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Live Workflow Demonstration: Advanced Processing and Visualization
Saturday, May 17, 2008
3:30 pm – 5:00 pm
Ballroom 6B
 

Advanced Processing & Visualization Workflow and Tools on Display at Live Workflow Demonstration

Friday morning’s general session demonstrated current processes for advanced processing & visualization and a look toward the future and how workflow and tools might be improved. Katherine Andriole, PhD, Paul Chang, MD, and Luciano Prevedello, MD, play acted roles in a typical scenario to illustrate how complicated the current situation is.

Andriole said that the advent of Multidetector CT and the maturation of PACS have been key to advancing post-processing applications. Andriole played the role of the CT technologist, Chang the radiologist, and Prevedello doubled as the surgeon and lab technologist as the team spotlighted different pain points in the process and how advanced processing & visualization fits into the workflow. The team used a hypothetical scenario to demonstrate an “embellished” version of a radiology department.

 
   
 

In the current general department workflow – ordering, scheduling, acquisition, interpretation, and reporting – advanced processing & visualization doesn’t really have a logical place. In their demonstration, the team illustrated how it is often unclear where APV fits. Communication between departments, uploading and transferring studies and images, and disparate schedules often combine for a process that is less than efficient. Current workflow issues include lack of automation, orchestration of all tasks, coordinating standalone systems, increased network traffic, poor communication among all players, what images should be sent to PACS, and what images should be archived. There are implications with large data sets, policy and procedure issues, medico-legal issues, and the health care payer environment.

The team proposed a post-processing workflow of the future, which they called “the Magic Box.” Each person would log in at their own station to complete their steps in the process. Requirements for success include no disruption to the radiologist workflow, no negative impact on PACS performance as a result of thin-slice data, and must be able to validate if images can be approximately read from the thin-slice data set.

As these tools become more available, said Prevedello, education must be in place to support the new workflow.
 

  SIIM gratefully acknowledges the support of the Live Workflow Demonstration session through an unrestricted educational grant provided by Philips Medical Systems.

 
Katherine P. Andriole, PhD 
Brigham and Women’s Hospital, Harvard Medical School
Paul J. Chang, MD
University of Chicago Pritzker School of Medicine
Luciano M. Prevedello, MD
Brigham and Women’s Hospital, Harvard Medical School

Be sure to attend our Advanced Processing and Visualization Workflow Demonstration providing a look at the current and possible future states during the Friday May 16, 2008 General Session from 8am to 9:30am in Ballroom 6B.

Advanced image processing, analysis and display have become essential tools for radiologists and other clinicians. These applications may improve diagnostic efficacy and assist in directing crucial treatment decisions. Recent applications and advances using CT, MRI and other imaging modalities facilitate and in fact require workflow changes to realize the full benefits of these technologies.



Come see today’s hell as we demonstrate current pain points in the imaging chain from exam protocoling, image acquisition, transmission, management, display, interpretation, review, and reporting while we visit the radiologist in the reading room, the technologist at the CT scanner, the image processor in the 3D lab, and the surgeon in the operating room. Then take a look at where advanced processing and visualization workflow should be and hear some suggestions for how we might get there.

Don’t miss Friday morning’s general session!                           

Abstract:                                                                                                                     The advent of Multi-Detector Computed Tomography (MDCT) combined with advances in computer applications has transformed standard bi-planar imaging and has introduced the ability to easily manipulate and review complex three-dimensional images using post-processing techniques. These tools are expected to have a positive impact on imaging by improving the diagnostic efficacy and in directing crucial treatment decisions. Processing may help in identifying case complications, and relaying the anatomic information in a manner familiar to the clinician, which may ultimately improve patient care. For this to happen, the integration of these applications within the usual workflow is of utmost importance.

Although post-processing applications have been recognized to be an important tool for diagnostic radiology, they have been sub-optimally used in many institutions despite multiple products being available for purchase.  The main reasons for this are the amount of time spent performing the processing; decreased availability of workstations; and a shortage of professionals trained to use these post-processing applications. Recently, with the ability to embed these applications into PACS, radiologists have had the opportunity to generate advanced post-processing images without disrupting their workflow. As these tools become more available and intuitive to use, and their value to radiological diagnosis and contributions to clinical patient management are documented, the need for information on the subject will increase.

The rationale for using radiologist-driven post-processing tools in clinical radiology are presented using specific case-based examples.  The problems and benefits associated with using these applications as part of the workflow are discussed.

 Learning Objectives

  • Demonstrate the principles of clinically useful post-processing tools in clinical radiology using a case-based approach.
  • Explain the obstacles involved in the integration of these tools with PACS.
  • Identify the limitations associated with using these techniques.