1st choice for Cardiovascular Imaging Software Solutions

LV & RV Function powered by QMass iconQMass


Benefits


  • Provides accurate, reproducible and validated results
  • Decreases inter-observer and intra-observer variability
  • Optimal comparison of results obtained from MR and CT images when using the same post-processing method (provided by QMass)

Features included:


  • LV and RV function analysis
  • Global function analysis (Simpson’s method) on short axis or transversal stack of cines
  • Quantification of custom volumes, such as atrial volumes
  • Area-length and Bi-plane volumetric analysis methods for long axis cines
  • Automatic contour detection of LV endo and epicardium and RV endocardium, semi- automatic contour editing
  • “LiveContour” algorithm to quickly detect endocardial contours
  • Automatic exclusion of images in short axis based on information in long axis ?
  • Auto-detection of papillary muscles and trabeculae with “MassK mode”
  • Quantification of EDV, ESV, SV, %EF, CO, CI, indexed values (BSA and height), (time to) peak filling and ejection rate ? Various BSA calculation methods for indexed results
  • Various normal ranges possible, calculation of z-scores
  • Analysis of regional parameters, such as wall motion, wall thickness, wall thickening and wall thickness changes over time

Did you know that:


the 3DView app on Medis Suite CT can be used as a reformatter to obtain suitable multi-phase multi-slice series for LV & RV Functional analysis?

Clinical Apps

All Medis Suite CT apps in blue are cleared for clinical use in Europe, the USA, Canada, Japan and South-Korea.

Medis, QMass and QAngio are registered trademarks of Medis Associated BV.

QMass and QFlow are based on image processing algorithms developed at the Division of Image Processing, Department of Radiology, Leiden University Medical Center, the Netherlands

Research Apps

All Medis Suite CT apps in purple are for research use only.

QAngio CT Research Edition is based on image processing algorithms developed at the Division of Image Processing, Department of Radiology, Leiden University Medical Center, the Netherlands