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 , Madison Chisholm , Bibek Dhakal , Morgan Mercredi , Mark D. Does , John C. Gore , 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 , Madison Chisholm , Bibek Dhakal , Morgan Mercredi , Mark D. Does , John C. Gore , 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}
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 , packing fraction , intra-cellular and and extra-cellular diffusion coefficients, as well as the frequency dependence of , 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.
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.