Clinical MEG : Cerebrovascular diseases 2 - 7 - 14 : MEG database for development of dementia diagnostic protocols : data collection and application

OBJECTIVE: Many studies of dementia mainly Alzheimer's disease (AD) by using MEG have been reported. Some results show there are some differences between patients and controls in MEG data. But it is still difficult to diagnose the disease in early stage using their methods because of large individual variation. We measured many patients and normal aged subjects, and extracted various parameters from the MEG data. Using this MEG database, we try to develop a more practical diagnostic protocol. METHODS: MEG measurements were performed in 3 conditions, spontaneous activities with eyes-closed and eyes-opened conditions, in executing a missing oddball task and listening to music. We also collected MRI images, MMSE scores, clinical features and so on. The database has three types of data. The first group data consists of MEG raw data, MRI images, measurement information and etc. The second group data consists of graphical analysis results such as magnetic field patterns, spectrograms of MEG signal. The third group data consists of characteristic parameters mainly extracted from the second data group. RESULTS: Some parameters had significant differences between AD and normal control (NC) statistically. We investigated a mutual relationship between these parameters, and found that some parameters were highly independent each other. We also collected the data of other dementia (FTD, VD, etc), and found the difference in some parameters. CONCLUSION: We made a MEG database for dementia study, and found characteristic parameters of MEG data to distinguish AD from NC. Combining these parameters may be enabled to design a more effective diagnose protocol for dementia.