Proc. SPIE. 6145, Medical Imaging 2006: PACS and Imaging Informatics
KEYWORDS: Data modeling, Data storage, Databases, Fourier transforms, Medical imaging, Time metrology, Image storage, Process modeling, Standards development, Picture Archiving and Communication System
With the increasing demand of PAC systems, more and more examinations are acquired by healthcare institutions which results in an enormous amount of image data and metadata information that needs to be archived and retrieved especially during disaster recovery. Last year we presented a Data Storage Grid (DSG) architecture based on the five-layer architecture design for Grid technology that provides 99.999% up time. The proposed solution was implemented as a three-site testbed and was developed using Globus 3.2 Toolkit. A grid architecture built on Globus middleware achieves reliability and availability through the distribution of hardware components and services. However, a DICOM-compliant DSG requires a Metadata Catalog to provide the DICOM header information available to DSG clients. For this reason, this paper describes the continued development of the DSG utilizing DICOM and IHE standards including the development of a fault-tolerant Metadata Catalog for a DICOM-compliant data grid environment.
The paper describes the methodology for the clinical design and implementation of a Location Tracking and Verification System (LTVS) that has distinct benefits for the Imaging Department at the Healthcare Consultation Center II (HCCII), an outpatient imaging facility located on the USC Health Science Campus. A novel system for tracking and verification of patients and staff in a clinical environment using wireless and facial biometric technology to monitor and automatically identify patients and staff was developed in order to streamline patient workflow, protect against erroneous examinations and create a security zone to prevent and audit unauthorized access to patient healthcare data under the HIPAA mandate. This paper describes the system design and integration methodology based on initial clinical workflow studies within a clinical environment. An outpatient center was chosen as an initial first step for the development and implementation of this system.
The deadline of HIPAA (Health Insurance Portability and Accountability Act) Security Rules has passed on February
2005; therefore being HIPAA compliant becomes extremely critical to healthcare providers. HIPAA mandates
healthcare providers to protect the privacy and integrity of the health data and have the ability to demonstrate examples
of mechanisms that can be used to accomplish this task. It is also required that a healthcare institution must be able to
provide audit trails on image data access on demand for a specific patient. For these reasons, we have developed a
HIPAA compliant auditing system (HCAS) for image data security in a PACS by auditing every image data access. The
HCAS was presented in 2005 SPIE. This year, two new components, LDSE (Lossless Digital Signature Embedding) and
LTVS (Patient Location Tracking and Verification System) logs, have been added to the HCAS. The LDSE can assure
medical image integrity in a PACS, while the LTVS can provide access control for a PACS by creating a security zone
in the clinical environment. By integrating the LDSE and LTVS logs with the HCAS, the privacy and integrity of image
data can be audited as well. Thus, a PACS with the HCAS installed can become HIPAA compliant in image data privacy
and integrity, access control, and audit control.
Proc. SPIE. 5748, Medical Imaging 2005: PACS and Imaging Informatics
KEYWORDS: Databases, Image segmentation, Image processing, Chromium, Computer simulations, Information technology, Image retrieval, Algorithm development, Information science, Picture Archiving and Communication System
Expectation of rapid image retrieval and distribution from PACS contributes to increased information technology (IT) infrastructure investments and continuing demands upon PACS administrators to respond to "slow" system calls. Studies show that it is important for computer users to be able to check on the progress of their task via progress indicators (e.g., time left to download file) to know that the computer is still working. By analogy, the ability to provide predicted delivery times to a PACS user may curb user expectations for "fast" response especially during peak hours. Allowing for some periods of slow response means PACS infrastructure do not have to be overbuilt and also reduce time spent by PACS administrators fielding user inquiries on image status. For this condition, a queryable PACS queue monitor is the cornerstone for providing a progress indicator to the user. The typical PACS server holds image file information and destination workstation information in a queue until the RetrieveSend process can send the image. We developed an agent that queries the contents of the PACS RetrieveSend queue in real-time and coded an algorithm to predict delivery time. Delivery time can be predicted from the number and types of images in progress and the download time of prior images that accounts for network load and performance at that time of day. We have developed a PACS queue monitor prototype that is being tested on clinical data using the PACS Simulator at the Imaging Processing and Informatics (IPI) Laboratory of the University of Southern California (USC).
Proc. SPIE. 5748, Medical Imaging 2005: PACS and Imaging Informatics
KEYWORDS: Data modeling, Data storage, Databases, Image processing, Fourier transforms, Data archive systems, Image retrieval, Data backup, Computer architecture, Picture Archiving and Communication System
Grid Computing represents the latest and most exciting technology to evolve from the familiar realm of parallel, peer-to-peer and client-server models that can address the problem of fault-tolerant storage for backup and recovery of clinical images. We have researched and developed a novel Data Grid testbed involving several federated PAC systems based on grid architecture. By integrating a grid computing architecture to the DICOM environment, a failed PACS archive can recover its image data from others in the federation in a timely and seamless fashion. The design reflects the five-layer architecture of grid computing: Fabric, Resource, Connectivity, Collective, and Application Layers. The testbed Data Grid architecture representing three federated PAC systems, the Fault-Tolerant PACS archive server at the Image Processing and Informatics Laboratory, Marina del Rey, the clinical PACS at Saint John's Health Center, Santa Monica, and the clinical PACS at the Healthcare Consultation Center II, USC Health Science Campus, will be presented. The successful demonstration of the Data Grid in the testbed will provide an understanding of the Data Grid concept in clinical image data backup as well as establishment of benchmarks for performance from future grid technology improvements and serve as a road map for expanded research into large enterprise and federation level data grids to guarantee 99.999 % up time.