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Numerical methods to achieve robust relaxometry mapping in multi-echo chemical shift-based MRI

机译:在基于多回波化学位移的MRI中实现鲁棒弛豫法映射的数值方法

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We investigate on the feasibility of numerical methods to provide robust transverse relaxation R2* mapping in magnetic resonance imaging (MRI) applications by using latest theoretical models corrected for multiple confounding factors. Currently, a performance improvement in state-of-the-art MRI relaxometry algorithms is challenging because of a non-negligible bias and still unsolved numerical instabilities. Here, R2* mapping reconstructions, including complex-fitting with multi-spectral fat-correction using single-decay and double-decay formulation, are explored in order to identify optimal configuration parameters and performance limits. In addition results are evaluated by performing a comparison between single and multiple fat spectrum pre-calibration routines. Complex fitting and fat-correction with multi-exponential decay formulation outperforms the standard single-decay approximation in various diagnostic scenarios. In the study of neuromuscular disorders (NMD) our achievements aim also to highlight how the subdivision of image space into a number of partitioned areas and the adoption of multiple independent pre-calibration provides reduced fitting error if compared with single pre-calibration. The improvements are demonstrated in both simulations and in vivo applications. Together, such results suggest potential perspectives for the development of relaxometry as a reliable tool to improve tissue characterization and monitoring of NMD.
机译:我们通过使用针对多种混杂因素校正的最新理论模型研究数值方法在磁共振成像(MRI)应用中提供鲁棒的横向弛豫R2 *映射的可行性。当前,由于不可忽略的偏差和仍未解决的数值不稳定性,目前最先进的MRI弛豫测量算法的性能改进具有挑战性。在此,探索了R2 *映射重建,包括使用单衰变和双衰变公式进行多光谱脂肪校正的复杂拟合,以确定最佳的配置参数和性能极限。另外,通过在单个和多个脂肪光谱预校准程序之间进行比较来评估结果。在各种诊断方案中,具有多指数衰减公式的复杂拟合和脂肪校正优于标准的单衰减近似。在神经肌肉疾病(NMD)的研究中,我们的成就还旨在强调与单次预校准相比,如何将图像空间细分为多个分区以及采用多个独立的预校准可减少拟合误差。在仿真和体内应用中都证明了这些改进。在一起,这些结果表明松弛法的发展作为改进组织表征和监测NMD的可靠工具的潜在前景。

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