{"title":"基于纤维自动定量的弥散张量成像在阿尔茨海默病中的应用。","authors":"Bo Yu, Zhongxiang Ding, Luoyu Wang, Qi Feng, Yifeng Fan, Xiufang Xu, Zhengluan Liao","doi":"10.2174/1567205019666220718142130","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Neuroimaging suggests that white matter microstructure is severely affected in Alzheimer's disease (AD) progression. However, whether alterations in white matter microstructure are confined to specific regions and whether they can be used as potential biomarkers to distinguish normal control (NC) from AD are unknown.</p><p><strong>Methods: </strong>In this cross-sectional study, 33 cases of AD and 25 cases of NC were recruited for automatic fiber quantification (AFQ). A total of 20 fiber bundles were equally divided into 100 segments for quantitative assessment of fractional anisotropy (FA), mean diffusivity (MD), volume and curvature. In order to further evaluate the diagnostic value, the maximum redundancy minimum (mRMR) and LASSO algorithms were used to select features, calculate the Radscore of each subject, establish logistic regression models, and draw ROC curves, respectively, to assess the predictive power of four different models.</p><p><strong>Results: </strong>There was a significant increase in the MD values in AD patients compared with healthy subjects. The differences were mainly located in the left cingulum hippocampus (HCC), left uncinate fasciculus (UF) and superior longitudinal fasciculus (SLF). The point-wise level of 20 fiber bundles was used as a classification feature, and the MD index exhibited the best performance to distinguish NC from AD.</p><p><strong>Conclusion: </strong>These findings contribute to the understanding of the pathogenesis of AD and suggest that abnormal white matter based on DTI-based AFQ analysis is helpful to explore the pathogenesis of AD.</p>","PeriodicalId":1,"journal":{"name":"Accounts of Chemical Research","volume":" ","pages":"469-478"},"PeriodicalIF":16.4000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Application of Diffusion Tensor Imaging Based on Automatic Fiber Quantification in Alzheimer's Disease.\",\"authors\":\"Bo Yu, Zhongxiang Ding, Luoyu Wang, Qi Feng, Yifeng Fan, Xiufang Xu, Zhengluan Liao\",\"doi\":\"10.2174/1567205019666220718142130\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Neuroimaging suggests that white matter microstructure is severely affected in Alzheimer's disease (AD) progression. However, whether alterations in white matter microstructure are confined to specific regions and whether they can be used as potential biomarkers to distinguish normal control (NC) from AD are unknown.</p><p><strong>Methods: </strong>In this cross-sectional study, 33 cases of AD and 25 cases of NC were recruited for automatic fiber quantification (AFQ). A total of 20 fiber bundles were equally divided into 100 segments for quantitative assessment of fractional anisotropy (FA), mean diffusivity (MD), volume and curvature. In order to further evaluate the diagnostic value, the maximum redundancy minimum (mRMR) and LASSO algorithms were used to select features, calculate the Radscore of each subject, establish logistic regression models, and draw ROC curves, respectively, to assess the predictive power of four different models.</p><p><strong>Results: </strong>There was a significant increase in the MD values in AD patients compared with healthy subjects. The differences were mainly located in the left cingulum hippocampus (HCC), left uncinate fasciculus (UF) and superior longitudinal fasciculus (SLF). The point-wise level of 20 fiber bundles was used as a classification feature, and the MD index exhibited the best performance to distinguish NC from AD.</p><p><strong>Conclusion: </strong>These findings contribute to the understanding of the pathogenesis of AD and suggest that abnormal white matter based on DTI-based AFQ analysis is helpful to explore the pathogenesis of AD.</p>\",\"PeriodicalId\":1,\"journal\":{\"name\":\"Accounts of Chemical Research\",\"volume\":\" \",\"pages\":\"469-478\"},\"PeriodicalIF\":16.4000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Accounts of Chemical Research\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.2174/1567205019666220718142130\",\"RegionNum\":1,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Accounts of Chemical Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2174/1567205019666220718142130","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
Application of Diffusion Tensor Imaging Based on Automatic Fiber Quantification in Alzheimer's Disease.
Background: Neuroimaging suggests that white matter microstructure is severely affected in Alzheimer's disease (AD) progression. However, whether alterations in white matter microstructure are confined to specific regions and whether they can be used as potential biomarkers to distinguish normal control (NC) from AD are unknown.
Methods: In this cross-sectional study, 33 cases of AD and 25 cases of NC were recruited for automatic fiber quantification (AFQ). A total of 20 fiber bundles were equally divided into 100 segments for quantitative assessment of fractional anisotropy (FA), mean diffusivity (MD), volume and curvature. In order to further evaluate the diagnostic value, the maximum redundancy minimum (mRMR) and LASSO algorithms were used to select features, calculate the Radscore of each subject, establish logistic regression models, and draw ROC curves, respectively, to assess the predictive power of four different models.
Results: There was a significant increase in the MD values in AD patients compared with healthy subjects. The differences were mainly located in the left cingulum hippocampus (HCC), left uncinate fasciculus (UF) and superior longitudinal fasciculus (SLF). The point-wise level of 20 fiber bundles was used as a classification feature, and the MD index exhibited the best performance to distinguish NC from AD.
Conclusion: These findings contribute to the understanding of the pathogenesis of AD and suggest that abnormal white matter based on DTI-based AFQ analysis is helpful to explore the pathogenesis of AD.
期刊介绍:
Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance.
Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.