Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.06.09.126748v1?rss=1 Authors: Maikusa, N. Abstract: Alzheimer's disease (AD), the most common type of dementia in elderly individuals, slowly and progressively diminishes cognitive function. Mild cognitive impairment is also a significant risk factor to the parthenogenesis of AD. Magnetic resonance imaging (MRI) images have become widely used to detection and understand the natural progression not only AD but also neurodegenerative disorders. For this purpose, construct a reliable cognitive normal database is important. However, differences in magnetic field strength, sex, and age between normal databese and evaluation data-set can affect the accuracy of detection and evaluation of AD and other neurodegenerative disorders. To solve this problem, we suggest a harmonized Z-score considering differences filed strength, sex and age derived from large (over 1,000 subjects) cognitive normal database including 1.5 T and 3T T1 brain MRI. And we evaluate our harmonized Z-score of discriminative power of AD and classification accuracy between stable MCI and progressive MCI. The harmonized Z-score of the hippocampus achieved high accuracy (AUC=0.96) for detection AD and moderate accuracy (AUC=0.70) for classification stable MCI and progressive MCI. These results show that our method not only can detect AD with high accuracy and high generalization capability but also can be valid to classify stable MCI and progressive MCI. Copy rights belong to original authors. Visit the link for more info