利用弥散 OGSE MRI 建立白质微观结构模型:模型和分析选择

IF 2.1 4区 医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Emma Friesen , Madison Chisholm , Bibek Dhakal , Morgan Mercredi , Mark D. Does , John C. Gore , Melanie Martin
{"title":"利用弥散 OGSE MRI 建立白质微观结构模型:模型和分析选择","authors":"Emma Friesen ,&nbsp;Madison Chisholm ,&nbsp;Bibek Dhakal ,&nbsp;Morgan Mercredi ,&nbsp;Mark D. Does ,&nbsp;John C. Gore ,&nbsp;Melanie Martin","doi":"10.1016/j.mri.2024.110221","DOIUrl":null,"url":null,"abstract":"<div><p>Alterations in white matter (WM) microstructure of the central nervous system have been shown to be pathophysiological presentations of various neurodegenerative disorders. Current methods for measuring such WM features require ex vivo tissue samples analyzed using electron microscopy. Magnetic Resonance Imaging (MRI) diffusion-weighted pulse sequences provide a non-invasive tool for estimating such microstructural features in vivo. The current project investigated the use of two methods of analysis, including the ROI-based (Region of Interest, RBA) and voxel-based analysis (VBA), as well as four mathematical models of WM microstructure, including the ActiveAx Frequency-Independent Extra-Axonal Diffusion (AAI), ActiveAx Frequency-Dependent Extra-Axonal Diffusion (AAD), AxCaliber Frequency-Independent Extra-Axonal Diffusion (ACI), and AxCaliber Frequency-Dependent Extra-Axonal Diffusion (ACD) models. Two mice samples imaged at 7 T and 15.2 T were analyzed. Both the AAI and AAD models provide a single value for each of the fit parameters, including mean effective axon diameter <span><math><mover><mi>AxD</mi><mo>¯</mo></mover></math></span>, packing fraction <span><math><msub><mi>f</mi><mi>in</mi></msub></math></span>, intra-cellular and <span><math><msub><mi>D</mi><mi>in</mi></msub></math></span> and extra-cellular <span><math><msub><mi>D</mi><mi>ex</mi></msub></math></span> diffusion coefficients, as well as the frequency dependence of <span><math><msub><mi>D</mi><mi>ex</mi></msub></math></span>, <span><math><msub><mi>β</mi><mi>ex</mi></msub></math></span> for the AAD model. The ACI and ACD models provide this, in addition to a distribution of axon diameters for a chosen ROI. VBA extends this, providing a parameter value for each voxel within the selected ROI, at the cost of increased computational load and analysis time. Overall, RBA-ACD and VBA-AAD were found to be optimal for parameter fitting to physically relevant values in a reasonable time frame. A full comparison of each combination of RBA and VBA with AAI, AAD, ACI, and ACD is provided to give the reader sufficient information to make an informed decision of which model is best for their own experiments.</p></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"113 ","pages":"Article 110221"},"PeriodicalIF":2.1000,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0730725X24002029/pdfft?md5=d10d02e6d2c3f79e3d27a0ae71b624be&pid=1-s2.0-S0730725X24002029-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Modelling white matter microstructure using diffusion OGSE MRI: Model and analysis choices\",\"authors\":\"Emma Friesen ,&nbsp;Madison Chisholm ,&nbsp;Bibek Dhakal ,&nbsp;Morgan Mercredi ,&nbsp;Mark D. Does ,&nbsp;John C. Gore ,&nbsp;Melanie Martin\",\"doi\":\"10.1016/j.mri.2024.110221\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Alterations in white matter (WM) microstructure of the central nervous system have been shown to be pathophysiological presentations of various neurodegenerative disorders. Current methods for measuring such WM features require ex vivo tissue samples analyzed using electron microscopy. Magnetic Resonance Imaging (MRI) diffusion-weighted pulse sequences provide a non-invasive tool for estimating such microstructural features in vivo. The current project investigated the use of two methods of analysis, including the ROI-based (Region of Interest, RBA) and voxel-based analysis (VBA), as well as four mathematical models of WM microstructure, including the ActiveAx Frequency-Independent Extra-Axonal Diffusion (AAI), ActiveAx Frequency-Dependent Extra-Axonal Diffusion (AAD), AxCaliber Frequency-Independent Extra-Axonal Diffusion (ACI), and AxCaliber Frequency-Dependent Extra-Axonal Diffusion (ACD) models. Two mice samples imaged at 7 T and 15.2 T were analyzed. Both the AAI and AAD models provide a single value for each of the fit parameters, including mean effective axon diameter <span><math><mover><mi>AxD</mi><mo>¯</mo></mover></math></span>, packing fraction <span><math><msub><mi>f</mi><mi>in</mi></msub></math></span>, intra-cellular and <span><math><msub><mi>D</mi><mi>in</mi></msub></math></span> and extra-cellular <span><math><msub><mi>D</mi><mi>ex</mi></msub></math></span> diffusion coefficients, as well as the frequency dependence of <span><math><msub><mi>D</mi><mi>ex</mi></msub></math></span>, <span><math><msub><mi>β</mi><mi>ex</mi></msub></math></span> for the AAD model. The ACI and ACD models provide this, in addition to a distribution of axon diameters for a chosen ROI. VBA extends this, providing a parameter value for each voxel within the selected ROI, at the cost of increased computational load and analysis time. Overall, RBA-ACD and VBA-AAD were found to be optimal for parameter fitting to physically relevant values in a reasonable time frame. A full comparison of each combination of RBA and VBA with AAI, AAD, ACI, and ACD is provided to give the reader sufficient information to make an informed decision of which model is best for their own experiments.</p></div>\",\"PeriodicalId\":18165,\"journal\":{\"name\":\"Magnetic resonance imaging\",\"volume\":\"113 \",\"pages\":\"Article 110221\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2024-08-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S0730725X24002029/pdfft?md5=d10d02e6d2c3f79e3d27a0ae71b624be&pid=1-s2.0-S0730725X24002029-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Magnetic resonance imaging\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0730725X24002029\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Magnetic resonance imaging","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0730725X24002029","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
引用次数: 0

摘要

中枢神经系统白质(WM)微结构的改变已被证明是各种神经退行性疾病的病理生理表现。目前测量这类白质特征的方法需要使用电子显微镜分析体外组织样本。磁共振成像(MRI)扩散加权脉冲序列提供了一种非侵入性工具,可用于估测体内的此类微结构特征。本项目研究了两种分析方法的使用,包括基于 ROI(感兴趣区,RBA)和基于体素的分析(VBA),以及四种 WM 显微结构数学模型,包括 ActiveAx 频率依赖性轴外扩散模型(AAI)、ActiveAx 频率依赖性轴外扩散模型(AAD)、AxCaliber 频率依赖性轴外扩散模型(ACI)和 AxCaliber 频率依赖性轴外扩散模型(ACD)。共分析了三组图像数据,包括在 7 T 和 15.2 T 下成像的两个小鼠样本。AAI 和 AAD 模型都为每个拟合参数提供了一个单一值,包括轴突直径 AxD¯、堆积分数 fin、胞内和胞外 Dex 扩散系数,以及 Dex 的频率依赖性,即 AAD 模型的 βex。ACI 和 ACD 模型除了提供所选 ROI 的轴突直径分布外,还提供了这些参数。VBA 对此进行了扩展,为所选区域内的每个体素提供了参数值,但代价是增加了计算负荷和分析时间。总体而言,RBA-ACD 和 VBA-AAD 被认为是在合理时间内将参数拟合到物理相关值的最佳方法。本报告对 RBA 和 VBA 与 AAI、AAD、ACI 和 ACD 的每种组合进行了全面比较,为读者提供了充分的信息,使他们能够做出明智的决定,选择最适合自己实验的模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modelling white matter microstructure using diffusion OGSE MRI: Model and analysis choices

Alterations in white matter (WM) microstructure of the central nervous system have been shown to be pathophysiological presentations of various neurodegenerative disorders. Current methods for measuring such WM features require ex vivo tissue samples analyzed using electron microscopy. Magnetic Resonance Imaging (MRI) diffusion-weighted pulse sequences provide a non-invasive tool for estimating such microstructural features in vivo. The current project investigated the use of two methods of analysis, including the ROI-based (Region of Interest, RBA) and voxel-based analysis (VBA), as well as four mathematical models of WM microstructure, including the ActiveAx Frequency-Independent Extra-Axonal Diffusion (AAI), ActiveAx Frequency-Dependent Extra-Axonal Diffusion (AAD), AxCaliber Frequency-Independent Extra-Axonal Diffusion (ACI), and AxCaliber Frequency-Dependent Extra-Axonal Diffusion (ACD) models. Two mice samples imaged at 7 T and 15.2 T were analyzed. Both the AAI and AAD models provide a single value for each of the fit parameters, including mean effective axon diameter AxD¯, packing fraction fin, intra-cellular and Din and extra-cellular Dex diffusion coefficients, as well as the frequency dependence of Dex, βex for the AAD model. The ACI and ACD models provide this, in addition to a distribution of axon diameters for a chosen ROI. VBA extends this, providing a parameter value for each voxel within the selected ROI, at the cost of increased computational load and analysis time. Overall, RBA-ACD and VBA-AAD were found to be optimal for parameter fitting to physically relevant values in a reasonable time frame. A full comparison of each combination of RBA and VBA with AAI, AAD, ACI, and ACD is provided to give the reader sufficient information to make an informed decision of which model is best for their own experiments.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Magnetic resonance imaging
Magnetic resonance imaging 医学-核医学
CiteScore
4.70
自引率
4.00%
发文量
194
审稿时长
83 days
期刊介绍: Magnetic Resonance Imaging (MRI) is the first international multidisciplinary journal encompassing physical, life, and clinical science investigations as they relate to the development and use of magnetic resonance imaging. MRI is dedicated to both basic research, technological innovation and applications, providing a single forum for communication among radiologists, physicists, chemists, biochemists, biologists, engineers, internists, pathologists, physiologists, computer scientists, and mathematicians.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信