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

人类大脑已经被广泛研究了几个世纪，但生物力学的作用仍然是未知的。然而，医学成像，实验和计算建模的最新进展已经导致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。脑生物力学建立了大脑的结构，功能和运动之间的关系，使用应用力学的方法。这个领先的美国繁荣、健康和基础设施工程（LEAP-HI）项目结合了新颖的医学成像方法、图像分析、计算建模和机械测试，以确定活脑组织的基本机械特性以及健康和患病组织之间的特性差异，并可能实现神经系统疾病的早期诊断和预防，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财政负担，提高数百万人的生活质量。将为科学和工程领域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、研究生和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。该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合并到一个半自动化的管道中，用于大脑力学的体内研究。超高场磁共振成像技术与自动成像建模集成相结合，将用于跨不同的时空尺度对大脑力学进行特定主题的研究。具体而言，将开发高分辨率机械，结构和连接神经成像工具，并将其与自动脑分割和有限元网格生成和等几何分析相结合，以创建多尺度脑力学计算机模型。然后，这些工具将被用来提供一个深入的表征的机械生物化学反应的创伤性脑损伤，在减压开颅术中风患者，朊病毒样蛋白的进展和痴呆症的脑萎缩之间的耦合。通过开发一个用于创建个性化，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力量，以更好地理解，改善治疗，该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准。

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.