Computational pipeline for the generation and validation of patient-specific mechanical models of brain development

Q3 Engineering
Mireia Alenyà , Xiaoyu Wang , Julien Lefèvre , Guillaume Auzias , Benjamin Fouquet , Elisenda Eixarch , François Rousseau , Oscar Camara
{"title":"Computational pipeline for the generation and validation of patient-specific mechanical models of brain development","authors":"Mireia Alenyà ,&nbsp;Xiaoyu Wang ,&nbsp;Julien Lefèvre ,&nbsp;Guillaume Auzias ,&nbsp;Benjamin Fouquet ,&nbsp;Elisenda Eixarch ,&nbsp;François Rousseau ,&nbsp;Oscar Camara","doi":"10.1016/j.brain.2022.100045","DOIUrl":null,"url":null,"abstract":"<div><p>The human brain develops from a smooth cortical surface in early stages of fetal life to a convoluted one postnatally, creating an organized ensemble of folds. Abnormal folding patterns are linked to neurodevelopmental disorders. However, the complex multi-scale interactions involved in cortical folding are not fully known yet. Computational models of brain development have contributed to better understand the process of cortical folding, but still leave several questions unanswered. A major limitation of the existing models is that they have basically been applied to synthetic examples or simplified brain anatomies. However, the integration of patient-specific longitudinal imaging data is key for improving the realism of simulations. In this work we present a complete computational pipeline to build and validate patient-specific mechanical models of brain development. Starting from the processing of fetal brain magnetic resonance images (MRI), personalised finite-element 3D meshes were generated, in which biomechanical models were run to simulate brain development. Several metrics were then employed to compare simulation results with neonatal images from the same subjects, on a common reference space. We applied the computational pipeline to a cohort of 29 subjects where fetal and neonatal MRI were available, including controls and ventriculomegaly cases. The neonatal brain simulations had several sulcal patterns similar to the ones observed in neonatal MRI data. However, the pipeline also revealed some limitations of the evaluated mechanical model and the importance of including patient-specific cortical thickness as well as regional and anisotropic growth to obtain more realistic and personalised brain development models.</p><p><strong>Statement of Significance:</strong> Computational modelling has emerged as a powerful tool to study the complex process of brain development during gestation. However, most of the studies performed so far have been carried out in synthetic or two-dimensional geometries due to the difficulties involved in processing real fetal data. Moreover, as there is no correspondence between meshes, comparing them or assessing whether they are realistic or not is not a trivial task. In this work we present a complete computational pipeline to build and validate patient-specific mechanical models of brain development, mainly based on open-source tools.</p></div>","PeriodicalId":72449,"journal":{"name":"Brain multiphysics","volume":"3 ","pages":"Article 100045"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666522022000028/pdfft?md5=1de0fa8ca4d696974474b8b56de564dc&pid=1-s2.0-S2666522022000028-main.pdf","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Brain multiphysics","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666522022000028","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 2

Abstract

The human brain develops from a smooth cortical surface in early stages of fetal life to a convoluted one postnatally, creating an organized ensemble of folds. Abnormal folding patterns are linked to neurodevelopmental disorders. However, the complex multi-scale interactions involved in cortical folding are not fully known yet. Computational models of brain development have contributed to better understand the process of cortical folding, but still leave several questions unanswered. A major limitation of the existing models is that they have basically been applied to synthetic examples or simplified brain anatomies. However, the integration of patient-specific longitudinal imaging data is key for improving the realism of simulations. In this work we present a complete computational pipeline to build and validate patient-specific mechanical models of brain development. Starting from the processing of fetal brain magnetic resonance images (MRI), personalised finite-element 3D meshes were generated, in which biomechanical models were run to simulate brain development. Several metrics were then employed to compare simulation results with neonatal images from the same subjects, on a common reference space. We applied the computational pipeline to a cohort of 29 subjects where fetal and neonatal MRI were available, including controls and ventriculomegaly cases. The neonatal brain simulations had several sulcal patterns similar to the ones observed in neonatal MRI data. However, the pipeline also revealed some limitations of the evaluated mechanical model and the importance of including patient-specific cortical thickness as well as regional and anisotropic growth to obtain more realistic and personalised brain development models.

Statement of Significance: Computational modelling has emerged as a powerful tool to study the complex process of brain development during gestation. However, most of the studies performed so far have been carried out in synthetic or two-dimensional geometries due to the difficulties involved in processing real fetal data. Moreover, as there is no correspondence between meshes, comparing them or assessing whether they are realistic or not is not a trivial task. In this work we present a complete computational pipeline to build and validate patient-specific mechanical models of brain development, mainly based on open-source tools.

用于生成和验证患者特定脑发育力学模型的计算管道
人类大脑从胎儿早期光滑的皮质表面发育到出生后错综复杂的皮质表面,形成有组织的褶皱合体。异常的折叠模式与神经发育障碍有关。然而,涉及皮质折叠的复杂的多尺度相互作用尚不完全清楚。大脑发育的计算模型有助于更好地理解皮层折叠的过程,但仍有几个问题没有得到解答。现有模型的一个主要限制是,它们基本上被应用于合成的例子或简化的大脑解剖。然而,整合患者特定的纵向成像数据是提高模拟真实性的关键。在这项工作中,我们提出了一个完整的计算管道来建立和验证患者特定的大脑发育力学模型。从处理胎儿脑磁共振图像(MRI)开始,生成个性化的有限元三维网格,其中运行生物力学模型来模拟大脑发育。然后采用几个指标来比较模拟结果与新生儿图像从相同的主题,在一个共同的参考空间。我们将计算管道应用于29名胎儿和新生儿MRI可用的受试者队列,包括对照组和脑室肿大病例。新生儿大脑模拟有几个与新生儿MRI数据中观察到的相似的脑沟模式。然而,该管道也揭示了所评估的力学模型的一些局限性,以及包括患者特异性皮质厚度以及区域和各向异性生长的重要性,以获得更真实和个性化的大脑发育模型。意义说明:计算模型已经成为研究妊娠期大脑发育复杂过程的有力工具。然而,由于处理真实胎儿数据的困难,迄今为止进行的大多数研究都是在合成或二维几何形状中进行的。此外,由于网格之间没有对应关系,比较它们或评估它们是否真实并不是一项微不足道的任务。在这项工作中,我们提出了一个完整的计算管道来构建和验证患者特定的大脑发育力学模型,主要基于开源工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Brain multiphysics
Brain multiphysics Physics and Astronomy (General), Modelling and Simulation, Neuroscience (General), Biomedical Engineering
CiteScore
4.80
自引率
0.00%
发文量
0
审稿时长
68 days
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信