How does a person prevent Alzheimer’s disease, and is there any treatment for this? Early diagnosis may not be the answer, but early interventions that help delay disease development. Therefore, early diagnosis of Alzheimer’s disease has become a priority for research. There is a lot of evidence that changes in white matter may contribute to the early diagnosis of Alzheimer’s disease.
Inter-agency researchers led by Yong Liu, a professor at the School of Artificial Intelligence, Beijing University of Postal and Telecommunications, Beijing, China, organized competition, created a multi-site spreading tensor Imaging (DTI) image platform and verified Alz Feasibility of white matter measures for Heimer’s diagnosis. This article is now online Brain Diseases.
“We conducted a competition to conduct diffusion measurements along 18 fiber regions, as the features extracted by the automated fiber quantification (AFQ) method are based on one of the largest DTI multi-site biobanks in the world,” Professor Liu said. “Current The dataset combines data from seven magnetic resonance imaging scanners from four hospitals in China, including 862 people with DTI images, T1 images, and demographic and psychological information.”
To extract white matter function, the team performed an AFQ pipeline consisting of three steps. First, they track whole brain fibers using a deterministic streamline tracing algorithm. They then segmented the fiber region into the waypoint region of the interest process and refined it using the fiber channel probability map. The second procedure is to repeatedly remove abnormal fibers away from the fiber core. On each node of each fiber, a lymph node diffusion characteristic is determined by resampling each fiber to 100 nodes that are averagely spaced between the two regions of interest.
During the competition, Liu and colleagues obtained solutions from scientists from universities/colleges in China, the United States and the United Kingdom. The purpose of competition is to evaluate and develop an analytical framework to optimize the performance of Alzheimer’s binary classification using diffusion measurements extracted along AFQ. According to the results, it is clear that the measurement of white matter fibers of DTIs demonstrates their utility in detecting Alzheimer’s disease at an early stage. The authors suggest that post hoc analyses for model interpretation, larger multimodal multi-site datasets and better algorithms will be more effective in early detection of Alzheimer’s disease.
The team successfully determined that white matter may be a biomarker for the early diagnosis of Alzheimer’s disease. Furthermore, Professor Liu said to the scientific characteristics: “The dataset and some of the code can be used as open source sources. The project we proposed in this study will benefit from participating in more researchers in shared data or machine learning models, as well as bringing biomarkers into place Material extraction serves as an open international challenge to predict Alzheimer’s disease has the largest available DTI dataset biobank. “He also added that they focus on the diagnosis of Alzheimer’s disease’s current challenges. Nevertheless, classification of many mental illnesses may be more beneficial for future clinical applications, thus bringing benefits to uncover pathological differences between diseases and to improve the accuracy of accurate diagnosis.
Journal Reference and Image Credit:
Yida Qu, Pan Wang, Bing Liu, Chengyuan Song, Dawei Wang, Hongwei Yang, Zengqiang Zhang…, Yong Liu, etc. “AI4AD: Artificial Intelligence Analysis of Alzheimer’s Disease Classification Based on Multi-Site DTI Database.” Brain Disease 1 (2021): 100005.
