帕金森病和不典型帕金森综合征分类的神经影像学研究进展。
Update on neuroimaging for categorization of Parkinson's disease and atypical parkinsonism.
机构信息
Institut du Cerveau - ICM, INSERM U 1127, CNRS UMR 7225, Sorbonne Université, Team 'Movement Investigations and Therapeutics' (MOV'IT).
ICM, Centre de NeuroImagerie de Recherche - CENIR.
出版信息
Curr Opin Neurol. 2021 Aug 1;34(4):514-524. doi: 10.1097/WCO.0000000000000957.
PURPOSE OF REVIEW
Differential diagnosis of Parkinsonism may be difficult. The objective of this review is to present the work of the last three years in the field of imaging for diagnostic categorization of parkinsonian syndromes focusing on progressive supranuclear palsy (PSP) and multiple system atrophy (MSA).
RECENT FINDINGS
Two main complementary approaches are being pursued. The first seeks to develop and validate manual qualitative or semi-quantitative imaging markers that can be easily used in clinical practice. The second is based on quantitative measurements of magnetic resonance imaging abnormalities integrated in a multimodal approach and in automatic categorization machine learning tools.
SUMMARY
These two complementary approaches obtained high diagnostic around 90% and above in the classical Richardson form of PSP and probable MSA. Future work will determine if these techniques can improve diagnosis in other PSP variants and early forms of the diseases when all clinical criteria are not fully met.
目的综述
帕金森病的鉴别诊断可能较为困难。本综述的目的是呈现过去三年在帕金森综合征诊断分类的影像学领域的研究工作，重点关注进行性核上性麻痹（PSP）和多系统萎缩（MSA）。
最近的发现
目前主要有两种互补的研究方法。第一种方法是开发和验证可在临床实践中轻松使用的手动定性或半定量成像标志物。第二种方法基于磁共振成像异常的定量测量，这些异常整合在多模态方法中，并应用于自动分类机器学习工具。
总结
这两种互补的方法在经典的 PSP 型和可能的 MSA 型中获得了约 90%及以上的高诊断准确率。未来的研究将确定这些技术是否可以提高其他 PSP 变体和疾病早期阶段的诊断准确性，此时并非所有临床标准都完全满足。
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