Continuous tracking of aortic aneurysm diameter with peripheral pulse waves: a computational framework combining...

Area of Science:

• Biomedical Engineering
• Cardiovascular Research
• Computational Modeling

Background:

• Abdominal aortic aneurysms (AAA) pose a significant mortality risk, affecting over 1% of adults over 50.
• Current surveillance methods (ultrasound, MRI) use intermittent imaging, potentially missing rapid aneurysm growth.
• Continuous monitoring could improve early detection and intervention for AAA.

Purpose of the Study:

• Investigate the feasibility of continuous AAA diameter tracking using peripheral pulse waves.
• Develop and evaluate computational models for pulse wave analysis in AAA surveillance.
• Assess the potential of photoplethysmography (PPG) for non-invasive AAA monitoring.

Main Methods:

• Utilized a simplified one-dimensional (1D) hemodynamic model for pulse wave propagation simulation.
• Employed a sequential Monte Carlo approach combining MCMC and Kalman filtering for parameter estimation and diameter tracking.
• Evaluated tracking accuracy through 12-month simulations on virtual patients with varying AAA growth patterns.

Main Results:

• Aggregating 1,600 PPG measurements reduced diameter uncertainty to 0.8 mm with known patient-specific parameters.
• Tracking simulations achieved an average RMSE of ~0.3 mm under ideal conditions.
• With population-level parameter bounds, median RMSE was 0.65 mm, demonstrating clinical relevance.

Conclusions:

• Peripheral pulse wave monitoring via PPG sensors shows promise for continuous AAA surveillance.
• This approach could complement traditional imaging, enabling earlier detection of AAA growth.
• Potential for more timely interventions and improved patient outcomes in AAA management.