How can a person prevent Alzheimer’s disease and there is any treatment for it? Early diagnosis may not be an answer, but it helps early interventions that are delaying the development of the disease. For this reason, Alzheimer’s early diagnosis became a priority in the investigation. There is substantial evidence that white -matter alterations can help Alzheimer’s early diagnosis.
The inter -institutional team of researchers, led by Yong Liu, professor at the Artificial Intelligence School, the University of Beijing Publications and Telecommunications, Beijing, China, organized competence and, through competition, created a multisitio diffusion tension image platform (DTI) validated the multisite diffusion tensioner image platform. The article is now on Brain disorders.
“We carry out a competition with dissemination measurements along 18 fiber tracts as extracted characteristics through the automated fiber quantification method (AFQ) based on one of the largest multisitio DTI biobankes worldwide,” Professor Liu said. “The current data set combined data from 7 magnetic resonance image scanners in 4 hospitals in China, containing a total of 862 people with DTI images, T1 images and demographic and psychological information.”
For the extraction of characteristics of the white matter, the team made an AFQ pipe that consisted of three steps. First, they tracked the fibers of the entire brain with an deterministic current line monitoring algorithm. Then they segment the fiber tracts with regions of point reference point of interest and refined them using a fiber tract probability map. A second procedure was to repeatedly eliminate abnormal fibers that evolved away from the fiber tract nucleus. In each node of each fiber, a nodal diffusion property was determined by sampling each fiber at 100 nodes equally spaced between the two regions of interest.
In the competition, Professor Liu and his colleagues obtained solutions from scientists from universities/institutes in China, the United States and the United Kingdom. The objective of the competition was to evaluate and develop an analytical framework to optimize the performance of Alzheimer’s binary classification using diffusion measurements along the main extensions of white matter extracted through AFQ. According to the results, it was clear that the DTI measures of the fibers of white matter demonstrated their usefulness in the detection of Alzheimer’s in the early stages. The authors have suggested that a post hoc analysis for an explanation of the model, a larger multimodality data set and better algorithms will be much more efficient for the early detection of Alzheimer’s.
The research team successfully determined that white matter could be a biomarker for Alzheimer’s early diagnosis. In addition, Professor Liu told science that it has to: “The data set and the parts of the codes are available as open sources. The project that we present in this study would benefit from having more researchers involved to share automatic learning data or models, as well as to frame the extraction of biomarkers as an open international challenge to predict Alzheimer Be more beneficial for future clinical applications, therefore, providing benefits to reveal pathological differences between disorders and increase the accuracy of a precise diagnosis.
Image magazine and credits:
Yida qu, bread wang, bing Liu, Chengyuan Song, Dawei Wang, Hongwei Yang, Zengqiang Zhang …, Yong Liu et al. “AI4AD: Artificial intelligence analysis for the classification of Alzheimer’s disease based on a multisitio DTI database.” Brain disorders 1 (2021): 100005. https://doi.org/10.1016/j.dscb.2021.100005
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