Imagine that you run a large city, and that up until now, the sole transportation available has been buses—but with the price of automobiles coming down, citizens suddenly want to drive cars.
Keith Dreyer, DO, Phd
This situation is somewhat analogous to what’s happening to 3D imaging in the radiology department at Massachusetts General Hospital (MGH), Boston. For a decade, MGH has spent large sums of money creating a world-class 3D imaging lab. Technologists have been rigorously trained to provide radiologists of various subspecialties with intricate, highly augmented 3D studies.
According to Keith Dreyer, DO, PhD, vice chair of radiology and informatics at MGH, of the 750,000 radiological exams done by the hospital each year, more than 50,000 now go through 3D postprocessing in the lab. To create these studies, technologists sit at specially designed 3D workstations where they follow highly evolved protocols to prepare the images for interpretation.
The huge advantage of the 3D lab model is that radiologists are being fed image sets already prepared for them. The radiologists can move quickly and efficiently from one case to the next without having to create views themselves.
The difficulty with the lab model, however, is exactly that—radiologists can’t interact with the studies to create their own views. Like passengers on the bus, they are dependent on the technologist drivers. If they want a special view, they have to request it. The bus has to turn to let them off at that stop.
Dreyer estimates that 90% of the studies rendered through the MGH 3D lab require no further work. It’s the remaining 10% that have to go back to the technologists for refinement. This wouldn’t be necessary (or, at least, it would be less necessary) if the radiologists could reformat the images themselves.
Fat and Thin
The 3D workstations where the technologists work run as fat clients. They contain the software necessary to create the 3D studies, and anyone who wants to create such a study has to go to the fat-client workstation and create the study there.
Now, new thin-client technology has evolved, enabling the end user—the radiologist or referring physician—to create 3D studies at a conventional radiology workstation, or even at a desktop PC. For many hospitals, this thin-client technology has been a godsend; smaller institutions can have their 3D renderings without gigantic outlays for a postprocessing lab, Dreyer notes. Because MGH has its lab already in place, however, and because it is such a large institution producing so many exams, the adoption of thin-client technology has been troublesome.
One of the problems has been scalability. Thin-client technology involves sending image data from the modality to a server (most often, from modality to PACS to a series of servers) that contains software to allow the 3D postprocessing of that image data. This centralized computer server acts as a master workstation where the image data can be manipulated prior to interpretation.
The centralized server uses Web-based technology to stream the 3D data out to other workstations or PCs, where radiologists or clinicians can manipulate the 3D images to suit their specific needs. With a thin client, the passengers on the bus become drivers of their own cars. If they need to remove bone electronically to study vascular structure, they don’t need to wait for a technologist. Radiologists using a thin client can interact with the original 3D studies (unlike the set views they receive from the lab), zeroing in on what they want to see.
As Dreyer notes, one of the problems with interactive thin clients is that the vendors have not yet solved the problem of allowing simultaneous access to studies by a large number of users. When an institution needs concurrent access for only a dozen or so end users, the thin-client servers work well. Dreyer says, however, “I’ve got 5,000 physicians who might all want to look at the same time—and realistically, I probably have 100 who might all want to look at the same time, so it’s really difficult for me. That’s why I’ve been working with vendors for years, so I can scale. It’s a real challenge, right now, to scale these things up to a big size, so that’s why we’ve been at this for a while.”
One company that has built its advanced visualization platform from the ground up on thin-client technology is Massachusetts-based Visage Imaging, a subsidiary of the Australia-based informatics organization