One hallmark unites the winning entries in the top five medical-imaging IT projects of 2012, cosponsored by Radiology Business Journal and the Society for Imaging Informatics in Medicine (SIIM): Each project represents a view beyond the traditional acquisition, archiving, and communication of radiological images. All of the winning entries take a global view of medical imaging:
- mining the data in the DICOM headers and dose sheets to produce a relevant number for patients’ exposure to radiation;
- solving the technical and operational problems of including non-DICOM images in PACS;
- creating a nonlinear, flexible workflow layer that can tell the radiologist whether a brain tumor has grown before he or she looks at the image, as well as creating a worklist for a geographically disparate organization;
- solving the interoperability issues inherent in the movement of pathology images to create a digital consultation portal for pathology; and
- scouring the electronic medical record (EMR) for the data required to create a safe protocol for a study.
The entries were judged on their innovation/ingenuity, on whether they met critical/urgent/unmet needs, on whether they improved quality, on the product/tool/idea validation or evaluation, and on the universality of the application. All six judges are members of the SIIM board: Donald K. Dennison is an imaging-vendor executive; J. Raymond Geis, MD, is a radiologist with Advanced Medical Imaging Consultants, PC (Fort Collins, Colorado); David S Hirschorn, MD, is director of radiology informatics at Staten Island University Hospital in New York; Elizabeth A. Krupinski, PhD, FSIIM, is a research professor in the departments of radiology and psychology at the University of Arizona; Wyatt M. Tellis, PhD, is an informaticist in the radiology and biomedical imaging department at the University of California–San Francisco; and James T. Whitfill, MD, is CMIO of Southwest Diagnostic Imaging, Ltd (Scottsdale, Arizona). Winners received a $1,000 scholarship to subsidize the cost of attending the 2012 annual SIIM meeting (an award made possible by an unrestricted grant from Bayer HealthCare, maker of the Certegra™ informatics platform). Radiation Dose Intelligent Analytics for CT Examinations (RADIANCE) In June 2012, Cook had one month remaining in her residency at the Hospital of the University of Pennsylvania in Philadelphia before she would begin a fellowship there in cardiovascular imaging. As a combined engineering and computer-science major in undergraduate school, Cook’s interest in IT actually preceded her interest in radiology. Cook credits mentors William Boone, MD, and Woojin Kim, MD, for their roles in the birth of the open-source CT dose-monitoring solution called RADIANCE. “We were at a conference when we started discussing the dose-monitoring problem,” Cook recalls. “When I got back to Philadelphia, I tested a few open-source optical–character-recognition (OCR) tools and stumbled upon something that worked. From there, I continued building and extending the application, and within a few months, we realized that we had a tool that could be useful not only to us, but to the rest of the community.” From the dose sheet, kilovoltage, milliamperage, reference milliamperage, volumetric CT dose index, dose–length product, and phantom type are gathered by RADIANCE. It also imports the total study milliamperage and dose–length product, if they are reported. RADIANCE pulls information from the DICOM study header about the study type, scanner, imaging facility, and patient. These data are stored in a searchable database, on top of which the RADIANCE dashboard, scorecards, and tool kit are built. “We can also query the RIS to pull information such as patient height/weight and personnel involved with the study,” Cook says. Over the summer, Cook plans to develop the HL7 messaging necessary to send the data to an EMR, RIS, or dictation system—news likely to cheer California providers required to include volumetric CT dose index and dose–length product in the imaging report. Problem/Objective There is growing interest in monitoring imaging-related radiation delivered to patients. With CT dose parameters conventionally stored as pixel data on image-based dose sheets, large-scale archival/analysis of these data has proved challenging. Data recorded on these dose sheets represent dose delivered to an acrylic phantom, not the individual patient. Solution Newer CT scanners include dose-related parameters