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Multi-tissue constrained spherical deconvolution for improved analysis of multi-shell diffusion MRI data

机译:多组织约束球面反褶积,用于改进多壳扩散MRI数据的分析

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Constrained spherical deconvolution (CSD) has become one of the most widely used methods to extract white matter (WM) fibre orientation information from diffusion-weighted MRI (DW-MRI) data, overcoming the crossing fibre limitations inherent in the diffusion tensor model. It is routinely used to obtain high quality fibre orientation distribution function (fODF) estimates and fibre tractograms and is increasingly used to obtain apparent fibre density (AFD) measures. Unfortunately, CSD typically only supports data acquired on a single shell in q-space. With multi-shell data becoming more and more prevalent, there is a growing need for CSD to fully support such data. Furthermore, CSD can only provide high quality fODF estimates in voxels containing WM only. In voxels containing other tissue types such as grey matter (GM) and cerebrospinal fluid (CSF), the WM response function may no longer be appropriate and spherical deconvolution produces unreliable, noisy fODF estimates. The aim of this study is to incorporate support for multi-shell data into the CSD approach as well as to exploit the unique b-value dependencies of the different tissue types to estimate a multi-tissue ODF. The resulting approach is dubbed multi-shell, multi-tissue CSD (MSMT-CSD) and is compared to the state-of-the-art single-shell, single-tissue CSD (SSST-CSD) approach. Using both simulations and real data, we show that MSMT-CSD can produce reliable WM/GM/CSF volume fraction maps, directly from the DW data, whereas SSST-CSD has a tendency to overestimate the WM volume in voxels containing GM and/or CSF. In addition, compared to SSST-CSD, MSMT-CSD can substantially increase the precision of the fODF fibre orientations and reduce the presence of spurious fODF peaks in voxels containing GM and/or CSF. Both effects translate into more reliable AFD measures and tractography results with MSMT-CSD compared to SSST-CSD. (C) 2014 Elsevier Inc. All rights reserved.
机译:约束球面反褶积(CSD)已成为从扩散加权MRI(DW-MRI)数据中提取白质(WM)纤维取向信息的最广泛使用的方法之一,克服了扩散张量模型固有的交叉纤维限制。它通常用于获得高质量的纤维取向分布函数(fODF)估计值和纤维束图,并越来越多地用于获得表观纤维密度(AFD)度量。不幸的是,CSD通常仅支持在q空间的单个外壳上获取的数据。随着多外壳数据的日益普及,越来越需要CSD完全支持此类数据。此外,CSD只能在仅包含WM的体素中提供高质量的fODF估计。在包含其他组织类型(例如灰质(GM)和脑脊髓液(CSF))的体素中,WM响应功能可能不再合适,并且球形反卷积会产生不可靠的,嘈杂的fODF估计值。这项研究的目的是将对多壳数据的支持纳入CSD方法,并利用不同组织类型的独特b值依赖性来估计多组织ODF。最终的方法被称为多壳,多组织CSD(MSMT-CSD),并且与最新的单壳,单组织CSD(SSST-CSD)方法进行了比较。使用模拟和实际数据,我们表明MSMT-CSD可以直接从DW数据生成可靠的WM / GM / CSF体积分数图,而SSST-CSD倾向于高估包含GM和/或脑脊液。此外,与SSST-CSD相比,MSMT-CSD可以显着提高fODF纤维取向的精度,并减少包含GM和/或CSF的体素中伪fODF峰的存在。与SSST-CSD相比,MSMT-CSD的这两种效果均可以转化为更可靠的AFD测量和体检结果。 (C)2014 Elsevier Inc.保留所有权利。

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