A mechanistic approach for intracranial pressure (ICP) level estimation.

Abstract

Abnormally increased intracranial pressure (ICP) requires clinical diagnosis before management; however, the only conclusive methods are invasive. In this study, we propose a non-invasive method to estimate ICP level using readily available MRI measurements. We used a mechanistic model of intracranial pulsatility, incorporating brain solid mechanics, and cerebrospinal fluid (CSF) flow dynamics. The model was personalised from brain displacement and blood/CSF data, to estimate ICP level using a harmonic balance method for efficiency. The efficiency of the method was demonstrated using synthetic data with a relative ICP level estimate error of less than 0.4% and speed-up of more than six times compared to classical optimisation methods. Moreover, the method showed robustness to high levels of noise as well as spatial and temporal resolutions. This study shows the potential of this method as a high-fidelity and non-invasive approach to estimate the ICP level. This non-invasive ICP level estimation method facilitates low-risk, cost-effective diagnosis of ICP-related pathologies.