图像技术的进步和人工智能集成用于神经退行性疾病管理:叙述性审查
Jinshan Xu1, Caiyun Gao2, Junhua Zhang1
1Department of Radiology, The Affiliated People's Hospital of Ningbo University, Ningbo, Zhejiang, China.
Molecular imaging
|March 4, 2026
概括
先进的神经成像和人工智能 (AI) 增强了神经退行性疾病的早期诊断和监测. 整合这些技术可以提供个性化的处理,但需要解决成本和可访问性障碍.
科学领域:
- 神经学 神经学
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 神经退行性疾病是渐进的,目前无法治愈的,影响着全球老龄化人口.
- 氧化应激和炎症是疾病进展的主要驱动因素.
- 神经成像和人工智能的进步为改善诊断和管理提供了机会.
研究的目的:
- 审查先进的神经成像和人工智能在诊断和监测神经退行性疾病中的作用.
- 突出这一领域的挑战和未来方向.
主要方法:
- 关于神经退行性疾病神经成像技术的出版文献的叙述性综述.
- 包括结构性MRI,fMRI,DTI,PET和SPECT,评估AI在图像分析中的整合.
- 专注于临床应用,技术进步和多式联络成像.
主要成果:
- 结构性MRI,fMRI和DTI揭示了大脑缩和微观结构变化.
- PET和SPECT提供了对新陈代谢和病理学的分子洞察力.
- 人工智能集成提高了诊断准确度,减少了变化,但成本和可访问性仍然是问题.
结论:
- 先进的成像和人工智能集成在神经退行性疾病管理方面具有变革性的潜力.
- 未来的工作应该集中在降低成本,可访问性和多式联运数据融合上.
- 这些进步有望提前检测和个性化治疗监测.
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