JMIR Publications

ABSTRACT

Background:

Non-invasive intracranial pressure (nICP) estimation is a desirable tool for clinical decision support and improving outcomes for patients with traumatic brain injury (TBI).

Objective:

Existing model-based nICP estimation methods, however, may be too slow or require data not easily obtained. This work considers nICP estimation frameworks driven by arterial blood pressure (ABP) measurements to better inform model development toward clinically-actionable timescales.

Methods:

Two types of model setup are tested and validated at multi-hour timescales to assess the benefits and limitations of applying each at long time periods.

Results:

Over hour-scale times with pulsatile ABP inflow, a simple estimation scheme which include systemic hemodynamic feedback outperforms a more complex nICP model with prescribed intracranial inflow, even under limited ABP data resolution. This indicates that feedback between the systemic vascular network and nICP estimation scheme is crucial to include when modeling over long intervals. We also show that the simple estimation data requirements can be reduced to one-minute averaged ABP summary data under generic waveform representation, but reduction of ABP-only dependence limits its utility in cases involving other brain injuries such as ischemic stroke and subarachnoid hemorrhage

Conclusions:

This indicates that feedback between the systemic vascular network and nICP estimation scheme is crucial to include when modeling over long intervals. We also show that the simple estimation data requirements can be reduced to one-minute averaged ABP summary data under generic waveform representation, but reduction of ABP-only dependence limits its utility in cases involving other brain injuries such as ischemic stroke and subarachnoid hemorrhage.