Huang Wanbin, Zong Jiabin, Li Ming, Li Tong-Fei, Pan Songqing, Xiao Zheman
Department of Neurology, Renmin Hospital of Wuhan University, Wuhan 430060, China.
Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
ACS Nano. 2025 May 6;19(17):16224-16247. doi: 10.1021/acsnano.5c01203. Epub 2025 Apr 23.
Epilepsy is a common neurological disorder characterized by a significant rate of disability. Accurate early diagnosis and precise localization of the epileptogenic zone are essential for timely intervention, seizure prevention, and personalized treatment. However, over 30% of patients with epilepsy exhibit negative results on electroencephalography and magnetic resonance imaging (MRI), which can lead to misdiagnosis and subsequent delays in treatment. Consequently, enhancing diagnostic methodologies is imperative for effective epilepsy management. The integration of nanomaterials with biomedicine has led to the development of diagnostic tools for epilepsy. Key advancements include nanomaterial-enhanced neural electrodes, contrast agents, and biochemical sensors. Nanomaterials improve the quality of electrophysiological signals and broaden the detection range of electrodes. In imaging, functionalized magnetic nanoparticles enhance MRI sensitivity, facilitating localization of the epileptogenic zone. NIR-II nanoprobes enable tracking of seizure-related biomarkers with deep tissue penetration. Furthermore, nanomaterials enhance the sensitivity of biochemical sensors for detecting epilepsy biomarkers, which is crucial for early detection. These advancements significantly increase diagnostic sensitivity and specificity. However, challenges remain, particularly regarding biosafety, quality control, and the scalability of fabrication processes. Overcoming these obstacles is essential for successful clinical translation. Artificial-intelligence-based big data analytics can facilitate the development of diagnostic tools by screening nanomaterials with specific properties. This approach may help to address current limitations and improve both effectiveness and safety. This review explores the application of nanomaterials in the diagnosis and detection of epilepsy, with the objective of inspiring innovative ideas and strategies to enhance diagnostic effectiveness.
癫痫是一种常见的神经系统疾病，致残率很高。准确的早期诊断和癫痫病灶区的精确定位对于及时干预、预防癫痫发作和个性化治疗至关重要。然而，超过30%的癫痫患者脑电图和磁共振成像（MRI）结果呈阴性，这可能导致误诊及后续治疗延误。因此，改进诊断方法对于有效管理癫痫至关重要。纳米材料与生物医学的结合催生了癫痫诊断工具的发展。主要进展包括纳米材料增强型神经电极、造影剂和生化传感器。纳米材料提高了电生理信号质量，拓宽了电极检测范围。在成像方面，功能化磁性纳米颗粒提高了MRI灵敏度，有助于癫痫病灶区的定位。近红外二区纳米探针能够深入组织追踪癫痫相关生物标志物。此外，纳米材料提高了检测癫痫生物标志物的生化传感器的灵敏度，这对早期检测至关重要。这些进展显著提高了诊断的灵敏度和特异性。然而，挑战依然存在，尤其是在生物安全性、质量控制和制造工艺的可扩展性方面。克服这些障碍对于成功实现临床转化至关重要。基于人工智能的大数据分析可以通过筛选具有特定性质的纳米材料来推动诊断工具的开发。这种方法可能有助于解决当前的局限性，提高有效性和安全性。本综述探讨了纳米材料在癫痫诊断和检测中的应用，旨在激发创新思路和策略，提高诊断效果。
