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Estimating intracranial parameters using an inverse mathematical model with viscoelastic elements that closely
Abed Nassir1, Guy Rosenthal2, Yuliya Zadka1
1Department of Biomedical Engineering, Faculty of Engineering, Tel Aviv University, Tel Aviv, Israel.
Computer Methods in Biomechanics and Biomedical Engineering
|February 2, 2024
Summary
A new mathematical model explains intracranial pressure (ICP) waveforms by incorporating viscoelasticity, significantly improving simulation accuracy compared to purely elastic models. This advance aids in understanding intracranial dynamics and estimating biomechanical parameters.
Area of Science:
- Biomedical Engineering
- Neuroscience
- Mathematical Modeling
Background:
- The relationship between arterial blood pressure (ABP) and intracranial pressure (ICP) waveforms is not fully understood.
- Existing models often oversimplify the cranial biomechanics involved.
Purpose of the Study:
- To develop and validate a mathematical model that accurately simulates intracranial pressure (ICP) waveforms based on arterial blood pressure (ABP) waveforms.
- To investigate the role of cranial viscoelasticity in generating ICP waveform morphology.
Main Methods:
- Modified a previously reported mathematical model to include viscoelastic elements.
- Utilized an inverse model methodology with patient data from traumatic brain injury patients.
- Analyzed 65 pairs of ICP and ABP waveforms from 13 patients.
Main Results:
- The viscoelastic model generated ICP waveforms that closely resembled measured data, showing a 16-fold increase in similarity index compared to a purely elastic model.
- The mean similarity index improved from 0.06 ± 0.12 SD to 0.96 ± 0.28 SD.
- Normalized root mean squared error (NRMSE) significantly decreased from 15.2% ± 4.8 to 2.09% ± 0.62.
Conclusions:
- The model's ability to generate complex ICP waveforms suggests it reflects intracranial dynamics.
- The findings indicate potential for estimating inaccessible intracranial biomechanical parameters.
- This research is a foundational step towards clinical applications in assessing intracranial conditions.
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