, ePAD records all image measurements and annotations in a data format that permits repurposing image data for analyses of alternative imaging biomarkers of treatment response. To determine the impact of ePAD on radiologist efficiency in quantitative assessment of imaging studies, a radiologist evaluated computed tomography (CT) imaging studies from 20 subjects having one baseline and three consecutive follow-up imaging studies with and without ePAD. The radiologist made measurements of target lesions in each imaging study using Response Evaluation Criteria in Solid Tumors 1.1 criteria, initially with the aid of ePAD, and then after a 30-day washout period, the exams were reread without ePAD. The mean total time required to review the images and summarize measurements of target lesions was 15% (P < .039) shorter using ePAD than without using this tool. In addition, it was possible to rapidly reanalyze the images to explore lesion cross-sectional area as an alternative imaging biomarker to linear measure.We conclude that ePAD appears promising to potentially improve reader efficiency for quantitative assessment of CT examinations, and it may enable discovery of future novel image-based biomarkers of cancer treatment response.National Cancer Institute, National Institutes of Health (grant U01CA142555)National Council for Scientific and Technological Development (CNPq grant 481837/2008-6

Métodos computacionais para otimização de desempenho em redes de imagem médica

Over the last few years, the medical imaging has consolidated its position as a major mean of clinical diagnosis. The amount of data generated by the medical imaging practice is increasing tremendously. As a result, repositories are turning into rich databanks of semi-structured data related to patients, ailments, equipment and other stakeholders involved in the medical imaging panorama. The exploration of these repositories for secondary uses of data promises to elevate the quality standards and efficiency of the medical practice. However, supporting these advanced usage scenarios in traditional institutional systems raises many technical challenges that are yet to be overcome. Moreover, the reported poor performance of standard protocols opened doors to the general usage of proprietary solutions, compromising the interoperability necessary for supporting these advanced scenarios. This thesis has researched, developed, and now proposes a series of computer methods and architectures intended to maximize the performance of multi-institutional medical imaging environments. The methods are intended to improve the performance of standard protocols for medical imaging content discovery and retrieval. The main goal is to use them to increase the acceptance of vendor-neutral solutions through the improvement of their performance. Moreover, it intends to promote the adoption of such standard technologies in advanced scenarios that are still a mirage nowadays, such as clinical research or data analytics directly on top of live institutional repositories. Finally, these achievements will facilitate the cooperation between healthcare institutions and researchers, resulting in an increment of healthcare quality and institutional efficiency.As diversas modalidades de imagem médica têm vindo a consolidar a sua posição dominante como meio complementar de diagnóstico. O número de procedimentos realizados e o volume de dados gerados aumentou significativamente nos últimos anos, colocando pressão nas redes e sistemas que permitem o arquivo e distribuição destes estudos. Os repositórios de estudos imagiológicos são fontes de dados ricas contendo dados semiestruturados relacionados com pacientes, patologias, procedimentos e equipamentos. A exploração destes repositórios para fins de investigação e inteligência empresarial, tem potencial para melhorar os padrões de qualidade e eficiência da prática clínica. No entanto, estes cenários avançados são difíceis de acomodar na realidade atual dos sistemas e redes institucionais. O pobre desempenho de alguns protocolos standard usados em ambiente de produção, conduziu ao uso de soluções proprietárias nestes nichos aplicacionais, limitando a interoperabilidade de sistemas e a integração de fontes de dados. Este doutoramento investigou, desenvolveu e propõe um conjunto de métodos computacionais cujo objetivo é maximizar o desempenho das atuais redes de imagem médica em serviços de pesquisa e recuperação de conteúdos, promovendo a sua utilização em ambientes de elevados requisitos aplicacionais. As propostas foram instanciadas sobre uma plataforma de código aberto e espera-se que ajudem a promover o seu uso generalizado como solução vendor-neutral. As metodologias foram ainda instanciadas e validadas em cenários de uso avançado. Finalmente, é expectável que o trabalho desenvolvido possa facilitar a investigação em ambiente hospitalar de produção, promovendo, desta forma, um aumento da qualidade e eficiência dos serviços.Programa Doutoral em Engenharia Informátic

Biomedical Image Processing and Classification

Biomedical image processing is an interdisciplinary field involving a variety of disciplines, e.g., electronics, computer science, physics, mathematics, physiology, and medicine. Several imaging techniques have been developed, providing many approaches to the study of the human body. Biomedical image processing is finding an increasing number of important applications in, for example, the study of the internal structure or function of an organ and the diagnosis or treatment of a disease. If associated with classification methods, it can support the development of computer-aided diagnosis (CAD) systems, which could help medical doctors in refining their clinical picture

Arquiteturas federadas para integração de dados biomédicos

Doutoramento Ciências da ComputaçãoThe last decades have been characterized by a continuous adoption of IT solutions in the healthcare sector, which resulted in the proliferation of tremendous amounts of data over heterogeneous systems. Distinct data types are currently generated, manipulated, and stored, in the several institutions where patients are treated. The data sharing and an integrated access to this information will allow extracting relevant knowledge that can lead to better diagnostics and treatments. This thesis proposes new integration models for gathering information and extracting knowledge from multiple and heterogeneous biomedical sources. The scenario complexity led us to split the integration problem according to the data type and to the usage specificity. The first contribution is a cloud-based architecture for exchanging medical imaging services. It offers a simplified registration mechanism for providers and services, promotes remote data access, and facilitates the integration of distributed data sources. Moreover, it is compliant with international standards, ensuring the platform interoperability with current medical imaging devices. The second proposal is a sensor-based architecture for integration of electronic health records. It follows a federated integration model and aims to provide a scalable solution to search and retrieve data from multiple information systems. The last contribution is an open architecture for gathering patient-level data from disperse and heterogeneous databases. All the proposed solutions were deployed and validated in real world use cases.A adoção sucessiva das tecnologias de comunicação e de informação na área da saúde tem permitido um aumento na diversidade e na qualidade dos serviços prestados, mas, ao mesmo tempo, tem gerado uma enorme quantidade de dados, cujo valor científico está ainda por explorar. A partilha e o acesso integrado a esta informação poderá permitir a identificação de novas descobertas que possam conduzir a melhores diagnósticos e a melhores tratamentos clínicos. Esta tese propõe novos modelos de integração e de exploração de dados com vista à extração de conhecimento biomédico a partir de múltiplas fontes de dados. A primeira contribuição é uma arquitetura baseada em nuvem para partilha de serviços de imagem médica. Esta solução oferece um mecanismo de registo simplificado para fornecedores e serviços, permitindo o acesso remoto e facilitando a integração de diferentes fontes de dados. A segunda proposta é uma arquitetura baseada em sensores para integração de registos electrónicos de pacientes. Esta estratégia segue um modelo de integração federado e tem como objetivo fornecer uma solução escalável que permita a pesquisa em múltiplos sistemas de informação. Finalmente, o terceiro contributo é um sistema aberto para disponibilizar dados de pacientes num contexto europeu. Todas as soluções foram implementadas e validadas em cenários reais

Plataforma web de monitorização de dose de radiação em imagem clínica

Mestrado em Engenharia de Computadores e TelemáticaA monitorização sistemática da exposição dos cidadãos à radiação ionizante associada aos procedimentos imagiológicos é fundamental para garantir a qualidade dos serviços clínicos. Esta atividade é importante no controlo de desempenho, na optimização de protocolos e na rápida rectificação das práticas erradas. Em teoria, os episódios de radiodiagnóstico devem sempre manter a exposição à radiação tão baixa quanto razoavelmente possível (princípio ALARA), preservando a qualidade de diagnóstico. Os sistemas de monitorização de dose automáticos podem ser úteis em todas as fases de procedimentos radiológicos, ajudando os profissionais de saúde a melhorar os seus comportamentos de dosimetria. Mais ainda, a exposição aplicada nos procedimentos deve ser planeada individualmente, o que significa que a monitorização da dose também deverá ser. Além disso, o acesso integrado à história imagiológica do paciente pode ser útil para efetuar um melhor tratamento. No entanto, muitos dos atuais sistemas de informação não permitem efetuar análise de dose e a sua monitorização contínua é rara. Neste contexto, o contributo desta dissertação é o Dose Center, uma ferramenta centrada no paciente que permite monitorizar e analisar a dose de radiação. Ela tem capacidade para extrair informação proveniente de diferentes fontes e permite uma visualização integrada de toda a informação relativa aos pacientes, quais os estudos realizados, a dose efetiva e cumulativa de radiação. A ferramenta permite ainda sinalizar os casos que excedam os limites pré-definidos de radiação, uma inequívoca contribuição para a melhoria da segurança do paciente.Systematic monitoring of radiation dose exposure is a key factor to increase the quality of radiological services. This activity may lead to performance control, protocol optimization and rapid rectification of wrong practices. Moreover, dose monitoring can help the healthcare professionals to improve their dosimetric behaviors. In theory, radiodiagnostic episodes should always keep the radiation exposure as low as reasonably achievable (ALARA), while preserving the quality of diagnosis. Hence, the applied exposure in the radiology departments shall be individually planned, which means that the dose monitoring should be performed individually to ensure an appropriate dose usage. Automatic dose monitoring systems may be helpful during all the phases of radiologic procedures and the integrated access to imagiologic history may be helpful to do a better patient treatment. However, many of actual healthcare information systems do not allow dose analysis and its continuous monitoring is rare. In this context, this document proposes the Dose Center, a software platform that provides a patient-centric radiation dose analysis and a monitoring system that was designed to automatically extract and analyze dose reports captured from distinct data sources. It provides several data analytics views like, for instance, by modality or patient, including the studies effective and cumulative dose radiation. Cases exceeding the radiation thresholds are signalizing, contributing this way to improve the patient safety

Uma arquitectura segura e colaborativa para registos de saúde electrónicos com suporte a mobilidade

Doutoramento em InformáticaDurante as ultimas décadas, os registos de saúde eletrónicos (EHR) têm evoluído para se adaptar a novos requisitos. O cidadão tem-se envolvido cada vez mais na prestação dos cuidados médicos, sendo mais pró ativo e desejando potenciar a utilização do seu registo. A mobilidade do cidadão trouxe mais desafios, a existência de dados dispersos, heterogeneidade de sistemas e formatos e grande dificuldade de partilha e comunicação entre os prestadores de serviços. Para responder a estes requisitos, diversas soluções apareceram, maioritariamente baseadas em acordos entre instituições, regiões e países. Estas abordagens são usualmente assentes em cenários federativos muito complexos e fora do controlo do paciente. Abordagens mais recentes, como os registos pessoais de saúde (PHR), permitem o controlo do paciente, mas levantam duvidas da integridade clinica da informação aos profissionais clínicos. Neste cenário os dados saem de redes e sistemas controlados, aumentando o risco de segurança da informação. Assim sendo, são necessárias novas soluções que permitam uma colaboração confiável entre os diversos atores e sistemas. Esta tese apresenta uma solução que permite a colaboração aberta e segura entre todos os atores envolvidos nos cuidados de saúde. Baseia-se numa arquitetura orientada ao serviço, que lida com a informação clínica usando o conceito de envelope fechado. Foi modelada recorrendo aos princípios de funcionalidade e privilégios mínimos, com o propósito de fornecer proteção dos dados durante a transmissão, processamento e armazenamento. O controlo de acesso _e estabelecido por políticas definidas pelo paciente. Cartões de identificação eletrónicos, ou certificados similares são utilizados para a autenticação, permitindo uma inscrição automática. Todos os componentes requerem autenticação mútua e fazem uso de algoritmos de cifragem para garantir a privacidade dos dados. Apresenta-se também um modelo de ameaça para a arquitetura, por forma a analisar se as ameaças possíveis foram mitigadas ou se são necessários mais refinamentos. A solução proposta resolve o problema da mobilidade do paciente e a dispersão de dados, capacitando o cidadão a gerir e a colaborar na criação e manutenção da sua informação de saúde. A arquitetura permite uma colaboração aberta e segura, possibilitando que o paciente tenha registos mais ricos, atualizados e permitindo o surgimento de novas formas de criar e usar informação clínica ou complementar.Since their early adoption Electronic Health Records (EHR) have been evolving to cope with increasing requirements from institutions, professionals and, more recently, from patients. Citizens became more involved demanding successively more control over their records and an active role on their content. Mobility brought also new requirements, data become scattered over heterogeneous systems and formats, with increasing di culties on data sharing between distinct providers. To cope with these challenges several solutions appeared, mostly based on service level agreements between entities, regions and countries. They usually required de ning complex federated scenarios and left the patient outside the process. More recent approaches, such as personal health records (PHR), enable patient control although raises clinical integrity doubts to other actors, such as physicians. Also, information security risk increase as data travels outside controlled networks and systems. To overcome this, new solutions are needed to facilitate trustable collaboration between the diverse actors and systems. In this thesis we present a solution that enables a secure and open collaboration between all healthcare actors. It is based on a service-oriented architecture that deals with the clinical data using a closed envelope concept. The architecture was modeled with minimal functionality and privileges bearing in mind strong protection of data during transmission, processing and storing. The access control is made through patient policies and authentication uses electronic identi cation cards or similar certi cates, enabling auto-enrollment. All the components require mutual authentication and uses cyphering mechanisms to assure privacy. We also present a threat model to verify, through our solution, if possible threats were mitigated or if further re nement is needed. The proposed solution solves the problem of patient mobility and data dispersion, and empowers citizens to manage and collaborate in their personal healthcare information. It also permits open and secure collaboration, enabling the patient to have richer and up to date records that can foster new ways to generate and use clinical or complementary information