Safe Hb Concentration Measurement during Bladder Irrigation Using Artificial Intelligence.

Area of Science:

• Biomedical Engineering
• Medical Device Technology
• Optical Sensing

Background:

• Continuous bladder irrigation (CBI) is crucial post-urological procedures.
• Monitoring hemoglobin (Hb) in CBI effluent can indicate bleeding.
• Existing methods for Hb monitoring in CBI are limited.

Purpose of the Study:

• To develop and validate a novel sensor for non-invasive Hb monitoring in CBI effluent.
• To ensure accurate Hb measurements despite potential air bubble interference.
• To assess the sensor's compatibility with various irrigants and measurement conditions.

Main Methods:

• Developed an optical sensor utilizing light absorption for Hb concentration measurement.
• Employed a specific light frequency for detecting both arterial and venous Hb.
• Implemented a neural network to detect and mitigate artifacts from air bubbles.
• Validated the sensor's performance with different irrigants and through glass shielding.

Main Results:

• The sensor accurately measures Hb concentrations up to 3.2 g/dL.
• The integrated neural network robustly detects air bubbles, safeguarding measurements.
• The sensor demonstrated reliable performance in a clinical study.
• Non-invasive monitoring is achievable with current irrigation systems.

Conclusions:

• The developed sensor offers a reliable, non-invasive method for monitoring Hb in CBI.
• The system effectively overcomes challenges like air bubbles in optical measurements.
• This technology has the potential to improve patient monitoring in urology.