Xiamen Key Laboratory of Psychoradiology and Neuromodulation, Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, China.
Image Processing Center, Beihang University, Beijing, China.
Nat Commun. 2024 Oct 25;15(1):9235. doi: 10.1038/s41467-024-53550-5.
Cerebrovascular abnormalities are critical indicators of stroke and neurodegenerative diseases like Alzheimer's disease (AD). Understanding the normal evolution of brain vessels is essential for detecting early deviations and enabling timely interventions. Here, for the first time, we proposed a pipeline exploring the joint evolution of cortical volumes (CVs) and arterial volumes (AVs) in a large cohort of 2841 individuals. Using advanced deep learning for vessel segmentation, we built normative models of CVs and AVs across spatially hierarchical brain regions. We found that while AVs generally decline with age, distinct trends appear in regions like the circle of Willis. Comparing healthy individuals with those affected by AD or stroke, we identified significant reductions in both CVs and AVs, wherein patients with AD showing the most severe impact. Our findings reveal gender-specific effects and provide critical insights into how these conditions alter brain structure, potentially guiding future clinical assessments and interventions.
脑血管异常是中风和阿尔茨海默病（AD）等神经退行性疾病的关键指标。了解脑血管的正常演变对于检测早期偏差和进行及时干预至关重要。在这里，我们首次提出了一个在一个由 2841 人组成的大型队列中探索皮质体积（CVs）和动脉体积（AVs）联合演变的管道。我们使用先进的深度学习方法进行血管分割，构建了跨越空间层次化脑区的 CVs 和 AVs 的规范模型。我们发现，虽然 AVs 通常随年龄增长而下降，但在像 Willis 环这样的区域出现了不同的趋势。将健康个体与受 AD 或中风影响的个体进行比较，我们发现 CVs 和 AVs 都有明显减少，其中 AD 患者受到的影响最为严重。我们的研究结果揭示了性别特异性影响，并提供了有关这些疾病如何改变大脑结构的重要见解，可能为未来的临床评估和干预提供指导。
