• AI
  • Molecular Imaging
  • CT
  • X-Ray
  • Ultrasound
  • MRI
  • Facility Management
  • Mammography

Vendors match wares in first ECR workstation face-off


Representatives for five workstation vendors worked fast and furiously to complete an assigned set of image postprocessing tasks during the ECR’s first workstation face-off Saturday.

Representatives for five workstation vendors worked fast and furiously to complete an assigned set of image postprocessing tasks during the ECR's first workstation face-off Saturday. The tasks covered common challenges in postprocessing: finding and measuring coronary stenoses revealed on coronary CT scans and polyps obtained via CT colonography. Representatives for the five vendors -- GE Healthcare, Philips MedicalSystems, Medical Solutions, TeraRecon, and Vital Images -- were given four minutes to put their workstations through cardiac and colon data sets provided by ECR. Summaries at the end showed surprisingly wide variations in their findings. Degrees of stenosis found by the systems ranged from a low of 42% to a high of 100%. Sizes of the largest polyps found ranged from 12 mm to 24 mm. The workstation face-off concept has spread rapidly since it was first introduced in 2003 at Stanford University's annual multislice CT conference in San Francisco. This year's ECR face-off featured the same five vendors who joined the original Stanford event, said Robert Taylor, president of TeraRecon and one of many industry observers who crowded into the session to watch. The approaches used have moved much closer to a common standard, Taylor said. Vendors apparently are watching each other and trying to duplicate the best features they observe at the face-off sessions. Still, difference remain among the five. Some workstations allowed users to set sensitivity for computer-aided polyp detection, and the number of potential polyps identified by CAD systems ranged from five (TeraRecon and Siemens) to 16 (GE). Strategies for measuring polyp size and stenosis ranged from highly automated to very nearly manual. For the coronary tests, participants were required to load images into the software, segment the coronary tree, label the coronaries either manually or automatically, report percent area and diameter of stenosis, and export a screenshot of the stenosis.

For the highest diameter stenosis, the results were:

  • Vital Images, 85%
  • GE, 23%
  • TeraRecon, 60%
  • Philips, 75%
  • Siemens, 75%

For the highest area stenosis, the results were:

  • Vital Images, 100%
  • GE, 42%
  • TeraRecon, 84%
  • Philips, 90%
  • Siemens, 95%

For the CT colonography test, the participants were required to precalculate the CAD results, load the data sets, show their most advanced visualization technique, show how to analyze a badly distended sigmoid, identify two of three polyps in the data set and take screen shots, perform automated size measurements and export the images to the report, and show the CAD results.

For the size of the largest lesion, the results were:

  • Vital Images, 21 mm
  • GE, 24 mm
  • TeraRecon, 13 mm
  • Philips 12 mm
  • Siemens, 17 mm

For number of CAD marks, the results were:

  • Vital Images, 12
  • GE, 16
  • TeraRecon, five
  • Siemens, five
  • Philips, 15

Related Videos
Where the USPSTF Breast Cancer Screening Recommendations Fall Short: An Interview with Stacy Smith-Foley, MD
A Closer Look at MRI-Guided Transurethral Ultrasound Ablation for Intermediate Risk Prostate Cancer
Improving the Quality of Breast MRI Acquisition and Processing
Can Fiber Optic RealShape (FORS) Technology Provide a Viable Alternative to X-Rays for Aortic Procedures?
Does Initial CCTA Provide the Best Assessment of Stable Chest Pain?
Making the Case for Intravascular Ultrasound Use in Peripheral Vascular Interventions
Can Diffusion Microstructural Imaging Provide Insights into Long Covid Beyond Conventional MRI?
Assessing the Impact of Radiology Workforce Shortages in Rural Communities
Emerging MRI and PET Research Reveals Link Between Visceral Abdominal Fat and Early Signs of Alzheimer’s Disease
Reimbursement Challenges in Radiology: An Interview with Richard Heller, MD
Related Content
© 2024 MJH Life Sciences

All rights reserved.