Machine learning-based biomechanical analysis for thoracic aortic aneurysm rupture risk assessment

基于机器学习的生物力学分析胸主动脉瘤破裂风险评估

• 批准号: 10365444
• 负责人: Liang Liang
• 金额: $ 60.47万
• 依托单位: UNIVERSITY OF MIAMI CORAL GABLES
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-12-03 至 2026-11-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10365444
• 关键词: 3-Dimensional; Adult; Aneurysm; Aorta; Aortic Aneurysm; Biomechanics; Caliber; Calibration; Cardiovascular system; Cause of Death; Cessation of life; Characteristics; Chest; Classification; Clinical; Clinical Trials; Computer Models; Computer software; Consumption; Data; Data Files; Data Set; Death Rate; Development; Devices; Disease; Dissection; Evaluation Studies; Event; Face; Finite Element Analysis; Follow-Up Studies; General Population; Geometry; Goals; Healthcare Systems; Human; Image; Learning; Machine Learning; Magic; Measures; Medical Records; Modeling; Natural Language Processing; Noise; Operative Surgical Procedures; Output; Patients; Performance; Population; Prevalence; Probability; Process; Risk; Risk Assessment; Rupture; Ruptured thoracic aortic aneurysm; Shapes; Source; Stress; Symptoms; Techniques; Testing; Thoracic Aortic Aneurysm; Thoracic aorta; Time; Tissue Sample; Uncertainty; Validation; Visualization; X-Ray Computed Tomography; base; biomechanical test; clinical application; cost; deep neural network; density; effectiveness testing; high risk; improved; in vivo; indexing; individual patient; innovation; insight; machine learning model; method development; mixed reality; novel; open source; prevent; programs; real time model; reconstruction; repaired; speech recognition

PROJECT SUMMARY Aortic aneurysm disease ranks consistently in the top 20 causes of death in the U.S. population. Thoracic aortic aneurysm (TAA) is a leading cause of death in adults. The progression of TAA is a silent process, yet rupture/dissection can occur suddenly, which often causes death. The deadly events are preventable by elective surgical repair, and the current criterion for surgical intervention states that surgery should be performed when TAA maximum diameter reaches 5 to 5.5 cm. However, this criterion cannot assess the risk of smaller TAAs (diameter≤5cm). It is estimated that there are millions of TAA patients in the U.S. with smaller TAAs, and these patients are unfortunately ignored by the current criterion. Thus, in this project, we propose an innovative approach of integrating machine learning (ML) and computational biomechanics for risk assessment of smaller TAAs. To achieve this goal, we will develop (1) ML models for automated thoracic aorta geometry reconstruction from 3D clinical CT images, which will enable a fast and streamlined analysis of TAA risk, (2) ML models for realtime TAA stress analysis, and (3) a probabilistic risk index that fuses the measured and computed patient characteristics (e.g. geometry, stress, material strength, etc) and takes into account uncertainties from different sources. The proposed approach will be developed and validated on an existing dataset of 1000 patients and a new dataset to be assembled from a longitudinal follow-up study of 600 patients, which will be the first large-scale study of machine learning-based biomechanical analysis for TAA risk assessment. This study will lead to a breakthrough in the fields of cardiovascular computational modeling and applied machine learning, provide new insights on how to better assess TAA risk, and reduce death by the silent and sudden killer of TAA disease.

项目摘要 在美国，主动脉瘤疾病始终在死亡的前20个原因中排名 人口。胸动脉瘤（TAA）是成人死亡的主要原因。进展 TAA是一个沉默的过程，但可能会突然发生破裂/解剖，这通常会导致死亡。 致命事件是通过选修手术修复和手术标准预防的 干预指出，当TAA最大直径达到5至5时，应进行手术 5.5厘米。但是，该标准无法评估较小的TAA（直径≤5cm）的风险。这是 据估计，美国有数百万的TAA患者，TAA较小，这些患者 不幸的是，当前标准忽略了。在这个项目中，我们提出了创新的 整合机器学习（ML）和风险计算生物力学的方法 评估较小的TAA。为了实现这一目标，我们将开发（1）自动化的ML模型 从3D临床CT图像重建胸主动脉几何形状，这将使快速且能够 简化了TAA风险分析，（2）用于实时TAA应力分析的ML模型和（3）A 概率风险指数融合了测量和计算的患者特征（例如 几何，压力，物质强度等）并考虑到不同的不确定性 来源。建议的方法将在1000的现有数据集中开发和验证 患者和一个新数据集将从600名患者的纵向随访研究中组装， 这将是对TAA的基于机器学习的生物力学分析的首次大规模研究 风险评估。这项研究将导致心血管领域的突破 计算建模和应用机器学习，提供有关如何更好的新见解 评估TAA风险，并通过TAA疾病的沉默和突然杀手减少死亡。