Advanced Visualization Spans the Enterprise
Source: Ziosoft
The demand for image post-processing by advanced visualization technology continues to grow across the healthcare enterprise. Maximum intensity projection (MIP), multiplanar reformation (MPR), and 3D modeling tools are in demand by radiologists, cardiologists, neurologists and surgeons specializing in oncologic, orthopedic, vascular, neuro and cardiac interventions.

Workstation-based advanced visualization systems have long been the technology’s workhorses; however, when images are generated, interpreted and utilized at multiple sites by multiple users, an enterprise-level system can deliver the scalability and efficiency that single-site systems cannot.

“We are beginning to experience a paradigm shift in the way images are being transferred from multislice modalities,” says Rasu Shrestha, MD, chief of the University of Pittsburgh Medical Center’s division of radiology informatics.

While primarily located in western Pennsylvania, Shrestha says that his network reaches out to many international centers to provide radiology services. The University of Pittsburgh Medical Center (UPMC) uses a mix of Vital Images Vitrea Enterprise Suite and GE Healthcare’s Advantage Workstation image post-processing tools. The UPMC network includes 20 hospitals and 30 imaging centers that complete about 2 million scans annually.

The adoption of enterprise-level advanced visualization technology means that terabytes of data can be sent over a network spanning a large geographic region, allowing clinicians to work on the same image for different specialties, Shrestha says.

Depending on the vendor and product, a radiologist and a surgeon can be working simultaneously on one data set in different locations, says Myron Pozniak, MD, chief of abdominal imaging division at the University of Wisconsin School of Medicine and Public Health.

Advanced visualization technology across the enterprise is “all about the transmission of findings to the clinicians,” says Pozniak. “It’s all about healthcare professionals who don’t image on a regular basis getting the bigger picture; seeing the entirety of the findings in a method in which they can absorb them. Words on a paper, axial slices and even some 2D images don’t quite do it, but if you have a volume-rendered 3D dataset that you can interact with and move around, it’s so much easier for the surgeon or anyone who has to intervene on a patient to understand what’s going on with that patient.”

Pozniak finds the Ziosoft Ziostation system, a thin-client advanced visualization technology system, deployed at his facility to be a big help in his consultations with referring clinicians. “It’s much easier for the non-imager to look at an abnormality and say ‘I understand’ when it’s shown to him or her in 3D. That’s really the big benefit [to enterprise advanced visualization],” he says.

A well-educated patient base is another reason for an uptick in enterprise-level advanced visualization technology deployments, according to Duleep Wikramanayake, chief information officer at Trumbull, Conn.-based Advanced Radiology Consultants, a user of Visage Imaging’s Visage CS.

Patients, Wikramanayake says, are becoming more educated on the imaging systems being used to diagnose issues within their bodies. Advanced visualization technologies, he says, are less invasive to the patient because you don’t have to cut somebody open and can therefore be a differentiator in where a patient goes for care.

The demand in this technology has created a glut of datasets needing to be managed by facilities.

Wikramanayake suggests in “terms of scalability, you want to invest in a thin client-server environment, because for all these studies and the amount of data transferring from place to place, you require a huge network. If you have a client server, you can get it up once and many people can access the images.”

Shrestha believes that data management systems, such as PACS, are changing and will be better able to leverage client capabilities—such as even larger image datasets—in the future.

“Currently, we are dealing with a tsunami of data,” he says. “On one hand, we have an issue dealing with large datasets and the clinical need to be more dependent on advanced visualization post-processing. On the other hand, facilities are stuck with imaging reconstructions built only a year or two ago and aren’t able to handle large data loads.”