Abstract

BackgroundCerebrovascular disease, in particular stroke, is a major public health challenge. An important biomarker is cerebral hemodynamics. To measure and quantify cerebral hemodynamics, however, only invasive, potentially harmful or time-to-treatment prolonging methods are available.ResultsWe present a simulation-based approach which allows calculation of cerebral hemodynamics based on the patient-individual vessel configuration derived from structural vessel imaging. For this, we implemented a framework allowing segmentation and annotation of brain vessels from structural imaging followed by 0-dimensional lumped simulation modeling of cerebral hemodynamics. For annotation, a 3D-graphical user interface was implemented. For 0D-simulation, we used a modified nodal analysis, which was adapted for easy implementation by code. The simulation enables identification of areas vulnerable to stroke and simulation of changes due to different systemic blood pressures. Moreover, sensitivity analysis was implemented allowing the live simulation of changes to simulate procedures and disease progression. Beyond presentation of the framework, we demonstrated in an exploratory analysis in 67 patients that the simulation has a high specificity and low-to-moderate sensitivity to detect perfusion changes in classic perfusion imaging.ConclusionsThe presented precision medicine approach using novel biomarkers has the potential to make the application of harmful and complex perfusion methods obsolete.

Highlights

  • Cerebrovascular disease, in particular stroke, is a major public health challenge

  • One of the most important parameters is the hemodynamic status [6]. This biomarker is already used in a precision medicine approach to identify individual patients benefiting from thrombolysis beyond the currently established treatment time windows which is crucial since often treatment is denied due to time constraints [7]

  • We developed a pipeline consisting of the following sequential steps: (1) segmentation of vessel information from structural data, in our case from time-of-flight (TOF) magnetic resonance imaging (MRI). (2) Annotation of the vessel tree with an easy-to-use graphical user interface (GUI)

Read more

Summary

Introduction

Cerebrovascular disease, in particular stroke, is a major public health challenge. An important biomarker is cerebral hemodynamics. Frey et al BioMed Eng OnLine (2021) 20:44 game-changer of stroke treatment success is precision medicine [3, 4] It aims to provide personalized therapy recommendations based on the individual features of the patient. This data is only available using specialized methodologies, i.e., Dynamic Susceptibility-weighted Contrast-enhanced Magnetic Resonance Imaging (DSC-MRI) perfusion, computed-tomography (CT)-perfusion, arterial spin labeling (ASL) perfusion or functional MRI [10,11,12,13,14] These techniques may harm patients through contrast agents, significantly prolong the time to treatment and lead to increased costs. Standardization of these complex methods is highly challenging [6, 15, 16]

Methods
Results
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call