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Rapid Simultaneous High-resolution Mapping of Myelin Water Fraction and Relaxation Times in Human Brain using BMC-mcDESPOT

机译:使用BMC-mcDESPOT快速同时高分辨率解析人脑中髓磷脂水的分数和弛豫时间

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摘要

A number of central nervous system (CNS) diseases exhibit changes in myelin content and magnetic resonance longitudinal, T1, and transverse, T2, relaxation times, which therefore represent important biomarkers of CNS pathology. Among the methods applied for measurement of myelin water fraction (MWF) and relaxation times, the multicomponent driven equilibrium single pulse observation of T1 and T2 (mcDESPOT) approach is of particular interest. mcDESPOT permits whole brain mapping of multicomponent T1 and T2, with data acquisition accomplished within a clinically realistic acquisition time. Unfortunately, previous studies have indicated the limited performance of mcDESPOT in the setting of the modest signal-to-noise range of high-resolution mapping, required for the depiction of small structures and to reduce partial volume effects. Recently, we showed that a new Bayesian Monte Carlo (BMC) analysis substantially improved determination of MWF from mcDESPOT imaging data. However, our previous study was limited in that it did not discuss determination of relaxation times. Here, we extend the BMC analysis to the simultaneous determination of whole-brain MWF and relaxation times using the two-component mcDESPOT signal model. Simulation analyses and in-vivo human brain studies indicate the overall greater performance of this approach compared to the stochastic region contraction (SRC) algorithm, conventionally used to derive parameter estimates from mcDESPOT data. SRC estimates of the transverse relaxation time of the long T2 fraction, T2,l, and the longitudinal relaxation time of the short T1 fraction, T1,s, clustered towards the lower and upper parameter search space limits, respectively, indicating failure of the fitting procedure. We demonstrate that this effect is absent in the BMC analysis. Our results also showed improved parameter estimation for BMC as compared to SRC for high-resolution mapping. Overall we find that the combination of BMC analysis and mcDESPOT, BMC-mcDESPOT, shows excellent performance for accurate high-resolution whole-brain mapping of MWF and bi-component transverse and longitudinal relaxation times within a clinically realistic acquisition time.
机译:许多中枢神经系统(CNS)疾病的髓鞘含量和磁共振纵向T1和横向T2弛豫时间都有变化,因此代表了CNS病理学的重要生物标志物。在用于测量髓磷脂水含量(MWF)和弛豫时间的方法中,T1和T2的多组分驱动平衡单脉冲观测(mcDESPOT)方法特别受关注。 mcDESPOT可以对多组分T1和T2进行全脑成像,并且可以在临床现实的采集时间内完成数据采集。不幸的是,先前的研究表明,在描述小型结构并减少部分体积影响所需的高分辨率映射的适度信噪范围内,mcDESPOT的性能有限。最近,我们表明,新的贝叶斯蒙特卡洛(BMC)分析从mcDESPOT成像数据中大大改善了MWF的测定。然而,我们先前的研究是有限的,因为它没有讨论确定弛豫时间。在这里,我们将BMC分析扩展到使用两分量mcDESPOT信号模型同时确定全脑MWF和松弛时间。仿真分析和体内人脑研究表明,与通常用于从mcDESPOT数据中得出参数估计值的随机区域收缩(SRC)算法相比,该方法的总体性能更高。 SRC估计长T2分数的横向弛豫时间T2,l和短T1分数的纵向弛豫时间T1,s分别朝向参数搜索空间上下限聚集,表明拟合失败程序。我们证明BMC分析中没有这种效果。我们的结果还表明,与用于高分辨率映射的SRC相比,BMC的参数估计有所改进。总体而言,我们发现BMC分析和mcDESPOT,BMC-mcDESPOT的组合在临床现实的采集时间内,对MWF的高精度高分辨率全脑标测以及双分量横向和纵向弛豫时间表现出卓越的性能。

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