A Community-Driven Validation Service for Standard Medical Imaging Objects

Digital medical imaging laboratories contain many distinct types of equipment provided by different manufacturers. Interoperability is a critical issue and the DICOM protocol is a de facto standard in those environments. However, manufacturers' implementation of the standard may have non-conformities at several levels, which will hinder systems' integration. Moreover, medical staff may be responsible for data inconsistencies when entering data. Those situations severely affect the quality of healthcare services since they can disrupt system operations. The existence of software able to confirm data quality and compliance with the DICOM standard is important for programmers, IT staff and healthcare technicians. Although there are a few solutions that try to accomplish this goal, they are unable to deal with certain situations that require user input. Furthermore, these cases usually require the setup of a working environment, which makes the sharing of validation information more difficult. This article proposes and describes the development of a Web DICOM validation service for the community. This solution requires no configuration by the user, promotes validation results share-ability in the community and preserves patient data privacy since files are de-identified on the client side.Comment: Computer Standards & Interfaces, 201

Integrating Clinical Trial Imaging Data Resources Using Service-Oriented Architecture and Grid Computing

Clinical trials which use imaging typically require data management and workflow integration across several parties. We identify opportunities for all parties involved to realize benefits with a modular interoperability model based on service-oriented architecture and grid computing principles. We discuss middleware products for implementation of this model, and propose caGrid as an ideal candidate due to its healthcare focus; free, open source license; and mature developer tools and support

Grid Analysis of Radiological Data

IGI-Global Medical Information Science Discoveries Research Award 2009International audienceGrid technologies and infrastructures can contribute to harnessing the full power of computer-aided image analysis into clinical research and practice. Given the volume of data, the sensitivity of medical information, and the joint complexity of medical datasets and computations expected in clinical practice, the challenge is to fill the gap between the grid middleware and the requirements of clinical applications. This chapter reports on the goals, achievements and lessons learned from the AGIR (Grid Analysis of Radiological Data) project. AGIR addresses this challenge through a combined approach. On one hand, leveraging the grid middleware through core grid medical services (data management, responsiveness, compression, and workflows) targets the requirements of medical data processing applications. On the other hand, grid-enabling a panel of applications ranging from algorithmic research to clinical use cases both exploits and drives the development of the services

Healthcare systems protection: All-in-one cybersecurity approach

Cyber risks are increasingly widespread as healthcare organizations play a defining role in society. Several studies have revealed an increase in cybersecurity threats in the industry, which should concern us all. When it comes to cybersecurity, the consequences can be felt throughout the organization, from the smallest processes to the overall ability of the organization to function. Typically, a cyberattack results in the disclosure of confidential information that undermines your competitive advantage and overall trust. Healthcare as a critical sector has, like many other sectors, a late bet on its transformation to cybersecurity across the board. This dissertation reinforces this need by presenting a value-added solution that helps strengthen the internal processes of healthcare units, enabling their primary mission of saving lives while ensuring the confidentiality and security of patient and institutional data. The solution is presented as a technological composite that translates into a methodology and innovative artifact for integration, monitoring, and security of critical medical infrastructures based on operational use cases. The approach that involves people, processes, and technology is based on a model that foresees the evaluation of potential assets for integration and monitoring, as well as leveraging the efficiency in responding to security incidents with the formal development of a process and mechanisms for alert and resolution of exposure and attack scenarios. On a technical level, the artifact relies on the integration of a medical image archiving system (PACS) into a SIEM to validate application logs that are linked to rules to map anomalous behaviors that trigger the incident management process on an IHS platform with custom-developed features. The choice for integration in the validation prototype of the PACS system is based not only on its importance in the orchestration of activities in the organization of a health institution, but also with the recent recommendations of various cybersecurity agencies and organizations for the importance of their protection in response to the latest trends in cyberattacks. In line with the results obtained, this approach will have full applicability in a real operational context, following the latest practices and technologies in the sector.Os riscos cibernéticos estão cada vez mais difundidos à medida que as organizações de cuidados de saúde desempenham um papel determinante na sociedade. Vários estudos revelaram um aumento das ameaças de cibersegurança no setor, o que nos deve preocupar a todos. Quando se trata de cibersegurança, as consequências podem ser sentidas em toda a organização, desde os mais pequenos processos até à sua capacidade global de funcionamento. Normalmente, um ciberataque resulta na divulgação de informações confidenciais que colocam em causa a sua vantagem competitiva e a confiança geral. O healthcare como setor crítico apresenta, como muitos outros setores, uma aposta tardia na sua transformação para a cibersegurança de forma generalizada. Esta dissertação reforça esta necessidade apresentando uma solução de valor acrescentado que ajuda a potenciar os processos internos das unidades de saúde possibilitando a sua missão principal de salvar vidas, aumentando a garantia de confidencialidade e segurança dos dados dos pacientes e instituições. A solução apresenta-se como um compósito tecnológico que se traduz numa metodologia e artefacto de inovação para integração, monitorização e segurança de infraestruturas médicas críticas baseado em use cases de operação. A abordagem que envolve pessoas, processos e tecnologia assenta num modelo que prevê a avaliação de potenciais ativos para integração e monitorização, como conta alavancar a eficiência na resposta a incidentes de segurança com o desenvolvimento formal de um processo e mecanismos para alerta e resolução de cenários de exposição e ataque. O artefacto, a nível tecnológico, conta com a integração do sistema de arquivo de imagem médica (PACS) num SIEM para validação de logs aplicacionais que estão associados a regras que mapeiam comportamentos anómalos que originam o despoletar do processo de gestão de incidentes numa plataforma IHS com funcionalidades desenvolvidas à medida. A escolha para integração no protótipo de validação do sistema PACS tem por base não só a sua importância na orquestração de atividades na orgânica duma instituição de saúde, mas também com as recentes recomendações de várias agências e organizações de cibersegurança para a importância da sua proteção em resposta às últimas tendências de ciberataques. Em linha com os resultados auscultados, esta abordagem terá total aplicabilidade em contexto real de operação, seguindo as mais recentes práticas e tecnologias no sector

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

The Impact of Grid on Health Care Digital Repositories

Grid computing has attracted worldwide attention in a variety of applications like Health Care. In this paper we identified the Grid services that could facilitate the integration and interoperation of Health Care data and frameworks world-wide. While many of the current Health Care Grid projects address issues such as data location and description on the Grid and the security aspects, the problems connected to data storage, integrity, preservation and distribution have been neglected. We describe the currently available Grid storage services and protocols that can come in handy when dealing with those problems. We further describe a Grid infrastructure to build a cooperative Health Care environment based on currently available Grid services and a service able to validate it

DigiPatICS: Digital Pathology Transformation of the Catalan Health Institute Network of 8 Hospitals—Planification, Implementation, and Preliminary Results

Artificial intelligence; Digital pathology; ImplementationInteligencia artificial; Patología digital; ImplementaciónIntel·ligència artificial; Patologia digital; ImplementacióComplete digital pathology transformation for primary histopathological diagnosis is a challenging yet rewarding endeavor. Its advantages are clear with more efficient workflows, but there are many technical and functional difficulties to be faced. The Catalan Health Institute (ICS) has started its DigiPatICS project, aiming to deploy digital pathology in an integrative, holistic, and comprehensive way within a network of 8 hospitals, over 168 pathologists, and over 1 million slides each year. We describe the bidding process and the careful planning that was required, followed by swift implementation in stages. The purpose of the DigiPatICS project is to increase patient safety and quality of care, improving diagnosis and the efficiency of processes in the pathological anatomy departments of the ICS through process improvement, digital pathology, and artificial intelligence tools.This project was funded by European Regional Development Funds, Programa operatiu FEDER de Catalunya 2014–2020 and SA18-014623 DIGIPATICS. UPC activity in this project was partially supported by PID2020-116907RB-I00 and funded by MCIN/AEI/10.13039/501100011033

DigiPatICS: Digital Pathology Transformation of the Catalan Health Institute Network of 8 hospitals—planification, implementation, and preliminary results

Complete digital pathology transformation for primary histopathological diagnosis is a challenging yet rewarding endeavor. Its advantages are clear with more efficient workflows, but there are many technical and functional difficulties to be faced. The Catalan Health Institute (ICS) has started its DigiPatICS project, aiming to deploy digital pathology in an integrative, holistic, and comprehensive way within a network of 8 hospitals, over 168 pathologists, and over 1 million slides each year. We describe the bidding process and the careful planning that was required, followed by swift implementation in stages. The purpose of the DigiPatICS project is to increase patient safety and quality of care, improving diagnosis and the efficiency of processes in the pathological anatomy departments of the ICS through process improvement, digital pathology, and artificial intelligence tools.This project was funded by European Regional Development Funds, Programa operatiu FEDER de Catalunya 2014–2020 and SA18-014623 DIGIPATICS. UPC activity in this project was partially supported by PID2020-116907RB-I00 and funded by MCIN/AEI/10.13039/501100011033Peer ReviewedArticle signat per 18 autors/es: Jordi Temprana-Salvador (1), Pablo López-García (2), Josep Castellví Vives (1),Lluís de Haro (2), Eudald Ballesta (2), Matias Rojas Abusleme (3), Miquel Arrufat (4), Ferran Marques (5), Josep R. Casas (5),Carlos Gallego (6), Laura Pons (7), José Luis Mate (7), Pedro Luis Fernández (7), Eugeni López-Bonet (8), Ramon Bosch (9), Salomé Martínez (10), Santiago Ramón y Cajal (1), and Xavier Matias-Guiu (11,12) // (1) Department of Pathology, Vall d’Hebron University Hospital, CIBERONC, 08035 Barcelona, Spain; (2) Functional Competence Center, Information Systems, Catalan Health Institute (Institut Català de la Salut), 08006 Barcelona, Spain; (3) Center for Telecommunications and Information Technology (Centre de Telecomunicacions i Tecnologies de la Informació, CTTI), Catalan Health Institute (Institut Català de la Salut), 08006 Barcelona, Spain; (4) Economic and Financial Management, Catalan Health Institute (Institut Català de la Salut), 08006 Barcelona, Spain; (5) Image Processing Group, Technical University of Catalonia (UPC), 08034 Barcelona, Spain; (6) Digital Medical Imaging System of Catalonia (SIMDCAT), TIC Salut, 08005 Barcelona, Spain, (7) Department of Pathology, Germans Trias i Pujol University Hospital, 08916 Badalona, Spain; (8) Department of Pathology, Doctor Josep Trueta Hospital of Girona, 17007 Girona, Spain; (9) Department of Pathology, Verge de la Cinta Hospital of Tortosa, 43500 Tarragona, Spain; (10) Department of Pathology, Joan XXIII University Hospital of Tarragona, 43005 Tarragona, Spain; (11) Department of Pathology, Arnau de Vilanova University Hospital, 25198 Lleida, Spain, (12) Department of Pathology, Bellvitge University Hospital, CIBERONC, 08907 Barcelona, SpainPostprint (published version