Peng Ying-Ju, Kuo Chen-Yuan, Chang Sheng-Wei, Lin Ching-Po, Tsai Yuan-Hsiung
Department of Diagnostic Radiology, Chang Gung Memorial Hospital, Chiayi, Taiwan.
Department of Diagnostic Radiology, Chang Gung University, Taoyuan, Taiwan.
Front Aging Neurosci. 2024 Sep 19;16:1409166. doi: 10.3389/fnagi.2024.1409166. eCollection 2024.
Previous studies have shown that stroke patients exhibit greater neuroimaging-derived biological "brain age" than control subjects. This difference, known as the brain age gap (BAG), is calculated by comparing the chronological age with predicted brain age and is used as an indicator of brain health and aging. However, whether stroke accelerates the process of brain aging in patients with small-volume infarcts has not been established. By utilizing longitudinal data, we aimed to investigate whether small-volume infarctions can significantly increase the BAG, indicating accelerated brain aging.
A total of 123 stroke patients presenting with small-volume infarcts were included in this retrospective study. The brain age model was trained via established protocols within the field of machine learning and the structural features of the brain from our previous study. We used -tests and regression analyses to assess longitudinal brain age changes after stroke and the associations between brain age, acute stroke severity, and poststroke outcome factors.
Significant brain aging occurred between the initial and 6-month follow-ups, with a mean increase in brain age of 1.04 years ( = 3.066, < 0.05). Patients under 50 years of age experienced less aging after stroke than those over 50 years of age ( = 0.245). Additionally, patients with a National Institute of Health Stroke Scale score >3 at admission presented more pronounced adverse effects on brain aging, even after adjusting for confounders such as chronological age, sex, and total intracranial volume ( = 7.339, = 0.008, = 0.059). There were significant differences in the proportional brain age difference at 6 months among the different functional outcome groups defined by the Barthel Index ( = 4.637, = 0.012, = 0.073).
Stroke accelerates the brain aging process, even in patients with relatively small-volume infarcts. This phenomenon is particularly accentuated in elderly patients, and both stroke severity and poststroke functional outcomes are closely associated with accelerated brain aging. Further studies are needed to explore the mechanisms underlying the accelerated brain aging observed in stroke patients, with a particular focus on the structural alterations and plasticity of the brain following minor strokes.
先前的研究表明，中风患者的神经影像学衍生生物“脑龄”比对照组受试者更大。这种差异被称为脑龄差距（BAG），通过将实际年龄与预测脑龄进行比较来计算，并用作脑健康和衰老的指标。然而，小体积梗死患者中中风是否会加速脑衰老过程尚未确定。通过利用纵向数据，我们旨在研究小体积梗死是否会显著增加BAG，表明脑衰老加速。
本回顾性研究共纳入123例出现小体积梗死的中风患者。脑龄模型通过机器学习领域既定的方案以及我们先前研究中的脑结构特征进行训练。我们使用t检验和回归分析来评估中风后脑龄的纵向变化以及脑龄、急性中风严重程度和中风后结局因素之间的关联。
在初始随访和6个月随访之间发生了显著的脑衰老，脑龄平均增加1.04岁（t = 3.066，p < 0.05）。50岁以下的患者中风后脑衰老程度低于50岁以上的患者（p = 0.245）。此外，入院时美国国立卫生研究院卒中量表评分>3的患者对脑衰老的不利影响更为明显，即使在调整了实际年龄、性别和总颅内体积等混杂因素后也是如此（t = 7.339，p = 0.008，p = 0.059）。根据Barthel指数定义的不同功能结局组在6个月时的比例脑龄差异存在显著差异（F = 4.637，p = 0.012，p = 0.073）。
中风会加速脑衰老过程，即使在梗死体积相对较小的患者中也是如此。这种现象在老年患者中尤为明显，中风严重程度和中风后功能结局均与脑衰老加速密切相关。需要进一步研究以探索中风患者中观察到的脑衰老加速的潜在机制，尤其关注小中风后脑的结构改变和可塑性。
