Workflow is a widely used term to describe the sequence of steps to accomplish a task. The use of workflow technology in medicine and medical imaging in particular is limited. In this article, we describe the application of a workflow engine to improve workflow in a radiology department. We implemented a DICOM-enabled workflow engine system in our department. We designed it in a way to allow for scalability, reliability, and flexibility. We implemented several workflows, including one that replaced an existing manual workflow and measured the number of examinations prepared in time without and with the workflow system. The system significantly increased the number of examinations prepared in time for clinical review compared to human effort. It also met the design goals defined at its outset. Workflow engines appear to have value as ways to efficiently assure that complex workflows are completed in a timely fashion.
Workflow management; System architecture; DICOM; Business process management
Recent information technology literature, in general, and radiology trade journals, in particular, are rife with allusions to the “cloud” suggesting that moving one’s compute and storage assets into someone else’s data center magically solves cost, performance, and elasticity problems. More likely, one is only trading one set of problems for another, including greater latency (aka slower turnaround times) since the image data must now leave the local area network and travel longer paths via encrypted tunnels. To offset this, an imaging system design is needed that reduces the number of high-latency image transmissions, yet can still leverage cloud strengths. This work explores the requirements for such a design.
DICOM; IHE; Cloud; WADO
The execution of a multisite trial frequently includes image collection. The Clinical Trials Processor (CTP) makes removal of protected health information highly reliable. It also provides reliable transfer of images to a central review site. Trials using central review of imaging should consider using CTP for handling image data when a multisite trial is being designed.
In the filmless imaging department, an integrated imaging and reporting system is only as strong as its weakest link. An outage or downtime of a key segment, such as the Picture Archive Communications System (PACS), is a significant threat to efficient workflow, quality of image interpretation, ordering clinician’s review, and ultimately patient care. A multidisciplinary team (including physicists, technologists, radiologists, operations, and IT) developed a backup system to provide business continuity (i.e., quality control, interpretation, reporting, and clinician access) during an extended outage of the main departmental PACS.
Computer hardware; Computer networks; Computers in medicine
Digital Imaging and Communications in Medicine (DICOM) has brought a very high level of standardization to medical images, allowing interoperability in many cases. However, there are still challenges facing the informaticist attempting to data mine DICOM objects. Images (and other objects) from different vintage equipment will encompass different levels of the standard, and there are also proprietary “shadow” tags to be aware of. The database architecture described herein “flattens” such differences by compiling a knowledge base of specific DICOM implementations and mapping variable data elements to a common lexicon for subsequent queries. The project is open sourced, built on open infrastructure, and is available at GitHub.
Data mining; Databases; Computer systems
The productivity gains, diagnostic benefit, and enhanced data availability to clinicians enabled by picture archiving and communication systems (PACS) are no longer in doubt. However, commercial PACS offerings are often extremely expensive initially and require ongoing support contracts with vendors to maintain them. Recently, several open-source offerings have become available that put PACS within reach of more users. However, they can be resource-intensive to install and assure that they have room for future growth—both for computational and storage capacity. An alternate approach, which we describe herein, is to use PACS built on virtual machines which can be moved from smaller to larger hardware as needed in a just-in-time manner. This leverages the cost benefits of Moore's Law for both storage and compute costs. We describe the approach and current results in this paper.
PACS; Open-source; Software; Digital subtraction angiography
The attractions of virtual computing are many: reduced costs, reduced resources and simplified maintenance. Any one of these would be compelling for a medical imaging professional attempting to support a complex practice on limited resources in an era of ever tightened reimbursement. In particular, the ability to run multiple operating systems optimized for different tasks (computational image processing on Linux versus office tasks on Microsoft operating systems) on a single physical machine is compelling. However, there are also potential drawbacks. High performance requirements need to be carefully considered if they are to be executed in an environment where the running software has to execute through multiple layers of device drivers before reaching the real disk or network interface. Our lab has attempted to gain insight into the impact of virtualization on performance by benchmarking the following metrics on both physical and virtual platforms: local memory and disk bandwidth, network bandwidth, and integer and floating point performance. The virtual performance metrics are compared to baseline performance on “bare metal.” The results are complex, and indeed somewhat surprising.
Computer hardware; Computer systems; Computers in medicine
This software tool locates and computes the intensity of radiation skin dose resulting from fluoroscopically guided interventional procedures. It is comprised of multiple modules. Using standardized body specific geometric values, a software module defines a set of male and female patients arbitarily positioned on a fluoroscopy table. Simulated X-ray angiographic (XA) equipment includes XRII and digital detectors with or without bi-plane configurations and left and right facing tables. Skin dose estimates are localized by computing the exposure to each 0.01 × 0.01 m2 on the surface of a patient irradiated by the X-ray beam. Digital Imaging and Communications in Medicine (DICOM) Structured Report Dose data sent to a modular dosimetry database automatically extracts the 11 XA tags necessary for peak skin dose computation. Skin dose calculation software uses these tags (gantry angles, air kerma at the patient entrance reference point, etc.) and applies appropriate corrections of exposure and beam location based on each irradiation event (fluoroscopy and acquistions). A physicist screen records the initial validation of the accuracy, patient and equipment geometry, DICOM compliance, exposure output calibration, backscatter factor, and table and pad attenuation once per system. A technologist screen specifies patient positioning, patient height and weight, and physician user. Peak skin dose is computed and localized; additionally, fluoroscopy duration and kerma area product values are electronically recorded and sent to the XA database. This approach fully addresses current limitations in meeting accreditation criteria, eliminates the need for paper logs at a XA console, and provides a method where automated ALARA montoring is possible including email and pager alerts.
Peak skin dose; sentinal event; DICOM structured report dose; patient entrance reference point; fluoroscopy; interventional radiology; Joint Commission (JC); radiation dose; Digital Imaging and Communications in Medicine (DICOM)
A typical choice faced by Picture Archiving and Communication System (PACS) administrators is deciding how many PACS workstations are needed and where they should be sited. Oftentimes, the social consequences of having too few are severe enough to encourage oversupply and underutilization. This is costly, at best in terms of hardware and electricity, and at worst (depending on the PACS licensing and support model) in capital costs and maintenance fees. The PACS administrator needs tools to asses accurately the use to which her fleet is being subjected, and thus make informed choices before buying more workstations. Lacking a vended solution for this challenge, we developed our own.
Clinical use determination; Computer systems; Cost savings; Data mining
Researchers in medical imaging have multiple challenges for storing, indexing, maintaining viability, and sharing their data. Addressing all these concerns requires a constellation of tools, but not all of them need to be local to the site. In particular, the data storage challenges faced by researchers can begin to require professional information technology skills. With limited human resources and funds, the medical imaging researcher may be better served with an outsourcing strategy for some management aspects. This paper outlines an approach to manage the main objectives faced by medical imaging scientists whose work includes processing and data mining on non-standard file formats, and relating those files to the their DICOM standard descendents. The capacity of the approach scales as the researcher’s need grows by leveraging the on-demand provisioning ability of cloud computing.
Imaging informatics; information storage and retrieval; internet technology
Radiology examinations are large. The advent of fast volume imaging is making that statement truer every year. PACS are based on the assumption of fast local networking and just-in-time image pull to the desktop. On the other hand, teleradiology has been developed on a push model to accommodate the challenges of moderate bandwidth, high-latency wide area networks (WANs). Our group faced the challenging task of creating a PACS environment that felt local, while pulling images across a 3,000-mile roundtrip WAN link. Initial tests showed WAN performance lagging local area network (LAN) performance by a factor of 30 times. A 16-month journey of explorations pulled the WAN value down to only 1.5 times slower than the LAN.
Enterprise PACS; wide area network (WAN); teleradiology
The U.S. National Press has brought to full public discussion concerns regarding the use of medical radiation, specifically x-ray computed tomography (CT), in diagnosis. A need exists for developing methods whereby assurance is given that all diagnostic medical radiation use is properly prescribed, and all patients’ radiation exposure is monitored. The “DICOM Index Tracker©” (DIT) transparently captures desired digital imaging and communications in medicine (DICOM) tags from CT, nuclear imaging equipment, and other DICOM devices across an enterprise. Its initial use is recording, monitoring, and providing automatic alerts to medical professionals of excursions beyond internally determined trigger action levels of radiation. A flexible knowledge base, aware of equipment in use, enables automatic alerts to system administrators of newly identified equipment models or software versions so that DIT can be adapted to the new equipment or software. A dosimetry module accepts mammography breast organ dose, skin air kerma values from XA modalities, exposure indices from computed radiography, etc. upon receipt. The American Association of Physicists in Medicine recommended a methodology for effective dose calculations which are performed with CT units having DICOM structured dose reports. Web interface reporting is provided for accessing the database in real-time. DIT is DICOM-compliant and, thus, is standardized for international comparisons. Automatic alerts currently in use include: email, cell phone text message, and internal pager text messaging. This system extends the utility of DICOM for standardizing the capturing and computing of radiation dose as well as other quality measures.
Data extraction; medical informatics applications; radiation dose; database management systems; knowledge base
Academic medical centers, in general, and radiation oncology research, in particular, rely heavily on custom software tools and applications. The code development is typically the responsibility of a single individual or at most a small team. Often these individuals are not professional programmers but physicists, students, and physicians. While they possess domain expertise and algorithm knowledge, they often are not fully aware of general “safe coding” practices—nor do they need the full complexity familiar in large commercial software projects to succeed. Rather, some simple guidelines we refer to as “programming in the small” can be used.
Quality assurance; software design; medical informatics applications
There is continual pressure on the radiology department to increase its productivity. Two important links to productivity in the computed/digital radiography (CR/DR) workflow chain are the postprocessing step by technologists and the primary diagnosis step by radiologists, who may apply additional image enhancements to aid them in diagnosis. With the large matrix size of CR and DR images and the computational complexity of these algorithms, it has been challenging to provide interactive image enhancement, particularly on full-resolution images. We have used a new programmable processor as the main computing engine of enhancement algorithms for CR or DR images. We have mapped these algorithms to the processor, maximally utilizing its architecture. On a 12-bit 2688 × 2688 image, we have achieved the execution time of 465Â ms for adaptive unsharp masking, window/level, image rotate, and lookup table operations using a single processor, which represents at least an order of magnitude improvement compared to the response time of current systems. This kind of performance facilitates rapid computation with preset parameter values and/or enables truly interactive QA processing on radiographs by technologists. The fast response time of these algorithms would be especially useful in a real-time radiology setting, where the radiologist’s waiting time in performing image enhancements before making diagnosis can be greatly reduced. We believe that the use of these processors for fast CR/DR image computing coupled with the seamless flow of images and patient data will enable the radiology department to achieve higher productivity.
Digital radiography; computed radiography; real-time radiology; high-performance computing; workflow; image enhancement; QA processing
A survey was conducted of radiology practices with productivity data from at least 3 of the following 4 workflows: film with manual transcription, filmless with manual transcription, film with speech recognition, and filmless with speech recognition. Two surveys were submitted to candidate sites. The first was used to ascertain suitable available data for follow-up. The second survey requested data for report turn around times, full-time equivalent (FTE) staffing levels, and report volume. Data were collected and stored in a Microsoft Access database and statistical analysis performed in Excel. Whereas several metrics were used, the normalized figure of reports-per-day/FTE was found to have improved an average of 1.9 (for filmless with speech recognition) and 2.3 (for film with speech recognition) over the film with manual transcription case. Filmless with manual transcription was only 1.4 times the value of the all manual case. At the 10% confidence level, both filmless with manual transcription and film with speech recognition workflows were found to have statistically significant enhanced productivity. Insufficient data exist to show if the fully automated workflow (filmless with speech recognition) offers benefits over 2 previous semiautomated workflows.
With each medical center department creating and maintaining its own patient care-related data, nursing and house staff may find it confusing to log into all the information systems necessary to achieve a global perspective of the patient’s state. The Medical Information Network Database application provides a logically centralized Worldwide Web viewing application for the physically distributed data. In addition to coordinating data displays for histories, laboratories, pathology, radiology, and discharge summaries, the application can be configured to apply rule sets to the data and remind caregivers of follow-up tests or of possible reactions to treatment protocols. The viewing client runs on any HTML 2.0-compliant browser, although certain applet enhancements (notably for viewing radiological images) require a browser with Java abilities. With this “thin client” approach, the application can be configured to coexist with other applications (such as a PACS viewer), thus centralizing information and reducing the overall number of computers in the medical center.
Worldwide Web; electronic medical record; DICOM; clinical information system