Stahl Janneck, McGuire Laura Stone, Abou-Mrad Tatiana, Saalfeld Sylvia, Behme Daniel, Alaraj Ali, Berg Philipp
Research Campus STIMULATE, University of Magdeburg, 39106 Magdeburg, Germany.
Department of Medical Engineering, University of Magdeburg, 39106 Magdeburg, Germany.
J Clin Med. 2025 Apr 11;14(8):2638. doi: 10.3390/jcm14082638.
: Intracranial arteriovenous malformations (AVMs) exhibit a complex vasculature characterized by a locally occurring tangled nidus connecting the arterial and venous system bypassing the capillary network. Clinically available imaging modalities may not give sufficient spatial or temporal resolution. Adequate 3D models of large vascular areas and a detailed blood flow analysis of the nidus including the surrounding vessels are not available yet. : Three representative AVM cases containing multimodal image data (3D rotational angiography, magnetic resonance angiography, magnetic resonance venography, and phase-contrast quantitative magnetic resonance imaging) are investigated. Image segmentation results in partial 3D models of the different vascular segments, which are merged into large-scale neurovascular models. Subsequently, image-based blood flow simulations are conducted based on the segmented models using patient-specific flow measurements as boundary conditions. : The segmentation results provide comprehensive 3D models of the overall arteriovenous morphology including realistic nidus vessels. The qualitative results of the hemodynamic simulations show realistic flow behavior in the complex vasculature. Feeding arteries exhibit increased wall shear stress (WSS) and higher flow velocities in two cases compared to contralateral vessels. In addition, feeding arteries are exposed to higher overall WSS with increased value variation between individual vessels (20.1 Pa ± 17.3 Pa) compared to the draining veins having a 62% lower WSS (8.9 Pa ± 5.9 Pa). Blood flow distribution is dragged towards the dominating circulation side feeding the nidus for all the cases quantified by the volume flow direction changes in the posterior communicating arteries. : This multimodal study demonstrates the feasibility of the presented workflow to acquire detailed blood flow predictions in large-scale AVM models based on complex image data. The hemodynamic models serve as a base for endovascular treatment modeling influencing flow patterns in distally located vasculatures.
颅内动静脉畸形（AVM）呈现出复杂的血管系统，其特征是局部出现的缠结病灶，连接动脉和静脉系统，绕过毛细血管网络。临床可用的成像方式可能无法提供足够的空间或时间分辨率。目前还没有适用于大血管区域的足够3D模型，也没有对病灶包括周围血管进行详细的血流分析。：研究了三个包含多模态图像数据（3D旋转血管造影、磁共振血管造影、磁共振静脉造影和相位对比定量磁共振成像）的代表性AVM病例。图像分割得到不同血管段的部分3D模型，这些模型被合并成大规模神经血管模型。随后，基于分割模型，以患者特定的血流测量作为边界条件进行基于图像的血流模拟。：分割结果提供了包括逼真的病灶血管在内的整个动静脉形态的综合3D模型。血流动力学模拟的定性结果显示了复杂血管系统中逼真的血流行为。在两个病例中，供血动脉与对侧血管相比，壁面剪应力（WSS）增加且流速更高。此外，与引流静脉相比，供血动脉暴露于更高的总体WSS，且各血管之间的值变化更大（20.1 Pa±17.3 Pa），引流静脉的WSS低62%（8.9 Pa±5.9 Pa）。通过后交通动脉中体积流方向变化量化的所有病例中，血流分布都被拉向为病灶供血的主导循环侧。：这项多模态研究证明了所提出的工作流程在基于复杂图像数据获取大规模AVM模型中详细血流预测的可行性。血流动力学模型为血管内治疗建模提供了基础，可影响远端血管系统中的血流模式。
