The final, formatted version of the article will be published soon.
ORIGINAL RESEARCH article
Front. Aging Neurosci.
Sec. Neurocognitive Aging and Behavior
Volume 16 - 2024 |
doi: 10.3389/fnagi.2024.1409166
Acceleration of brain aging after small-volume infarcts
Provisionally accepted- 1 Department of Diagnostic Radiology, Chiayi Chang Gung Memorial Hospital, Chiayi, Taiwan
- 2 Chang Gung University, Taoyuan, Taichung County, Taiwan
- 3 Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan
- 4 Department of Education and Research, Taipei City Hospital, Taipei, Taiwan
Introduction Previous studies have shown that stroke patients exhibit greater neuroimaging-derived biological "brain age" than control subjects by using the difference observed between chronological age and predicted brain age, referred to as the brain age gap (BAG), to reflect 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. Methods 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 work. We used t 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. Results There was significant brain aging between the initial and 6-month follow-ups, with a mean increase in brain age of 1.04 years. (t = 3.066, p < 0.05). Patients under 50 years of age experienced less aging after stroke than those over 50 years of age (p = 0.245). Additionally, patients with a National Institute of Health Stroke Scale score greater than 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 (F1,117 = 7.339, p = 0.008, η2 = 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 (F2,118= 4.637, p = 0.012, η2 = 0.073). Conclusion Stroke accelerates the brain aging process, even in patients with relatively small 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 stroke.
Keywords: Aging, Stroke, Retrospective Studies, Brain, Magnetic Resonance Imaging, machine learning, Neuroimaging, Infarction
Received: 07 Apr 2024; Accepted: 27 Aug 2024.
Copyright: © 2024 Peng, Kuo, Chang, Lin and Tsai. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Yuan-Hsiung Tsai, Department of Diagnostic Radiology, Chiayi Chang Gung Memorial Hospital, Chiayi, Taiwan
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.