发表机构
Isfahan University of Technology; University of Isfahan（伊斯法罕理工大学; 伊斯法罕大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究对比了跨解剖结构迁移与稀疏插值在主动脉流固耦合代理模型中的表现，发现零样本迁移效果差，而基于稀疏锚点的插值方法（如径向基函数）显著更优，为数字孪生代理层提供了初步计算验证。
AI 中文摘要
流固耦合（FSI）代理模型的可信度要求区分跨独立解剖结构的迁移与在已采样表面内的插值。从血管模型库中选取四个去标识化的人体主动脉模型，重建为独立的管腔和标称1.5毫米壁厚域，并在匹配的首周期双向流固耦合条件下进行分析。基于仅几何特征的LightGBM先验模型，在三个解剖结构上通过留一解剖结构法开发，在第四个解剖结构上进行零样本评估，随后通过后零样本稀疏场补全案例研究对六个目标进行探测。零样本迁移在所有目标上表现不佳。在百分之五锚点水平（203个锚点，3852个评估节点）下，先验加自适应达到振荡剪切指数（OSI）的R²为0.603。然而，仅在三个开发解剖结构上训练的相同锚点对照组在多个结果上表现更强：反距离加权达到R²=0.829（OSI）、0.617（峰值von Mises应力）、0.676（平均应力）；径向基函数插值达到0.917、0.714、0.778。因此，稀疏的解剖结构内标签支持场补全，但这一四个解剖结构的队列没有证据表明跨解剖结构先验在直接插值之外增加了价值。我们将此视为迈向测量关联数字孪生的第一个计算阶段：此处评估了代理/更新层，而更大的队列、收敛的FSI、可测量的患者侧输入和物理信息学习仍是未来工作，而非声称完整的临床孪生。我们的代码、数据和计算文件可在https://github.com/ali-nourbakhsh2005/Aortic-FSI-Sparse-Field-Completion获取。
英文摘要
Surrogate credibility for fluid-structure interac- tion (FSI) requires distinguishing transfer across independent anatomies from interpolation within an already sampled surface. Four de-identified human aortic models from the Vascular Model Repository were reconstructed into separate lumen and nominal 1.5-mm wall domains and analyzed under matched first-cycle two-way FSI. A geometry-only LightGBM prior, selected by leave-one-anatomy-out development on three anatomies, was zero-shot evaluated on a fourth, then probed with a post-zero- shot sparse field-completion case study over six targets. Zero-shot transfer was poor across all targets. At a five-percent anchor level (203 anchors, 3,852 evaluation nodes), prior-plus-adaptation reached an oscillatory shear index (OSI) R2 of 0.603. However, same-anchor controls tuned only on the three development anatomies were stronger for several outcomes: inverse-distance weighting reached R2 = 0.829 (OSI), 0.617 (peak von Mises stress), 0.676 (mean stress); radial basis function interpolation reached 0.917, 0.714, 0.778. Sparse within-anatomy labels thus support field completion, but this four-anatomy cohort gives no evidence the cross-anatomy prior adds value beyond direct interpolation. We frame this as a first computational stage toward a measurement-linked digital twin: the surrogate/update layer is evaluated here, while larger cohorts, converged FSI, measurable patient-side inputs, and physics-informed learning remain future work, not a claim of a complete clinical twin. Our code, data and computation files are available at https://github. com/ali-nourbakhsh2005/Aortic-FSI-Sparse-Field-Completion
Comments8 pages, 6 figures, Under review at ICBME 2026
