Synthetic quantitative MRI through relaxometry modelling.
Synthetic quantitative MRI through relaxometry modelling.
复制标题
通过松弛模型建模合成定量MRI。
DOI：
10.1002/nbm.3658
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发表时间：
2016-12
影响因子：
2.9
通讯作者：
Weiskopf, Nikolaus
中科院分区：
文献类型：
--
作者：
Callaghan, Martina F.;Mohammadi, Siawoosh;Weiskopf, Nikolaus
定量 MRI (qMRI) 提供对底层组织微观结构敏感的特定物理参数的标准化测量，是使用 MRI 通过体内组织学获得生物学相关指标图谱的第一步。最近提出的模型描述了 qMRI 参数的相互依赖性。将这些模型与图像合成的概念相结合，指向了一种合成 qMRI 的新方法，其中通过使用生物物理模型来构建根本不同的物理特性的图。在这项研究中，在最近提出的线性松弛测量模型的背景下研究了合成 qMRI 的实用性。考虑了两种神经影像应用。首先，通过利用松弛测量模型的超定性质以及数据中伪影不一致的事实，从运动损坏的数据合成无伪影定量图。在第二个应用中，合成磁化转移（MT）饱和度图而无需获取MT加权体积，这直接导致采集的比吸收率降低。这一特性对于超高场应用尤其重要。相对于使用 T 1 加权图像或 R 1 图的分割，合成 MT 图可以提供改进的深层灰质结构分割。所提出的合成 qMRI 方法有望最大限度地从 qMRI 协议中提取与组织微观结构相关的高质量信息，并进一步加深我们对这些 qMRI 参数之间相互关系的理解。
Quantitative MRI (qMRI) provides standardized measures of specific physical parameters that are sensitive to the underlying tissue microstructure and are a first step towards achieving maps of biologically relevant metrics through in vivo histology using MRI. Recently proposed models have described the interdependence of qMRI parameters. Combining such models with the concept of image synthesis points towards a novel approach to synthetic qMRI, in which maps of fundamentally different physical properties are constructed through the use of biophysical models. In this study, the utility of synthetic qMRI is investigated within the context of a recently proposed linear relaxometry model. Two neuroimaging applications are considered. In the first, artefact‐free quantitative maps are synthesized from motion‐corrupted data by exploiting the over‐determined nature of the relaxometry model and the fact that the artefact is inconsistent across the data. In the second application, a map of magnetization transfer (MT) saturation is synthesized without the need to acquire an MT‐weighted volume, which directly leads to a reduction in the specific absorption rate of the acquisition. This feature would be particularly important for ultra‐high field applications. The synthetic MT map is shown to provide improved segmentation of deep grey matter structures, relative to segmentation using T 1‐weighted images or R 1 maps. The proposed approach of synthetic qMRI shows promise for maximizing the extraction of high quality information related to tissue microstructure from qMRI protocols and furthering our understanding of the interrelation of these qMRI parameters.
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影响因子：
4.4
作者：
Helms, Gunther;Dechent, Peter
通讯作者：
Dechent, Peter
影响因子：
3.3
作者：
Callaghan, Martina F.;Helms, Gunther;Lutti, Antoine;Mohammadi, Siawoosh;Weiskopf, Nikolaus
通讯作者：
Weiskopf, Nikolaus
影响因子：
4.2
作者：
Callaghan MF;Freund P;Draganski B;Anderson E;Cappelletti M;Chowdhury R;Diedrichsen J;Fitzgerald TH;Smittenaar P;Helms G;Lutti A;Weiskopf N
通讯作者：
Weiskopf N
影响因子：
3.3
作者：
Li, X;Rooney, WD;Springer, CS
通讯作者：
Springer, CS
影响因子：
19.7
作者：
BOBMAN, SA;RIEDERER, SJ;WANG, HZ
通讯作者：
WANG, HZ