发表机构
Tianjin Medical University（天津医科大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
提出端到端框架，结合自主3D开口定位、可变形流架构、递归树状态机和非线性血流动力学求解器，实现患者特异性冠状动脉中心线提取，优于线性模型缺血评估。
AI 中文摘要
从体积医学图像中提取患者特异性血管树是计算血管造影和非侵入性血流动力学评估的基础。传统的体素分割模型常常切断细小的分叉，而启发式欧几里得最小生成树则引入非解剖学捷径。此外，线性泊肃叶流忽略了动脉狭窄处的二次动能耗散，低估了缺血情况。我们构建了一个端到端框架，将连续的几何树状生成与非线性血流动力学解耦。首先，一个自主3D开口标志定位头，具有双窦查询通道和球形门控细化，消除了中心线播种依赖，在原始对比度上下文中实现了队列平均定位误差7.63毫米（左冠状动脉7.43毫米，右冠状动脉7.83毫米；71.4%≤8.0毫米）。其次，一个空间接地可变形步进流架构通过三线性采样查询连续3D特征金字塔，顺序生成具有锚点边界约束（X(0)=P_start）的轨迹。第三，一个自顶向下递归树状状态机通过树非极大值抑制检测分叉峰值，并参数化前驱父指针（p_k<k），保证单一连通无环树拓扑（β_0=1, β_1=0），具有可微分的步进终止。第四，一个迭代Picard非线性基尔霍夫求解器，采用Young-Tsai/Gould二次耗散，强制机器精度质量守恒（残差5.82e-11毫升/秒）。在14名开发患者中，在标准化在体狭窄应力测试（Q_0=4.0毫升/秒）下，线性泊肃叶流在14/14例中将75%直径病变错误分类为非缺血性（FFR>0.80），而我们的非线性求解器捕获功能性缺血（FFR=0.5864，病变差异32.89毫米汞柱，p=6.10e-5），具有3.66倍侧支分流。测试集防火墙隔离得以维持。
英文摘要
Extracting patient-specific vascular trees from volumetric medical images is fundamental to computational angiography and non-invasive hemodynamic assessment. Conventional voxel segmentation models often sever delicate bifurcations, while heuristic Euclidean Minimum Spanning Trees introduce non-anatomical shortcuts. Moreover, linear Poiseuille flow neglects quadratic kinetic dissipation across arterial narrowings, underestimating ischemia. We formulate an end-to-end framework decoupling continuous geometric arborescence generation from non-linear hemodynamics. First, an autonomous 3D Ostium Landmark Localization Head with dual-sinus query channels and spherical-gated refinement eliminates centerline seeding dependency, achieving cohort mean localization error of 7.63 mm (7.43 mm LCA, 7.83 mm RCA; 71.4% <= 8.0 mm) from raw contrast context. Second, a Spatially-Grounded Deformable Step Flow Architecture queries continuous 3D feature pyramids via trilinear sampling, sequentially generating trajectories with anchor boundary enforcement (X(0) = P_start). Third, a Top-Down Recursive Arborescence State Machine detects bifurcation peaks via Tree-NMS and parameterizes predecessor parent pointers (p_k < k), guaranteeing single connected acyclic tree topology (beta_0 = 1, beta_1 = 0) with differentiable step termination. Fourth, an iterative Picard non-linear Kirchhoff solver with Young-Tsai / Gould quadratic dissipation enforces machine-precision mass conservation (residual 5.82e-11 mL/s). Across 14 development patients under standardized in-silico stenosis stress testing (Q_0 = 4.0 mL/s), linear Poiseuille flow misclassifies 75% diameter lesions as non-ischemic (FFR > 0.80) in 14/14 cases, whereas our non-linear solver captures functional ischemia (FFR = 0.5864, lesion disparity 32.89 mmHg, p = 6.10e-5) with 3.66x collateral shunting. Test set firewall isolation was maintained.
Comments10 pages, 4 figures
