发表机构
Penn Institute for Computational Science, University of Pennsylvania; Department of Radiology, University of Pennsylvania; Department of Mechanical Engineering and Applied Mechanics, University of Pennsylvania; Children’s Hospital of Philadelphia; Diagnostics Institute, Cleveland Clinic Florida; Department of Surgery, University of Pennsylvania; Department of Bioengineering, University of Pennsylvania（宾夕法尼亚大学计算科学研究所; 宾夕法尼亚大学放射学系; 宾夕法尼亚大学机械工程与应用力学系; 费城儿童医院; 克利夫兰诊所佛罗里达诊断研究所; 宾夕法尼亚大学外科学系; 宾夕法尼亚大学生物工程系）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究开发了基于4D CTA的患者特异性升主动脉应变估计框架，经nnU-Net等技术验证其可靠性，发现应变与主动脉直径等临床指标相关，可用于无创评估主动脉力学。
AI 中文摘要
目的：开发并验证一种从4D计算机断层血管造影（CTA）生成空间分辨升主动脉应变估计的框架，并表征不同分割源和空间尺度下的可靠性。方法：我们使用nnU-Net分割、优化的表面重网格化、可变形配准以及基于网格的应变估计构建患者特异性主动脉应变图谱。有限元（FE）衍生的合成4D CT序列为配准验证提供了受控参考变形。我们表征了不同分割源和拉普拉斯-贝尔特拉米（LB）谱尺度下的应变可靠性，并评估了应变与直径、主动脉高度指数（AHI）及年龄的关联。结果：对于观察者衍生网格，配准衍生的中位应变与FE参考应变的偏差极小（0.0013）；对于nnU-Net衍生网格，该偏差为0.0056。不同分割源间的中位应变偏差低且95%一致性界限（LoA）较窄（观察者间：偏差=-0.0045，LoA[-0.0490,0.0399]；nnU-Net与观察者对比：偏差=-0.0052，LoA[-0.0340,0.0237]）。95百分位应变的差异更大，尤其在观察者间对比中。LB谱分析显示低频应变结构优先保留，k=5重建可将分割相关分歧降低52%-56%。95百分位面积应变与最大升主动脉直径（r=-0.493，p=0.005）、AHI（r=-0.488，p=0.005）及年龄（r=-0.479，p=0.006）呈负相关。3例重度主动脉瓣反流（AR）病例显示出异质性区域应变模式。结论：该框架可从4D CTA重复估计升主动脉应变，表征其在不同分割源和空间尺度下的可靠性，并展现出无创评估患者特异性主动脉力学的潜力。
英文摘要
Objective: To develop and validate a framework for spatially resolved ascending aortic strain estimation from 4D computed tomography angiography (CTA) and characterize reliability across segmentation sources and spatial scales. Methods: We constructed patient-specific aortic strain maps using nnU-Net segmentation, optimized surface remeshing, deformable registration, and mesh-based strain estimation. Finite element (FE)-derived synthetic 4D CT sequences provided controlled reference deformations for registration validation. Strain reliability was characterized across segmentation sources and Laplace-Beltrami (LB) spectral scales. Associations with diameter, aortic height index (AHI), and age were assessed. Results: Registration-derived median strain showed minimal bias relative to FE-reference strain for observer-derived (0.0013) and nnU-Net-derived meshes (0.0056). Median strain exhibited low bias and narrow 95% limits of agreement (LoA) across segmentation sources (interobserver: bias = -0.0045, LoA [-0.0490, 0.0399]; nnU-Net versus observer: bias = -0.0052, LoA [-0.0340, 0.0237]). Differences were greater for 95th-percentile strain, particularly in the interobserver comparison. LB spectral analysis showed preferential preservation of low-frequency strain organization, with k = 5 reconstructions reducing segmentation-related disagreement by 52-56%. The 95th-percentile areal strain was inversely associated with maximum ascending aortic diameter (r = -0.493, p = 0.005), AHI (r = -0.488, p = 0.005), and age (r = -0.479, p = 0.006). Three high-grade AR cases showed heterogeneous regional strain patterns. Conclusion: This framework reproducibly estimates ascending aortic strain from 4D CTA, characterizes its reliability across segmentation sources and spatial scales, and demonstrates its potential for noninvasive assessment of patient-specific aortic mechanics.
