KEYWORDS: Medical imaging, Imaging systems, Clouds, Picture Archiving and Communication System, Information security, Medicine, Systems modeling, Computer security, Control systems, Diagnostics
The evolution of cloud computing is driving the next generation of medical imaging systems. However, privacy and security concerns have been consistently regarded as the major obstacles for adoption of cloud computing by healthcare domains. OpenID Connect, combining OpenID and OAuth together, is an emerging representational state transfer-based federated identity solution. It is one of the most adopted open standards to potentially become the de facto standard for securing cloud computing and mobile applications, which is also regarded as “Kerberos of cloud.” We introduce OpenID Connect as an authentication and authorization service in cloud-based diagnostic imaging (DI) systems, and propose enhancements that allow for incorporating this technology within distributed enterprise environments. The objective of this study is to offer solutions for secure sharing of medical images among diagnostic imaging repository (DI-r) and heterogeneous picture archiving and communication systems (PACS) as well as Web-based and mobile clients in the cloud ecosystem. The main objective is to use OpenID Connect open-source single sign-on and authorization service and in a user-centric manner, while deploying DI-r and PACS to private or community clouds should provide equivalent security levels to traditional computing model.
IHE XDS-I profile proposes an architecture model for cross-enterprise medical image sharing, but there are only a few clinical implementations reported. Here, we investigate three pilot studies based on the IHE XDS-I profile to see whether we can use this architecture as a foundation for image sharing solutions in a variety of health-care settings. The first pilot study was image sharing for cross-enterprise health care with federated integration, which was implemented in Huadong Hospital and Shanghai Sixth People’s Hospital within the Shanghai Shen-Kang Hospital Management Center; the second pilot study was XDS-I–based patient-controlled image sharing solution, which was implemented by the Radiological Society of North America (RSNA) team in the USA; and the third pilot study was collaborative imaging diagnosis with electronic health-care record integration in regional health care, which was implemented in two districts in Shanghai. In order to support these pilot studies, we designed and developed new image access methods, components, and data models such as RAD-69/WADO hybrid image retrieval, RSNA clearinghouse, and extension of metadata definitions in both the submission set and the cross-enterprise document sharing (XDS) registry. We identified several key issues that impact the implementation of XDS-I in practical applications, and conclude that the IHE XDS-I profile is a theoretically good architecture and a useful foundation for medical image sharing solutions across multiple regional health-care providers.
KEYWORDS: Clouds, Picture Archiving and Communication System, Diagnostics, Medicine, Imaging systems, Systems modeling, Telecommunications, Medical imaging, System integration, Prototyping
The evolution of cloud computing is driving the next generation of diagnostic imaging (DI) systems. Cloud-based DI systems are able to deliver better services to patients without constraining to their own physical facilities. However, privacy and security concerns have been consistently regarded as the major obstacle for adoption of cloud computing by healthcare domains. Furthermore, traditional computing models and interfaces employed by DI systems are not ready for accessing diagnostic images through mobile devices. RESTful is an ideal technology for provisioning both mobile services and cloud computing. OpenID Connect, combining OpenID and OAuth together, is an emerging REST-based federated identity solution. It is one of the most perspective open standards to potentially become the de-facto standard for securing cloud computing and mobile applications, which has ever been regarded as “Kerberos of Cloud”. We introduce OpenID Connect as an identity and authentication service in cloud-based DI systems and propose enhancements that allow for incorporating this technology within distributed enterprise environment. The objective of this study is to offer solutions for secure radiology image sharing among DI-r (Diagnostic Imaging Repository) and heterogeneous PACS (Picture Archiving and Communication Systems) as well as mobile clients in the cloud ecosystem. Through using OpenID Connect as an open-source identity and authentication service, deploying DI-r and PACS to private or community clouds should obtain equivalent security level to traditional computing model.
The deployment of regional and national Electronic Health Record solutions has been a focus of many countries throughout the past decade. Most of these deployments have taken the approach of “sharing” imaging exams via portals and web-based viewers. The motivation of portal/web-based access is driven by a) the perception that review of imaging exams via portal methods is satisfactory to all users and b) the perceived complexity of ingesting foreign exams into local systems. This research project set out to objectively evaluate who really needs foreign exams within their local systems, what those systems might be and how often this is required. Working on the belief that Foreign Exam Management (FEM) is required to support clinical workflow, the project implemented a FEM capability within an XDSI. b domain to identify the design challenges and nuances associated with FEM.
The deployment of regional and national Electronic Health Record solutions has been a focus of many countries throughout the past decade. A major challenge for these deployments has been support for ubiquitous image viewing. More specifically, these deployments require an imaging solution that can work over the Internet, leverage any point of service device: desktop, tablet, phone; and access imaging data from any source seamlessly. Whereas standards exist to enable ubiquitous image viewing, few if any solutions exist that leverage these standards and meet the challenge. Rather, most of the currently available web based DI viewing solutions are either proprietary solutions or require special plugins. We developed a true zero foot print browser based DI viewing solution based on the Web Access DICOM Objects (WADO) and Cross-enterprise Document Sharing for Imaging (XDS-I.b) standards to a) demonstrate that a truly ubiquitous image viewer can be deployed; b) identify the gaps in the current standards and the design challenges for developing such a solution. The objective was to develop a viewer, which works on all modern browsers on both desktop and mobile devices. The implementation allows basic viewing functionalities of scroll, zoom, pan and window leveling (limited). The major gaps identified in the current DICOM WADO standards are a lack of ability to allow any kind of 3D reconstruction or MPR views. Other design challenges explored include considerations related to optimization of the solution for response time and low memory foot print.
One key problem for continuity of patient care is identification of a proper method to share and exchange patient medical records among multiple hospitals and healthcare providers. This paper focuses in the imaging document component of medical record. The XDS-I (Cross- Enterprise Document Sharing – Image) Profile based on the IHE IT-Infrastructure extends and specializes XDS to support imaging “document” sharing in an affinity domain. We present three studies about image sharing solutions based on IHE XDS-I Profile. The first one is to adopt the IHE XDS-I profile as a technical guide to design image and report sharing mechanisms between hospitals for regional healthcare service in Shanghai. The second study is for collaborating image diagnosis in regional healthcare services. The latter study is to investigate the XDS-I based clearinghouse for patient controlled image sharing in the RSNA Image Sharing Network Project. We conclude that the IHE XDS/XDS-I profiles can be used as the foundation to design medical image document sharing for Various Healthcare Services.
At modest compression ratios, lossy compression schemes allow substantial image size reduction without a significant loss in visual information. This is a consequence of the coding engines' transformation (such as the Discrete Cosine Transfomation (DCT) and the Discrete Wavelet Transform (DWT) in combination with quantization and truncation operations which all exploit the characteristics of the human visual system to achieve file-size reduction. The objective of our study was to determine levels of lossy compression that can be confidently used in diagnostic imaging. We conducted an extensive clinical evaluation using a standardized methodology incorporating two recognized evaluation techniques: Diagnostic Accuracy with Receiver Operating Characteristic (ROC) Analysis and Original-Revealed Forced Choice. Images covering 5 modalities and 7 anatomical regions were compressed at 3 different levels using JPEG and JPEG 2000 compression algorithms.
To enable radiologists across Canada to evaluate images for our study, we developed a dedicated software application that was synchronized to a centralized server; which allowed results were reported, in real-time, to the central database via the Internet.
In order to obtain findings that were relevant to everyday clinical evaluation, images were not viewed under a strict laboratory environment, but rather they were read under typical viewing conditions that comply with current standards of practice.
We present here the methodology and specific technology developed for the purpose of this study, we explain the specific problems that we have encountered during the implementation and we give preliminary results.
Our preliminary findings suggest that the most appropriate compression algorithm and compression ratios are largely dependent on the image specifics including the type/ modality and anatomical region studied.
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