Microemboli detection on extracorporeal bypass circuits

J E Lynch1, J B Riley

  • 1Luna Innovations Incorporated, Hampton, VA, USA. lyncht@lunainnovations.com

Perfusion
|September 16, 2008
PubMed

Insights

Gaseous microembolization during cardiopulmonary bypass (CPB) is linked to adverse brain outcomes. Monitoring for gaseous microemboli (GME) can reduce embolic load, with new ultrasonic imaging improving detection and quantification.

Area of Science:

  • Cardiovascular Surgery
  • Neurology
  • Biomedical Engineering

Background:

  • Gaseous microembolization during cardiopulmonary bypass (CPB) is associated with negative cerebral outcomes.
  • Quantifying this link is challenging due to factors like bubble size, location, and patient comorbidities.
  • Studies show significant differences in cerebral emboli counts between patients with and without stroke or major cardiac complications.

Purpose of the Study:

  • To review methods for monitoring and reducing gaseous microemboli (GME) during CPB.
  • To compare different ultrasonic detection technologies for GME.
  • To highlight the advantages of fixed-beam ultrasonic imaging for quantifying embolic load.

Main Methods:

  • Review of case reports and laboratory studies on GME monitoring and reduction techniques.
  • Analysis of methods to improve CPB circuit design and priming procedures.
  • Comparison of ultrasonic detection technologies: through-transmission gross air detectors, Doppler ultrasound, and fixed-beam ultrasonic imaging.

Main Results:

  • Various strategies can reduce the embolic load delivered during CPB.
  • Different ultrasonic detection methods yield varying GME counts.
  • Fixed-beam ultrasonic imaging offers improved monitoring, measurement, and quantification of embolic load.

Conclusions:

  • Effective monitoring and reduction of GME during CPB are crucial for mitigating adverse cerebral outcomes.
  • Fixed-beam ultrasonic imaging represents a significant advancement in accurately assessing embolic load during CPB.
  • Understanding variations in detection technologies is key to interpreting GME data.