Advanced visualization technology in medicine, the utilization of software-based tools for image reconstruction and analysis, is generally accepted as the province of diagnostic radiology. However, other medical disciplines such as radiation oncology, cardiology, and orthopedics are employing these applications to deliver effective treatment, identify and track the progression of disease as well as plan surgical interventions.
As the technology rapidly moves beyond its radiology-centric origins, a wider variety of clinicians are demanding access to processed image reconstructions—and they want the image datasets as quickly as possible.
The embrace of advanced visualization software by the clinical continuum presents workflow challenges to a practice utilizing the technology, according to Paul J. Chang, MD, professor and vice-chairman of radiology informatics as well as medical director of pathology informatics at the University of Chicago School of Medicine, and medical director of enterprise imaging at the University of Chicago Hospitals.
“There are three dominant workflow models for advanced visualization processing,” Chang says. “The radiologist can do it; a super-technologist trained on the software can do it; or you can outsource it.”
In the diagnostic trenches, most practices opt for a hybrid that may incorporate all three models, he says. However, irrespective of what model is being used, a group must have an infrastructure in place that does advanced visualization processing efficiently.
“Your infrastructure and workflow model has to be agile, flexible and scalable enough to be able to support all three dominant models simultaneously,” Chang says. “Most facilities will have the radiologist and super-tech model in place, and there are some that use all three models.”
For example, in his role as a diagnostic radiologist, he finds that there are some reconstructions that require more of his time to perform than is practical given the volume of imaging exams he must interpret. In these cases, it is vastly more efficient and economical for a technologist skilled in utilization of the advanced visualization software to perform the image processing, and then have it sent to him for clinical interpretation.
Elliot Fishman, MD, professor of radiology and oncology at the Johns Hopkins University School of Medicine in Baltimore, and director of diagnostic imaging and director of the division of abdominal imaging and CT at the Johns Hopkins Hospital has been a long-time user of advanced visualization technology. He recommends that practices seeking to add advanced visualization capabilities to their service lines first look at their image acquisition protocols.
“The first thing, of course, is the ability to acquire the data sets,” he says. “So, whatever CT scanner you have, you need to know how to use the scanner well. You need to have it optimized, because when all is said and done unless you have a good data set, nothing else happens.”
Achieving expertise on the advanced visualization application is the next step a practice must take for successful deployment of the technology, Fishman says.
“The interpreting clinician must gain expertise on the advanced visualization software; it’s this post-processing that allows you to make an accurate diagnosis,” he says. “You need to know how to do the post-processing both accurately and in a timely fashion.”
Fishman states that the reasons most often cited for not performing cardiac CT studies are that it’s too hard to get the data and its too time consuming in the post-processing of the image data.
“Advanced visualization applications have changed—they’re much better; the tools are easier, simpler, and more quantitative, but you still have to learn how to use it,” he says. “I strongly recommend that, as the interpreting physician, you know how to do it yourself. It can’t be something a third-party does and then gives you the information—you need to be interactive with the data set or you’re just not going to feel comfortable reading the studies.”
The 3D laboratory
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