CAAS QCA Bifurcation

CAAS QCA Bifurcation is quantitative coronary analysis specifically developed for lesions analysis of coronary angiographic images across bifurcated vessels. CAAS QCA Bifurcation is available as an option to the CAAS QCA module. Pie Medical Imaging offers accurate contour detection of bifurcated coronary arteries as well as obstruction and subsegment* analysis.

 

Coronary lesions located in bifurcations are associated with a higher rate of complications and restenosis. A number of innovative techniques and dedicated devices are being developed. In order to assess the efficacy of these techniques and devices CAAS QCA Bifurcation analysis is developed.

 


 

CAAS QCA Bifurcation demo

Bifurcation demo

 

       

Click here to learn about the methods of the CAAS QCA bifurcation software (FLASH demonstration).

  • Click on the images to take a closer look at CAAS QCA Bifurcation software:

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Download CAAS QCA Bifurcation PDF

 

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Go to the CAAS QCA Bifurcation literature section

 

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Contact us for a CAAS QCA Bifurcation demo 

 

 Key benefits CAAS QCA Bifurcation 
  • New approach to bifurcation analysis
  • Accurate and reproducible results
  • Based on proven CAAS algorithms
  • Well documented and understood
  • First choice for clinical research

 

  Key product features CAAS QCA Bifurcation
  • Fast detection of contours of bifurcated vessels
  • Automatic obstruction analyses
  • Handling of the bifurcation as a single unambiguous object
  • Local reference obstruction analysis

Key results CAAS QCA
Bifurcation

  • Diameters and Reference diameters for all segments
  • % Diameter stenosis
  • Automatic Bifurcation Stent Segmental Analysis*
  • Length stenotic segment

CAAS QCA reads and writes DICOM files in standard chapter-10 format and is available for Microsoft Windows 200, XP and Vista. The software is easy to integrate with cardiology and radiology PACS systems. Results can be saved as DICOM, DICOM SR and XLM file. CAAS QCA is 510(k) cleared and CE labeled.

 

* Available for QCA Research