{"title":"基于弥散张量成像的脑纤维束重建及其影响因素初探","authors":"Pinqin Wang","doi":"10.54254/2753-8818/45/20240663","DOIUrl":null,"url":null,"abstract":"This paper focuses on the methods and progress of brain fiber bundle construction based on diffusion tensor imaging data, and conducts a preliminary exploration of the construction results. The study is based on 45 subjects in the public database, using different software to construct nerve fiber bundles for comparison, calculating the number of fiber bundle tracking under different parameters, and finally conducting a t-test on the fiber bundle connection strength of the left and right brain. The nerve fibers constructed by different software are relatively consistent and also consistent with human brain nerve fibers. A more relaxed length threshold will increase the number of fiber tracking, and as the angle threshold increases, the number of fiber tracking will first increase and then decrease. There are differences in the connection strength of the left and right brain. This preliminary study provides a foundation for further exploring brain connectivity and analyzing differences between individuals or patient groups. While the fiber bundles constructed matched expectations, more validation is needed against post-mortem dissections or other imaging techniques. Additionally, expanding the study to include more subjects and analyzing specific fiber bundles or regions could provide more detailed insights. The methods and parameters evaluated in this work help establish best practices for fiber tracking and analyzing connectivity strength metrics. With refinement, such fiber bundle analysis tools may help researchers better understand structural brain networks and differences related to development, aging or disease.","PeriodicalId":341023,"journal":{"name":"Theoretical and Natural Science","volume":"29 13","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A preliminary exploration of brain fiber bundle reconstruction and its influencing factors based on diffusion tensor imaging\",\"authors\":\"Pinqin Wang\",\"doi\":\"10.54254/2753-8818/45/20240663\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper focuses on the methods and progress of brain fiber bundle construction based on diffusion tensor imaging data, and conducts a preliminary exploration of the construction results. The study is based on 45 subjects in the public database, using different software to construct nerve fiber bundles for comparison, calculating the number of fiber bundle tracking under different parameters, and finally conducting a t-test on the fiber bundle connection strength of the left and right brain. The nerve fibers constructed by different software are relatively consistent and also consistent with human brain nerve fibers. A more relaxed length threshold will increase the number of fiber tracking, and as the angle threshold increases, the number of fiber tracking will first increase and then decrease. There are differences in the connection strength of the left and right brain. This preliminary study provides a foundation for further exploring brain connectivity and analyzing differences between individuals or patient groups. While the fiber bundles constructed matched expectations, more validation is needed against post-mortem dissections or other imaging techniques. Additionally, expanding the study to include more subjects and analyzing specific fiber bundles or regions could provide more detailed insights. The methods and parameters evaluated in this work help establish best practices for fiber tracking and analyzing connectivity strength metrics. With refinement, such fiber bundle analysis tools may help researchers better understand structural brain networks and differences related to development, aging or disease.\",\"PeriodicalId\":341023,\"journal\":{\"name\":\"Theoretical and Natural Science\",\"volume\":\"29 13\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Theoretical and Natural Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.54254/2753-8818/45/20240663\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Theoretical and Natural Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.54254/2753-8818/45/20240663","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
本文主要研究基于扩散张量成像数据的脑纤维束构建方法和进展,并对构建结果进行初步探讨。研究以公共数据库中的 45 名受试者为研究对象,使用不同软件构建神经纤维束进行对比,计算不同参数下的纤维束追踪数量,最后对左右脑的纤维束连接强度进行 t 检验。不同软件构建的神经纤维相对一致,也与人脑神经纤维一致。较宽松的长度阈值会增加纤维追踪的数量,随着角度阈值的增加,纤维追踪的数量会先增加后减少。左右脑的连接强度存在差异。这项初步研究为进一步探索大脑连接性和分析个体或患者群体之间的差异奠定了基础。虽然构建的纤维束符合预期,但还需要根据尸体解剖或其他成像技术进行更多验证。此外,扩大研究范围,纳入更多受试者,分析特定纤维束或区域,可以提供更详细的见解。这项工作中评估的方法和参数有助于建立纤维跟踪和连接强度指标分析的最佳实践。经过改进,这种纤维束分析工具可以帮助研究人员更好地了解大脑结构网络以及与发育、衰老或疾病相关的差异。
A preliminary exploration of brain fiber bundle reconstruction and its influencing factors based on diffusion tensor imaging
This paper focuses on the methods and progress of brain fiber bundle construction based on diffusion tensor imaging data, and conducts a preliminary exploration of the construction results. The study is based on 45 subjects in the public database, using different software to construct nerve fiber bundles for comparison, calculating the number of fiber bundle tracking under different parameters, and finally conducting a t-test on the fiber bundle connection strength of the left and right brain. The nerve fibers constructed by different software are relatively consistent and also consistent with human brain nerve fibers. A more relaxed length threshold will increase the number of fiber tracking, and as the angle threshold increases, the number of fiber tracking will first increase and then decrease. There are differences in the connection strength of the left and right brain. This preliminary study provides a foundation for further exploring brain connectivity and analyzing differences between individuals or patient groups. While the fiber bundles constructed matched expectations, more validation is needed against post-mortem dissections or other imaging techniques. Additionally, expanding the study to include more subjects and analyzing specific fiber bundles or regions could provide more detailed insights. The methods and parameters evaluated in this work help establish best practices for fiber tracking and analyzing connectivity strength metrics. With refinement, such fiber bundle analysis tools may help researchers better understand structural brain networks and differences related to development, aging or disease.