Since segmentation of magnetic resonance images is one of the most important initial steps in brain magnetic resonance image processing, success in this part has a great influence on the quality of outcomes of subsequent steps. In the past few decades, numerous methods have been introduced for classification of such images, but typically they perform well only on a specific subset of images, do not generalize well to other image sets, and have poor computational performance. In this study, we provided a method for segmentation of magnetic resonance images of the brain that despite its simplicity has a high accuracy. We compare the performance of our proposed algorithm with similar evolutionary algorithms on a pixel-by-pixel basis. Our algorithm is tested across varying sets of magnetic resonance images and demonstrates high speed and accuracy. It should be noted that in initial steps, the algorithm is computationally intensive requiring a large number of calculations; however, in subsequent steps of the search process, the number is reduced with the segmentation focused only in the target area.
Image processing; Segmentation; Optimization algorithm; Ant colony optimization
The objective of this study is to evaluate a natural language processing (NLP) algorithm that determines American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) final assessment categories from radiology reports. This HIPAA-compliant study was granted institutional review board approval with waiver of informed consent. This cross-sectional study involved 1,165 breast imaging reports in the electronic medical record (EMR) from a tertiary care academic breast imaging center from 2009. Reports included screening mammography, diagnostic mammography, breast ultrasound, combined diagnostic mammography and breast ultrasound, and breast magnetic resonance imaging studies. Over 220 reports were included from each study type. The recall (sensitivity) and precision (positive predictive value) of a NLP algorithm to collect BI-RADS final assessment categories stated in the report final text was evaluated against a manual human review standard reference. For all breast imaging reports, the NLP algorithm demonstrated a recall of 100.0 % (95 % confidence interval (CI), 99.7, 100.0 %) and a precision of 96.6 % (95 % CI, 95.4, 97.5 %) for correct identification of BI-RADS final assessment categories. The NLP algorithm demonstrated high recall and precision for extraction of BI-RADS final assessment categories from the free text of breast imaging reports. NLP may provide an accurate, scalable data extraction mechanism from reports within EMRs to create databases to track breast imaging performance measures and facilitate optimal breast cancer population management strategies.
Breast Imaging Reporting and Data System (BI-RADS); Natural language processing; Imaging informatics; Breast
Radiology reports are permanent legal documents that serve as official interpretation of imaging tests. Manual analysis of textual information contained in these reports requires significant time and effort. This study describes the development and initial evaluation of a toolkit that enables automated identification of relevant information from within these largely unstructured text reports. We developed and made publicly available a natural language processing toolkit, Information from Searching Content with an Ontology-Utilizing Toolkit (iSCOUT). Core functions are included in the following modules: the Data Loader, Header Extractor, Terminology Interface, Reviewer, and Analyzer. The toolkit enables search for specific terms and retrieval of (radiology) reports containing exact term matches as well as similar or synonymous term matches within the text of the report. The Terminology Interface is the main component of the toolkit. It allows query expansion based on synonyms from a controlled terminology (e.g., RadLex or National Cancer Institute Thesaurus [NCIT]). We evaluated iSCOUT document retrieval of radiology reports that contained liver cysts, and compared precision and recall with and without using NCIT synonyms for query expansion. iSCOUT retrieved radiology reports with documented liver cysts with a precision of 0.92 and recall of 0.96, utilizing NCIT. This recall (i.e., utilizing the Terminology Interface) is significantly better than using each of two search terms alone (0.72, p = 0.03 for liver cyst and 0.52, p = 0.0002 for hepatic cyst). iSCOUT reliably assembled relevant radiology reports for a cohort of patients with liver cysts with significant improvement in document retrieval when utilizing controlled lexicons.
Controlled vocabulary; Natural language processing; Information storage and retrieval
Digital radiology departments could benefit from the ability to integrate and visualize data (e.g. information reflecting complex workflow states) from all of their imaging and information management systems in one composite presentation view. Leveraging data warehousing tools developed in the business world may be one way to achieve this capability. In total, the concept of managing the information available in this data repository is known as Business Intelligence or BI. This paper describes the concepts used in Business Intelligence, their importance to modern Radiology, and the steps used in the creation of a prototype model of a data warehouse for BI using open-source tools.
Data collection; data mining; databases; data extraction; knowledge management; online analytical processing (OLAP)
The First Society for Computer Applications in Radiology (SCAR) Transforming the Radiological Interpretation Process (TRIP™) Conference and Workshop, “Transforming Medical Imaging” was held on January 31–February 1, 2005 in Bethesda, MD. Representatives from all areas of medical and scientific imaging—academia, research, industry, and government agencies—joined together to discuss the future of medical imaging and potential new ways to manage the explosion in numbers, size, and complexity of images generated by today's continually advancing imaging technologies. The two-day conference included plenary, scientific poster, and breakout sessions covering six major research areas related to TRIP™. These topic areas included human perception, image processing and computer-aided detection, data visualization, image set navigation and usability, databases and systems integration, and methodology evaluation and performance validation. The plenary presentations provided a general status review of each broad research field to use as a starting point for discussion in the breakout sessions, with emphasis on specific topics requiring further study. The goals for the breakout sessions were to define specific research questions in each topic area, to list the impediments to carrying out research in these fields, to suggest possible solutions and near- and distant-future directions for each general topic, and to report back to the general session. The scientific poster session provided another mechanism for presenting and discussing TRIP™-related research. This report summarizes each plenary and breakout session, and describes the group recommendations as to the issues facing the field, major impediments to progress, and the outlook for radiology in the short and long term. The conference helped refine the definition of the SCAR TRIP™ Initiative and the problems facing radiology with respect to the dramatic growth in medical imaging data, and it underscored a present and future need for the support of interdisciplinary translational research in radiology bridging bench-to-bedside. SCAR will continue to fund research grants exploring TRIP™ solutions. In addition, the organization proposes providing an infrastructure to foster collaborative research partnerships between SCAR corporate and academic members in the form of a TRIP™ Imaging Informatics Network (TRIPI2N).
Large data sets; radiological image interpretation paradigm; medical imaging informatics
The aim of this study is to determine if network-enabled personal digital assistants (PDAs) can be used to facilitate the timely delivery of urgent radiological exam results by reducing the interval from when the radiologist's initial interpretation is available to when it is first viewed by an emergency department (ED) physician. A web- and Java message service (JMS)-based application was built to replace the original fax-based wet-read procedure. The new system allows radiologists to enter wet-reads from the picture archiving and communication system (PACS) display station and to track discrepancies between the wet-read and final report. It also notifies the ED physicians when exam results are available via the PDAs and permits them to view the full text of the wet-read and final reports from the devices. The new system is compared to the original procedure with the results showing improvements with the wireless method. Furthermore, feedback from a qualitative survey of PDA users was positive, suggesting that PDAs may provide one means for accessing urgent clinical data at the point of care.
integrated systems; Java Message Service (JMS); urgent exams; Personal Digital Assistant (PDA); mobile computing; Radiology Information System (RIS); Picture Archiving and Communication System (PACS); results reporting; handheld devices
The Society for Computer Applications in Radiology (SCAR) Transforming the Radiological Interpretation Process (TRIP™) Initiative aims to spearhead research, education, and discovery of innovative solutions to address the problem of information and image data overload. The initiative will foster interdisciplinary research on technological, environmental and human factors to better manage and exploit the massive amounts of data. TRIP™ will focus on the following basic objectives: improving the efficiency of interpretation of large data sets, improving the timeliness and effectiveness of communication, and decreasing medical errors. The ultimate goal of the initiative is to improve the quality and safety of patient care. Interdisciplinary research into several broad areas will be necessary to make progress in managing the ever-increasing volume of data. The six concepts involved are human perception, image processing and computer-aided detection (CAD), visualization, navigation and usability, databases and integration, and evaluation and validation of methods and performance. The result of this transformation will affect several key processes in radiology, including image interpretation; communication of imaging results; workflow and efficiency within the health care enterprise; diagnostic accuracy and a reduction in medical errors; and, ultimately, the overall quality of care.
large data sets, radiological image interpretation paradigm
This article describes an application for capturing, delivering, and tracking urgent radiology exam results. Urgent exam findings are entered using a Web form embedded within the Picture archiving and communication system (PACS) display station. The findings are then accessible via soft copy using the PACS display stations, hospital information system (HIS) terminals, or wireless-enabled personal digital assistants (PDAs) or via hard copy printouts that are generated automatically or on demand. Additionally, quality control is performed on those findings entered by radiology residents and fellows, the results of which are used for both performance tracking and educational activities. The application was developed using Sun Microsystems’ Java programming language. The Java Message Service (JMS) was used to manage the delivery of findings. JMS provides a robust, flexible framework for exchanging messages between disparate applications. The application is now used for all urgent exams; completely replacing the original paper-based system. The use of JMS provides the necessary level of reliability needed by this application.
Integration; Java Message Service (JMS); urgent exams; PACS; clinical information systems; RIS; HIS; PDA
An objective assessment and comparison of computed radiography (CR) versus digital radiography (DR) and screen-film for performing upright chest examinations on outpatients is presented in terms of workflow, productivity, speed of service, and potential cost justification. Perceived ease of use and workflow of each device is collected via a technologist opinion survey. Productivity is measured as the rate of patient throughput from normalized timing studies. The overall speed of service is calculated from the time of examination ordering as stamped in the radiology information system (RIS), to the time of image availability on the picture archiving and communication system (PACS), to the time of interpretation rendered (from the RIS). A cost comparison is discussed in terms of potential productivity gains and device expenditures. Comparative results of a screen-film (analog) dedicated chest unit versus a CR reader and a DR dedicated chest unit show a higher patient throughput for the digital systems. A mean of 8.2 patients were moved through the analog chest room per hour, versus 9.2 patients per hour using the CR system and 10.7 patients per hour with the DR system. This represents a 12% increase in patient throughput for CR over screen-film; a 30% increase in patient throughput for DR over screen-film, which is statistically significant; and a 16% increase in patient throughput for DR over CR, which is not statistically significant. Measured time to image availability for interpretation is much faster for both CR and DR versus screen-film, with the mean minutes to image availability calculated as 29.2 ± 14.3 min for screen-film, 6.7 ± 1.5 min for CR, and 5.7 ± 2.5 min for DR. This represents an improved time to image availability of 77% for CR over screen-film, 80% for DR over screen-film, and 15% for DR over CR. These results are statistically significant (P <.0001) for both CR over screen-film and DR over screen-film but not statistically significant for DR over CR. A comparison of the digital technology costs illustrates that the high cost of DR may not be justifiable unless a facility has a steady high patient volume to run the device at or near 100% productivity. Both CR and DR can improve workflow and productivity over analog screen-film in a PACS for delivery of projection radiography services in an outpatient environment. Cost justification for DR over CR appears to be tied predominantly to high patient volume and continuous rather than sporadic use patterns.
Purpose: At present, there are two basic picture archiving and communication system (PACS) architectures: centralized with a central cache and controller, and distributed with a distributed cache and central controller. A third architecture proposed here is an autonomous one with a distributed cache and no controller. This report will investigate the performance (as measured be central processing unit [CPU] and networkload, scalability, and examination retrieval and display latency) of these three types.Methods: The distributed PACS architecture will be simulated using an IM PAX R3.5 (AGFA, Ridgefield Park, NJ) PACS, while the centralized design will be simulated using an IMPAX R4 (AGFA) PACS. The autonomous system will be designed and implementedin-house. The autonomous system consists of two types of entities: basic components such as acquisition gateways, display stations, and long-term archives, and registry servers, which store global state information about the individual PACS components. The key feature of the autonomous system will be the replacement of the central PACS controller by the registry servers. In this scenario the registry servers monitor the interactions between the components, but do not directly govern them. Instead each component will contain the application logic it requires and will use the state information from the registry servers to take the appropriate action, such as routing images, prefetching studies, and expiring images from near line cache. In addition the routing of examinations will be optimized to reduce the duplication of image data. Display stations will be categorized by specialty (neuroradiology, pediatrics, chest, etc) and will retrieve studies for display on demand from intermediate servers dedicated to the corresponding specialty. Studies will be routed only to the intermediate servers and not to display stations.Results: By distributing the application logic, an autonomous PACS architecture can provide increased fault tolerance and therefore increased uptime. In addition, the lack of a central controller and the use of intermediate servers improve the scalability of the system, as well as reduce CPU and network loads.
Common object request broker architecture (CORBA) is a method for invoking distributed objects across a network. There has been some activity in applying this software technology to Digital Imaging and Communications in Medicine (DICOM), but no documented demonstration of how this would actually work. We report a CORBA demonstration that is functionally equivalent and in some ways superior to the DICOM communication protocol. In addition, in and outside of medicine, there is great interest in the use of extensible markup language (XML) to provide interoperation between databases. An example implementation of the DICOM data structure in XML will also be demonstrated. Using Visibroker ORB from Inprise (Scotts Valley, CA), a test bed was developed to simulate the principle DICOM operations: store, query, and retrieve (SQR). SQR is the most common interaction between a modality device application entity (AE) such as a computed tomography (CT) scanner, and a storage component, as well as between a storage component and a workstation. The storage of a CT study by invoking one of several storage objects residing on a network was simulated and demonstrated. In addition, XML database descriptors were used to facilitate the transfer of DICOM header information between independent databases. CORBA is demonstrated to have great potential for the next version of DICOM. It can provide redundant protection against single points of failure. XML appears to be an excellent method of providing interaction between separate databases managing the DICOM information object model, and may therefore eliminate the common use of proprietary client-server databases in commercial implementations of picture archiving and communication systems (PACS).
This study compares the timeliness of radiology interpretation of Emergency Department (ED) imaging examinations in a picture archiving and communication system (PACS) before and after implementation of an automated paging system for notification of image availability. An alphanumeric pager for each radiology subspecialty (chest, pediatrics, bone, neuroradiology, and body) was used to alert the responsible radiologist that an ED imaging examination is available to be viewed on the PACS. The paging system was programmed to trigger off of the PACS database when an image is received on the appropriate radiology display station. The pager message includes the radiology accession number and examination description (such as chest, two-view, or c-spine, etc). The PACS paging tool performance was assessed by calculating the time elapsed, for each ED imaging examination, from the Time Imaged to the Time of Interpretation, where the Time Imaged is the actual image completion time measured at the imaging modality, and the Time Interpreted is the time a radiology interpretation is rendered to the ED, and is measured from the Radiology-to-ED fax time stamp. These measures were analyzed pre- and post-paging system implementation to determine any impact of the automated notification tool on radiology service turnaround time. Results show an improved radiology response time from image completion to interpretation rendered to ED clinicians, down from hour(s) to minutes, with the automated paging examination notification system. Examinations are read by the appropriate radiology specialty section in a more timely fashion, and fewer cases go unread by radiology.
Early picture archiving and communication systems (PACS) were characterized by the use of very expensive hardware devices, cumbersome display stations, duplication of database content, lack of interfaces to other clinical information systems, and immaturity in their understanding of the folder manager concepts and workflow reengineering. They were implemented historically at large academic medical centers by biomedical engineers and imaging informaticists. PACS were nonstandard, home-grown projects with mixed clinical acceptance. However, they clearly showed the great potential for PACS and filmless medical imaging. Filmless radiology is a reality today. The advent of efficient softcopy display of images provides a means for dealing with the ever-increasing number of studies and number of images per study. Computer power has increased, and archival storage cost has decreased to the extent that the economics of PACS is justifiable with respect to film. Network bandwidths have increased to allow large studies of many megabytes to arrive at display stations within seconds of examination completion. PACS vendors have recognized the need for efficient workflow and have built systems with intelligence in the mangement of patient data. Close integration with the hospital information system (HIS)-radiology information system (RIS) is critical for system functionality. Successful implementation of PACS requires integration or interoperation with hospital and radiology information systems. Besides the economic advantages, secure rapid access to all clinical information on patients, including imaging studies, anytime and anywhere, enhances the quality of patient care, although it is difficult to quantify. Medical image management systems are maturing, providing access outside of the radiology department to images and clinical information throughout the hospital or the enterprise via the Internet. Small and medium-sized community hospitals, private practices, and outpatient centers in rural areas will begin realizing the benefits of PACS already realized by the large tertiary care academic medical centers and research institutions. Hand-held devices and the Worldwide Web are going to change the way people communicate and do business. The impact on health care will be huge, including radiology. Computer-aided diagnosis, decision support tools, virtual imaging, and guidance systems will transform our practice as value-added applications utilizing the technologies pushed by PACS development efforts. Outcomes data and the electronic medical record (EMR) will drive our interactions with referring physicians and we expect the radiologist to become the informaticist, a new version of the medical management consultant.
picture archiving and communication systems (PACS); image storage and retrieval; folder manager; workflow manager; radiology information systems; computers; digital radiology
The purpose of this communication is to report on the testing of the disaster recovery capability of our hierarchical storage management (HSM) system. Disaster recovery implementation is a requirement of every mission-critical information technology project. Picture archiving and communications systems (PACS) certainly falls into this category, even though the counterpart, conventional film archive, has no protection against fire, for example. We have implemented a method for hierarchical storage with wavelet technology that maximizes on-site case storage (using lossy compression), retains bit-preserved image data for legal purposes, provides an off-site backup (lossless bit-preserving wavelet transform), and provides for disaster recovery. Recovery from a natural (earthquake and subsequent fire) or technical (system crash and data loss) disaster was simulated by attempting to restore from the off-site image and database backup to clean core PACS components. The only existing loaded software was the operating system. The database application was reloaded locally, and then the database contents and image store were loaded from the off-site component of the HSM system. The following measurements were analyzed: (1) the ability to recover all data; (2) the integrity of the recovered database and image data; (3) the time to recover the database relative to the number of studies and age of the archive, as well as bandwidth between the local and remote site; and (4) the time to recover image data relative to compression ratio, number of studies, number of images, and time depth of the archive. This HSM system, which maximizes on-site storage, maintains a legal record, and provides off-site backup, also facilitates disaster recovery for a PACS.
Proper prefetching of relevant prior examinations from a picture archiving and communication system (PACS) archive, when a patient is scheduled for a new imaging study, and sending the historic images to the display station where the new examination is expected to be routed and subsequently read out, can greatly facilitate interpretation and review, as well as enhance radiology departmental workflow and PACS performance. In practice, it has proven extremely difficult to implement an automatic prefetch as successful as the experienced fileroom clerk. An algorithm based on defined metagroup categories for examination type mnemonics has been designed and implemented as one possible solution to the prefetch problem. The metagroups such as gastrointestinal (GI) tract, abdomen, chest, etc, can represent, in a small number of categories, the several hundreds of examination, types performed by a, typical radiology department. These metagroups can be defined in a table of examination mnemonics that maps a particular mnemonic to a metagroup or groups, and vice versa. This table is used to effect the prefetch rules of relevance. A given examination may relate to several prefetch categories, and preferences are easily configurable for a particular site. The prefetch algorithm metatable was implemented in database structured query language (SQL) using a many-to-many fetch category strategy. Algorithm performance was measured by analyzing the appropriateness of the priors fetched based on the examination type of the current study. Fetched relevant priors, missed relevant priors, fetched priors that were not relevant to the current examination, and priors not fetched that were not relevant were used to calculate sensitivity and specificity for the prefetch method. The time required for real-time requesting of priors not previously prefetched was also measured. The sensitivity of the prefetch algorithm was detarmined to be 98.3% and the specificity 100%. Time required for on-demand requesting of priors was 9.5 minutes on average, although this time varied based on age of the prior examination and on the time of day and database traffic. A prefetch algorithm based on metatable examination mnemonic categories can pull the most appropriate relevant priors, reduce the number of missed relevant priors, and therefore reduce the time involved for the manual task of on-demand requests of priors. Network and database traffic can be reduced as well by decreasing the number of priors selected from the archive and subsequently transmitted to the display stations, through elimination of transactions on examinations not relevant to the current study.
Current challenges facing picture archiving and communication systems (PACS) center around database design and functionality. Workflow issues and folder manager concepts such as autorouting, prefetching, hanging protocols, and hierarchical storage management are driven by a properly designed database that ultimately directly impacts the clinical utility of a PACS. The key issues in PACS database design that enable radiologist-friendly, cost-effective, and datasecure systems will be discussed, including database difficulties of the DICOM standard, HIS/RIS/PACS (hospital information system/radiology information system) connectivity, and database issues in data acquisition, data dissemination, and data display.
picture archiving and communication system; database; folder manager; workflow manager; hospital information system/radiology information system
Much work has been done to optimize the display of cross-sectional modality imaging examinations for soft-copy reading (ie, window/level tissue presets, and format presentations such as tile and stack modes, four-on-one, nine-on-one, etc). Less attention has been paid to the display of digital forms of the conventional projection x-ray. The purpose of this study is to assess the utility of providing presets for computed radiography (CR) soft-copy display, based not on the window/level settings, but on processing applied to the image optimized for visualization of specific findings, pathologies, etc (ie, pneumothorax, tumor, tube location). It is felt that digital display of CR images based on finding-specific processing presets has the potential to: speed reading of digital projection x-ray examinations on soft copy; improve diagnostic efficacy; standardize display across examination type, clinical scenario, improtant key findings, and significant negatives; facilitate image comparison; and improve confidence in and acceptance of soft-copy reading. Clinical chest images are acquired using an Agfa-Gevaert (Mortsel, Belgium) ADC 70 CR scanner and Fuji (Stamford, CT) 9000 and AC2 Cr scanners. Those demonstrating pertinent findings are transferred over the clinical picture archiving and communications system (PACS) network to a research image processing station (Agfa PS5000), where the optimal image-processing settings per finding, pathologic category, etc, are developed in conjunction with a thoracic radiologist, by manipulating the multiscale image contrast amplification (Agfa MUSICA) algorithm parameters. Soft-copy display of images processed with finding-specific settings are compared with the standard default image presentation for 50 cases of each category. Comparison is scored using a 5-point scale with the positive scale denoting the standard presentation is preferred over the finding-specific processing, the negative scale denoting the finding-specific processing is preferred over the standard presentation, and zero denoting no difference. Processing settings have been developed for several findings including pneumothorax and lung nodules, and clinical cases are currently being collected in preparation for formal clinical trials. Preliminary results indicate a preference for the optimized-processing presentation of images over the standard default, particularly by inexperienced radiology residents and referring clinicians.
Digital acquisition of data from the various imaging modalities for input to a picture archiving and communication system (PACS) is discussed. Essential features for successful clinical implementation including Digital Imaging and Communications in Medicine (DICOM) compliance, radiology information system (RIS)/hospital information system (HIS) interfacing, and workflow integration are detailed. Image acquisition from the inherently digital cross-sectional modalities are described, as well as digital acquisition of the conventional projection x-ray using computed radiography (CR), direct digital radiography (DDR), and film digitizers.
The University of California at San Francisco (USCF) Department of Radiology currently has a clinically operational picture archiving and communication system (PACS) that is thirty-five percent filmless, with the goal of becoming seventy-five percent filmless within the year. The design and implementation of the clinical PACS has been a collaborative effort between an academic research laboratory and a commercial vendor partner. Images are digitally acquired from three computed radiography (CR) scanners, five computed tomography (CT) scanners, five magnetic resonance (MR) imagers, three digital fluoroscopic rooms, an ultrasound mini-PACS and a nuclear medicine mini-PACS. The DICOM (Digital Imaging and Communications in Medicine) standard communications protocol and image format is adhered to throughout the PACS. Images are archived in hierarchical staged fashion, on a RAID (redundant array of inexpensive disks) and on magneto-optical disk jukeboxes. The clinical PACS uses an object-oriented Oracle SQL (systems query language) database, and interfaces to the Radiology Information System using the HL7 (Health Languages 7) standard. Components are networked using a combination of switched and fast ethernet, and ATM (asynchronous transfer mode), all over fiber optics. The wide area network links six UCSF sites in San Francisco. A combination of high and medium resolution dual-monitor display stations have been placed throughout the Department of Radiology, the Emergency Department (ED) and Intensive Care Units (ICU). A continuing quality improvement (CQI) committee has been formed to facilitate the PACS installation and training, workflow modifications, quality assurance and clinical acceptance. This committee includes radiologists at all levels (resident, fellow, attending), radiology technologists, film library personnel, ED and ICU clinian end-users, and PACS team members. The CQI committee has proved vital in the creation of new management procedures, providing a means for user feedback and education, and contributing to the overall acceptance of, and user satisfaction with the system. Well developed CQI procedures have been essential to the successful clinical operation of the PACS as UCSF Radiology moves toward, a filmless department.
PACS; continuing quality improvement (CQI); quality assurance (QA); filmless