Abstract
Background
The apparent diffusion coefficient (ADC) from diffusion-weighted imaging (DWI) can quantify alterations in water diffusivity resulting from microscopic structural changes from amnestic mild cognitive impairment (aMCI) and Alzheimer's disease (AD).
Purpose
To investigate the ADC value for aMCI and AD using Brain Search (BS) software based on anatomical volumes of interest (AVOI).
Material and Methods
In total, 174 aged people were screened, and 25 patients with AD, 26 patients with aMCI, and 18 normal controls (NCs) were recruited. DWI was performed at 1.5 T with a fluid-attenuated inversion recovery (FLAIR), and the independent ADC mapping was generated after imaging acquisition. Ninety regional parcellations were adopted in a Brain Search (BS) based on the automated anatomic labeling atlas. The gray scale intensities (water diffusivity) from the collected ADC mappings were analyzed with BS. The mean value of each anatomical brain region was compared among aMCI, AD, and NC. The statistically significant (
Results
During the pathological process of AD, the changes of water diffusivity appeared first in the left hippocampus, then gradually progressed to the bilateral sides and eventually displayed right lateralization. The ADC values from aMCI were obviously elevated compared to the values from the NC group in the left limbic cortex. Between the AD and NC groups, the significantly different brain areas included the bilateral hippocampus, the Cingulum_Mid, the ParaHippocampal_R, and the Temporal and Frontal lobes. There was a negative correlation between the ADC values and the scores from MMSE, MoCA, the Digit test, Raven's IQ, and WAIS IQ. Additionally, the ADC values were positively correlated with the scores from CDR, ADL, and ADAS-Cog.
Conclusion
The water diffusivity for aMCI and AD displays asymmetric anatomical lateralization. The water diffusivity alterations can be analyzed and visualized with our newly designed analytic imaging software, BS, which can be used as a good reference for examining and diagnosing aMCI and AD patients.
Keywords
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