Increasing evidence demonstrates that there is marked damage and dysfunction in the white matter in Alzheimer's disease (AD). The present study investigates the nature of white matter damage of patients with Alzheimer's disease with diffusion tensor magnetic resonance imaging (DTI) and analyses the relationship between the white matter damage and the cognition function. DTI, as well as T1 fluid attenuated inversion recovery (FLAIR) and T2-FLAIR, was performed on probable patients of Alzheimer's disease, and sex and age matched healthy volunteers to measure the fractional anisotropy (FA) and mean diffusivity (MD) in the genu and splenium of the corpus callosum, anterior and posterior limbs of the internal capsule, and the white matter of frontal, temporal, parietal, and occipital lobes. FA was lower in the splenium of corpus callosum, as well as in the white matter of the frontal, temporal, and parietal lobes from patients with Alzheimer's disease than in the corresponding region from healthy controls and was strongly positive correlated with MMSE scores, whereas FA appeared no different in the anterior and posterior limbs of internal capsule, occipital lobes white matter, and the genu of corpus callosum between the patients and healthy controls. MD was significantly higher in the splenium of corpus callosum and parietal lobes white matter from patients than in that those from healthy controls and was strongly negative correlated with MMSE scores, whereas MD in the anterior and posterior limbs of internal capsule, as well as in frontal, temporal, occipital lobes white matter and the genu of corpus callosum, was not different between the patients and healthy controls. The most prominent alteration of FA and MD was in the splenium of corpus callosum. Our results suggested that white matter of patients with Alzheimer's disease was selectively impaired and the extent of damage had a strong correlation with the cognitive function, and that selective impairment reflected the cortico-cortical and cortico-subcortical disconnections in the pathomechanism of Alzheimer's disease. The values of FA and MD in white matter, especially in the splenium of corpus callosum in AD patients, might be a more appropriate surrogate marker for monitoring the disease progression.

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Highlights A CT dataset contains 416 COVID-19 positive CT scans and 412 common pneumonia CT scans is publicly available. A multi-scale convolutional neural network can accurately differentiate COVID-19 and other common pneumonia on chest CT scans with limited number of training data. An AI system has comparable diagnostic sensitivity (89.1% vs 84.8%, p -value = 0.724), specificity (85.7% vs 83.3%, p -value = 1.000), and accuracy (87.5% vs 84.1%, p -value = 0.804) than experienced radiologists.