LEAP-HI: Tackling Brain Diseases with Mechanics: A Data-Driven Approach to Merge Advanced Neuroimaging and Multi-Physics Modeling

几个世纪以来，人们对人脑进行了广泛的研究，但生物力学的作用大多尚不清楚。然而，最近在医学成像、实验和计算建模方面的进展导致了越来越多的证据将人脑的生物力学与大脑发育、疾病和损伤的主要过程联系起来。大脑生物力学利用应用力学的方法，建立了大脑的结构、功能和运动之间的关系。这一领先的美国繁荣、健康和基础设施工程(LEAP-HI)项目结合了新的医学成像方法、图像分析、计算建模和机械测试，以确定活的脑组织的基本机械属性以及健康和患病组织之间的属性差异，并可能使早期诊断和预防神经疾病，如中风、创伤性脑损伤和痴呆症。因此，该项目有可能减轻社会的经济负担，提高数百万人的生活质量。将为科学和工程领域中代表性不足的群体提供脑力学方面的外展活动，并为本科生和研究生以及博士后研究人员提供培训机会。这项研究将为研究健康和疾病中的人脑机械生物学提供一个新的平台。研究小组将开发一种新的方法，将先进的神经成像工具和多物理大脑建模结合到一个半自动管道中，用于活体脑力学研究。超高场磁共振成像技术与自动成像-建模集成将被用于实现跨不同时空尺度的特定于受试者的脑力学研究。具体地说，将开发超高分辨率的机械、结构和连接神经成像工具，并将其与用于有限元和等距分析的脑自动分割和网格生成集成在一起，以创建多尺度脑力学计算机模型。然后，这些工具将被用来深入描述创伤性脑损伤、中风患者去骨瓣减压术中的机械性生化反应，以及痴呆症患者普恩样蛋白进展和脑萎缩之间的耦合。通过开发创建个性化的、数据驱动的大脑模型的管道，研究团队将展示组合成像、建模和机器学习技术的变革性力量，以更好地理解、改善治疗，并最终为神经疾病提供预防医学。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The human brain has been studied extensively for centuries, but the role of biomechanics remains mostly unknown. Recent advances in medical imaging, experimentation, and computational modeling, however, have led to a growing body of evidence linking biomechanics of the human brain with major processes in brain development, disease, and damage. Brain biomechanics establishes a relationship between the brain’s structure, function, and motion using the methods of applied mechanics. This Leading Engineering for America's Prosperity, Health, and Infrastructure (LEAP-HI) project combines novel medical imaging methods, image analysis, computational modeling, and mechanical testing to determine the fundamental mechanical properties of living brain tissues and the differences in properties between healthy and diseased tissues, and may enable the early diagnosis and prevention of neurological disorders, such as stroke, traumatic brain injury, and dementia. As such, the project has the potential to reduce the financial burden on society and increase the quality of life for millions of people. Outreach activities in brain mechanics will be provided for underrepresented groups in science and engineering, as well as training opportunities for undergraduate and graduate students, and postdoctoral researchers.The research will provide a novel platform for investigating the mechanobiology of the human brain in health and disease. The research team will develop a novel approach to merge advanced neuroimaging tools and multi-physics brain modeling into a semi-automated pipeline for the in vivo investigation of brain mechanics. Ultrahigh field magnetic resonance imaging technology merged with automated imaging-modeling integration will be utilized to enable the subject-specific investigation of brain mechanics across disparate spatio-temporal scales. Specifically, ultrahigh resolution mechanical, structural, and connectomic neuroimaging tools will be developed and integrated with automatic brain segmentation and mesh generation for finite element and isogeometric analysis to create multi-scale brain mechanics computer models. These tools will then be utilized to provide an in-depth characterization of the mechanobiochemical response of traumatic brain injury, in decompressive craniectomies for stroke patients, and the coupling between prion-like protein progression and cerebral atrophy in dementia. By developing a pipeline for the creation of personalized, data-driven brain models, the research team will demonstrate the transformative power of combined imaging, modeling, and machine learning techniques towards better understanding, improved treatment, and ultimately preventive medicine for neurological disorders.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.