Structure Preserving Polytopal Discontinuous Galerkin Methods for the Numerical Modeling of Neurodegenerative Diseases

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2024-06-20 DOI:10.1007/s10915-024-02581-7
Mattia Corti, Francesca Bonizzoni, Paola F. Antonietti
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Abstract

Many neurodegenerative diseases are connected to the spreading of misfolded prionic proteins. In this paper, we analyse the process of misfolding and spreading of both \(\alpha \)-synuclein and Amyloid-\(\beta \), related to Parkinson’s and Alzheimer’s diseases, respectively. We introduce and analyze a positivity-preserving numerical method for the discretization of the Fisher-Kolmogorov equation, modelling accumulation and spreading of prionic proteins. The proposed approximation method is based on the discontinuous Galerkin method on polygonal and polyhedral grids for space discretization and on \(\vartheta -\)method time integration scheme. We prove the existence of the discrete solution and a convergence result where the Implicit Euler scheme is employed for time integration. We show that the proposed approach is structure-preserving, in the sense that it guarantees that the discrete solution is non-negative, a feature that is of paramount importance in practical application. The numerical verification of our numerical model is performed both using a manufactured solution and considering wavefront propagation in two-dimensional polygonal grids. Next, we present a simulation of \(\alpha \)-synuclein spreading in a two-dimensional brain slice in the sagittal plane. The polygonal mesh for this simulation is agglomerated maintaining the distinction of white and grey matter, taking advantage of the flexibility of PolyDG methods in the mesh construction. Finally, we simulate the spreading of Amyloid-\(\beta \) in a patient-specific setting by using a three-dimensional geometry reconstructed from magnetic resonance images and an initial condition reconstructed from positron emission tomography. Our numerical simulations confirm that the proposed method is able to capture the evolution of Parkinson’s and Alzheimer’s diseases.

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用于神经退行性疾病数值建模的结构保持型多顶点非连续伽勒金方法
许多神经退行性疾病都与折叠错误的朊病毒蛋白的扩散有关。在本文中,我们分析了分别与帕金森病和阿尔茨海默病有关的突触核蛋白和淀粉样蛋白的错误折叠和扩散过程。我们介绍并分析了一种用于 Fisher-Kolmogorov 方程离散化的正性保留数值方法,该方法模拟了朊病毒蛋白的积累和扩散。所提出的近似方法基于多边形和多面体网格上的非连续伽勒金方法进行空间离散化,并基于\(\vartheta -\)方法的时间积分方案。我们证明了离散解的存在性以及采用隐式欧拉方案进行时间积分时的收敛结果。我们证明了所提出的方法是结构保留的,因为它保证了离散解是非负的,而这一特征在实际应用中是至关重要的。我们使用人造解法和考虑二维多边形网格中的波前传播对我们的数值模型进行了数值验证。接下来,我们展示了矢状面上二维大脑切片中 \(α \)-突触核蛋白扩散的模拟。利用 PolyDG 方法在网格构建中的灵活性,该模拟的多边形网格被聚集在一起,保持了白质和灰质的区别。最后,我们利用从磁共振图像重建的三维几何图形和从正电子发射断层扫描重建的初始条件,模拟了淀粉样蛋白(beta)在患者特定环境中的扩散。我们的数值模拟证实,所提出的方法能够捕捉帕金森病和阿尔茨海默病的演变过程。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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