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在老年帕金森病中,代谢网络重塑和人工智能驱动的精确诊断:多式成像技术的进步

Jinshuo Liu¹, Pengbo Yang¹, Zihao Wang¹

¹Xinjiang Medical University,No.567, Shangde North Road, Shuimogou District,Urumqi City, Xinjiang Uygur Autonomous Region, Urumchi 830000, PR China; The Second Affiliated Hospital of Xinjiang Medical University, No. 38, North Second Lane, Nanhu East Road, Urumqi, Xinjiang Uygur Autonomous Region, Urumchi 830000, PR China.

Archives of gerontology and geriatrics

|August 13, 2025

概括

像帕金森氏症这样的神经退行性疾病中独特的代谢网络模式可以使用多式神经成像识别. 人工智能 (AI) 提高了诊断准确度,并有助于为这些疾病制定个性化治疗策略.

科学领域:

神经科学是一个神经科学.
医疗成像医学成像
人工智能的人工智能

背景情况:

帕金森病 (PD) 涉及多巴胺基神经元退化和异常的代谢网络,由临床异质性复杂化.
多模式神经成像研究已经对PD的病理机制和代谢模式有了更深入的了解.

研究的目的:

探索神经退行性疾病中代谢网络模式的诊断和亚型化能力.
评估人工智能驱动的多式联络放射学在提高差异诊断和亚型有效性方面的作用.

主要方法:

使用18F-FDG PET/CT与多式联络神经成像技术相结合.
应用人工智能 (AI) 驱动的多式联络放射学分析,整合代谢和结构特征.

主要成果:

帕金森病 (PD) 显示与运动症状相关的氨酸过度代谢和与认知衰退相关的额头/脑周低代谢.
多个系统缩 (MSA) 呈现大脑小脑-突的低代谢,而渐进的超核性麻 (PSP) 显示中脑前额网络解离.
人工智能驱动的放射学显著改善了PD亚型和差异诊断的准确性,代谢变化先于形态变化.

结论:

独特的代谢网络模式,结合人工智能对多式联络数据的分析,对于精确的神经退行性疾病亚型和个性化疗法至关重要.
建立多中心数据共享框架和标准化代谢数据库对于优化人工智能模型和加速代谢生物标志物的临床翻译至关重要.

关键词:

人工智能的人工智能是人工智能.差异诊断是一种差异诊断.德国联邦财政部-PET 老年神经学老年神经学代谢网络是一种代谢网络.多模式成像技术多模式成像技术帕金森病是帕金森病的一种.

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