Unconstrained quantitative magnetization transfer imaging: disentangling T1 of the free and semi-solid spin pools.

ArXiv Pub Date : 2024-04-01
Jakob Assländer, Andrew Mao, Elisa Marchetto, Erin S Beck, Francesco La Rosa, Robert W Charlson, Timothy M Shepherd, Sebastian Flassbeck
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Abstract

Since the inception of magnetization transfer (MT) imaging, it has been widely assumed that Henkelman's two spin pools have similar longitudinal relaxation times, which motivated many researchers to constrain them to each other. However, several recent publications reported a T1s of the semi-solid spin pool that is much shorter than T1f of the free pool. While these studies tailored experiments for robust proofs-of-concept, we here aim to quantify the disentangled relaxation processes on a voxel-by-voxel basis in a clinical imaging setting, i.e., with an effective resolution of 1.24mm isotropic and full brain coverage in 12min. To this end, we optimized a hybrid-state pulse sequence for mapping the parameters of an unconstrained MT model. We scanned four people with relapsing-remitting multiple sclerosis (MS) and four healthy controls with this pulse sequence and estimated T1f1.84s and T1s0.34s in healthy white matter. Our results confirm the reports that T1sT1f and we argue that this finding identifies MT as an inherent driver of longitudinal relaxation in brain tissue. Moreover, we estimated a fractional size of the semi-solid spin pool of m0s0.212, which is larger than previously assumed. An analysis of T1f in normal-appearing white matter revealed statistically significant differences between individuals with MS and controls.

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Abstract Image

关于脑组织中的多路径纵向自旋弛豫。
本文的目的是通过断言自由和半固体自旋池的T1弛豫时间之间的显著差异,证实先前的报告将磁化转移(MT)确定为脑组织纵向弛豫的内在驱动因素。此外,我们旨在确定一种在临床成像环境中逐体素量化这些弛豫过程的途径,即标称分辨率为1mm各向同性,12分钟内全脑覆盖。为此,我们优化了一个混合状态脉冲序列,用于映射无约束MT模型的参数。我们用这种脉冲序列扫描了4名复发-缓解型多发性硬化症(MS)患者和4名健康对照者,估计了健康WM的自由和半固体自旋池的T1f≈1.90s和T1s≈0.327s,证实了以前的报道,并质疑了常用的假设T1s=T1f或T1s=1s。此外,我们估计了半固态自旋池的分数大小为m0s≈0.202,这比之前假设的要大。对正常白质T1f的分析显示,MS患者和对照组之间存在统计学上的显著差异。总之,我们证实脑组织中的纵向自旋弛豫由MT主导,并且混合状态促进了无约束MT模型的体素拟合,这使得能够分析细微的神经退行性变。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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