Egger K, Rijntjes M
Klinik für Neuroradiologie, Universitätsklinikum Freiburg, Medizinische Fakultät, Albert-Ludwigs-Universität, Freiburg, Deutschland.
Klinik für Neurologie, Universitätsklinikum Freiburg, Medizinische Fakultät, Albert-Ludwigs-Universität Freiburg, Freiburg, Deutschland.
Nervenarzt. 2018 Aug;89(8):875-884. doi: 10.1007/s00115-018-0568-3.
The differential diagnosis of atypical dementia remains difficult. The use of positron emission tomography (PET) still represents the gold standard for imaging diagnostics. According to the current evidence, however, magnetic resonance imaging (MRI) is almost equal to fluorodeoxyglucose (FDG)-PET, but only when using new big data and machine learning methods. In cases of atypical dementia, especially in younger patients and for follow-up, MRI is preferable to computed tomography (CT). In the clinical routine, promising MRI procedures are e. g. the automated volumetry of anatomical 3D images, as well as a non-contrast-enhanced MRI perfusion method, called arterial spin labeling (ASL). Because of the rapidly growing amount of biomarker data, there is a need for computer-aided big data analyses and artificial intelligence. Based on fast analyses of the diverse and rapidly increasing amount of clinical, imaging, epidemiological, molecular genetic and economic data, new knowledge on the pathogenesis, prevention and treatment can be generated. Technical availability, homogenization of the underlying data and the availability of large reference data are the basis for the widespread establishment of promising analytical methods.
非典型痴呆的鉴别诊断仍然困难。正电子发射断层扫描（PET）的应用仍是影像诊断的金标准。然而，根据目前的证据，磁共振成像（MRI）几乎等同于氟脱氧葡萄糖（FDG）-PET，但前提是使用新的大数据和机器学习方法。在非典型痴呆病例中，尤其是在年轻患者中以及用于随访时，MRI优于计算机断层扫描（CT）。在临床实践中，有前景的MRI检查方法例如解剖学三维图像的自动容积测量，以及一种称为动脉自旋标记（ASL）的非增强MRI灌注方法。由于生物标志物数据量迅速增长，需要计算机辅助的大数据分析和人工智能。基于对各种快速增加的临床、影像、流行病学、分子遗传学和经济数据的快速分析，可以产生关于发病机制、预防和治疗的新知识。技术可用性、基础数据的同质化以及大型参考数据的可用性是广泛建立有前景的分析方法的基础。
