Cerebral small vessel disease(CSVD)is a leading cause of age-related microvascular cognitive decline,resulting in significant morbidity and decreased quality of life.Despite a progress on its key pathophysiological ba...Cerebral small vessel disease(CSVD)is a leading cause of age-related microvascular cognitive decline,resulting in significant morbidity and decreased quality of life.Despite a progress on its key pathophysiological bases and general acceptance of key terms from neuroimaging findings as observed on the magnetic resonance imaging(MRI),key questions on CSVD remain elusive.Enhanced relationships and reliable lesion studies,such as white matter tractography using diffusion-based MRI(dMRI)are necessary in order to improve the assessment of white matter architecture and connectivity in CSVD.Diffusion tensor imaging(DTI)and tractography is an application of dMRI that provides data that can be used to non-invasively appraise the brain white matter connections via fiber tracking and enable visualization of individual patient-specific white matter fiber tracts to reflect the extent of CSVD-associated white matter damage.However,due to a lack of standardization on various sets of software or image pipeline processing utilized in this technique that driven mostly from research setting,interpreting the findings remain contentious,especially to inform an improved diagnosis and/or prognosis of CSVD for routine clinical use.In this minireview,we highlight the advances in DTI pipeline processing and the prospect of this DTI metrics as potential imaging biomarker for CSVD,even for subclinical CSVD in at-risk individuals.展开更多
弥散张量磁共振成像(DT-MRI)的脑白质纤维追踪成像利用脑白质水分子弥散构成的弥散张量信息追踪脑白质纤维束并无创重建其3维结构图像。针对现有追踪方法一般以局部体素的弥散张量为主要追踪依据,缺乏对纤维结构、弥散度等人体解剖结构...弥散张量磁共振成像(DT-MRI)的脑白质纤维追踪成像利用脑白质水分子弥散构成的弥散张量信息追踪脑白质纤维束并无创重建其3维结构图像。针对现有追踪方法一般以局部体素的弥散张量为主要追踪依据,缺乏对纤维结构、弥散度等人体解剖结构和生理机能的综合考量的缺陷,该文基于贝叶斯理论框架综合分析追踪路径与各体素弥散张量方向和纤维束几何结构相关性,并使用弥散度和追踪纤维角度对两者进行约束,获得各步追踪方向的概率密度分布,通过Markov Chain Monte Carlo采样确定其追踪方向进行追踪成像,通过多次追踪获得具有统计意义的3维结果。最后利用文中方法在合成弥散张量数据上进行了成像仿真,在真实脑部DT-MRI数据上进行了成像实验。仿真和实验结果表明,该方法能实现预期的脑白质纤维追踪成像,比现有追踪成像方法结果更可靠,可重复性更强。展开更多
文摘Cerebral small vessel disease(CSVD)is a leading cause of age-related microvascular cognitive decline,resulting in significant morbidity and decreased quality of life.Despite a progress on its key pathophysiological bases and general acceptance of key terms from neuroimaging findings as observed on the magnetic resonance imaging(MRI),key questions on CSVD remain elusive.Enhanced relationships and reliable lesion studies,such as white matter tractography using diffusion-based MRI(dMRI)are necessary in order to improve the assessment of white matter architecture and connectivity in CSVD.Diffusion tensor imaging(DTI)and tractography is an application of dMRI that provides data that can be used to non-invasively appraise the brain white matter connections via fiber tracking and enable visualization of individual patient-specific white matter fiber tracts to reflect the extent of CSVD-associated white matter damage.However,due to a lack of standardization on various sets of software or image pipeline processing utilized in this technique that driven mostly from research setting,interpreting the findings remain contentious,especially to inform an improved diagnosis and/or prognosis of CSVD for routine clinical use.In this minireview,we highlight the advances in DTI pipeline processing and the prospect of this DTI metrics as potential imaging biomarker for CSVD,even for subclinical CSVD in at-risk individuals.
文摘弥散张量磁共振成像(DT-MRI)的脑白质纤维追踪成像利用脑白质水分子弥散构成的弥散张量信息追踪脑白质纤维束并无创重建其3维结构图像。针对现有追踪方法一般以局部体素的弥散张量为主要追踪依据,缺乏对纤维结构、弥散度等人体解剖结构和生理机能的综合考量的缺陷,该文基于贝叶斯理论框架综合分析追踪路径与各体素弥散张量方向和纤维束几何结构相关性,并使用弥散度和追踪纤维角度对两者进行约束,获得各步追踪方向的概率密度分布,通过Markov Chain Monte Carlo采样确定其追踪方向进行追踪成像,通过多次追踪获得具有统计意义的3维结果。最后利用文中方法在合成弥散张量数据上进行了成像仿真,在真实脑部DT-MRI数据上进行了成像实验。仿真和实验结果表明,该方法能实现预期的脑白质纤维追踪成像,比现有追踪成像方法结果更可靠,可重复性更强。
