Improved biomechanical metrics of cerebral vasospasm identified via sensitivity analysis of a 1D cerebral circulation...

Area of Science:

• Biomedical Engineering
• Cardiovascular Physiology
• Medical Diagnostics

Background:

• Cerebral vasospasm (CVS) is a critical complication of subarachnoid hemorrhage and stroke.
• Current diagnosis via Doppler ultrasound has limitations in sensitivity for peripheral vasculature.
• There is a need for alternative biomarkers for accurate CVS diagnosis and monitoring.

Purpose of the Study:

• To identify novel biomarkers for diagnosing cerebral vasospasm.
• To explore alternative methods beyond blood velocity for CVS detection.
• To enhance the characterization and monitoring of CVS progression.

Main Methods:

• Utilized a 1D modeling approach to simulate pulse wave propagation in a cerebral network.
• Employed a Gaussian process statistical emulator for sensitivity analysis.
• Characterized the effects of vasospasm on waveform properties at multiple simulated locations.

Main Results:

• Identified specific pulse wave features correlated with vasospasm.
• Demonstrated that the minimum rate of velocity change is a more effective biomarker than blood velocity for CVS stratification.
• Showcased the potential of waveform analysis for characterizing vasospasm severity and progression.

Conclusions:

• Pulse wave analysis offers a promising alternative for diagnosing and monitoring cerebral vasospasm.
• The minimum rate of velocity change is a key feature for improved CVS detection.
• The methodology can be extended to diagnose other cardiovascular diseases through pulse wave decoding.