KEYWORDS: Picture Archiving and Communication System, Molecular imaging, Preclinical imaging, Data archive systems, Human-machine interfaces, Data conversion, Radiology, Data storage, Standards development, Pre-clinical research
Advances in biology, computer technology and imaging technology have given rise to a scientific specialty referred to as
molecular imaging, which is the in vivo imaging of cellular and molecular pathways using contrast-enhancing targeting
agents. Increasing amounts of molecular imaging research are being performed at pre-clinical stages, generating diverse
datasets that are unstructured and thereby lacking in archiving and distribution solutions. Since PACS in radiology is a
mature clinical archiving solution, a method is proposed to convert current imaging files from preclinical molecular
imaging studies into DICOM formats for archival and retrieval from PACS systems. A web-based DICOM gateway is
presented with an emphasis on metadata mapping in the DICOM header, system connectivity, and overall user
workflow. This effort to conform preclinical imaging data to the DICOM standard is necessary to utilize current PACS
solutions for preclinical imaging data content archiving and distribution.
KEYWORDS: Data storage, Imaging informatics, Data archive systems, Databases, Picture Archiving and Communication System, Imaging systems, Data storage servers, Radiology, Data modeling, Medical imaging
The Medical Imaging Informatics Data Grid project is an enterprise infrastructure solution developed at the University
of Southern California for archiving digital medical images and structured reports. Migration methodology and policies
are needed to maintain continuous data availability as data volumes are being copied and/or moved within a data grid's
multi-site storage devices. In the event a storage device is unavailable, a copy of its contents should be available at a live
secondary storage device within the data grid to provide continuous data availability. In the event a storage device within the data grid is running out of space, select data volumes should be moved seamlessly to a tier-2 storage device for long-term storage, without interruption to front-end users. Thus the database and file migration processes involved must not disrupt the existing workflows in the data grid model. This paper discusses the challenges, policies, and protocols required to provide data persistence through data migration in the Medical Imaging Informatics Data Grid.
KEYWORDS: Databases, Data modeling, Animal model studies, Molecular imaging, Preclinical imaging, Imaging systems, Systems modeling, Process modeling, Data archive systems, Data storage
Research images and findings reports generated during imaging-based small animal imaging experiments are typically
kept by imaging facilities on workstations or by investigators on burned DVD's. There usually lacks structure and
organization to these data content, and are limited to directory and file names to help users find their data files. A study-centric
database design is a fundamental step towards imaging systems integration and also a research data grid infrastructure for multi-institution collaborations and translational research. This paper will present a novel relational
database model to maintain experimental metadata for studies, raw imaging files, post-processed images, and
quantitative findings, all generated during most imaging-based animal-model studies. The integration of experimental
metadata into a single database can alleviate current investigative dependency on hand-written records for current and
previous experimental data. Furthermore, imaging workstations and systems that are integrated with this database can be
streamlined in their data workflow with automated query services. This novel database model is being implemented in a molecular imaging data grid for evaluation with animal-model imaging studies provided from the Molecular Imaging Center at USC.
KEYWORDS: Molecular imaging, Data modeling, Data archive systems, Data centers, Preclinical imaging, Databases, Information science, Human-machine interfaces, Data backup, Picture Archiving and Communication System
The animal-to-researcher workflow in many of today's small animal imaging center is burdened with proprietary data
limitations, inaccessible back-up methods, and imaging results that are not easily viewable across campus. Such
challenges decrease the amount of scans performed per day at the center and requires researchers to wait longer for their
images and quantified results. Furthermore, data mining at the small animal imaging center is often limited to researcher
names and date-labelled archiving hard-drives. To gain efficiency and reliable access to small animal imaging data, such
a center needs to move towards an integrated workflow with file format normalization services, metadata databases,
expandable archiving infrastructure, and comprehensive user interfaces for query / retrieval tools - achieving all in a
cost-effective manner.
This poster presentation demonstrates how grid technology can support such a molecular imaging and small animal
imaging research community to bridge the needs between imaging modalities and clinical researchers. Existing projects
have utilized the Data Grid in PACS tier 2 backup solutions, where fault-tolerance is a high priority, as well as imagingbased
clinical trials where data security and auditing are primary concerns. Issues to be addressed include, but are not
limited to, novel database designs, file format standards, virtual archiving and distribution workflows, and potential grid
computing for 3-D reconstructions, co-registration, and post-processing analysis.
A Data Grid for medical images has been developed at the Image Processing and Informatics Laboratory, USC to
provide distribution and fault-tolerant storage of medical imaging studies across Internet2 and public domain. Although
back-up policies and grid certificates guarantee privacy and authenticity of grid-access-points, there still lacks a method
to guarantee the sensitive DICOM images have not been altered or corrupted during transmission across a public domain.
This paper takes steps toward achieving full image transfer security within the Data Grid by utilizing DICOM image
authentication and a HIPAA-compliant auditing system. The 3-D lossless digital signature embedding procedure
involves a private 64 byte signature that is embedded into each original DICOM image volume, whereby on the
receiving end the signature can to be extracted and verified following the DICOM transmission. This digital signature
method has also been developed at the IPILab. The HIPAA-Compliant Auditing System (H-CAS) is required to monitor
embedding and verification events, and allows monitoring of other grid activity as well. The H-CAS system federates the
logs of transmission and authentication events at each grid-access-point and stores it into a HIPAA-compliant database.
The auditing toolkit is installed at the local grid-access-point and utilizes Syslog [1], a client-server standard for log
messaging over an IP network, to send messages to the H-CAS centralized database. By integrating digital image
signatures and centralized logging capabilities, DICOM image integrity within the Medical Imaging and Informatics
Data Grid can be monitored and guaranteed without loss to any image quality.
The Medical Imaging Informatics (MI2) Data Grid developed at the USC Image Processing and Informatics Laboratory
enables medical images to be shared securely between multiple imaging centers. Current applications include an
imaging-based clinical trial setting where multiple field sites perform image acquisition and a centralized radiology core
performs image analysis, often using computer-aided diagnosis tools (CAD) that generate a DICOM-SR to report their
findings and measurements. As more and more CAD tools are being developed in the radiology field, the generated
DICOM Structure Reports (SR) holding key radiological findings and measurements that are not part of the DICOM
image need to be integrated into the existing Medical Imaging Informatics Data Grid with the corresponding imaging
studies. We will discuss the significance and method involved in adapting DICOM-SR into the Medical Imaging
Informatics Data Grid. The result is a MI2 Data Grid repository from which users can send and receive DICOM-SR
objects based on the imaging-based clinical trial application. The services required to extract and categorize information
from the structured reports will be discussed, and the workflow to store and retrieve a DICOM-SR file into the existing
MI2 Data Grid will be shown.
As clinical imaging and informatics systems continue to integrate the healthcare enterprise, the need to
prevent patient mis-identification and unauthorized access to clinical data becomes more apparent
especially under the Health Insurance Portability and Accountability Act (HIPAA) mandate. Last year, we
presented a system to track and verify patients and staff within a clinical environment. This year, we
further address the biometric verification component in order to determine which Biometric system is the
optimal solution for given applications in the complex clinical environment. We install two biometric
identification systems including fingerprint and facial recognition systems at an outpatient imaging facility,
Healthcare Consultation Center II (HCCII). We evaluated each solution and documented the advantages
and pitfalls of each biometric technology in this clinical environment.
KEYWORDS: Databases, Clinical trials, Computer aided design, Data storage, Image analysis, Radiology, Medical imaging, Computer aided diagnosis and therapy, Data backup, Data integration
In recent imaging-based clinical trials, quantitative image analysis (QIA) and computer-aided diagnosis (CAD) methods
are increasing in productivity due to higher resolution imaging capabilities. A radiology core doing clinical trials have
been analyzing more treatment methods and there is a growing quantity of metadata that need to be stored and managed.
These radiology centers are also collaborating with many off-site imaging field sites and need a way to communicate
metadata between one another in a secure infrastructure. Our solution is to implement a data storage grid with a fault-tolerant
and dynamic metadata database design to unify metadata from different clinical trial experiments and field sites.
Although metadata from images follow the DICOM standard, clinical trials also produce metadata specific to regions-of-interest
and quantitative image analysis. We have implemented a data access and integration (DAI) server layer where
multiple field sites can access multiple metadata databases in the data grid through a single web-based grid service. The
centralization of metadata database management simplifies the task of adding new databases into the grid and also
decreases the risk of configuration errors seen in peer-to-peer grids. In this paper, we address the design and
implementation of a data grid metadata storage that has fault-tolerance and dynamic integration for imaging-based
clinical trials.
KEYWORDS: Clinical trials, Data storage, Radiology, Databases, Image analysis, Medical imaging, Data archive systems, Tolerancing, Software development, Local area networks
Clinical trials play a crucial role in testing new drugs or devices in modern medicine. Medical imaging has also become
an important tool in clinical trials because images provide a unique and fast diagnosis with visual observation and
quantitative assessment. A typical imaging-based clinical trial consists of: 1) A well-defined rigorous clinical trial
protocol, 2) a radiology core that has a quality control mechanism, a biostatistics component, and a server for storing and
distributing data and analysis results; and 3) many field sites that generate and send image studies to the radiology core.
As the number of clinical trials increases, it becomes a challenge for a radiology core servicing multiple trials to have a
server robust enough to administrate and quickly distribute information to participating radiologists/clinicians worldwide.
The Data Grid can satisfy the aforementioned requirements of imaging based clinical trials. In this paper, we present a
Data Grid architecture for imaging-based clinical trials. A Data Grid prototype has been implemented in the Image
Processing and Informatics (IPI) Laboratory at the University of Southern California to test and evaluate performance in
storing trial images and analysis results for a clinical trial. The implementation methodology and evaluation protocol of
the Data Grid are presented.
KEYWORDS: Picture Archiving and Communication System, Data storage, Data backup, Human-machine interfaces, Image restoration, Data archive systems, Image processing, Information science, Image registration, Computing systems
A cross-continental Data Grid infrastructure has been developed at the Image Processing and Informatics (IPI) research
laboratory as a fault-tolerant image data backup and disaster recovery solution for Enterprise PACS. The Data Grid
stores multiple copies of the imaging studies as well as the metadata, such as patient and study information, in
geographically distributed computers and storage devices involving three different continents: America, Asia and
Europe. This effectively prevents loss of image data and accelerates data recovery in the case of disaster. However, the
lack of centralized management system makes the administration of the current Data Grid difficult. Three major
challenges exist in current Data Grid management: 1. No single user interface to access and administrate each
geographically separate component; 2. No graphical user interface available, resulting in command-line-based
administration; 3. No single sign-on access to the Data Grid; administrators have to log into every Grid component with
different corresponding user names/passwords.
In this paper we are presenting a prototype of a unique web-based access interface for both Data Grid administrators and
users. The interface has been designed to be user-friendly; it provides necessary instruments to constantly monitor the
current status of the Data Grid components and their contents from any locations, contributing to longer system up-time.
A CAD method of calculating wall thickness of carotid vessels addresses the time-consuming issue of using B-mode ultrasound as well as inter- and intra-observer variability in results. Upon selection of a region-of-interest and filtering of a series of ultrasound carotid images, the CAD is able to measure the geometry of the lumen and plaque surfaces using a least-square fitting of the active contours during systole and diastole. To evaluate the approach, ultrasound image sequences from 30 patients were submitted to the procedure. The images were stored on an international data grid repository that consists of three international sites: Image Processing and Informatics (IPI) Laboratory at University of Southern California, USA; InCor (Heart Institute) at Sao Paulo, Brazil, and Hong Kong Polytechnic University, Hong Kong. The three chosen sites are connected with high speed international networks including the Internet2, and the Brazilian National Research and Education Network (RNP2). The Data Grid was used to store, backup, and share the ultrasound images and analysis results, which provided a large-scale and a virtual data system. In order to study the variability between the automatic and manual definition of artery boundaries, the pooled mean and the standard deviation for the difference between measurements of lumen diameter were computed. The coefficient of variation and correlation were also calculated. For the studied population the difference between manual and automatic measurement of the lumen diameter (LD) and intima-media-thickness (IMT) were 0.12 +/-0.10 and 0.09+/- 0.06, respectively.
By implementing a tracking and verification system, clinical facilities can effectively monitor workflow and heighten information security in today's growing demand towards digital imaging informatics. This paper presents the technical design and implementation experiences encountered during the development of a Location Tracking and Verification System (LTVS) for a clinical environment. LTVS integrates facial biometrics with wireless tracking so that administrators can manage and monitor patient and staff through a web-based application. Implementation challenges fall into three main areas: 1) Development and Integration, 2) Calibration and Optimization of Wi-Fi Tracking System, and 3) Clinical Implementation. An initial prototype LTVS has been implemented within USC's Healthcare Consultation Center II Outpatient Facility, which currently has a fully digital imaging department environment with integrated HIS/RIS/PACS/VR (Voice Recognition).
KEYWORDS: Picture Archiving and Communication System, Data backup, Data storage, Data archive systems, Chromium, Magnetic resonance imaging, Surgery, Internet, Device simulation, Computed tomography
With the development of PACS technology and an increasing demand by medical facilities to become filmless, there is a need for a fast and efficient method of providing data backup for disaster recovery and downtime scenarios. At the Image Processing Informatics Lab (IPI), an ASP Backup Archive was developed using a fault-tolerant server with a T1 connection to serve the PACS at the St. John's Health Center (SJHC) Santa Monica, California. The ASP archive server has been in clinical operation for more than 18 months, and its performance was presented at this SPIE Conference last year. This paper extends the ASP Backup Archive to serve the PACS at the USC Healthcare Consultation Center II (HCC2) utilizing an Internet2 connection. HCC2 is a new outpatient facility that recently opened in April 2004. The Internet2 connectivity between USC's HCC2 and IPI has been established for over one year. There are two novelties of the current ASP model: 1) Use of Internet2 for daily clinical operation, and 2) Modifying the existing backup archive to handle two sites in the ASP model.
This paper presents the evaluation of the ASP Backup Archive based on the following two criteria: 1) Reliability and performance of the Internet2 connection between HCC2 and IPI using DICOM image transfer in a clinical environment, and 2) Ability of the ASP Fault-Tolerant backup archive to support two separate clinical PACS sites simultaneously. The performances of using T1 and Internet2 at the two different sites are also compared.
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