Realizing digital signatures for medical imaging and reporting in a PACS environment

Business Model for the Security of a Large-Scale PACS, Compliance with ISO/27002:2013 Standard

Data security is a critical issue in an organization; a proper information security management (ISM) is an ongoing process that seeks to build and maintain programs, policies, and controls for protecting information. A hospital is one of the most complex organizations, where patient information has not only legal and economic implications but, more importantly, an impact on the patient's health. Imaging studies include medical images, patient identification data, and proprietary information of the study; these data are contained in the storage device of a PACS. This system must preserve the confidentiality, integrity, and availability of patient information. There are techniques such as firewalls, encryption, and data encapsulation that contribute to the protection of information. In addition, the Digital Imaging and Communications in Medicine (DICOM) standard and the requirements of the Health Insurance Portability and Accountability Act (HIPAA) regulations are also used to protect the patient clinical data. However, these techniques are not systematically applied to the picture and archiving and communication system (PACS) in most cases and are not sufficient to ensure the integrity of the images and associated data during transmission. The ISO/IEC 27001:2013 standard has been developed to improve the ISM. Currently, health institutions lack effective ISM processes that enable reliable interorganizational activities. In this paper, we present a business model that accomplishes the controls of ISO/IEC 27002:2013 standard and criteria of security and privacy from DICOM and HIPAA to improve the ISM of a large-scale PACS. The methodology associated with the model can monitor the flow of data in a PACS, facilitating the detection of unauthorized access to images and other abnormal activities.

Merging medical informatics and automated diagnostic methods

In many instances disease diagnosis is more of an art than a science due to the complexity of disease, lack of detailed information on parameters that are indicative of the disease, and lack of sufficient data to apply these parameters to both diagnosis and treatment. Broad-based expansion of electronic health records (EHRs) will produce additional data for improved model development. However many obstacles remain. Patient record content is not broadly available because of privacy concerns and the lack of standardization of EHR formats. If available on a large scale, de-identified medical records can provide a basis for development of disease models by removing privacy concerns. Once comprehensive disease models have been developed that assist in identifying possible diseases and also include parameters that were utilized along with their relative importance, automated analytic methods can be used to indicate the likelihood of the presence of specific diseases. Although the physician will always remain as the final expert, these methods can provide an expanded information set and provide analysis that is too complex for standard methods.

A medical application integrating remote 3D visualization tools to access picture archiving and communication system on mobile devices

With computing capability and display size growing, the mobile device has been used as a tool to help clinicians view patient information and medical images anywhere and anytime. However, for direct interactive 3D visualization, which plays an important role in radiological diagnosis, the mobile device cannot provide a satisfactory quality of experience for radiologists. This paper developed a medical system that can get medical images from the picture archiving and communication system on the mobile device over the wireless network. In the proposed application, the mobile device got patient information and medical images through a proxy server connecting to the PACS server. Meanwhile, the proxy server integrated a range of 3D visualization techniques, including maximum intensity projection, multi-planar reconstruction and direct volume rendering, to providing shape, brightness, depth and location information generated from the original sectional images for radiologists. Furthermore, an algorithm that changes remote render parameters automatically to adapt to the network status was employed to improve the quality of experience. Finally, performance issues regarding the remote 3D visualization of the medical images over the wireless network of the proposed application were also discussed. The results demonstrated that this proposed medical application could provide a smooth interactive experience in the WLAN and 3G networks.