Vessel distance mapping: Quantification of subcortical arterial and venous vascular patterns to study their interdependency

大脑的完整性和功能分别依赖于通过动脉和静脉血管系统的血液供应和排出。皮质下结构涉及运动、感觉、认知和行为任务，由大脑主要动脉灌流。这些大动脉的灌注区在不同受试者的空间上是不同的。这种可变性会影响小的穿通动脉的组织。我们假设，皮质下灌注区的这种变异性是从动脉侧通过毛细血管床传播到皮质下静脉的组织中。因此，我们怀疑皮质下动脉和静脉血管是相互依赖的，并且存在不同的血管模式。因此，如果单个皮质下血管的轨迹发生改变，这可能会导致其周围的动脉和静脉网络发生变化，以维持局部血管-血管-血管距离的特定模式。据我们所知，这种假设的动脉-静脉模式的相互依存关系到目前为止还没有得到全面的研究。为了在活人身上无创地验证这一假说，已经确定了以下目标：(1)使用超高场MRI和预期运动校正来达到所需的高分辨率(体素大小和0.4 mm)以描绘穿通动静脉(2)使用血管过滤器分割血管并应用距离变换来计算血管距离图(3)使用无监督聚类找到常见的皮质下动-静脉模式(4)由专家彻底验证每个处理步骤通过实现这些目标，将建立一种新的、全自动的血管距离模式分析技术。此外，证明动脉和静脉血管系统的相互依赖性可能会对小血管成像、诊断和治疗产生总体上的影响，因为相互依赖可能使联合评估比关注血管系统的单侧更有希望。由于神经退行性疾病的血管成分和衰老可以诱导特定的血管-血管模式的进展，该方法可以作为未来纵向研究的新的生物标志物。

The integrity and function of the brain rely on the supply and draining of blood through the arterial and venous vasculature, respectively. Subcortical structures, involved in motor, sensory, cognitive and behavioral tasks, are perfused by the major cerebral arteries. The perfusion territories of these large arteries are spatially variable between subjects. This variability influences the organization of small, perforating arteries. We hypothesize that this variability in subcortical perfusion territories is propagated from the arterial side through the capillary bed into the organization of subcortical veins. Thus, we suspect that subcortical arterial and venous vasculatures are interdependent and that distinct vessel patterns exist. Therefore, if the trajectory of an individual, subcortical vessel is altered, this could induce changes within its surrounding arterial and venous network to maintain a specific pattern of local vessel-vessel-distances. To our best knowledge, this hypothesized interdependency of the arterial-venous patterns has not been studied comprehensively to date. To validate non-invasively this hypothesis in living humans, the following objectives have been identified:(1) Use ultra-high field MRI and prospective motion correction to achieve the required high resolutions (voxel size < 0.4mm) to depict the perforating arteries and veins(2) Segment the vasculature using a vesselness filter and apply distance transform to compute vascular distance maps(3) Find common, subcortical arterial-venous patterns using unsupervised clustering(4) Validate each processing step thoroughly by expertsBy addressing these objectives, a novel, fully automatic technique to analyze vascular distance patterns will be established. Further, proving the interdependency of the arterial and venous vasculature could have an impact on small vessel imaging, diagnose, and treatment in general, as an interdependency might render a joint assessment more promising that focusing on a single side of the vasculature. As the vascular component of neurodegenerative diseases and aging could induce specific vessel-vessel-pattern progressions, the proposed approach could be used as a new biomarker in future, longitudinal studies.