McGill Research Center for Studies in Aging, Montreal, Canada.
Curr Opin Neurol. 2023 Oct 1;36(5):481-490. doi: 10.1097/WCO.0000000000001198. Epub 2023 Aug 3.
The purpose is to review the latest advances of brain imaging for the diagnosis of Alzheimer disease (AD).
Brain imaging techniques provide valuable and complementary information to support the diagnosis of Alzheimer disease in clinical and research settings. The recent FDA accelerated approvals of aducanumab, lecanemab and donanemab made amyloid-PET critical in helping determine the optimal window for anti-amyloid therapeutic interventions. Tau-PET, on the other hand, is considered of key importance for the tracking of disease progression and for monitoring therapeutic interventions in clinical trials. PET imaging for microglial activation, astrocyte reactivity and synaptic degeneration are still new techniques only used in the research field, and more studies are needed to validate their use in the clinical diagnosis of AD. Finally, artificial intelligence has opened new prospective in the early detection of AD using MRI modalities.
Brain imaging techniques using PET improve our understanding of the different AD-related pathologies and their relationship with each other along the course of disease. With more robust validation, machine learning and deep learning algorithms could be integrated with neuroimaging modalities to serve as valuable tools for clinicians to make early diagnosis and prognosis of AD.
目的在于回顾脑影像学在阿尔茨海默病（AD）诊断中的最新进展。
脑影像学技术为支持 AD 的临床和研究环境中的诊断提供了有价值的、互补的信息。最近 FDA 加速批准了 aducanumab、lecanemab 和 donanemab，使淀粉样蛋白-PET 对确定抗淀粉样蛋白治疗干预的最佳窗口期至关重要。另一方面，tau-PET 被认为对疾病进展的跟踪和临床试验中的治疗干预监测具有关键重要性。用于小胶质细胞激活、星形胶质细胞反应和突触退化的 PET 成像仍然是仅在研究领域使用的新技术，需要更多的研究来验证其在 AD 临床诊断中的应用。最后，人工智能在使用 MRI 模式进行 AD 的早期检测方面开辟了新的前景。
使用正电子发射断层扫描（PET）的脑影像学技术提高了我们对不同 AD 相关病理学及其在疾病过程中的相互关系的理解。随着更强大的验证，机器学习和深度学习算法可以与神经影像学模式相结合，作为临床医生进行 AD 早期诊断和预后的有价值的工具。
