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Model-Based Reconstruction for T1 Mapping Using Single-Shot Inversion-Recovery Radial FLASH

机译:T1映射的基于模型的重构,采用单次反转恢复径向FLASH

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Quantitative parameter mapping in MRI is typically performed as a two-step procedure where serial imaging is followed by pixelwise model fitting. In contrast, model-based reconstructions directly reconstruct parameter maps from raw data without explicit image reconstruction. Here, we propose a method that determines T1 maps directly from multi-channel raw data as obtained by a single-shot inversion-recovery radial FLASH acquisition with a Golden Angle view order. Joint reconstruction of a T1, spin-density and flip-angle map is formulated as a nonlinear inverse problem and solved by the iteratively regularized Gauss-Newton method. Coil sensitivity profiles are determined from the same data in a preparatory step of the reconstruction. Validations included numerical simulations, in vitro MRI studies of an experimental T1 phantom, and in vivo studies of brain and abdomen of healthy subjects at a field strength of 3 T. The results obtained for a numerical and experimental phantom demonstrated excellent accuracy and precision of model-based T1 mapping. In vivo studies allowed for high-resolution T1 mapping of human brain (0.5-0.75 mm in-plane, 4 mm section thickness) and liver (1.0 mm, 5 mm section) within 3.6-5 s. In conclusion, the proposed method for model-based T1 mapping may become an alternative to two-step techniques, which rely on model fitting after serial image reconstruction. More extensive clinical trials now require accelerated computation and online implementation of the algorithm. (C) 2016 Wiley Periodicals, Inc.
机译:MRI中的定量参数映射通常按两步程序执行,在串行成像之后进行逐像素模型拟合。相反,基于模型的重建可直接从原始数据重建参数图,而无需显式图像重建。在这里,我们提出一种直接从多通道原始数据确定T1映射的方法,该原始数据是通过以Golden Angle视图顺序进行单次反转恢复径向FLASH采集获得的。 T1,自旋密度和翻转角图的联合重构被公式化为非线性逆问题,并通过迭代正则化的高斯-牛顿法求解。在重建的准备步骤中,根据相同数据确定线圈灵敏度曲线。验证包括数值模拟,实验性T1体模的体外MRI研究以及场强为3 T的健康受试者的大脑和腹部的体内研究。数值体模和实验体模获得的结果证明了模型的出色准确性和精确度基于T1的映射。体内研究允许在3.6-5 s内对人脑(平面内0.5-0.75 mm,切片厚度4 mm)和肝脏(1.0 mm,5 mm切片)进行高分辨率T1成像。总之,所提出的基于模型的T1映射方法可能会成为两步技术的替代方法,后者依赖于串行图像重建后的模型拟合。现在,更广泛的临床试验要求算法的加速计算和在线实施。 (C)2016威利期刊公司

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