LOng-Term anatomical fluid dynamics for new Univentricular heartS palliation (LOTUS)

功能性单室心脏（UVH）患儿预后较差，尽管手术治疗。该项目旨在建立一个开源的人工智能和计算流体动力学（CFD）工具，以确定外科医生使用的Fontan手术的“最佳”设计，以延长患者的预期寿命（目前为20-30年）。UVH患者的详细成像将由USM提供，以产生3D几何形状，英国数值模型可以应用于此。USM目前每年治疗40-50例新的UVH患者和150例随访患者，因此他们拥有一个庞大的数据库，涵盖了随着患者生长和不同姑息期而变化的广泛解剖形态。该数据库能够构建一个新颖的数学模型，说明晚年的形态/血流如何取决于手术过程，并预测“最佳”手术设计，最大限度地减少Fontan循环的负面影响。结合高保真曲线离散化、多尺度建模和机器学习，CFD工具将可靠地为外科手术的长期影响提供信息，包括英国团队的新型生理Fontan手术。预期的结果。1. 复杂先天性心脏缺损患者的长期预后研究，特别是所有UVH患者。2. 巩固马来西亚和英国团队之间的伙伴关系，为USM人员提供培训，介绍CFD工具，以优化手术。3. 开发一种针对患者的开源计算工具，以优化功能性UVH儿童的外科手术程序，以提高长期生活质量。4. 将人工智能技术与基于多面体离散的高效可靠的多尺度CFD模型相结合，预测手术的长期结果。5. 我们设想该项目的工具将为UVH缓解失败的原因提供新的见解。6. 该工具还将允许基于更多生理类型的手术连接验证新的Fontan程序，例如英国团队最近提出并评估的CFD研究。

Children with functionally univentricular hearts (UVH) have poor life prognosis, despite surgical treatment. This project aims to build an open-source combined Artificial Intelligence and Computational Fluid Dynamics (CFD) tool to determine 'optimal' designs for the Fontan procedure to be used by surgeons, to enhance patient life expectancy (currently 20-30 years).Detailed imaging from UVH patients will be provided by USM to produce 3D geometries on which UK numerical models can be applied. USM currently treats 40-50 new UVH patients/year and 150 in follow-up, therefore they have a large databank covering a wide range of anatomical morphologies changing with patient growth and various palliative stages. This databank enables the construction of a novel mathematical model of how morphology/flow in later life depends on surgical procedure, with the prediction of the 'optimal' surgical design minimizing the negative impact of the Fontan circulation. Combining high-fidelity curvilinear discretization, multiscale modelling, and machine learning, the CFD tool will reliably inform on long-term impact of surgical procedures, including a novel physiological Fontan procedure by the UK team.Expected outcomes. 1. Study of the long-term prognosis of subjects with complex congenital heart defects, specifically following all patients with UVH. 2. Consolidate partnership between Malaysia and UK teams, provide training to USM personnel introducing CFD tools for surgery optimisation. 3. Develop a patient-specific open-source computational tool to optimize surgical procedures in children with functionally UVH, for better long-term quality of life. 4. Combine artificial intelligence techniques with efficient and reliable multiscale CFD modelling based on recent polyhedral discretisations to predict long-term outcome of surgery. 5. We envisage that the project's tool will provide a new insight on the reason for the failure of UVH palliation. 6. The tool will also permit the validation of new Fontan procedures based on more physiological types of surgical connections, such as the one recently proposed and evaluated with CFD studies by the UK team.