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Summary

Accurate-BV is an image processing algorithm that automatically tracks and retrieves clinically relevant features from each perforator blood vessel within a volume of interest. Accurate-BV’s precision is at voxel-level (~1 mm) and the software calculates: calibre, tortuosity, exit point at fascia, subcutaneous course orientation, and intramuscular course length.

This CAD system extracts accurate and consistent characteristics of the analysed perforators, namely from the Deep Inferior Epigastric Artery (DIEA), enabling superior clinical outcomes based on objective findings.

Challenge | Opportunity

The incoherencies between the imaging studies and the surgical findings presented by the current manual method implicate higher healthcare costs. Solutions based on 3D imaging software have been tested in DIEP flap planning, but they fail to provide precise information on perforator location and properties, which is critical for a thorough surgical planning. Moreover, conventional methodologies for blood vessel segmentation have a poor performance in tracking blood vessels perforators, especially in the intramuscular portion where the signal-to-noise ratio is low.

Main Advantages

  • Reduce DIEP flap surgery and recovery duration, as well as overall complications;
  • Increase the quality of breast reconstruction and patients’ satisfaction;
  • Avoid surgery rescheduling due to incorrect preoperative assessment of blood vessels
  • Support analysis of perforator blood vessels, reducing radiologists’ workload and easing the tracking of blood vessels in regions of difficult evaluation (i.e., intramuscular).

Applications

  • Preoperative planning of DIEP flap surgery

Track and analyse tubular structures in large series of two-dimensional medical images

  • Technology Reference

    16-3415
  • Commercial Rights

    Exclusive
  • Development Stage

    Lab prototype (TRL 3-4)
  • IPR Status

    Patent pending
  • Licensing Availability

    World
  • Industrial Categories

    Healthcare
  • Tags

    Medical imaging, e-Health, Computer-aided diagnosis, Software
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